paperANA.bib

@article{bae2022,
  title = {Forecast {{Characteristics}} of {{Radar Data Assimilation Based}} on the {{Scales}} of {{Precipitation Systems}}},
  author = {Bae, Jeong-Ho and Min, Ki-Hong},
  date = {2022-01},
  journaltitle = {Remote Sensing},
  volume = {14},
  number = {3},
  pages = {605},
  publisher = {{Multidisciplinary Digital Publishing Institute}},
  issn = {2072-4292},
  doi = {10.3390/rs14030605},
  url = {https://www.mdpi.com/2072-4292/14/3/605},
  urldate = {2022-04-04},
  abstract = {Radar data with high spatiotemporal resolution and automatic weather station (AWS) data are used in the data assimilation experiment to improve the precipitation forecast of a numerical model. The numerical model considered in this study is the Weather Research and Forecasting (WRF) model with double-moment 6-class microphysics scheme (WDM6). We calculated the radar equivalent reflectivity factor using high resolution WRF and compared it with radar observations in South Korea. To compare the precipitation forecast characteristics of the three-dimensional variational (3D-Var) assimilation of radar data, four experiments were performed based on the scales of precipitation systems. Comparison of the 24 h accumulated rainfall with surface observation data, contoured frequency by altitude diagram (CFAD), time–height cross sections (THCS), and vertical hydrometeor profiles was used to evaluate the accuracy of the simulation of precipitation. The model simulations were performed with and without 3D-VAR radar reflectivity, radial velocity and AWS assimilation for two mesoscale convective cases and two synoptic scale cases. The combined effect of the radar and AWS data assimilation experiment improved the location of the precipitation area and rainfall intensity compared to the control run. There is a noticeable scale dependence in the improvement of precipitation systems. Improvements in simulating mesoscale convective systems were larger compared to synoptically driven precipitation systems.},
  issue = {3},
  langid = {english},
  keywords = {3D-Var,data assimilation,precipitation,radar,WRF},
  file = {/home/pao/Zotero/zotero-library/storage/A88VJFN6/Bae_Min_2022_Forecast Characteristics of Radar Data Assimilation Based on the Scales of.pdf}
}

@article{banos2021,
  title = {Assessment of the Data Assimilation Framework for the {{Rapid Refresh Forecast System}} v0.1 and Impacts on Forecasts of Convective Storms},
  author = {Banos, Ivette H. and Mayfield, Will D. and Ge, Guoqing and Sapucci, Luiz F. and Carley, Jacob R. and Nance, Louisa},
  date = {2021-10-05},
  journaltitle = {Geoscientific Model Development Discussions},
  pages = {1--36},
  publisher = {{Copernicus GmbH}},
  issn = {1991-959X},
  doi = {10.5194/gmd-2021-289},
  url = {https://gmd.copernicus.org/preprints/gmd-2021-289/},
  urldate = {2022-04-21},
  abstract = {{$<$}p{$><$}strong class="journal-contentHeaderColor"{$>$}Abstract.{$<$}/strong{$>$} The Rapid Refresh Forecast System (RRFS) is currently under development and aims to replace the National Centers for Environmental Prediction (NCEP) operational suite of regional and convective scale modeling systems in the next upgrade. In order to achieve skillful forecasts comparable to the current operational suite, each component of the RRFS needs to be configured through exhaustive testing and evaluation. The current data assimilation component uses the Gridpoint Statistical Interpolation (GSI) system. In this study, various data assimilation algorithms and configurations in GSI are assessed for their impacts on RRFS analyses and forecasts of a squall line over Oklahoma on 4 May 2020. Results show that a baseline RRFS run without data assimilation is able to represent the observed convection, but with stronger cells and large location errors. With data assimilation, these errors are reduced, especially in the 4 and 6\&thinsp;h forecasts using 75\&thinsp;\% of the ensemble background error covariance (BEC) and with the supersaturation removal function activated in GSI. Decreasing the vertical ensemble localization radius in the first 10 layers of the hybrid analysis results in overall less skillful forecasts. Convection and precipitation are overforecast in most forecast hours when using planetary boundary layer pseudo-observations, but the root mean square error and bias of the 2\&thinsp;h forecast of 2\&thinsp;m dew point temperature are reduced by 1.6\&thinsp;K during the afternoon hours. Lighter hourly accumulated precipitation is predicted better when using 100\&thinsp;\% ensemble BEC in the first 4\&thinsp;h forecast, but heavier hourly accumulated precipitation is better predicted with 75\&thinsp;\% ensemble BEC. Our results provide insight into current capabilities of the RRFS data assimilation system and identify configurations that should be considered as candidates for the first version of RRFS.{$<$}/p{$>$}},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/XZXW2YF4/Banos et al_2021_Assessment of the data assimilation framework for the Rapid Refresh Forecast.pdf}
}

@article{bao2015,
  title = {Impacts of {{AMSU-A}}, {{MHS}} and {{IASI}} Data Assimilation on Temperature and Humidity Forecasts with {{GSI}}–{{WRF}} over the Western {{United States}}},
  author = {Bao, Y. and Xu, J. and Powell Jr., A. M. and Shao, M. and Min, J. and Pan, Y.},
  date = {2015-10-14},
  journaltitle = {Atmospheric Measurement Techniques},
  shortjournal = {Atmos. Meas. Tech.},
  volume = {8},
  number = {10},
  pages = {4231--4242},
  issn = {1867-8548},
  doi = {10.5194/amt-8-4231-2015},
  url = {https://www.atmos-meas-tech.net/8/4231/2015/},
  urldate = {2020-05-07},
  abstract = {Abstract. Using NOAA's Gridpoint Statistical Interpolation (GSI) data assimilation system and NCAR's Advanced Research WRF (Weather Research and Forecasting) (ARW-WRF) regional model, six experiments are designed by (1) a control experiment (CTRL) and five data assimilation (DA) experiments with different data sets, including (2) conventional data only (CON); (3) microwave data (AMSU-A + MHS) only (MW); (4) infrared data (IASI) only (IR); (5) a combination of microwave and infrared data (MWIR); and (6) a combination of conventional, microwave and infrared observation data (ALL). One-month experiments in July 2012 and the impacts of the DA on temperature and moisture forecasts at the surface and four vertical layers over the western United States have been investigated. The four layers include lower troposphere (LT) from 800 to 1000 hPa, middle troposphere (MT) from 400 to 800 hPa, upper troposphere (UT) from 200 to 400 hPa, and lower stratosphere (LS) from 50 to 200 hPa. The results show that the regional GSI–WRF system is underestimating the observed temperature in the LT and overestimating in the UT and LS. The MW DA reduced the forecast bias from the MT to the LS within 30 h forecasts, and the CON DA kept a smaller forecast bias in the LT for 2-day forecasts. The largest root mean square error (RMSE) is observed in the LT and at the surface (SFC). Compared to the CTRL, the MW DA produced the most positive contribution in the UT and LS, and the CON DA mainly improved the temperature forecasts at the SFC. However, the IR DA gave a negative contribution in the LT. Most of the observed humidity in the different vertical layers is overestimated in the humidity forecasts except in the UT. The smallest bias in the humidity forecast occurred at the SFC and in the UT. The DA experiments apparently reduced the bias from the LT to UT, especially for the IR DA experiment, but the RMSEs are not reduced in the humidity forecasts. Compared to the CTRL, the IR DA experiment has a larger RMSE in the moisture forecast, although the smallest bias is found in the LT and MT.},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Bao/bao_2015_impacts_of_amsu-a,_mhs_and_iasi_data_assimilation_on_temperature_and_humidity.pdf}
}

@article{beck2004,
  title = {Impact of Nesting Strategies in Dynamical Downscaling of Reanalysis Data},
  author = {Beck, A. and Ahrens, B. and Stadlbacher, K.},
  date = {2004},
  journaltitle = {Geophysical Research Letters},
  volume = {31},
  number = {19},
  issn = {1944-8007},
  doi = {10.1029/2004GL020115},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2004GL020115},
  urldate = {2022-08-22},
  abstract = {Coarse–grid global numerical weather simulations or analysis data have to be downscaled, e.g., with nested limited–area models (LAMs), for regional interpretation. Here, the impact of different one–way nesting strategies on precipitation simulations over the European Alps with the LAM ALADIN is studied. The LAM is forced by initial and lateral boundary data derived from ERA40 reanalyses with 120 km horizontal gridspacing and 6 h update interval. The nesting strategies considered include relaxation–based techniques with direct nesting of the high–resolution LAM (horizontal gridspacing Δx = 12 km; domain size 2800 × 2500 km2) or double nesting with an intermediate–resolution nest (Δx = 50 km). Additionally, the impact of a spectral initialization technique is investigated. Results indicate that the considered nesting strategies are comparably successful in terms of precipitation simulation, despite the large resolution jump (120 to 12 km) involved. Thus, the cheapest method in terms of computational resources, i.e., direct nesting, seems to be the most adequate for dynamical downscaling of reanalysis data over complex terrain.},
  langid = {english},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2004GL020115},
  file = {/home/pao/Zotero/zotero-library/storage/8JZT9DYB/Beck et al_2004_Impact of nesting strategies in dynamical downscaling of reanalysis data.pdf}
}

@article{berri2012,
  title = {Verification of a {{Synthesized Method}} for the {{Calculation}} of {{Low-Level Climatological Wind Fields Using}} a {{Mesoscale Boundary-Layer Model}}},
  author = {Berri, Guillermo J. and Nuin, Jorgelina S. Galli and Sraibman, Laura and Bertossa, German},
  date = {2012-02},
  journaltitle = {Boundary-Layer Meteorology},
  shortjournal = {Boundary-Layer Meteorol},
  volume = {142},
  number = {2},
  pages = {329--337},
  issn = {0006-8314, 1573-1472},
  doi = {10.1007/s10546-011-9677-2},
  url = {http://link.springer.com/10.1007/s10546-011-9677-2},
  urldate = {2020-05-07},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Berri/berri_2012_verification_of_a_synthesized_method_for_the_calculation_of_low-level.pdf}
}

@article{brooks2003,
  title = {The Spatial Distribution of Severe Thunderstorm and Tornado Environments from Global Reanalysis Data},
  author = {Brooks, Harold E and Lee, James W and Craven, Jeffrey P},
  date = {2003-07},
  journaltitle = {Atmospheric Research},
  shortjournal = {Atmospheric Research},
  volume = {67--68},
  pages = {73--94},
  issn = {01698095},
  doi = {10.1016/S0169-8095(03)00045-0},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0169809503000450},
  urldate = {2021-05-14},
  abstract = {Proximity sounding analysis has long been a tool to determine environmental conditions associated with different kinds of weather events and to discriminate between them. It has been limited, necessarily, by the spatial and temporal distribution of soundings. The recent development of reanalysis datasets that cover the globe with spatial grid spacing on the order of 200 km and temporal spacing every 6 h allows for the possibility of increasing the number of proximity soundings by creating ‘‘pseudo-soundings.’’ We have used the National Center for Atmospheric Research (NCAR)/United States National Centers for Environmental Prediction (NCEP) reanalysis system to create soundings and find environmental conditions associated with significant severe thunderstorms (hail at least 5 cm in diameter, wind gusts at least 120 km hÀ 1, or a tornado of at least F2 damage) and to discriminate between significant tornadic and non-tornadic thunderstorm environments in the eastern United States for the period 1997 – 1999. Applying the relationships from that region to Europe and the rest of the globe, we have made estimates of the frequency of favorable conditions for significant severe thunderstorms. Southern Europe has the greatest frequency of significant severe thunderstorm environments, particularly over the Spanish plateau and the region east of the Adriatic Sea. Favorable significant tornadic environments are found in France and east of the Adriatic. Worldwide, favorable significant thunderstorm environments are concentrated in equatorial Africa, the central United States, southern Brazil and northern Argentina, and near the Himalayas. Tornadic environments are by far the most common in the central United States, with lesser areas in southern Brazil and northern Argentina.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/8L96CXR6/Brooks et al. - 2003 - The spatial distribution of severe thunderstorm an.pdf}
}

@article{candille2007,
  title = {Verification of an {{Ensemble Prediction System}} against {{Observations}}},
  author = {Candille, G. and Côté, C. and Houtekamer, P. L. and Pellerin, G.},
  date = {2007-07},
  journaltitle = {Monthly Weather Review},
  shortjournal = {Mon. Wea. Rev.},
  volume = {135},
  number = {7},
  pages = {2688--2699},
  issn = {0027-0644, 1520-0493},
  doi = {10.1175/MWR3414.1},
  url = {http://journals.ametsoc.org/doi/10.1175/MWR3414.1},
  urldate = {2020-05-07},
  abstract = {A verification system has been developed for the ensemble prediction system (EPS) at the Canadian Meteorological Centre (CMC). This provides objective criteria for comparing two EPSs, necessary when deciding whether or not to implement a new or revised EPS. The proposed verification methodology is based on the continuous ranked probability score (CRPS), which provides an evaluation of the global skill of an EPS. Its reliability/resolution partition, proposed by Hersbach, is used to measure the two main attributes of a probabilistic system. Also, the characteristics of the reliability are obtained from the two first moments of the reduced centered random variable (RCRV), which define the bias and the dispersion of an EPS. Resampling bootstrap techniques have been applied to these scores. Confidence intervals are thus defined, expressing the uncertainty due to the finiteness of the number of realizations used to compute the scores. All verifications are performed against observations to provide more independent validations and to avoid any local systematic bias of an analysis. A revised EPS, which has been tested at the CMC in a parallel run during the autumn of 2005, is described in this paper. This EPS has been compared with the previously operational one with the verification system presented above. To illustrate the verification methodology, results are shown for the temperature at 850 hPa. The confidence intervals are computed by taking into account the spatial correlation of the data and the temporal autocorrelation of the forecast error. The revised EPS performs significantly better for all the forecast ranges, except for the resolution component of the CRPS where the improvement is no longer significant from day 7. The significant improvement of the reliability is mainly due to a better dispersion of the ensemble. Finally, the verification system correctly indicates that variations are not significant when two theoretically similar EPSs are compared.},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Candille/candille_2007_verification_of_an_ensemble_prediction_system_against_observations.pdf}
}

@article{casaretto2022,
  title = {High-{{Resolution NWP Forecast Precipitation Comparison}} over {{Complex Terrain}} of the {{Sierras}} de {{Córdoba}} during {{RELAMPAGO-CACTI}}},
  author = {Casaretto, Gimena and Dillon, Maria Eugenia and Salio, Paola and Skabar, Yanina García and Nesbitt, Stephen W. and Schumacher, Russ S. and García, Carlos Marcelo and Catalini, Carlos},
  date = {2022-02-01},
  journaltitle = {Weather and Forecasting},
  volume = {37},
  number = {2},
  pages = {241--266},
  publisher = {{American Meteorological Society}},
  issn = {1520-0434, 0882-8156},
  doi = {10.1175/WAF-D-21-0006.1},
  url = {https://journals.ametsoc.org/view/journals/wefo/37/2/WAF-D-21-0006.1.xml},
  urldate = {2022-07-26},
  abstract = {Abstract Sierras de Córdoba (Argentina) is characterized by the occurrence of extreme precipitation events during the austral warm season. Heavy precipitation in the region has a large societal impact, causing flash floods. This motivates the forecast performance evaluation of 24-h accumulated precipitation and vertical profiles of atmospheric variables from different numerical weather prediction (NWP) models with the final aim of helping water management in the region. The NWP models evaluated include the Global Forecast System (GFS), which parameterizes convection, and convection-permitting simulations of the Weather Research and Forecasting (WRF) Model configured by three institutions: University of Illinois at Urbana–Champaign (UIUC), Colorado State University (CSU), and National Meteorological Service of Argentina (SMN). These models were verified with daily accumulated precipitation data from rain gauges and soundings during the RELAMPAGO-CACTI field campaign. Generally all configurations of the higher-resolution WRFs outperformed the lower-resolution GFS based on multiple metrics. Among the convection-permitting WRF Models, results varied with respect to rainfall threshold and forecast lead time, but the WRFUIUC mostly performed the best. However, elevation-dependent biases existed among the models that may impact the use of the data for different applications. There is a dry (moist) bias in lower (upper) pressure levels which is most pronounced in the GFS. For Córdoba an overestimation of the northern flow forecasted by the NWP configurations at lower levels was encountered. These results show the importance of convection-permitting forecasts in this region, which should be complementary to the coarser-resolution global model forecasts to help various users and decision-makers.},
  langid = {english}
}

@article{cecil2012,
  title = {Toward a {{Global Climatology}} of {{Severe Hailstorms}} as {{Estimated}} by {{Satellite Passive Microwave Imagers}}},
  author = {Cecil, Daniel J. and Blankenship, Clay B.},
  date = {2012-01-15},
  journaltitle = {Journal of Climate},
  volume = {25},
  number = {2},
  pages = {687--703},
  publisher = {{American Meteorological Society}},
  issn = {0894-8755, 1520-0442},
  doi = {10.1175/JCLI-D-11-00130.1},
  url = {https://journals.ametsoc.org/view/journals/clim/25/2/jcli-d-11-00130.1.xml},
  urldate = {2021-05-14},
  abstract = {{$<$}section class="abstract"{$><$}h2 class="abstractTitle text-title my-1" id="d69634688e65"{$>$}Abstract{$<$}/h2{$><$}p{$>$}An 8-yr climatology of storms producing large hail is estimated from satellite measurements using Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). This allows a unique, consistent comparison between regions that cannot be consistently compared using ground-based records because of varying data collection standards. Severe hailstorms are indicated most often in a broad region of northern Argentina and southern Paraguay and a smaller region in Bangladesh and eastern India. Numerous hailstorms are also estimated in the central and southeastern United States, northern Pakistan and northwestern India, central and western Africa, and southeastern Africa (and adjacent waters). Fewer hailstorms are estimated for other regions over land and scattered across subtropical oceans. Very few are estimated in the deep tropics other than in Africa. Most continental regions show seasonality with hailstorms peaking in late spring or summer. The South Asian monsoon alters the hailstorm climatology around the Indian subcontinent. About 75\% of the hailstorms on the eastern side (around Bangladesh) occur from April through June, generally before monsoon onset. Activity shifts northwest to northern India in late June and July. An arc along the foothills in northern Pakistan becomes particularly active from mid-June through mid-August. The AMSR-E measurements are limited to early afternoon and late night. Tropical Rainfall Measuring Mission (TRMM) measurements are used to investigate diurnal variability in the tropics and subtropics. All of the prominent regions have hailstorm peaks in late afternoon and early evening. The United States and central Africa have the fewest overnight and early morning storms, while subtropical South America and Bangladesh have the most.{$<$}/p{$><$}/section{$>$}},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/ZY9RZMN3/Cecil_Blankenship_2012_Toward a Global Climatology of Severe Hailstorms as Estimated by Satellite.pdf}
}

@article{chang2017,
  title = {Assimilation of {{Hourly Surface Observations}} with the {{Canadian High-Resolution Ensemble Kalman Filter}}},
  author = {Chang, Weiguang and Jacques, Dominik and Fillion, Luc and Baek, Seung-Jong},
  date = {2017-10-20},
  journaltitle = {Atmosphere-Ocean},
  volume = {55},
  number = {4-5},
  pages = {247--263},
  publisher = {{Taylor \& Francis}},
  issn = {0705-5900},
  doi = {10.1080/07055900.2017.1384361},
  url = {https://doi.org/10.1080/07055900.2017.1384361},
  urldate = {2020-09-14},
  abstract = {An hourly-cycling ensemble Kalman filter (EnKF) working at 2.5 km horizontal grid spacing is implemented over southern Ontario (Canada) to assimilate Meteorological Terminal Aviation Routine Weather Reports (METARs) in addition to the observations assimilated operationally at the Canadian Meteorological Centre. This high-resolution EnKF (HREnKF) system employs ensemble land analyses and perturbed roughness length to prevent an ensemble spread that is too small near the surface. The HREnKF then performs continuously for a four-day period, from which twelve-hour ensemble forecasts are launched every six hours. The impact on analyses and short-term forecasts of assimilating METAR data is given special attention.It is shown that using ensemble land surface analyses increases near-surface ensemble spreads for temperature and specific humidity. Perturbing roughness length enlarges the spread for surface wind. Given sufficient ensemble spread, the four-day case study shows that the near-surface model state is brought closer to surface observations during the cycling process. The impact of assimilating surface data can also be seen at higher levels by using aircraft reports for verification. The ensemble forecast verification suggests that METAR data assimilation improves ensemble forecasts of air temperature and dewpoint near the surface up to a lead time of six hours or even longer. However, only minor improvement is found in surface wind forecasts.},
  keywords = {data assimilation,ensemble Kalman Filter,high resolution,METAR data},
  annotation = {\_eprint: https://doi.org/10.1080/07055900.2017.1384361},
  file = {/home/pao/Dropbox/Papers Zotero/Chang/chang_2017_assimilation_of_hourly_surface_observations_with_the_canadian_high-resolution.pdf}
}

@article{chen2001,
  title = {Coupling an {{Advanced Land Surface}}–{{Hydrology Model}} with the {{Penn State}}–{{NCAR MM5 Modeling System}}. {{Part I}}: {{Model Implementation}} and {{Sensitivity}}},
  shorttitle = {Coupling an {{Advanced Land Surface}}–{{Hydrology Model}} with the {{Penn State}}–{{NCAR MM5 Modeling System}}. {{Part I}}},
  author = {Chen, Fei and Dudhia, Jimy},
  date = {2001-04-01},
  journaltitle = {Monthly Weather Review},
  volume = {129},
  number = {4},
  pages = {569--585},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2},
  url = {https://journals.ametsoc.org/view/journals/mwre/129/4/1520-0493_2001_129_0569_caalsh_2.0.co_2.xml},
  urldate = {2021-06-24},
  abstract = {{$<$}section class="abstract"{$><$}h2 class="abstractTitle text-title my-1" id="d61241058e68"{$>$}Abstract{$<$}/h2{$><$}p{$>$}This paper addresses and documents a number of issues related to the implementation of an advanced land surface–hydrology model in the Penn State–NCAR fifth-generation Mesoscale Model (MM5). The concept adopted here is that the land surface model should be able to provide not only reasonable diurnal variations of surface heat fluxes as surface boundary conditions for coupled models, but also correct seasonal evolutions of soil moisture in the context of a long-term data assimilation system. In a similar way to that in which the modified Oregon State University land surface model (LSM) has been used in the NCEP global and regional forecast models, it is implemented in MM5 to facilitate the initialization of soil moisture. Also, 1-km resolution vegetation and soil texture maps are introduced in the coupled MM5–LSM system to help identify vegetation/water/soil characteristics at fine scales and capture the feedback of these land surface forcings. A monthly varying climatological 0.15° × 0.15° green vegetation fraction is utilized to represent the annual control of vegetation on the surface evaporation. Specification of various vegetation and soil parameters is discussed, and the available water capacity in the LSM is extended to account for subgrid-scale heterogeneity. The coupling of the LSM to MM5 is also sensitive to the treatment of the surface layer, especially the calculation of the roughness length for heat/moisture. Including the effect of the molecular sublayer can improve the simulation of surface heat flux. It is shown that the soil thermal and hydraulic conductivities and the surface energy balance are very sensitive to soil moisture changes. Hence, it is necessary to establish an appropriate soil moisture data assimilation system to improve the soil moisture initialization at fine scales.{$<$}/p{$><$}/section{$>$}},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/XZG8Y2AL/Chen_Dudhia_2001_Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5.pdf}
}

@article{chen2015,
  title = {Roles of Wind Shear at Different Vertical Levels: {{Cloud}} System Organization and Properties},
  shorttitle = {Roles of Wind Shear at Different Vertical Levels},
  author = {Chen, Qian and Fan, Jiwen and Hagos, Samson and Gustafson, William I. and Berg, Larry K.},
  date = {2015},
  journaltitle = {Journal of Geophysical Research: Atmospheres},
  volume = {120},
  number = {13},
  pages = {6551--6574},
  issn = {2169-8996},
  doi = {10.1002/2015JD023253},
  url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2015JD023253},
  urldate = {2021-02-01},
  abstract = {Understanding critical processes that contribute to the organization of mesoscale convective systems (MCSs) is important for accurate weather forecasts and climate predictions. In this study, we investigate the effects of wind shear at different vertical levels on the organization and properties of convective systems using the Weather Research and Forecasting model with spectral bin microphysics. Based on a control run for a MCS with weak wind shear (Ctrl), we find that increasing wind shear at the lower troposphere (L-shear) leads to a more organized quasi-line convective system. Strong wind shear in the middle troposphere (M-shear) tends to produce large vorticity and form a mesocyclone circulation and an isolated strong storm that leans toward supercellular structure. By increasing wind shear at the upper vertical levels only (U-shear), the organization of the convection is not changed much, but the convective intensity is weakened. Increasing wind shear in the middle troposphere for the selected case results in a significant drying, and the drying is more significant when conserving moisture advection at the lateral boundaries, contributing to the suppressed convective strength and precipitation relative to Ctrl. Precipitation in the L-shear and U-shear does not change much from Ctrl. Evident changes of cloud macrophysical and microphysical properties in the strong wind shear cases are mainly due to large changes in convective organization and water vapor. The insights obtained from this study help us better understand the major factors contributing to convective organization and precipitation.},
  langid = {english},
  keywords = {cloud properties,convection organization,deep convection,wind shear},
  annotation = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2015JD023253},
  file = {/home/pao/Dropbox/Papers Zotero/Chen/chen_2015_roles_of_wind_shear_at_different_vertical_levels_-_cloud_system_organization_and.pdf}
}

@article{chen2016,
  title = {Assimilating Surface Observations in a Four-Dimensional Variational {{Doppler}} Radar Data Assimilation System to Improve the Analysis and Forecast of a Squall Line Case},
  author = {Chen, Xingchao and Zhao, Kun and Sun, Juanzhen and Zhou, Bowen and Lee, Wen-Chau},
  date = {2016-10},
  journaltitle = {Advances in Atmospheric Sciences},
  shortjournal = {Adv. Atmos. Sci.},
  volume = {33},
  number = {10},
  pages = {1106--1119},
  issn = {0256-1530, 1861-9533},
  doi = {10.1007/s00376-016-5290-0},
  url = {https://link.springer.com/10.1007/s00376-016-5290-0},
  urldate = {2022-04-04},
  abstract = {This paper examines how assimilating surface observations can improve the analysis and forecast ability of a fourdimensional Variational Doppler Radar Analysis System (VDRAS). Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational (4DVAR) data assimilation system. A squall-line case observed during a field campaign is selected to investigate the performance of the technique. A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions. The surface-based cold pool, divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation. Three experiments—assimilating radar data only, assimilating radar data with surface data blended in a mesoscale background, and assimilating both radar and surface observations with a 4DVAR cost function—are conducted to examine the impact of the surface data assimilation. Independent surface and wind profiler observations are used for verification. The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations. It is also shown that the additional surface data can help improve the analysis and forecast at low levels. Surface and low-level features of the squall line—including the surface warm inflow, cold pool, gust front, and low-level wind—are much closer to the observations after assimilating the surface data in VDRAS.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/ERUZRSDS/Chen et al. - 2016 - Assimilating surface observations in a four-dimens.pdf}
}

@article{cherubini2006,
  title = {The {{Impact}} of {{Satellite-Derived Atmospheric Motion Vectors}} on {{Mesoscale Forecasts}} over {{Hawaii}}},
  author = {Cherubini, T. and Businger, S. and Velden, C. and Ogasawara, R.},
  date = {2006-07-01},
  journaltitle = {Monthly Weather Review},
  volume = {134},
  number = {7},
  pages = {2009--2020},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/MWR3163.1},
  url = {https://journals.ametsoc.org/view/journals/mwre/134/7/mwr3163.1.xml},
  urldate = {2022-04-04},
  abstract = {Abstract Tropospheric motions can be inferred from geostationary satellites by tracking clouds and water vapor in sequential imagery. These atmospheric motion vectors (AMV) have been operationally assimilated into global models for the past three decades, with positive forecast impacts. This paper presents results from a study to assess the impact of AMV derived from Geostationary Operational Environmental Satellite (GOES) imagery on mesoscale forecasts over the conventional data-poor central North Pacific region. These AMV are derived using the latest automated processing methodologies by the University of Wisconsin—Cooperative Institute for Meteorological Satellite Studies (CIMSS). For a test case, a poorly forecast subtropical cyclone (kona low) that occurred over Hawaii on 23–27 February 1997 was chosen. The Local Analysis and Prediction System (LAPS) was used to assimilate GOES-9 AMV data and to produce fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) initial conditions. The satellite wind assimilation is carried out on the 27-km-resolution domain covering the central Pacific area. The MM5 was run with three two-way nested domains (27, 9, and 3 km), with the innermost domain moving with the kona low. The AMV data are found to influence the cyclone’s development, improving the prediction of the cyclone’s central pressure and the track of the low’s center. Since September 2003, GOES-10 AMV data have been routinely accessed from CIMSS in real time and assimilated into the University of Hawaii (UH) LAPS, providing high-resolution initial conditions for twice-daily runs of MM5 at the Mauna Kea Weather Center collocated at the UH. It is found that the direct assimilation of AMV data into LAPS has a positive impact on the forecast accuracy of the UH LAPS/MM5 operational forecasting system when validated with observations in Hawaii. The implications of the results are discussed.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/7PDIW5NC/Cherubini et al_2006_The Impact of Satellite-Derived Atmospheric Motion Vectors on Mesoscale.pdf}
}

@article{Cheyenne2019,
  title = {Cheyenne: {{HPE}}/{{SGI ICE XA System}} ({{University Community Computing}})},
  author = {{Computational and Information Systems Laboratory}},
  date = {2019},
  journaltitle = {National Center for Atmospheric Research Boulder, CO},
  doi = {doi:10.5065/D6RX99HX}
}

@article{cisl_rda_ds084.1,
  title = {{{NCEP GFS}} 0.25 Degree Global Forecast Grids Historical Archive},
  author = {{National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce}},
  date = {2015},
  publisher = {{Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory}},
  address = {Boulder CO},
  url = {https://doi.org/10.5065/D65D8PWK}
}

@misc{cisl_rda_ds337.0,
  title = {{{NCEP ADP}} Global Upper Air and Surface Weather Observations ({{PREPBUFR}} Format)},
  author = {{National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce}},
  date = {2008},
  publisher = {{Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory}},
  location = {{Boulder CO}},
  url = {https://doi.org/10.5065/Z83F-N512}
}

@article{clark2017,
  title = {Generation of {{Ensemble Mean Precipitation Forecasts}} from {{Convection-Allowing Ensembles}}},
  author = {Clark, Adam J.},
  date = {2017-08-01},
  journaltitle = {Weather and Forecasting},
  volume = {32},
  number = {4},
  pages = {1569--1583},
  publisher = {{American Meteorological Society}},
  issn = {1520-0434, 0882-8156},
  doi = {10.1175/WAF-D-16-0199.1},
  url = {https://journals.ametsoc.org/view/journals/wefo/32/4/waf-d-16-0199_1.xml},
  urldate = {2022-03-10},
  abstract = {Abstract Methods for generating ensemble mean precipitation forecasts from convection-allowing model (CAM) ensembles based on a simple average of all members at each grid point can have limited utility because of amplitude reduction and overprediction of light precipitation areas caused by averaging complex spatial fields with strong gradients and high-amplitude features. To combat these issues with the simple ensemble mean, a method known as probability matching is commonly used to replace the ensemble mean amounts with amounts sampled from the distribution of ensemble member forecasts, which results in a field that has a bias approximately equal to the average bias of the ensemble members. Thus, the probability matched mean (PM mean hereafter) is viewed as a better representation of the ensemble members compared to the mean, and previous studies find that it is more skillful than any of the individual members. Herein, using nearly a year’s worth of data from a CAM-based ensemble running in real time at the National Severe Storms Laboratory, evidence is provided that the superior performance of the PM mean is at least partially an artifact of the spatial redistribution of precipitation amounts that occur when the PM mean is computed over a large domain. Specifically, the PM mean enlarges big areas of heavy precipitation and shrinks or even eliminates smaller ones. An alternative approach for the PM mean is developed that restricts the grid points used to those within a specified radius of influence. The new approach has an improved spatial representation of precipitation and is found to perform more skillfully than the PM mean at large scales when using neighborhood-based verification metrics.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/WJ8MLRQ4/Clark_2017_Generation of Ensemble Mean Precipitation Forecasts from Convection-Allowing.pdf}
}

@online{deelia2017,
  title = {El SMN y la red argentina de radares meteorológicos},
  author = {de Elía, Ramón and Vidal, Luciano and Lohigorry, Pedro},
  options = {useprefix=true},
  date = {2017},
  url = {http://hdl.handle.net/20.500.12160/625},
  abstract = {This Note describes the weather radar network of Argentina, highlighting in particular its genesis, its history and its technical as well as institutional characteristics today. In addition, the expectation regarding its further development in the next few years is also discussed.},
  langid = {spanish},
  file = {/home/pao/Zotero/zotero-library/storage/85LLXYUX/de Elía et al. - El SMN y la red argentina de radares meteorológico.pdf}
}

@article{dillon2016,
  title = {Application of the {{WRF-LETKF Data Assimilation System}} over {{Southern South America}}: {{Sensitivity}} to {{Model Physics}}},
  shorttitle = {Application of the {{WRF-LETKF Data Assimilation System}} over {{Southern South America}}},
  author = {Dillon, María E. and Skabar, Yanina García and Ruiz, Juan and Kalnay, Eugenia and Collini, Estela A. and Echevarría, Pablo and Saucedo, Marcos and Miyoshi, Takemasa and Kunii, Masaru},
  date = {2016-02},
  journaltitle = {Weather and Forecasting},
  shortjournal = {Wea. Forecasting},
  volume = {31},
  number = {1},
  pages = {217--236},
  issn = {0882-8156, 1520-0434},
  doi = {10.1175/WAF-D-14-00157.1},
  url = {http://journals.ametsoc.org/doi/10.1175/WAF-D-14-00157.1},
  urldate = {2020-05-21},
  abstract = {Improving the initial conditions of short-range numerical weather prediction (NWP) models is one of the main goals of the meteorological community. Development of data assimilation and ensemble forecast systems is essential in any national weather service (NWS). In this sense, the local ensemble transform Kalman filter (LETKF) is a methodology that can satisfy both requirements in an efficient manner. The Weather Research and Forecasting (WRF) Model coupled with the LETKF, developed at the University of Maryland, College Park, have been implemented experimentally at the NWS of Argentina [Servicio Meteorológico Nacional (SMN)], but at a somewhat lower resolution (40 km) than the operational Global Forecast System (GFS) at that time (27 km). The purpose of this work is not to show that the system presented herein is better than the higher-resolution GFS, but that its performance is reasonably comparable, and to provide the basis for a continued improved development of an independent regional data assimilation and forecasting system. The WRF-LETKF system is tested during the spring of 2012, using the prepared or quality controlled data in Binary Universal Form for Representation of Meteorological Data (PREPBUFR) observations from the National Centers for Environmental Prediction (NCEP) and lateral boundary conditions from the GFS. To assess the effect of model error, a single-model LETKF system (LETKF-single) is compared with a multischeme implementation (LETKF-multi), which uses different boundary layer and cumulus convection schemes for the generation of the ensemble of forecasts. The performance of both experiments during the test period shows that the LETKF-multi usually outperforms the LETKF-single, evidencing the advantages of the use of the multischeme approach. Both data assimilation systems are slightly worse than the GFS in terms of the synoptic environment representation, as could be expected given their lower resolution. Results from a case study of a strong convective system suggest that the LETKF-multi improves the location of the most intense area of precipitation with respect to the LETKF-single, although both systems show an underestimation of the total accumulated precipitation. These preliminary results encourage continuing the development of an operational data assimilation system based on WRF-LETKF at the SMN.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/BK6S5VMD/Dillon et al. - 2016 - Application of the WRF-LETKF Data Assimilation Sys.pdf}
}

@article{dillon2019,
  title = {Sensibilidad de un sistema de asimilación de datos por ensambles a diferentes configuraciones, implementado en el sur de Sudamérica},
  author = {Dillon, María E. and García Skabar, Yanina and Kalnay, Eugenia and Ruiz, Juan J. and Collini, Estela A.},
  date = {2019},
  journaltitle = {Meteorológica},
  volume = {44},
  number = {2},
  pages = {15--34},
  url = {http://www.meteorologica.org.ar/nota/sensibilidad-de-un-sistema-de-asimilacion-de-datos-por-ensambles-a-diferentes-configuraciones-implementado-en-el-sur-de-sudamerica/},
  urldate = {2020-06-23},
  abstract = {Uno de los mayores desafíos en la predicción numérica del tiempo es el de reducir la incertidumbre de las condiciones iniciales. Con el fin de abordar esta problemática, variados esfuerzos se están llevando a cabo en el Servicio Meteorológico Nacional de Argentina (SMN). En este artículo se presenta la evaluación del sistema regional de asimilación por ensambles WRF-LETKF (Weather Research and Forecasting model – Local Ensemble Transform Kalman Filter). El dominio cubre el Sur de Sudamérica con una resolución horizontal de 40 km, y el período de prueba utilizado es de dos meses (noviembre y diciembre de 2012). El sistema de asimilación consta de un ensamble de 40 miembros e incorpora observaciones tanto convencionales como provenientes de satélites. En este trabajo, se evaluó el impacto de utilizar un ensamble multi física incluyendo en sus miembros distintas opciones de parametrizaciones de cumulus y capa límite planetaria. Se halló que dicha estrategia generalmente produce resultados mejores comparada con un sistema de ensamble en el cual todos los miembros poseen las mismas parametrizaciones. También se exploró la inclusión de bordes perturbados, pero no se encontró un impacto significativo con la metodología propuesta. Otro experimento consistió en la inclusión de los perfiles verticales de temperatura y humedad de los AIRS (Atmospheric Infrared Sounders) en la asimilación, cuya evaluación demostró un impacto positivo en los resultados. Finalmente, se comparó la media de los pronósticos por ensamble inicializados con los análisis de las diferentes variantes del sistema WRF-LETKF con un pronóstico determinístico del WRF inicializado con los análisis provistos por  el GFS (Global Forecast System). Si bien generalmente dicha comparación mostró un impacto positivo de la asimilación de datos a escala regional, también mostró la necesidad de que el sistema regional mantenga la información de mayor escala provista por el modelo global.},
  langid = {spanish}
}

@article{dillon2021,
  title = {A Rapid Refresh Ensemble Based Data Assimilation and Forecast System for the {{RELAMPAGO}} Field Campaign},
  author = {Dillon, María Eugenia and Maldonado, Paula and Corrales, Paola and Skabar, Yanina García and Ruiz, Juan and Sacco, Maximiliano and Cutraro, Federico and Mingari, Leonardo and Matsudo, Cynthia and Vidal, Luciano and Rugna, Martin and Hobouchian, María Paula and Salio, Paola and Nesbitt, Stephen and Saulo, Celeste and Kalnay, Eugenia and Miyoshi, Takemasa},
  date = {2021-09-25},
  journaltitle = {Atmospheric Research},
  shortjournal = {Atmospheric Research},
  pages = {105858},
  issn = {0169-8095},
  doi = {10.1016/j.atmosres.2021.105858},
  url = {https://www.sciencedirect.com/science/article/pii/S0169809521004142},
  urldate = {2021-09-28},
  abstract = {This paper describes the lessons learned from the implementation of a regional ensemble data assimilation and forecast system during the intensive observing period of the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign (central Argentina, November–December 2018). This system is based on the coupling of the Weather Research and Forecasting (WRF) model and the Local Ensemble Transform Kalman Filter (LETKF). It combines multiple data sources both global and locally available like high-resolution surface networks, AMDAR data from local aircraft flights, soundings, AIRS retrievals, high-resolution GOES-16 wind estimates, and local radar data. Hourly analyses with grid spacing of 10\,km are generated along with warm-start 36-h ensemble-forecasts, which are initialized from the rapid refresh analyses every three hours. A preliminary evaluation shows that a forecast error reduction is achieved due to the assimilated observations. However, cold-start forecasts initialized from the Global Forecasting System Analysis slightly outperform the ones initialized from the regional assimilation system discussed in this paper. The system uses a multi-physics approach, focused on the use of different cumulus and planetary boundary layer schemes allowing us to conduct an evaluation of different model configurations over central Argentina. We found that the best combinations for forecasting surface variables differ from the best ones for forecasting precipitation, and that differences among the schemes tend to dominate the forecast ensemble spread for variables like precipitation. Lessons learned from this experimental system are part of the legacy of the RELAMPAGO field campaign for the development of advanced operational data assimilation systems in South America.},
  langid = {english},
  keywords = {Regional data assimilation,Regional ensemble forecasts,RELAMPAGO}
}

@article{ebert2001,
  title = {Ability of a {{Poor Man}}'s {{Ensemble}} to {{Predict}} the {{Probability}} and {{Distribution}} of {{Precipitation}}},
  author = {Ebert, Elizabeth E.},
  date = {2001-10-01},
  journaltitle = {Monthly Weather Review},
  volume = {129},
  number = {10},
  pages = {2461--2480},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/1520-0493(2001)129<2461:AOAPMS>2.0.CO;2},
  url = {https://journals.ametsoc.org/view/journals/mwre/129/10/1520-0493_2001_129_2461_aoapms_2.0.co_2.xml},
  urldate = {2022-03-10},
  abstract = {Abstract A poor man's ensemble is a set of independent numerical weather prediction (NWP) model forecasts from several operational centers. Because it samples uncertainties in both the initial conditions and model formulation through the variation of input data, analysis, and forecast methodologies of its component members, it is less prone to systematic biases and errors that cause underdispersive behavior in single-model ensemble prediction systems (EPSs). It is also essentially cost-free. Its main disadvantage is its relatively small size. This paper investigates the ability of a poor man's ensemble to provide forecasts of the probability and distribution of rainfall in the short range, 1–2 days. The poor man's ensemble described here consists of 24- and 48-h daily quantitative precipitation forecasts (QPFs) from seven operational NWP models. The ensemble forecasts were verified for a 28-month period over Australia using gridded daily rain gauge analyses. Forecasts of the probability of precipitation (POP) were skillful for rain rates up to 50 mm day−1 for the first 24-h period, exceeding the skill of the European Centre for Medium-Range Weather Forecasts EPS. Probabilistic skill was limited to lower rain rates during the second 24 h. The skill and accuracy of the ensemble mean QPF far exceeded that of the individual models for both forecast periods when standard measures such as the root-mean-square error and equitable threat score were used. Additional measures based on the forecast location and intensity of individual rain events substantiated the improvements associated with the ensemble mean QPF. The greatest improvement was seen in the location of the forecast rain pattern, as the mean displacement from the observations was reduced by 30\%. As a result the number of event forecasts that could be considered “hits” (forecast rain location and maximum intensity close to the observed) improved markedly. Averaging to produce the ensemble mean caused a large bias in rain area and a corresponding reduction in mean and maximum rain intensity. Several alternative deterministic ensemble forecasts were tested, with the most successful using probability matching to reassign the ensemble mean rain rates using the rain rate distribution of the component QPFs. This eliminated most of the excess rain area and increased the maximum rain rates, improving the event hit rate. The dependence of the POP and ensemble mean results on the number of members included in the ensemble was investigated using the 24-h model QPFs. When ensemble members were selected randomly the performance improved monotonically with increasing ensemble size, with verification statistics approaching their asymptotic limits for an ensemble size of seven. When the members were chosen according to greatest overall skill the ensemble performance peaked when only five or six members were used. This suggests that the addition of ensemble members with lower skill can degrade the overall product. Low values of the spread–skill correlation indicate that it is not possible to predict the forecast skill from the spread of the ensemble alone. However, the number of models predicting a particular rain event gives a good indication of the likelihood of the ensemble to envelop the location and magnitude of that event.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/VKDG7HYY/Ebert_2001_Ability of a Poor Man's Ensemble to Predict the Probability and Distribution of.pdf}
}

@article{eyre2020,
  title = {Assimilation of Satellite Data in Numerical Weather Prediction. {{Part I}}: {{The}} Early Years},
  shorttitle = {Assimilation of Satellite Data in Numerical Weather Prediction. {{Part I}}},
  author = {Eyre, J. R. and English, S. J. and Forsythe, M.},
  date = {2020},
  journaltitle = {Quarterly Journal of the Royal Meteorological Society},
  volume = {146},
  number = {726},
  pages = {49--68},
  issn = {1477-870X},
  doi = {10.1002/qj.3654},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/qj.3654},
  urldate = {2022-03-30},
  abstract = {Developments in the assimilation of satellite data in numerical weather prediction (NWP), from the first experiments in the late 1960s to the present day, are presented in a two-part review article. This first part reviews the early years, up to about the year 2000. It includes summaries of the relevant satellite remote sensing technologies, the theoretical and practical challenges faced when assimilating their data within NWP systems, and the impacts on forecast skill. An important part of this story concerns developments in the assimilation of information on atmospheric temperature and humidity provided by data from passive infrared and microwave radiometers. Following early successes with the assimilation of retrieved temperature profiles, there followed a problematic period, as other aspects of NWP systems improved and the impacts of satellite sounding data declined. Positive impacts were re-established in the 1990s through moves towards more direct assimilation of radiance information. Another important theme concerns developments in the assimilation of wind information via atmospheric motion vectors, which underwent a series of improvements during these years. Additional contributions were provided by information on ocean surface wind from scatterometers. Some contributions from other technologies during this period are also summarised.},
  langid = {english},
  keywords = {data assimilation,numerical weather prediction (NWP),observation,satellite},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3654}
}

@article{eyre2022,
  title = {Assimilation of Satellite Data in Numerical Weather Prediction. {{Part II}}: {{Recent}} Years},
  shorttitle = {Assimilation of Satellite Data in Numerical Weather Prediction. {{Part II}}},
  author = {Eyre, J. R. and Bell, W. and Cotton, J. and English, S. J. and Forsythe, M. and Healy, S. B. and Pavelin, E. G.},
  date = {2022},
  journaltitle = {Quarterly Journal of the Royal Meteorological Society},
  volume = {148},
  number = {743},
  pages = {521--556},
  issn = {1477-870X},
  doi = {10.1002/qj.4228},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/qj.4228},
  urldate = {2022-03-30},
  abstract = {Developments in the assimilation of satellite data in numerical weather prediction (NWP), from the first experiments in the late 1960s to the present day, are presented in a two-part review article. This part, Part II, reviews the progress in recent years, from about 2000. It includes summaries of advances in the relevant satellite remote-sensing technologies and in methods to assimilate observations from these instruments into NWP systems. It also summarises impacts on forecast skill. Continued progress has been made on the assimilation of passive infrared (IR) sounding data and microwave (MW) sounding and imaging data. This has included data from hyperspectral IR sounders, which first became available during this period. Advances in the use of cloud-affected radiances, from both IR and MW instruments, have been made. In support of this progress, further developments have been made in fast radiative transfer models and in bias correction techniques, and work has continued to improve understanding and representation of observation uncertainties. Continued progress has also been made on the use of wind information from satellites, including atmospheric motion vectors and scatterometer data. A new source of temperature and humidity information, from radio occultation observations, has become available during the period and has been exploited by many NWP centres. The impact of satellite data on NWP accuracy is continually assessed using a range of methods and metrics. Some results from recent Observing System Experiments (OSEs) and Forecast Sensitivity to Observation Impact (FSOI) assessment are presented and other methods are discussed. The role of satellite data in NWP-based atmospheric reanalysis systems is also described.},
  langid = {english},
  keywords = {data assimilation,NWP,observation,satellite},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4228}
}

@article{gao2015,
  title = {Assimilation of Wind Speed and Direction Observations: Results from Real Observation Experiments},
  shorttitle = {Assimilation of Wind Speed and Direction Observations},
  author = {Gao, Feng and Huang, Xiang-Yu and Jacobs, Neil A. and Wang, Hongli},
  date = {2015-12-01},
  journaltitle = {Tellus A: Dynamic Meteorology and Oceanography},
  volume = {67},
  number = {1},
  pages = {27132},
  publisher = {{Taylor \& Francis}},
  issn = {null},
  doi = {10.3402/tellusa.v67.27132},
  url = {https://doi.org/10.3402/tellusa.v67.27132},
  urldate = {2021-05-14},
  abstract = {The assimilation of wind observations in the form of speed and direction (asm\_sd) by the Weather Research and Forecasting Model Data Assimilation System (WRFDA) was performed using real data and employing a series of cycling assimilation experiments for a 2-week period, as a follow-up for an idealised post hoc assimilation experiment. The satellite-derived Atmospheric Motion Vectors (AMV) and surface dataset in Meteorological Assimilation Data Ingest System (MADIS) were assimilated. This new method takes into account the observation errors of both wind speed (spd) and direction (dir), and WRFDA background quality control (BKG-QC) influences the choice of wind observations, due to data conversions between (u,v) and (spd, dir). The impacts of BKG-QC, as well as the new method, on the wind analysis were analysed separately. Because the dir observational errors produced by different platforms are not known or tuned well in WRFDA, a practical method, which uses similar assimilation weights in comparative trials, was employed to estimate the spd and dir observation errors. The asm\_sd produces positive impacts on analyses and short-range forecasts of spd and dir with smaller root-mean-square errors than the u,v-based system. The bias of spd analysis decreases by 54.8\%. These improvements result partly from BKG-QC screening of spd and dir observations in a direct way, but mainly from the independent impact of spd (dir) data assimilation on spd (dir) analysis, which is the primary distinction from the standard WRFDA method. The potential impacts of asm\_sd on precipitation forecasts were evaluated. Results demonstrate that the asm\_sd is able to indirectly improve the precipitation forecasts by improving the prediction accuracies of key wind-related factors leading to precipitation (e.g. warm moist advection and frontogenesis).},
  keywords = {observation error,observation operator,quality control,variational assimilation,WRFDA},
  annotation = {\_eprint: https://doi.org/10.3402/tellusa.v67.27132},
  file = {/home/pao/Zotero/zotero-library/storage/F8DUSNVH/Gao et al_2015_Assimilation of wind speed and direction observations.pdf}
}

@misc{garcia2019,
  title = {Argentina Mesonet Data. {{Version}} 1.1. {{UCAR}}/{{NCAR}} - Earth Observing Laboratory.},
  author = {Garcia, Fernando and Ruiz, Juan and Salio, Paola and Bechis, Hernan and Nesbitt, Steve},
  date = {2019},
  url = {https://doi.org/10.26023/JEXB-W6B6-E310}
}

@article{gasperoni2018,
  title = {Assessing {{Impacts}} of the {{High-Frequency Assimilation}} of {{Surface Observations}} for the {{Forecast}} of {{Convection Initiation}} on 3 {{April}} 2014 within the {{Dallas}}–{{Fort Worth Test Bed}}},
  author = {Gasperoni, Nicholas A. and Wang, Xuguang and Brewster, Keith A. and Carr, Frederick H.},
  date = {2018-11-01},
  journaltitle = {Monthly Weather Review},
  volume = {146},
  number = {11},
  pages = {3845--3872},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/MWR-D-18-0177.1},
  url = {https://journals.ametsoc.org/view/journals/mwre/146/11/mwr-d-18-0177.1.xml},
  urldate = {2022-04-04},
  abstract = {Abstract The Nationwide Network of Networks (NNoN) concept was introduced by the National Research Council to address the growing need for a national mesoscale observing system and the continued advancement toward accurate high-resolution numerical weather prediction. The research test bed known as the Dallas–Fort Worth (DFW) Urban Demonstration Network was created to experiment with many kinds of mesoscale observations that could be used in a data assimilation system. Many nonconventional observations, including Earth Networks and Citizen Weather Observer Program surface stations, are combined with conventional operational data to form the test bed network. A principal component of the NNoN effort is the quantification of observation impact from several different sources of information. In this study, the GSI-based EnKF system was used together with the WRF-ARW Model to examine impacts of observations assimilated for forecasting convection initiation (CI) in the 3 April 2014 hail storm case. Data denial experiments tested the impact of high-frequency (5 min) assimilation of nonconventional data on the timing and location of CI and subsequent storm evolution. Results showed nonconventional observations were necessary to capture details in the dryline structure causing localized enhanced convergence and leading to CI. Diagnosis of denial-minus-control fields showed the cumulative influence each observing network had on the resulting CI forecast. It was found that most of this impact came from the assimilation of thermodynamic observations in sensitive areas along the dryline gradient. Accurate metadata were found to be crucial toward the future application of nonconventional observations in high-resolution assimilation and forecast systems.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/H3SXIRPJ/Gasperoni et al_2018_Assessing Impacts of the High-Frequency Assimilation of Surface Observations.pdf}
}

@inproceedings{goncalvesdegoncalves2015,
  title = {A Rapid Update Data Assimilation Cycle over {{South America}} Using {{3DVar}} and {{EnKF}}},
  booktitle = {The 20th {{International TOVS Study Conference}} ({{ITSC-20}})},
  author = {Goncalves de Goncalves, Luis G. and Sapucci, Luiz and Vendrasco, Eder and de Mattos, João Gerd and Ferreira, Camila and Khamis, Eduardo and Cruz, Nicolas},
  options = {useprefix=true},
  date = {2015},
  publisher = {{The 20th International TOVS Study Conference (ITSC-20)}},
  location = {{Lake Geneva, Wisconsin, USA}}
}

@unknown{goncalvesdegoncalves2015a,
  title = {A Rapid Update Data Assimilation Cycle over {{South America}} Using {{3DVar}} and {{EnKF}}},
  author = {Goncalves de Goncalves, Luis Gustavo and Sapucci, Luiz and Vendrasco, Eder and de Mattos, João Gerd and Ferreira, Camila and Khamis, Eduardo and Cruz, Nicolas},
  options = {useprefix=true},
  date = {2015-10},
  journaltitle = {The 20th International TOVS Study Conference (ITSC-20)},
  location = {{Lake Geneva, Wisconsin, USA}},
  doi = {DOI:10.13140/RG.2.1.5143.7205},
  eventtitle = {The 20th {{International TOVS Study Conference}} ({{ITSC-20}})},
  file = {/home/pao/Zotero/zotero-library/storage/SSLREC33/Goncalves de Goncalves et al_2015_A rapid update data assimilation cycle over South America using 3DVar and EnKF.pdf}
}

@article{grell2013,
  title = {A Scale and Aerosol Aware Stochastic Convective Parameterization for Weather and Air Quality Modeling},
  author = {Grell, G. A. and Freitas, S. R.},
  date = {2013-09-11},
  journaltitle = {Atmospheric Chemistry and Physics Discussions},
  shortjournal = {Atmos. Chem. Phys. Discuss.},
  volume = {13},
  number = {9},
  pages = {23845--23893},
  issn = {1680-7375},
  doi = {10.5194/acpd-13-23845-2013},
  url = {https://www.atmos-chem-phys-discuss.net/13/23845/2013/},
  urldate = {2020-05-21},
  abstract = {Abstract. A convective parameterization is described and evaluated that may be used in high resolution non-hydrostatic mesoscale models as well as in modeling systems with unstructured varying grid resolutions and for convection aware simulations. This scheme is based on a stochastic approach originally implemented by Grell and Devenyi (2002). Two approaches are tested on resolutions ranging from 20 to 5 km. One approach is based on spreading subsidence to neighboring grid points, the other one on a recently introduced method by Arakawa et al. (2011). Results from model intercomparisons, as well as verification with observations indicate that both the spreading of the subsidence and Arakawa's approach work well for the highest resolution runs. Because of its simplicity and its capability for an automatic smooth transition as the resolution is increased, Arakawa's approach may be preferred. Additionally, interactions with aerosols have been implemented through a CCN dependent autoconversion of cloud water to rain as well as an aerosol dependent evaporation of cloud drops. Initial tests with this newly implemented aerosol approach show plausible results with a decrease in predicted precipitation in some areas, caused by the changed autoconversion mechanism. This change also causes a significant increase of cloud water and ice detrainment near the cloud tops. Some areas also experience an increase of precipitation, most likely caused by strengthened downdrafts.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/T8AD8U7L/Grell and Freitas - 2013 - A scale and aerosol aware stochastic convective pa.pdf}
}

@article{gustafsson2018,
  title = {Survey of Data Assimilation Methods for Convective‐scale Numerical Weather Prediction at Operational Centres},
  author = {Gustafsson, Nils and Janjić, Tijana and Schraff, Christoph and Leuenberger, Daniel and Weissmann, Martin and Reich, Hendrik and Brousseau, Pierre and Montmerle, Thibaut and Wattrelot, Eric and Bučánek, Antonín and Mile, Máté and Hamdi, Rafiq and Lindskog, Magnus and Barkmeijer, Jan and Dahlbom, Mats and Macpherson, Bruce and Ballard, Sue and Inverarity, Gordon and Carley, Jacob and Alexander, Curtis and Dowell, David and Liu, Shun and Ikuta, Yasutaka and Fujita, Tadashi},
  date = {2018-04},
  journaltitle = {Quarterly Journal of the Royal Meteorological Society},
  shortjournal = {Q.J.R. Meteorol. Soc.},
  volume = {144},
  number = {713},
  pages = {1218--1256},
  issn = {0035-9009, 1477-870X},
  doi = {10.1002/qj.3179},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/qj.3179},
  urldate = {2020-05-07},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Gustafsson/gustafsson_2018_survey_of_data_assimilation_methods_for_convective‐scale_numerical_weather.pdf}
}

@article{ha2014,
  title = {Influence of {{Surface Observations}} in {{Mesoscale Data Assimilation Using}} an {{Ensemble Kalman Filter}}},
  author = {Ha, So-Young and Snyder, Chris},
  date = {2014-04-01},
  journaltitle = {Monthly Weather Review},
  volume = {142},
  number = {4},
  pages = {1489--1508},
  issn = {0027-0644, 1520-0493},
  doi = {10.1175/MWR-D-13-00108.1},
  url = {http://journals.ametsoc.org/doi/10.1175/MWR-D-13-00108.1},
  urldate = {2021-03-19},
  abstract = {The assimilation of surface observations using an ensemble Kalman filter (EnKF) approach was successfully performed in the Advanced Research version of the Weather Research and Forecasting Model (WRF) coupled with the Data Assimilation Research Testbed (DART) system. The mesoscale cycling experiment for the continuous ensemble data assimilation was verified against independent surface mesonet observations and demonstrated the positive impact on short-range forecasts over the contiguous U.S. (CONUS) domain throughout the month-long period of June 2008. The EnKF assimilation of surface observations was found useful for systematically improving the simulation of the depth and the structure of the planetary boundary layer (PBL) and the reduction of surface bias errors. These benefits were extended above PBL and resulted in a better precipitation forecast for up to 12 h. With the careful specification of observation errors, not only the reliability of the ensemble system but also the quality of the following forecast was improved, especially in moisture. In this retrospective case study of a squall line, assimilation of surface observations produced analysis increments consistent with the structure and dynamics of the boundary layer. As a result, it enhanced the horizontal gradient of temperature and moisture across the frontal system to provide a favorable condition for the convective initiation and the following heavy rainfall prediction in the Oklahoma Panhandle. Even with the assimilation of upper-level observations, the analysis without the assimilation of surface observations simulated a surface cold front that was much weaker and slower than observed.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/LF84MK49/Ha and Snyder - 2014 - Influence of Surface Observations in Mesoscale Dat.pdf}
}

@report{han2006,
  title = {{{JCSDA Community Radiative Transfer Model}} ({{CRTM}})—Version 1},
  author = {Han, Y and Van Delst, Paul and Liu, Q and Weng, F. and Yan, B. and Treadon, Russ and Derber, John},
  date = {2006},
  series = {{{NOAA Technical Report NESDIS}} 122},
  pages = {40},
  location = {{Washington, D.C.}},
  url = {https://repository.library.noaa.gov/view/noaa/1157/noaa_1157_DS1.pdf}
}

@article{hong2006,
  title = {A {{New Vertical Diffusion Package}} with an {{Explicit Treatment}} of {{Entrainment Processes}}},
  author = {Hong, Song-You and Noh, Yign and Dudhia, Jimy},
  date = {2006-09},
  journaltitle = {Monthly Weather Review},
  shortjournal = {Mon. Wea. Rev.},
  volume = {134},
  number = {9},
  pages = {2318--2341},
  issn = {0027-0644, 1520-0493},
  doi = {10.1175/MWR3199.1},
  url = {http://journals.ametsoc.org/doi/10.1175/MWR3199.1},
  urldate = {2020-05-21},
  abstract = {This paper proposes a revised vertical diffusion package with a nonlocal turbulent mixing coefficient in the planetary boundary layer (PBL). Based on the study of Noh et al. and accumulated results of the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm that is suitable for weather forecasting and climate prediction models is developed. The major ingredient of the revision is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme is found to improve several features compared with the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, which alleviates the well-known problems in the MediumRange Forecast (MRF) PBL. Excessive mixing in the mixed layer in the presence of strong winds is resolved. Overly rapid growth of the PBL in the case of the Hong and Pan is also rectified. The scheme has been successfully implemented in the Weather Research and Forecast model producing a more realistic structure of the PBL and its development. In a case study of a frontal tornado outbreak, it is found that some systematic biases of the large-scale features such as an afternoon cold bias at 850 hPa in the MRF PBL are resolved. Consequently, the new scheme does a better job in reproducing the convective inhibition. Because the convective inhibition is accurately predicted, widespread light precipitation ahead of a front, in the case of the MRF PBL, is reduced. In the frontal region, the YSU PBL scheme improves some characteristics, such as a double line of intense convection. This is because the boundary layer from the YSU PBL scheme remains less diluted by entrainment leaving more fuel for severe convection when the front triggers it.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/3QCV34KC/Hong et al. - 2006 - A New Vertical Diffusion Package with an Explicit .pdf}
}

@article{hong2006a,
  title = {The {{WRF Single Moment}} 6-{{Class Microphysics Scheme}} ({{WSM6}})},
  author = {Hong, Song-You and Kim, Ju-Hye and Lim, Jeong-ock and Dudhia, Jimy},
  date = {2006-03},
  journaltitle = {Journal of the Korean Meteorological Society},
  volume = {42},
  pages = {129--151}
}

@report{hu2018,
  title = {Grid-Point {{Statistical Interpolation}} ({{GSI}}) {{User}}'s {{Guide Version}} 3.7},
  author = {Hu, Ming and Ge, Guoqing and Zhou, Chunhua and Stark, Don and Shao, Hui and Newman, Kathryn and Beck, Jeff and Zhang, Xin},
  date = {2018},
  pages = {149},
  institution = {{Developmental Testbed Center}},
  url = {https://dtcenter.org/community-code/gridpoint-statistical-interpolation-gsi/documentation}
}

@report{huffman2018,
  title = {{{NASA Global Precipitation Measurement}} ({{GPM}}) {{Integrated Multi-satellitE Retrievals}} for {{GPM}} ({{IMERG}})},
  author = {Huffman, George and Bolvin, David and Braithwaite, Dan and Hsu, Kuolin and Joyce, Robert and Kidd, Christopher and Nelkin, Eric and Sorooshian, S. and Tan, J. and Xie,, Pingping},
  date = {2018-02-07},
  pages = {35},
  institution = {{National Aeronautics and Space Administration (NASA)}},
  url = {https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/IMERG_ATBD_V5.pdf},
  urldate = {2020-06-23},
  file = {/home/pao/Zotero/zotero-library/storage/XU5K3YXN/IMERG_ATBD_V5.pdf}
}

@article{hunt2007,
  title = {Efficient Data Assimilation for Spatiotemporal Chaos: {{A}} Local Ensemble Transform {{Kalman}} Filter},
  shorttitle = {Efficient Data Assimilation for Spatiotemporal Chaos},
  author = {Hunt, Brian R. and Kostelich, Eric J. and Szunyogh, Istvan},
  date = {2007-06},
  journaltitle = {Physica D: Nonlinear Phenomena},
  shortjournal = {Physica D: Nonlinear Phenomena},
  volume = {230},
  number = {1-2},
  pages = {112--126},
  issn = {01672789},
  doi = {10.1016/j.physd.2006.11.008},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0167278906004647},
  urldate = {2020-05-07},
  abstract = {Data assimilation is an iterative approach to the problem of estimating the state of a dynamical system using both current and past observations of the system together with a model for the system’s time evolution. Rather than solving the problem from scratch each time new observations become available, one uses the model to “forecast” the current state, using a prior state estimate (which incorporates information from past data) as the initial condition, then uses current data to correct the prior forecast to a current state estimate. This Bayesian approach is most effective when the uncertainty in both the observations and in the state estimate, as it evolves over time, are accurately quantified. In this article, we describe a practical method for data assimilation in large, spatiotemporally chaotic systems. The method is a type of “ensemble Kalman filter”, in which the state estimate and its approximate uncertainty are represented at any given time by an ensemble of system states. We discuss both the mathematical basis of this approach and its implementation; our primary emphasis is on ease of use and computational speed rather than improving accuracy over previously published approaches to ensemble Kalman filtering. We include some numerical results demonstrating the efficiency and accuracy of our implementation for assimilating real atmospheric data with the global forecast model used by the US National Weather Service.},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Hunt/hunt_2007_efficient_data_assimilation_for_spatiotemporal_chaos_-_a_local_ensemble.pdf;/home/pao/Zotero/zotero-library/storage/472C7IRG/Hunt et al. - 2007 - Efficient data assimilation for spatiotemporal cha.pdf}
}

@article{iacono2008,
  title = {Radiative Forcing by Long-Lived Greenhouse Gases: {{Calculations}} with the {{AER}} Radiative Transfer Models},
  shorttitle = {Radiative Forcing by Long-Lived Greenhouse Gases},
  author = {Iacono, Michael J. and Delamere, Jennifer S. and Mlawer, Eli J. and Shephard, Mark W. and Clough, Shepard A. and Collins, William D.},
  date = {2008-07-02},
  journaltitle = {Journal of Geophysical Research},
  shortjournal = {J. Geophys. Res.},
  volume = {113},
  number = {D13},
  pages = {D13103},
  issn = {0148-0227},
  doi = {10.1029/2008JD009944},
  url = {http://doi.wiley.com/10.1029/2008JD009944},
  urldate = {2020-05-21},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/5QJDTM2M/Iacono et al. - 2008 - Radiative forcing by long-lived greenhouse gases .pdf}
}

@article{irving2016,
  title = {A {{Minimum Standard}} for {{Publishing Computational Results}} in the {{Weather}} and {{Climate Sciences}}},
  author = {Irving, Damien},
  date = {2016-07-01},
  journaltitle = {Bulletin of the American Meteorological Society},
  volume = {97},
  number = {7},
  pages = {1149--1158},
  publisher = {{American Meteorological Society}},
  issn = {0003-0007, 1520-0477},
  doi = {10.1175/BAMS-D-15-00010.1},
  url = {https://journals.ametsoc.org/view/journals/bams/97/7/bams-d-15-00010.1.xml},
  urldate = {2022-07-21},
  abstract = {Abstract Weather and climate science has undergone a computational revolution in recent decades, to the point where all modern research relies heavily on software and code. Despite this profound change in the research methods employed by weather and climate scientists, the reporting of computational results has changed very little in relevant academic journals. This lag has led to something of a reproducibility crisis, whereby it is impossible to replicate and verify most of today’s published computational results. While it is tempting to simply decry the slow response of journals and funding agencies in the face of this crisis, there are very few examples of reproducible weather and climate research upon which to base new communication standards. In an attempt to address this deficiency, this essay describes a procedure for reporting computational results that was employed in a recent Journal of Climate paper. The procedure was developed to be consistent with recommended computational best practices and seeks to minimize the time burden on authors, which has been identified as the most important barrier to publishing code. It should provide a starting point for weather and climate scientists looking to publish reproducible research, and it is proposed that journals could adopt the procedure as a minimum standard.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/R2YI2G4U/Irving_2016_A Minimum Standard for Publishing Computational Results in the Weather and.pdf}
}

@article{janjic1994,
  title = {The {{Step-Mountain Eta Coordinate Model}}: {{Further Developments}} of the {{Convection}}, {{Viscous Sublayer}}, and {{Turbulence Closure Schemes}}},
  shorttitle = {The {{Step-Mountain Eta Coordinate Model}}},
  author = {Janjić, Zaviša I.},
  date = {1994-05-01},
  journaltitle = {Monthly Weather Review},
  shortjournal = {Mon. Wea. Rev.},
  volume = {122},
  number = {5},
  pages = {927--945},
  publisher = {{American Meteorological Society}},
  issn = {0027-0644},
  doi = {10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2},
  url = {https://journals.ametsoc.org/doi/10.1175/1520-0493%281994%29122%3C0927%3ATSMECM%3E2.0.CO%3B2},
  urldate = {2020-05-21},
  abstract = {The step-mountain eta model has shown a surprising skill in forecasting severe storms. Much of the credit for this should be given to the Betts and Miller (hereafter referred to as BM) convection scheme and the Mellor-Yamada (hereafter referred to as MY) planetary boundary layer (PBL) formulation. However, the eta model was occasionally producing heavy spurious precipitation over warm water, as well as widely spread light precipitation over oceans. In addition, the convective forcing, particularly the shallow one, could lead to negative entropy changes. As the possible causes of the problems, the convection scheme, the processes at the air-water interface, and the MY level 2 and level 2.5 PBL schemes were reexamined. A major revision of the BM scheme was made, a new marine viscous sublayer scheme was designed, and the MY schemes were retuned. The deep convective regimes are postulated to be characterized by a parameter called “cloud efficiency.” The relaxation time is extended for low cloud efficiencies and vice versa. It is also postulated that there is a range of reference equilibrium states. The specific reference state is chosen depending on the cloud efficiency. The treatment of the shallow cloud tops was modified, and the shallow reference humidity profiles are specified requiring that the entropy change be nonnegative. Over the oceans there are two layers: (a) a viscous sublayer with the vertical transports determined by the molecular diffusion, and (b) a layer above it with the vertical transports determined by the turbulence. The viscous sublayer operates in different regimes depending on the roughness Reynolds number. The MY level 2.5 turbulent kinetic energy (TKE) is initialized from above in the PBL, so that excessive TKE is dissipated at most places during the PBL spinup. The method for calculating the MY level 2.5 master length scale was rectified. To demonstrate the effects of the new schemes for the deep convection and the viscous sublayer, tests were made using two summer cases: one with heavy spurious precipitation, and another with a successful 36-h forecast of a tropical storm. The new schemes had dramatic positive impacts on the case with the spurious precipitation. The results were also favorable in the tropical storm case. The developments presented here were incorporated into the eta model in 1990. The details of further research will be reported elsewhere. The eta model became operational at the National Meteorological Center, Washington, D.C., in June 1993.},
  file = {/home/pao/Dropbox/Papers Zotero/Janjić/janjić_1994_the_step-mountain_eta_coordinate_model_-_further_developments_of_the_convection,.pdf}
}

@article{jones2013,
  title = {Assimilation of {{Satellite Infrared Radiances}} and {{Doppler Radar Observations}} during a {{Cool Season Observing System Simulation Experiment}}},
  author = {Jones, Thomas A. and Otkin, Jason A. and Stensrud, David J. and Knopfmeier, Kent},
  date = {2013-10},
  journaltitle = {Monthly Weather Review},
  shortjournal = {Mon. Wea. Rev.},
  volume = {141},
  number = {10},
  pages = {3273--3299},
  issn = {0027-0644, 1520-0493},
  doi = {10.1175/MWR-D-12-00267.1},
  url = {http://journals.ametsoc.org/doi/10.1175/MWR-D-12-00267.1},
  urldate = {2020-05-07},
  abstract = {An observing system simulation experiment is used to examine the impact of assimilating water vapor–sensitive satellite infrared brightness temperatures and Doppler radar reflectivity and radial velocity observations on the analysis accuracy of a cool season extratropical cyclone. Assimilation experiments are performed for four different combinations of satellite, radar, and conventional observations using an ensemble Kalman filter assimilation system. Comparison with the high-resolution ‘‘truth’’ simulation indicates that the joint assimilation of satellite and radar observations reduces errors in cloud properties compared to the case in which only conventional observations are assimilated. The satellite observations provide the most impact in the mid- to upper troposphere, whereas the radar data also improve the cloud analysis near the surface and aloft as a result of their greater vertical resolution and larger overall sample size. Errors in the wind field are also significantly reduced when radar radial velocity observations were assimilated. Overall, assimilating both satellite and radar data creates the most accurate model analysis, which indicates that both observation types provide independent and complimentary information and illustrates the potential for these datasets for improving mesoscale model analyses and ensuing forecasts.},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Jones/jones_2013_assimilation_of_satellite_infrared_radiances_and_doppler_radar_observations.pdf}
}

@article{kain2004,
  title = {The {{Kain}}–{{Fritsch Convective Parameterization}}: {{An Update}}},
  author = {Kain, John S},
  date = {2004},
  journaltitle = {JOURNAL OF APPLIED METEOROLOGY},
  volume = {43},
  pages = {12},
  abstract = {Numerous modifications to the Kain–Fritsch convective parameterization have been implemented over the last decade. These modifications are described, and the motivating factors for the changes are discussed. Most changes were inspired by feedback from users of the scheme (primarily numerical modelers) and interpreters of the model output (mainly operational forecasters). The specific formulation of the modifications evolved from an effort to produce desired effects in numerical weather prediction while also rendering the scheme more faithful to observations and cloud-resolving modeling studies.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/AN75QC9M/Kain - 2004 - The Kain–Fritsch Convective Parameterization An U.pdf}
}

@article{liang2019,
  title = {Multi-{{Grid Nesting Ability}} to {{Represent Convections Across}} the {{Gray Zone}}},
  author = {Liang, Xin-Zhong and Li, Qi and Mei, Haixia and Zeng, Mingjian},
  date = {2019},
  journaltitle = {Journal of Advances in Modeling Earth Systems},
  volume = {11},
  number = {12},
  pages = {4352--4376},
  issn = {1942-2466},
  doi = {10.1029/2019MS001741},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2019MS001741},
  urldate = {2022-08-22},
  abstract = {This study investigated the multi-grid nesting ability of a limited area model to effectively represent convections across the gray zone, the resolution around 1–10 km where both cumulus parameterization and explicit convection are problematic. It evaluated the sensitivity of Meiyu rainfall forecasts in Jiangsu, China to model configurations of grid nesting and convection treatment. These configurations consisted of grid spacings from 30, 15, 9, 5, 3 to 1 km, single or double or triple nested grids, and the traditional Kain-Fritsch (KF) or scale-aware Grell-Freitas cumulus parameterization or the explicit convection in the outer domain [O]. In single nesting [O], coarse grids ({$>$}3–5 km) required parameterization to represent organized cumuli, while explicitly resolving convections in finer grids were necessary to improve forecasts. In double nesting [O] using cumulus parameterization at 30–9 km with the inner domain [I] using explicit convection at 1 km, the nesting ratio could be as large as 30 without significantly impacting [I] forecasts. This suggests a pragmatic approach to avoid the challenge in representing convections across the gray zone. Using Grell-Freitas may improve mean [O] rainfall distributions, but this was not true for [I] forecasts due to counter errors in space and time, which were larger than using KF and at coarser grids. Triple nesting with a middle 3- or 5-km grid was unnecessary and could even degrade [I] forecasts. Nesting [O] using KF to parameterize cumuli at 15 km with [I] explicitly resolving convections at 1 km achieved the best overall rainfall forecast in Jiangsu.},
  langid = {english},
  keywords = {cumulus parameterization,explicit convection,gray zone,grid nesting,precipitation forecast skill,scale-aware},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019MS001741},
  file = {/home/pao/Zotero/zotero-library/storage/GID8LID6/Liang et al_2019_Multi-Grid Nesting Ability to Represent Convections Across the Gray Zone.pdf}
}

@article{lim2014,
  title = {Assimilation of Clear Sky {{Atmospheric Infrared Sounder}} Radiances in Short-Term Regional Forecasts Using Community Models},
  author = {Lim, Agnes H. and Jung, James A. and Huang, Hung-Lung A. and Ackerman, Steven A. and Otkin, Jason A.},
  date = {2014-04},
  journaltitle = {Journal of Applied Remote Sensing},
  shortjournal = {JARS},
  volume = {8},
  number = {1},
  pages = {083655},
  publisher = {{SPIE}},
  issn = {1931-3195, 1931-3195},
  doi = {10.1117/1.JRS.8.083655},
  url = {https://www.spiedigitallibrary.org/journals/journal-of-applied-remote-sensing/volume-8/issue-1/083655/Assimilation-of-clear-sky-Atmospheric-Infrared-Sounder-radiances-in-short/10.1117/1.JRS.8.083655.full},
  urldate = {2022-08-24},
  abstract = {Regional assimilation experiments of clear-sky Atmospheric Infrared Sounder (AIRS) radiances were performed using the gridpoint statistical interpolation three-dimensional variational assimilation system coupled to the weather research and forecasting model. The data assimilation system and forecast model used in this study are separate community models; it cannot be assumed that the coupled systems work optimally. Tuning was performed on the data assimilation system and forecast model. Components tuned included the background error covariance matrix, the satellite radiance bias correction, the quality control procedures for AIRS radiances, the forecast model resolution, and the infrared channel selection. Assimilation metrics and diagnostics from the assimilation system were used to identify problems when combining separate systems. Forecasts initiated from analyses after assimilation were verified with model analyses, rawinsondes, nonassimilated satellite radiances, and 24 h–accumulated precipitation. Assimilation of clear sky AIRS radiances showed the largest improvement in temperature and radiance brightness temperature bias when compared with rawinsondes and satellite observations, respectively. Precipitation skill scores displayed minor changes with AIRS radiance assimilation. The 00 and 12 coordinated universal time (UTC) forecasts were typically of better quality than the 06 and 18 UTC forecasts, possibly due to the amount of AIRS data available for each assimilation cycle.}
}

@article{lin2017a,
  title = {Satellite {{Radiance Data Assimilation}} within the {{Hourly Updated Rapid Refresh}}},
  author = {Lin, Haidao and Weygandt, Stephen S. and Benjamin, Stanley G. and Hu, Ming},
  date = {2017-08-01},
  journaltitle = {Weather and Forecasting},
  shortjournal = {Wea. Forecasting},
  volume = {32},
  number = {4},
  pages = {1273--1287},
  publisher = {{American Meteorological Society}},
  issn = {0882-8156},
  doi = {10.1175/WAF-D-16-0215.1},
  url = {https://journals.ametsoc.org/waf/article/32/4/1273/41099/Satellite-Radiance-Data-Assimilation-within-the},
  urldate = {2020-06-18},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Lin/lin_2017_satellite_radiance_data_assimilation_within_the_hourly_updated_rapid_refresh.pdf}
}

@article{maejima2019,
  title = {Impact of {{Dense}} and {{Frequent Surface Observations}} on 1-{{Minute-Update Severe Rainstorm Prediction}}: {{A Simulation Study}}},
  shorttitle = {Impact of {{Dense}} and {{Frequent Surface Observations}} on 1-{{Minute-Update Severe Rainstorm Prediction}}},
  author = {Maejima, Yasumitsu and Miyoshi, Takemasa and Kunii, Masaru and Seko, Hiromu and Sato, Kae},
  date = {2019},
  journaltitle = {Journal of the Meteorological Society of Japan. Ser. II},
  volume = {97},
  number = {1},
  pages = {253--273},
  doi = {10.2151/jmsj.2019-014},
  abstract = {This study aims to investigate the potential impact of surface observations with a high spatial and temporal density on a local heavy rainstorm prediction. A series of Observing System Simulation Experiments (OSSEs) are performed using the Local Ensemble Transform Kalman Filter with the Japan Meteorological Agency non-hydrostatic model at 1-km resolution and with 1-minute update cycles. For the nature run of the OSSEs, a 100-m resolution simulation is performed for the heavy rainstorm case that caused five fatalities in Kobe, Japan on July 28, 2008. Synthetic radar observation data, both reflectivity and Doppler velocity, are generated at 1-km resolution every minute from the 100-m resolution nature run within a 60-km range, simulating the phased array weather radar (PAWR) at Osaka University. The control experiment assimilates only the radar data, and two sensitivity experiments are performed to investigate the impact of additional surface observations obtained every minute at 8 and 167 stations in Kobe. The results show that the dense and frequent surface observations have a significant positive impact on the analyses and forecasts of the local heavy rainstorm, although the number of assimilated observations is three orders of magnitude less than the PAWR data. Equivalent potential temperature and convergence at the low levels are improved, contributing to intensified convective cells and local heavy rainfalls.},
  keywords = {local ensemble transform Kalman filter,rainfall prediction,surface data assimilation},
  file = {/home/pao/Zotero/zotero-library/storage/UARWIH3E/Maejima et al_2019_Impact of Dense and Frequent Surface Observations on 1-Minute-Update Severe.pdf}
}

@article{maldonado2020,
  title = {Parameter {{Sensitivity}} of the {{WRF}}–{{LETKF System}} for {{Assimilation}} of {{Radar Observations}}: {{Imperfect-Model Observing System Simulation Experiments}}},
  shorttitle = {Parameter {{Sensitivity}} of the {{WRF}}–{{LETKF System}} for {{Assimilation}} of {{Radar Observations}}},
  author = {Maldonado, Paula and Ruiz, Juan and Saulo, Celeste},
  date = {2020-08-01},
  journaltitle = {Weather and Forecasting},
  volume = {35},
  number = {4},
  pages = {1345--1362},
  publisher = {{American Meteorological Society}},
  issn = {1520-0434, 0882-8156},
  doi = {10.1175/WAF-D-19-0161.1},
  url = {https://journals.ametsoc.org/view/journals/wefo/35/4/wafD190161.xml},
  urldate = {2022-07-12},
  abstract = {Abstract Specification of suitable initial conditions to accurately forecast high-impact weather events associated with intense thunderstorms still poses a significant challenge for convective-scale forecasting. Radar data assimilation has been showing encouraging results to produce an accurate estimate of the state of the atmosphere at the mesoscale, as it combines high-spatiotemporal-resolution observations with convection-permitting numerical weather prediction models. However, many open questions remain regarding the configuration of state-of-the-art data assimilation systems at the mesoscale and their potential impact upon short-range weather forecasts. In this work, several observing system simulation experiments of a mesoscale convective system were performed to assess the sensitivity of the local ensemble transform Kalman filter to both relaxation-to-prior spread (RTPS) inflation and horizontal localization of the error covariance matrix. Realistic large-scale forcing and model errors have been taken into account in the simulation of reflectivity and Doppler velocity observations. Overall, the most accurate analyses in terms of RMSE were produced with a relatively small horizontal localization cutoff radius (\textasciitilde 3.6–7.3 km) and large RTPS inflation parameter (\textasciitilde 0.9–0.95). Additionally, the impact of horizontal localization on short-range ensemble forecast was larger compared to inflation, almost doubling the lead times up to which the effect of using a more accurate state to initialize the forecast persisted.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/A2AZWDJI/Maldonado et al_2020_Parameter Sensitivity of the WRF–LETKF System for Assimilation of Radar.pdf}
}

@article{maldonado2021,
  title = {Sensitivity to {{Initial}} and {{Boundary Perturbations}} in {{Convective-Scale Ensemble-Based Data Assimilation}}: {{Imperfect-Model OSSEs}}},
  shorttitle = {Sensitivity to {{Initial}} and {{Boundary Perturbations}} in {{Convective-Scale Ensemble-Based Data Assimilation}}},
  author = {Maldonado, Paula and Ruiz, Juan and Saulo, Celeste},
  date = {2021},
  journaltitle = {SOLA},
  shortjournal = {SOLA},
  volume = {17},
  number = {0},
  pages = {96--102},
  issn = {1349-6476},
  doi = {10.2151/sola.2021-015},
  url = {https://www.jstage.jst.go.jp/article/sola/17/0/17_2021-015/_article},
  urldate = {2021-06-24},
  abstract = {This study investigates the impact of applying different types of initial and boundary perturbations for convective-scale ensemble data assimilation systems. Several observing system simulation experiments (OSSEs) were performed with a 2-km horizontal resolution, considering a realistic environment, taking model error into account, and combining different perturbations’ types with warm/cold start initialization. Initial perturbations produce a longlasting impact on the analysis’s quality, particularly for variables not directly linked to radar observations. Warm-started experiments provide the most accurate analysis and forecasts and a more consistent ensemble spread across the different spatial scales. Random small-scale perturbations exhibit similar results, although a longer convergence time is required to up-and-downscale the initial perturbations to obtain a similar error reduction. Adding random large-scale perturbations reduce the error in the first assimil­ ation cycles but produce a slightly detrimental effect afterward.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/23UW93FF/Maldonado et al. - 2021 - Sensitivity to Initial and Boundary Perturbations .pdf}
}

@article{mallick2020,
  title = {Assimilation of {{GOES-16}} Satellite Derived Winds into the Warn-on-Forecast System},
  author = {Mallick, Swapan and Jones, Thomas A.},
  date = {2020-11-15},
  journaltitle = {Atmospheric Research},
  shortjournal = {Atmospheric Research},
  volume = {245},
  pages = {105131},
  issn = {0169-8095},
  doi = {10.1016/j.atmosres.2020.105131},
  url = {https://www.sciencedirect.com/science/article/pii/S016980952031067X},
  urldate = {2022-04-10},
  abstract = {The Advanced Baseline Imager (ABI) onboard the GOES-R series of geostationary satellites provides an opportunity to generate high-resolution satellite derived wind vectors over continental United States not possible from previous satellites. This study investigates the quality and the impact of assimilating satellite-derived winds (or Atmospheric Motion Vectors, AMVs) from the GOES-16 geostationary satellite on high-impact weather forecasts using the NOAA's ensemble based Warn-on-Forecast System (WoFS). The WoFS runs at convection allowing scales (\textasciitilde 3~km) with a 15-min cycling frequency assimilating all available observations including conventional, radar and GOES-16 cloud water path retrievals over a limited area domain. Four severe weather events during 2018 are considered in this study to assess the potential impacts of assimilating GOES-16 AMVs into the WoFS. A total of eight experiments performed, four that assimilate AMV data and the remaining four do not with all including conventional, radar, and other satellite data. This research represents the first step to assimilated high-resolution satellite derived winds into the convective-allowing ensemble data assimilation system. The results show that the overall impact of assimilation of AMVs is small, but positive for probabilistic forecasts of reflectivity objects.},
  langid = {english},
  keywords = {Atmospheric Motion Vectors,Data Assimilation,GOES-R,Numerical Weather Prediction,Warn-on-Forecast}
}

@incollection{markowski2010,
  title = {Organization of {{Isolated Convection}}},
  booktitle = {Mesoscale {{Meteorology}} in {{Midlatitudes}}},
  author = {Markowski, Paul and Richardson, Yvette},
  date = {2010},
  pages = {201--244},
  publisher = {{John Wiley \& Sons, Ltd}},
  doi = {10.1002/9780470682104.ch8},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9780470682104.ch8},
  urldate = {2021-07-19},
  abstract = {This chapter contains sections titled: Role of vertical wind shear Single-cell convection Multicellular convection Supercellular convection},
  isbn = {978-0-470-68210-4},
  langid = {english},
  keywords = {convective storms,linear theory of midlevel mesocyclogenesis,multicellular convection,organization of isolated convection,organized in a variety of ways,role of vertical wind shear,single-cell convection,spectrum of storm types - as a function of vertical wind shear,supercellular convection,the most common form of convection in midlatitudes},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/9780470682104.ch8}
}

@article{matsudo2015,
  title = {Verification of {{WRF-ARW}} Convective-Resolving Forecasts over {{Southeastern South America}}},
  author = {Matsudo, C. and García Skabar, Yanina and Ruiz, Juan and Vidal, Luciano and Salio, Paola},
  date = {2015-07-01},
  journaltitle = {Mausam},
  shortjournal = {Mausam},
  volume = {66},
  pages = {445--456},
  abstract = {During November-December 2012, high-resolution (4 km-38 vertical levels), convection-allowing 48 hours WRF-ARW forecasts were produced at the National Weather Service of Argentina. The aim of this paper is to evaluate hourly quantitative precipitation forecasts to assess the model performance on representing its location, intensity, spatial variability and diurnal cycle. The focus is on the central-east region of Argentina and south of Brazil. The study is based on a combination of visual comparison of forecasted and estimates accumulated precipitation fields and objective scores calculated employing 8-km resolution CMORPH (CPC MORPHing technique) satellite rainfall estimations. Additional insight is gained by examining an organized convective event occurred during 6th and 7th December, 2012. As a complement, radar data is considered to evaluate convective features using simulated model reflectivity. Results show that WHIP model forecast captures quite well the position and timing of the major convective events, even though the magnitude of events was underestimated. Total amounts averaged over the verification domain are underestimated as well as the areal coverage for small thresholds. In general, results suggest that convection-allowing WRF-ARW model has the potential to improve short range forecasts over the region although it should be evaluated over a longer period of time.},
  file = {/home/pao/Zotero/zotero-library/storage/2AKX9SDX/Matsudo et al_2015_Verification of WRF-ARW convective-resolving forecasts over Southeastern South.pdf}
}

@article{matsudo2021,
  title = {Verificación de los pronósticos del esquema determinístico del modelo WRF para el año 2020},
  author = {Matsudo, Cynthia and Salles, María Alejandra and García Skabar, Yanina},
  date = {2021-07},
  publisher = {{Servicio Meteorológico Nacional. Dirección de Productos de Modelación Ambiental y Sensores Remotos. Dirección Nacional de Ciencia e Innovación en Productos y Servicios}},
  url = {http://repositorio.smn.gob.ar/handle/20.500.12160/1595},
  urldate = {2022-07-26},
  abstract = {Esta nota técnica se desarrolla en el marco del Plan de Verificación Transversal de pronóstico del  SMN. Aquí se presentan los resultados de la verificación de los pronósticos operativos del modelo  WRF del esquema determinístico correspondientes al año 2020. Las variables que se verifican son  las siguientes: temperatura a 2m, temperatura de rocío a 2m, temperatura mínima y máxima diaria,  precipitación acumulada en 24 horas y magnitud del viento a 10m. Las observaciones para la  verificación provienen de la red de estaciones de superficie del SMN. Se comparan los resultados  con los correspondientes al modelo GFS. En líneas generales todas las variables pronosticadas  muestran un desempeño similar o superior a los pronósticos obtenidos con GFS. La calibración de  las temperaturas demuestra una mejora respecto de las mismas sin calibrar. Asimismo se puede ver  que la calidad del pronóstico de la temperatura máxima es mejor que la de la temperatura mínima.  Por otro lado, esta verificación contribuyó a detectar errores importantes en el pronóstico de la  temperatura de rocío así como los de la magnitud del viento.},
  langid = {spanish},
  annotation = {Accepted: 2021-07-05T19:26:04Z},
  file = {/home/pao/Zotero/zotero-library/storage/T8ES8VZS/Matsudo et al_2021_Verificación de los pronósticos del esquema determinístico del modelo WRF para.pdf}
}

@article{miyoshi2012a,
  title = {Using {{AIRS}} Retrievals in the {{WRF-LETKF}} System to Improve Regional Numerical Weather Prediction},
  author = {Miyoshi, Takemasa and Kunii, Masaru},
  date = {2012-12-01},
  journaltitle = {Tellus A: Dynamic Meteorology and Oceanography},
  volume = {64},
  number = {1},
  pages = {18408},
  publisher = {{Taylor \& Francis}},
  issn = {null},
  doi = {10.3402/tellusa.v64i0.18408},
  url = {https://doi.org/10.3402/tellusa.v64i0.18408},
  urldate = {2020-10-20},
  abstract = {In addition to conventional observations, atmospheric temperature and humidity profile data from the Atmospheric Infrared Sounder (AIRS) Version 5 retrieval products are assimilated into the Weather Research and Forecasting (WRF) model, using the local ensemble transform Kalman filter (LETKF). Although a naive assimilation of all available quality-controlled AIRS retrieval data yields an inferior analysis, the additional enhancements of adaptive inflation and horizontal data thinning result in a general improvement of numerical weather prediction skill due to AIRS data. In particular, the adaptive inflation method is enhanced so that it no longer assumes temporal homogeneity of the observing network and allows for a better treatment of the temporally inhomogeneous AIRS data. Results indicate that the improvements due to AIRS data are more significant in longer-lead forecasts. Forecasts of Typhoons Sinlaku and Jangmi in September 2008 show improvements due to AIRS data.},
  keywords = {data assimilation,ensemble Kalman filter,numerical weather prediction,satellite sounding data},
  annotation = {\_eprint: https://doi.org/10.3402/tellusa.v64i0.18408},
  file = {/home/pao/Dropbox/Papers Zotero/Miyoshi/miyoshi_2012_using_airs_retrievals_in_the_wrf-letkf_system_to_improve_regional_numerical.pdf}
}

@article{mlawer1997,
  title = {Radiative Transfer for Inhomogeneous Atmospheres: {{RRTM}}, a Validated Correlated-k Model for the Longwave},
  shorttitle = {Radiative Transfer for Inhomogeneous Atmospheres},
  author = {Mlawer, Eli J. and Taubman, Steven J. and Brown, Patrick D. and Iacono, Michael J. and Clough, Shepard A.},
  date = {1997},
  journaltitle = {Journal of Geophysical Research: Atmospheres},
  volume = {102},
  number = {D14},
  pages = {16663--16682},
  issn = {2156-2202},
  doi = {10.1029/97JD00237},
  url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/97JD00237},
  urldate = {2021-06-24},
  abstract = {A rapid and accurate radiative transfer model (RRTM) for climate applications has been developed and the results extensively evaluated. The current version of RRTM calculates fluxes and cooling rates for the longwave spectral region (10–3000 cm−1) for an arbitrary clear atmosphere. The molecular species treated in the model are water vapor, carbon dioxide, ozone, methane, nitrous oxide, and the common halocarbons. The radiative transfer in RRTM is performed using the correlated-k method: the k distributions are attained directly from the LBLRTM line-by-line model, which connects the absorption coefficients used by RRTM to high-resolution radiance validations done with observations. Refined methods have been developed for treating bands containing gases with overlapping absorption, for the determination of values of the Planck function appropriate for use in the correlated-k approach, and for the inclusion of minor absorbing species in a band. The flux and cooling rate results of RRTM are linked to measurement through the use of LBLRTM, which has been substantially validated with observations. Validations of RRTM using LBLRTM have been performed for the midlatitude summer, tropical, midlatitude winter, subarctic winter, and four atmospheres from the Spectral Radiance Experiment campaign. On the basis of these validations the longwave accuracy of RRTM for any atmosphere is as follows: 0.6 W m−2 (relative to LBLRTM) for net flux in each band at all altitudes, with a total (10–3000 cm−1) error of less than 1.0 W m−2 at any altitude; 0.07 K d−1 for total cooling rate error in the troposphere and lower stratosphere, and 0.75 K d−1 in the upper stratosphere and above. Other comparisons have been performed on RRTM using LBLRTM to gauge its sensitivity to changes in the abundance of specific species, including the halocarbons and carbon dioxide. The radiative forcing due to doubling the concentration of carbon dioxide is attained with an accuracy of 0.24 W m−2, an error of less than 5\%. The speed of execution of RRTM compares favorably with that of other rapid radiation models, indicating that the model is suitable for use in general circulation models.},
  langid = {english},
  annotation = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/97JD00237},
  file = {/home/pao/Zotero/zotero-library/storage/ED4X4RVI/Mlawer et al_1997_Radiative transfer for inhomogeneous atmospheres.pdf}
}

@article{nakanishi2009,
  title = {Development of an {{Improved Turbulence Closure Model}} for the {{Atmospheric Boundary Layer}}},
  author = {Nakanishi, Mikio and Niino, Hiroshi},
  date = {2009},
  journaltitle = {Journal of the Meteorological Society of Japan},
  shortjournal = {JMSJ},
  volume = {87},
  number = {5},
  pages = {895--912},
  issn = {0026-1165},
  doi = {10.2151/jmsj.87.895},
  url = {http://joi.jlc.jst.go.jp/JST.JSTAGE/jmsj/87.895?from=CrossRef},
  urldate = {2020-05-21},
  abstract = {An improved Mellor–Yamada (MY) turbulence closure model (MYNN model: Mellor–Yamada–Nakanishi–Niino model) that we have developed is summarized and its performance is demonstrated against a large-eddy simulation (LES) of a convective boundary layer. Unlike the original MY model, the MYNN model considers e¤ects of buoyancy on pressure covariances and e¤ects of stability on the turbulent length scale, with model constants determined from a LES database. One-dimensional simulations of Day 33 of the Wangara field experiment, which was conducted in a flat area of southeastern Australia in 1967, are made by the MY and MYNN models and the results are compared with horizontal-average statistics obtained from a threedimensional LES. The MYNN model improves several weak points of the MY model such as an insu‰cient growth of the convective boundary layer, and underestimates of the turbulent kinetic energy and the turbulent length scale; it reproduces fairly well the results of the LES including the vertical distributions of the mean and turbulent quantities. The improved performance of the MYNN model relies mainly on the new formulation of the turbulent length scale that realistically increases with decreasing stability, and partly on the parameterization of the pressure covariances and the expression for stability functions for third-order turbulent fluxes.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/MKCKAPSC/Nakanishi and Niino - 2009 - Development of an Improved Turbulence Closure Mode.pdf}
}

@article{necker2020,
  title = {A Convective‐scale 1,000‐member Ensemble Simulation and Potential Applications},
  author = {Necker, Tobias and Geiss, Stefan and Weissmann, Martin and Ruiz, Juan and Miyoshi, Takemasa and Lien, Guo‐Yuan},
  date = {2020-04},
  journaltitle = {Quarterly Journal of the Royal Meteorological Society},
  shortjournal = {Q.J.R. Meteorol. Soc},
  volume = {146},
  number = {728},
  pages = {1423--1442},
  issn = {0035-9009, 1477-870X},
  doi = {10.1002/qj.3744},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/qj.3744},
  urldate = {2020-05-21},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/7KKXQVDK/Necker et al. - 2020 - A convective‐scale 1,000‐member ensemble simulatio.pdf}
}

@article{nesbitt2021,
  title = {A Storm Safari in {{Subtropical South America}}: Proyecto {{RELAMPAGO}}},
  shorttitle = {A Storm Safari in {{Subtropical South America}}},
  author = {Nesbitt, Stephen W. and Salio, Paola V. and Ávila, Eldo and Bitzer, Phillip and Carey, Lawrence and Chandrasekar, V. and Deierling, Wiebke and Dominguez, Francina and Dillon, Maria Eugenia and Garcia, C. Marcelo and Gochis, David and Goodman, Steven and Hence, Deanna A. and Kosiba, Karen A. and Kumjian, Matthew R. and Lang, Timothy and Luna, Lorena Medina and Marquis, James and Marshall, Robert and McMurdie, Lynn A. and Nascimento, Ernani Lima and Rasmussen, Kristen L. and Roberts, Rita and Rowe, Angela K. and Ruiz, Juan José and Sabbas, Eliah F. M. T. São and Saulo, A. Celeste and Schumacher, Russ S. and Skabar, Yanina Garcia and Machado, Luiz Augusto Toledo and Trapp, Robert J. and Varble, Adam and Wilson, James and Wurman, Joshua and Zipser, Edward J. and Arias, Ivan and Bechis, Hernán and Grover, Maxwell A.},
  date = {2021-04-19},
  journaltitle = {Bulletin of the American Meteorological Society},
  volume = {-1},
  pages = {1--64},
  publisher = {{American Meteorological Society}},
  issn = {0003-0007, 1520-0477},
  doi = {10.1175/BAMS-D-20-0029.1},
  url = {https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-20-0029.1/BAMS-D-20-0029.1.xml},
  urldate = {2021-05-12},
  abstract = {{$<$}section class="abstract"{$><$}h2 class="abstractTitle text-title my-1" id="d125981809e494"{$>$}Abstract{$<$}/h2{$><$}p{$>$}This article provides an overview of the experimental design, execution, education and public outreach, data collection, and initial scientific results from the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. RELAMPAGO was a major field campaign conducted in Córdoba and Mendoza provinces in Argentina, and western Rio Grande do Sul State in Brazil in 2018-2019 that involved more than 200 scientists and students from the US, Argentina, and Brazil. This campaign was motivated by the physical processes and societal impacts of deep convection that frequently initiates in this region, often along the complex terrain of the Sierras de Córdoba and Andes, and often grows rapidly upscale into dangerous storms that impact society. Observed storms during the experiment produced copious hail, intense flash flooding, extreme lightning flash rates and other unusual lightning phenomena, but few tornadoes. The 5 distinct scientific foci of RELAMPAGO: convection initiation, severe weather, upscale growth, hydrometeorology, and lightning and electrification are described, as are the deployment strategies to observe physical processes relevant to these foci. The campaign’s international cooperation, forecasting efforts, and mission planning strategies enabled a successful data collection effort. In addition, the legacy of RELAMPAGO in South America, including extensive multi-national education, public outreach, and social media data-gathering associated with the campaign, is summarized.{$<$}/p{$><$}/section{$>$}},
  issue = {aop},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/R9GX7TSP/Nesbitt et al_2021_A storm safari in Subtropical South America.pdf}
}

@article{otsuka2015,
  title = {Assimilation {{Experiments}} of {{MTSAT Rapid Scan Atmospheric Motion Vectors}} on a {{Heavy Rainfall Event}}},
  author = {Otsuka, Michiko and Kunii, Masaru and Seko, Hiromu and Shimoji, Kazuki and Hayashi, Masahiro and Yamashita, Koji},
  date = {2015},
  journaltitle = {Journal of the Meteorological Society of Japan. Ser. II},
  volume = {93},
  number = {4},
  pages = {459--475},
  doi = {10.2151/jmsj.2015-030},
  abstract = {Atmospheric motion vectors (AMVs) derived from 5-min rapid scan (RS) imagery of the Multi-functional Transport Satellite are expected to capture small-scale distributions of airflows better than typical AMVs derived from 30-min imagery because the observation interval of RS-AMV is shorter. The impact of these high-frequency data on the numerical forecasting of a heavy rainfall near a stationary front was investigated by conducting data assimilation experiments. As a part of preparation for the assimilation, RS-AMVs were compared with the first-guess field obtained from the Japan Meteorological Agency (JMA) nonhydrostatic model (NHM). The comparison result indicated that the RS-AMVs were of good quality and could be used in the JMA’s operational NHM with 4D variational data assimilation (JNoVA). Assimilation experiments investigating a heavy rainfall event were conducted using different lengths of assimilation time slot and time intervals of spatial thinning for the assimilation of the RS-AMV data. The assimilation of RS-AMVs caused the initial wind fields to enhance the upper-level divergence and low-level convergence around the front. Consequently, the forecast of the rainfall amount was increased near the front, and the verification scores were slightly improved over the control experiment in the early forecast hours.},
  keywords = {atmospheric motion vector (AMV),data assimilation,rapid scan data,satellite},
  file = {/home/pao/Zotero/zotero-library/storage/X9CPP65N/Otsuka et al_2015_Assimilation Experiments of MTSAT Rapid Scan Atmospheric Motion Vectors on a.pdf}
}

@article{ouaraini2015,
  title = {Sensitivity of Regional Ensemble Data Assimilation Spread to Perturbations of Lateral Boundary Conditions},
  author = {Ouaraini, Rachida El and Berre, Loïk and Fischer, Claude and Sayouty, El Hassan},
  date = {2015-12-01},
  journaltitle = {Tellus A: Dynamic Meteorology and Oceanography},
  volume = {67},
  number = {1},
  pages = {28502},
  publisher = {{Taylor \& Francis}},
  issn = {null},
  doi = {10.3402/tellusa.v67.28502},
  url = {https://doi.org/10.3402/tellusa.v67.28502},
  urldate = {2021-06-24},
  abstract = {The implementation of a regional ensemble data assimilation and forecasting system requires the specification of appropriate perturbations of lateral boundary conditions (LBCs), in order to simulate associated errors. The sensitivity of analysis and 6-h forecast ensemble spread to these perturbations is studied here formally and experimentally by comparing three different LBC configurations for the ensemble data assimilation system of the ALADIN-France limited-area model (LAM). While perturbed initial LBCs are provided by the perturbed LAM analyses in each ensemble, the three ensemble configurations differ with respect to LBCs used at 3- and 6-h forecast ranges, which respectively correspond to: (1) perturbed LBCs provided by the operational global ensemble data assimilation system (GLBC), which is considered as a reference configuration; (2) unperturbed LBCs (ULBC) obtained from the global deterministic model; (3) perturbed LBCs obtained by adding random draws of an error covariance model (PLBC) to the global deterministic system. A formal analysis of error and perturbation equations is first carried out, in order to provide an insight of the relative effects of observation perturbations and of LBC perturbations at different ranges, in the various ensemble configurations. Horizontal variations of time-averaged ensemble spread are then examined for 6-h forecasts. Despite the use of perturbed initial LBCs, the regional ensemble ULBC is underdispersive not only near the lateral boundaries, but also in approximately one-third of the inner area, due to advection during the data assimilation cycle. This artefact is avoided in PLBC through the additional use of non-zero LBC perturbations at 3- and 6-h ranges, and the sensitivity to the amplitude scaling of the covariance model is illustrated for this configuration. Some aspects of the temporal variation of ensemble spread and associated sensitivities to LBC perturbations are also studied. These results confirm the importance of LBC perturbations for regional ensemble data assimilation. They also indicate that perturbing initial LBC is not sufficient to obtain realistic ensemble spread, whereas this can be achieved approximately by using random covariance draws for simulating LBC errors during the forecast and associated data assimilation cycling.},
  keywords = {data assimilation,ensemble spread,lateral boundary conditions,regional ensemble},
  annotation = {\_eprint: https://doi.org/10.3402/tellusa.v67.28502},
  file = {/home/pao/Zotero/zotero-library/storage/3LY464P7/Ouaraini et al_2015_Sensitivity of regional ensemble data assimilation spread to perturbations of.pdf}
}

@article{rasmussen2014,
  title = {Severe Convection and Lightning in Subtropical {{South America}}},
  author = {Rasmussen, Kristen L. and Zuluaga, Manuel D. and Houze, Robert A.},
  date = {2014},
  journaltitle = {Geophysical Research Letters},
  volume = {41},
  number = {20},
  pages = {7359--7366},
  issn = {1944-8007},
  doi = {10.1002/2014GL061767},
  url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2014GL061767},
  urldate = {2021-05-14},
  abstract = {Satellite radar and radiometer data show that subtropical South America has the world's deepest convective storms, robust mesoscale convective systems, and very frequent large hail. We determine severe weather characteristics for the most intense precipitation features seen by satellite in this region. In summer, hail and lightning concentrate over the foothills of western Argentina. Lightning has a nocturnal maximum associated with storms having deep and mesoscale convective echoes. In spring, lightning is maximum to the east in association with storms having mesoscale structure. A tornado alley is over the Pampas, in central Argentina, distant from the maximum hail occurrence, in association with extreme storms. In summer, flash floods occur over the Andes foothills associated with storms having deep convective cores. In spring, slow-rise floods occur over the plains with storms of mesoscale dimension. This characterization of high-impact weather in South America provides crucial information for socioeconomic implications and public safety.},
  langid = {english},
  keywords = {extreme storms,flooding,hail,lightning,tornadoes,TRMM satellite},
  annotation = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2014GL061767},
  file = {/home/pao/Zotero/zotero-library/storage/58GMVR74/Rasmussen et al_2014_Severe convection and lightning in subtropical South America.pdf}
}

@article{roberts2008,
  title = {Assessing the Spatial and Temporal Variation in the Skill of Precipitation Forecasts from an {{NWP}} Model},
  author = {Roberts, Nigel},
  date = {2008},
  journaltitle = {Meteorological Applications},
  volume = {15},
  number = {1},
  pages = {163--169},
  issn = {1469-8080},
  doi = {10.1002/met.57},
  url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/met.57},
  urldate = {2020-05-26},
  abstract = {It is becoming increasingly important to be able to verify the spatial accuracy of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction (NWP) models. In this article, the fractions skill score (FSS) approach has been used to perform a scale-selective evaluation of precipitation forecasts during 2003 from the Met Office mesoscale model (12 km grid length). The investigation shows how skill varies with spatial scale, the scales over which the data assimilation (DA) adds most skill, and how the loss of that skill is dependent on both the spatial scale and the rainfall coverage being examined. Although these results come from a specific model, they demonstrate how this verification approach can provide a quantitative assessment of the spatial behaviour of new finer-resolution models and DA techniques. Copyright © 2008 Royal Meteorological Society},
  langid = {english},
  keywords = {forecasts,precipitation,scale-selective,verification},
  annotation = {\_eprint: https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/met.57},
  file = {/home/pao/Dropbox/Papers Zotero/Roberts/roberts_2008_assessing_the_spatial_and_temporal_variation_in_the_skill_of_precipitation.pdf}
}

@article{roberts2020,
  title = {What {{Does}} a {{Convection-Allowing Ensemble}} of {{Opportunity Buy Us}} in {{Forecasting Thunderstorms}}?},
  author = {Roberts, Brett and Gallo, Burkely T. and Jirak, Israel L. and Clark, Adam J. and Dowell, David C. and Wang, Xuguang and Wang, Yongming},
  date = {2020-12},
  journaltitle = {Weather and Forecasting},
  volume = {35},
  number = {6},
  pages = {2293--2316},
  issn = {0882-8156, 1520-0434},
  doi = {10.1175/WAF-D-20-0069.1},
  url = {https://journals.ametsoc.org/view/journals/wefo/35/6/WAF-D-20-0069.1.xml},
  urldate = {2021-08-31},
  abstract = {The High Resolution Ensemble Forecast v2.1 (HREFv2.1), an operational convection-allowing model (CAM) ensemble, is an ‘‘ensemble of opportunity’’ wherein forecasts from several independently designed deterministic CAMs are aggregated and postprocessed together. Multiple dimensions of diversity in the HREFv2.1 ensemble membership contribute to ensemble spread, including model core, physics parameterization schemes, initial conditions (ICs), and time lagging. In this study, HREFv2.1 forecasts are compared against the High Resolution Rapid Refresh Ensemble (HRRRE) and the Multiscale data Assimilation and Predictability (MAP) ensemble, two experimental CAM ensembles that ran during the 5-week Spring Forecasting Experiment (SFE) in spring 2018. The HRRRE and MAP are formally designed ensembles with spread achieved primarily through perturbed ICs. Verification in this study focuses on composite radar reflectivity and updraft helicity to assess ensemble performance in forecasting convective storms. The HREFv2.1 shows the highest overall skill for these forecasts, matching subjective real-time impressions from SFE participants. Analysis of the skill and variance of ensemble member forecasts suggests that the HREFv2.1 exhibits greater spread and more effectively samples model uncertainty than the HRRRE or MAP. These results imply that to optimize skill in forecasting convective storms at 1–2-day lead times, future CAM ensembles should employ either diverse membership designs or sophisticated perturbation schemes capable of representing model uncertainty with comparable efficacy.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/H532LDRN/Roberts et al. - 2020 - What Does a Convection-Allowing Ensemble of Opport.pdf}
}

@article{ruiz2010,
  title = {{{WRF Model Sensitivity}} to {{Choice}} of {{Parameterization}} over {{South America}}: {{Validation}} against {{Surface Variables}}},
  shorttitle = {{{WRF Model Sensitivity}} to {{Choice}} of {{Parameterization}} over {{South America}}},
  author = {Ruiz, Juan J. and Saulo, Celeste and Nogués-Paegle, Julia},
  date = {2010-08-01},
  journaltitle = {Monthly Weather Review},
  shortjournal = {Mon. Wea. Rev.},
  volume = {138},
  number = {8},
  pages = {3342--3355},
  publisher = {{American Meteorological Society}},
  issn = {0027-0644},
  doi = {10.1175/2010MWR3358.1},
  url = {https://journals.ametsoc.org/mwr/article/138/8/3342/71137/WRF-Model-Sensitivity-to-Choice-of},
  urldate = {2020-06-23},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Ruiz/ruiz_2010_wrf_model_sensitivity_to_choice_of_parameterization_over_south_america_-2.pdf}
}

@article{sawada2019,
  title = {Impacts of {{Assimilating High-Resolution Atmospheric Motion Vectors Derived}} from {{Himawari-8}} on {{Tropical Cyclone Forecast}} in {{HWRF}}},
  author = {Sawada, Masahiro and Ma, Zaizhong and Mehra, Avichal and Tallapragada, Vijay and Oyama, Ryo and Shimoji, Kazuki},
  date = {2019-10-01},
  journaltitle = {Monthly Weather Review},
  volume = {147},
  number = {10},
  pages = {3721--3740},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/MWR-D-18-0261.1},
  url = {https://journals.ametsoc.org/view/journals/mwre/147/10/mwr-d-18-0261.1.xml},
  urldate = {2022-04-04},
  abstract = {Abstract The impact of the assimilation of high spatial and temporal resolution atmospheric motion vectors (AMVs) on tropical cyclone (TC) forecasts has been investigated. The high-resolution AMVs are derived from the full disk scan of the new generation geostationary satellite Himawari-8. Forecast experiments for three TCs in 2016 in a western North Pacific basin are performed using the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting Model (HWRF). Two different ensemble–variational hybrid data assimilation configurations (using background error covariance created by global ensemble forecast and HWRF ensemble forecast), based on the Gridpoint Statistical Interpolation (GSI), are used for the sensitivity experiments. The results show that the inclusion of high-resolution Himawari-8 AMVs (H8AMV) can benefit the track forecast skill, especially for long-range lead times. The diagnosis of optimal steering flow indicates that the improved track forecast seems to be attributed to the improvement of initial steering flow surrounding the TC. However, the assimilation of H8AMV increases the negative intensity bias and error, especially for short-range forecast lead times. The investigation of the structural change from the assimilation of H8AMV revealed that the following two factors are likely related to this degradation: 1) an increase of inertial stability outside the radius of maximum wind (RMW), which weakens the boundary layer inflow; and 2) a drying around and outside the RMW. Assimilating H8AMV using background error covariance created from HWRF ensemble forecast contributes to a significant reduction in negative intensity bias and error, and there is a significant benefit to TC size forecast.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/X6K6R6LD/Sawada et al_2019_Impacts of Assimilating High-Resolution Atmospheric Motion Vectors Derived from.pdf}
}

@article{shao2016,
  title = {Bridging {{Research}} to {{Operations Transitions}}: {{Status}} and {{Plans}} of {{Community GSI}}},
  shorttitle = {Bridging {{Research}} to {{Operations Transitions}}},
  author = {Shao, Hui and Derber, John and Huang, Xiang-Yu and Hu, Ming and Newman, Kathryn and Stark, Donald and Lueken, Michael and Zhou, Chunhua and Nance, Louisa and Kuo, Ying-Hwa and Brown, Barbara},
  date = {2016-08-01},
  journaltitle = {Bulletin of the American Meteorological Society},
  volume = {97},
  number = {8},
  pages = {1427--1440},
  issn = {0003-0007, 1520-0477},
  doi = {10.1175/BAMS-D-13-00245.1},
  url = {https://journals.ametsoc.org/doi/10.1175/BAMS-D-13-00245.1},
  urldate = {2021-03-13},
  abstract = {Abstract             With a goal of improving operational numerical weather prediction (NWP), the Developmental Testbed Center (DTC) has been working with operational centers, including, among others, the National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), National Aeronautics and Space Administration (NASA), and the U.S. Air Force, to support numerical models/systems and their research, perform objective testing and evaluation of NWP methods, and facilitate research-to-operations transitions. This article introduces the first attempt of the DTC in the data assimilation area to help achieve this goal. Since 2009, the DTC, NCEP’s Environmental Modeling Center (EMC), and other developers have made significant progress in transitioning the operational Gridpoint Statistical Interpolation (GSI) data assimilation system into a community-based code management framework. Currently, GSI is provided to the public with user support and is open for contributions from internal developers as well as the broader research community, following the same code transition procedures. This article introduces measures and steps taken during this community GSI effort followed by discussions of encountered challenges and issues. The purpose of this article is to promote contributions from the research community to operational data assimilation capabilities and, furthermore, to seek potential solutions to stimulate such a transition and, eventually, improve the NWP capabilities in the United States.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/2RZ78BLE/Shao et al. - 2016 - Bridging Research to Operations Transitions Statu.pdf}
}

@article{singh2016,
  title = {Impact of the Assimilation of {{INSAT-3D}} Radiances on Short-Range Weather Forecasts: {{Assimilation}} of {{INSAT-3D Radiances}}},
  shorttitle = {Impact of the Assimilation of {{INSAT-3D}} Radiances on Short-Range Weather Forecasts},
  author = {Singh, Randhir and Ojha, Satya P. and Kishtawal, C. M. and Pal, P. K. and Kiran Kumar, A. S.},
  date = {2016-01},
  journaltitle = {Quarterly Journal of the Royal Meteorological Society},
  shortjournal = {Q.J.R. Meteorol. Soc.},
  volume = {142},
  number = {694},
  pages = {120--131},
  issn = {00359009},
  doi = {10.1002/qj.2636},
  url = {http://doi.wiley.com/10.1002/qj.2636},
  urldate = {2020-05-07},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Singh/singh_2016_impact_of_the_assimilation_of_insat-3d_radiances_on_short-range_weather.pdf}
}

@inproceedings{skabar2018,
  title = {Implementación del modelo WRF en alta resolución en el Servicio Meteorológico Nacional},
  author = {Skabar, Yanina GARCÍA and Matsudo, Cynthia and Hobouchian, María Paula and Ruiz, Juan and Righetti, Silvina},
  date = {2018},
  pages = {2},
  publisher = {{Servicio Meteorológico Nacional}},
  location = {{Rosario, Santa Fe, Argentina}},
  abstract = {This work describes the operational implementation of a High Resolution version of Weather Research and Forecasting Model (WRF) in the National Meteorological Service. Validation of the temperature and precipitation forecasts generated from July 2017 to June 2018 is shown, adding a comparison with the NCEP Global Forecast System (GFS) forecasts. Results indicate that WRF model generally perform better than GFS.},
  eventtitle = {XIII CONGREMET},
  langid = {spanish},
  file = {/home/pao/Zotero/zotero-library/storage/BQK582TR/Skabar et al. - IMPLEMENTACIÓN DEL MODELO WRF EN ALTA RESOLUCIÓN E.pdf}
}

@report{skamarock2008,
  title = {A {{Description}} of the {{Advanced Research WRF Version}} 3},
  author = {Skamarock, William C and Klemp, Joseph B and Dudhia, Jimy and Gill, David O and Barker, Dale M and Duda, Michael G and Huang, Xiang-Yu and Wang, Wei and Powers, Jordan G},
  date = {2008-06},
  pages = {125},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/VIG7N39R/Skamarock et al. - A Description of the Advanced Research WRF Version.pdf}
}

@article{sobash2015,
  title = {Assimilating {{Surface Mesonet Observations}} with the {{EnKF}} to {{Improve Ensemble Forecasts}} of {{Convection Initiation}} on 29 {{May}} 2012},
  author = {Sobash, Ryan A. and Stensrud, David J.},
  date = {2015-09-01},
  journaltitle = {Monthly Weather Review},
  volume = {143},
  number = {9},
  pages = {3700--3725},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/MWR-D-14-00126.1},
  url = {https://journals.ametsoc.org/view/journals/mwre/143/9/mwr-d-14-00126.1.xml},
  urldate = {2022-04-04},
  abstract = {Abstract Surface data assimilation (DA) has the potential to improve forecasts of convection initiation (CI) and short-term forecasts of convective evolution. Since the processes driving CI occur on scales inadequately observed by conventional observation networks, mesoscale surface networks could be especially beneficial given their higher temporal and spatial resolution. This work aims to assess the impact of high-frequency assimilation of mesonet surface DA on ensemble forecasts of CI initialized with ensemble Kalman filter (EnKF) analyses of the 29 May 2012 convective event over the southern Great Plains. Mesonet and conventional surface observations were assimilated every 5 min for 3 h from 1800 to 2100 UTC and 3-h ensemble forecasts were produced. Forecasts of CI timing and location were improved by assimilating the surface datasets in comparison to experiments where mesonet data were withheld. This primarily occurred due to a more accurate representation of the boundary layer moisture profile across the domain, especially in the vicinity of a dryline and stationary boundary. Ensemble forecasts produced by assimilating surface observations at hourly intervals, instead of every 5 min, showed only minor improvements in CI. The 5-min assimilation of mesonet data improved forecasts of the placement and timing of CI for this particular event due to the ability of mesonet data to capture rapidly evolving mesoscale features and to constrain model biases, particularly surface moisture errors, during the cycling period.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/A2WH2P64/Sobash_Stensrud_2015_Assimilating Surface Mesonet Observations with the EnKF to Improve Ensemble.pdf}
}

@misc{sondeos,
  title = {Multi-Network Composite Highest Resolution Radiosonde Data. {{Version}} 1.3. {{UCAR}}/{{NCAR}} - Earth Observing Laboratory.},
  author = {UCAR/NCAR - Earth Observing Laboratory},
  date = {2020},
  url = {https://doi.org/10.26023/GKFF-YNBJ-BV14}
}

@article{sun2014,
  title = {Use of {{NWP}} for {{Nowcasting Convective Precipitation}}: {{Recent Progress}} and {{Challenges}}},
  shorttitle = {Use of {{NWP}} for {{Nowcasting Convective Precipitation}}},
  author = {Sun, Juanzhen and Xue, Ming and Wilson, James W. and Zawadzki, Isztar and Ballard, Sue P. and Onvlee-Hooimeyer, Jeanette and Joe, Paul and Barker, Dale M. and Li, Ping-Wah and Golding, Brian and Xu, Mei and Pinto, James},
  date = {2014-03-01},
  journaltitle = {Bulletin of the American Meteorological Society},
  volume = {95},
  number = {3},
  pages = {409--426},
  publisher = {{American Meteorological Society}},
  issn = {0003-0007, 1520-0477},
  doi = {10.1175/BAMS-D-11-00263.1},
  url = {https://journals.ametsoc.org/view/journals/bams/95/3/bams-d-11-00263.1.xml},
  urldate = {2021-05-14},
  abstract = {{$<$}section class="abstract"{$><$}p{$>$}Traditionally, the nowcasting of precipitation was conducted to a large extent by means of extrapolation of observations, especially of radar ref lectivity. In recent years, the blending of traditional extrapolation-based techniques with high-resolution numerical weather prediction (NWP) is gaining popularity in the nowcasting community. The increased need of NWP products in nowcasting applications poses great challenges to the NWP community because the nowcasting application of high-resolution NWP has higher requirements on the quality and content of the initial conditions compared to longer-range NWP. Considerable progress has been made in the use of NWP for nowcasting thanks to the increase in computational resources, advancement of high-resolution data assimilation techniques, and improvement of convective-permitting numerical modeling. This paper summarizes the recent progress and discusses some of the challenges for future advancement.{$<$}/p{$><$}/section{$>$}},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/ZNDHGDTG/Sun et al_2014_Use of NWP for Nowcasting Convective Precipitation.pdf}
}

@article{vera2006,
  title = {The {{South American Low-Level Jet Experiment}}},
  author = {Vera, C. and Baez, J. and Douglas, M. and Emmanuel, C. B. and Marengo, J. and Meitin, J. and Nicolini, M. and Nogues-Paegle, J. and Paegle, J. and Penalba, O. and Salio, P. and Saulo, C. and Silva Dias, M. A. and Dias, P. Silva and Zipser, E.},
  date = {2006-01},
  journaltitle = {Bulletin of the American Meteorological Society},
  shortjournal = {Bull. Amer. Meteor. Soc.},
  volume = {87},
  number = {1},
  pages = {63--78},
  issn = {0003-0007, 1520-0477},
  doi = {10.1175/BAMS-87-1-63},
  url = {http://journals.ametsoc.org/doi/10.1175/BAMS-87-1-63},
  urldate = {2020-05-07},
  langid = {english},
  file = {/home/pao/Dropbox/Papers Zotero/Vera/vera_2006_the_south_american_low-level_jet_experiment.pdf}
}

@article{wang2021,
  title = {The {{Impact}} of {{Assimilating Satellite Radiance Observations}} in the {{Copernicus European Regional Reanalysis}} ({{CERRA}})},
  author = {Wang, Zheng Qi and Randriamampianina, Roger},
  date = {2021-01},
  journaltitle = {Remote Sensing},
  volume = {13},
  number = {3},
  pages = {426},
  publisher = {{Multidisciplinary Digital Publishing Institute}},
  issn = {2072-4292},
  doi = {10.3390/rs13030426},
  url = {https://www.mdpi.com/2072-4292/13/3/426},
  urldate = {2022-04-05},
  abstract = {The assimilation of microwave and infrared (IR) radiance satellite observations within numerical weather prediction (NWP) models have been an important component in the effort of improving the accuracy of analysis and forecast. Such capabilities were implemented during the development of the high-resolution Copernicus European Regional Reanalysis (CERRA), funded by the Copernicus Climate Change Services (C3S). The CERRA system couples the deterministic system with the ensemble data assimilation to provide periodic updates of the background error covariance matrix. Several key factors for the assimilation of radiances were investigated, including appropriate use of variational bias correction (VARBC), surface-sensitive AMSU-A observations and observation error correlation. Twenty-one-day impact studies during the summer and winter seasons were conducted. Generally, the assimilation of radiances has a small impact on the analysis, while greater impacts are observed on short-range (12 and 24-h) forecasts with an error reduction of 1–2\% for the mid and high troposphere. Although, the current configuration provided less accurate forecasts from 09 and 18 UTC analysis times. With the increased thinning distances and the rejection of IASI observation over land, the errors in the analyses and 3 h forecasts on geopotential height were reduced up to 2\%.},
  issue = {3},
  langid = {english},
  keywords = {Copernicus Climate Change Services (C3S),data assimilation,limited area model,radiance observations,regional reanalysis,satellite observations},
  file = {/home/pao/Zotero/zotero-library/storage/U5KI4AXX/Wang_Randriamampianina_2021_The Impact of Assimilating Satellite Radiance Observations in the Copernicus.pdf}
}

@online{weston2019,
  title = {Investigations into the Assimilation of {{AMSU-A}} in the Presence of Cloud and Precipitation},
  author = {Weston, Peter and Geer, Alan and Bormann, Niels and Bormann, Niels},
  date = {2019},
  series = {{{EUMETSAT}}/{{ECMWF Fellowship Programme Research Report}}},
  publisher = {{ECMWF}},
  issn = {50},
  doi = {10.21957/ewahn9ce},
  file = {/home/pao/Dropbox/Papers Zotero/Weston/weston_2019_investigations_into_the_assimilation_of_amsu-a_in_the_presence_of_cloud_and.pdf}
}

@article{wheatley2010,
  title = {The {{Impact}} of {{Assimilating Surface Pressure Observations}} on {{Severe Weather Events}} in a {{WRF Mesoscale Ensemble System}}},
  author = {Wheatley, Dustan M. and Stensrud, David J.},
  date = {2010-05-01},
  journaltitle = {Monthly Weather Review},
  volume = {138},
  number = {5},
  pages = {1673--1694},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/2009MWR3042.1},
  url = {https://journals.ametsoc.org/view/journals/mwre/138/5/2009mwr3042.1.xml},
  urldate = {2022-04-04},
  abstract = {Abstract Surface pressure observations are assimilated into a Weather Research and Forecast ensemble using an ensemble Kalman filter (EnKF) approach and the results are compared with observations for two severe weather events. Several EnKF experiments are performed to evaluate the relative impacts of two very different pressure observations: altimeter setting (a total pressure field) and 1-h surface pressure tendency. The primary objective of this study is to determine the surface pressure observation that is most successful in producing realistic mesoscale features, such as convectively driven cold pools, which often play an important role in future convective development. Results show that ensemble-mean pressure analyses produced from the assimilation of surface temperature, moisture, and winds possess significant errors in regard to mesohigh strength and location. The addition of surface pressure tendency observations within the assimilation yields limited ability to constrain such errors, while the assimilation of altimeter setting yields accurate depictions of the mesoscale pressure patterns associated with mesoscale convective systems. The mesoscale temperature patterns produced by all the ensembles are quite similar and tend to reproduce the observed features. Results suggest that even though surface pressure observations can have large cross covariances with temperature and the wind components, the resulting analyses fail to improve upon the EnKF temperature and wind analyses that exclude the surface pressure observations. Ensemble forecasts following the assimilation period show the potential to improve short-range forecasting of surface pressure.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/JYZL7XUK/Wheatley_Stensrud_2010_The Impact of Assimilating Surface Pressure Observations on Severe Weather.pdf}
}

@article{whitaker2008,
  title = {Ensemble {{Data Assimilation}} with the {{NCEP Global Forecast System}}},
  author = {Whitaker, Jeffrey S. and Hamill, Thomas M. and Wei, Xue and Song, Yucheng and Toth, Zoltan},
  date = {2008-02-01},
  journaltitle = {Monthly Weather Review},
  volume = {136},
  number = {2},
  pages = {463--482},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/2007MWR2018.1},
  url = {https://journals.ametsoc.org/view/journals/mwre/136/2/2007mwr2018.1.xml},
  urldate = {2022-04-04},
  abstract = {Abstract Real-data experiments with an ensemble data assimilation system using the NCEP Global Forecast System model were performed and compared with the NCEP Global Data Assimilation System (GDAS). All observations in the operational data stream were assimilated for the period 1 January–10 February 2004, except satellite radiances. Because of computational resource limitations, the comparison was done at lower resolution (triangular truncation at wavenumber 62 with 28 levels) than the GDAS real-time NCEP operational runs (triangular truncation at wavenumber 254 with 64 levels). The ensemble data assimilation system outperformed the reduced-resolution version of the NCEP three-dimensional variational data assimilation system (3DVAR), with the biggest improvement in data-sparse regions. Ensemble data assimilation analyses yielded a 24-h improvement in forecast skill in the Southern Hemisphere extratropics relative to the NCEP 3DVAR system (the 48-h forecast from the ensemble data assimilation system was as accurate as the 24-h forecast from the 3DVAR system). Improvements in the data-rich Northern Hemisphere, while still statistically significant, were more modest. It remains to be seen whether the improvements seen in the Southern Hemisphere will be retained when satellite radiances are assimilated. Three different parameterizations of background errors unaccounted for in the data assimilation system (including model error) were tested. Adding scaled random differences between adjacent 6-hourly analyses from the NCEP–NCAR reanalysis to each ensemble member (additive inflation) performed slightly better than the other two methods (multiplicative inflation and relaxation-to-prior).},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/EQY8CLIE/Whitaker et al_2008_Ensemble Data Assimilation with the NCEP Global Forecast System.pdf}
}

@article{whitaker2012,
  title = {Evaluating {{Methods}} to {{Account}} for {{System Errors}} in {{Ensemble Data Assimilation}}},
  author = {Whitaker, Jeffrey S. and Hamill, Thomas M.},
  date = {2012-09},
  journaltitle = {Monthly Weather Review},
  shortjournal = {Mon. Wea. Rev.},
  volume = {140},
  number = {9},
  pages = {3078--3089},
  issn = {0027-0644, 1520-0493},
  doi = {10.1175/MWR-D-11-00276.1},
  url = {http://journals.ametsoc.org/doi/10.1175/MWR-D-11-00276.1},
  urldate = {2020-05-21},
  abstract = {Inflation of ensemble perturbations is employed in ensemble Kalman filters to account for unrepresented error sources. The authors propose a multiplicative inflation algorithm that inflates the posterior ensemble in proportion to the amount that observations reduce the ensemble spread, resulting in more inflation in regions of dense observations. This is justified since the posterior ensemble variance is more affected by sampling errors in these regions. The algorithm is similar to the ‘‘relaxation to prior’’ algorithm proposed by Zhang et al., but it relaxes the posterior ensemble spread back to the prior instead of the posterior ensemble perturbations.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/DWJEFIUQ/Whitaker and Hamill - 2012 - Evaluating Methods to Account for System Errors in.pdf}
}

@article{wu2014,
  title = {Influence of {{Assimilating Satellite-Derived Atmospheric Motion Vector Observations}} on {{Numerical Analyses}} and {{Forecasts}} of {{Tropical Cyclone Track}} and {{Intensity}}},
  author = {Wu, Ting-Chi and Liu, Hui and Majumdar, Sharanya J. and Velden, Christopher S. and Anderson, Jeffrey L.},
  date = {2014-01-01},
  journaltitle = {Monthly Weather Review},
  volume = {142},
  number = {1},
  pages = {49--71},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/MWR-D-13-00023.1},
  url = {https://journals.ametsoc.org/view/journals/mwre/142/1/mwr-d-13-00023.1.xml},
  urldate = {2022-04-04},
  abstract = {Abstract The influence of assimilating enhanced atmospheric motion vectors (AMVs) on mesoscale analyses and forecasts of tropical cyclones (TC) is investigated. AMVs from the geostationary Multifunctional Transport Satellite (MTSAT) are processed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS, University of Wisconsin–Madison) for the duration of Typhoon Sinlaku (2008), which included a rapid intensification phase and a slow, meandering track. The ensemble Kalman filter and the Weather Research and Forecasting Model are utilized within the Data Assimilation Research Testbed. In addition to conventional observations, three different groups of AMVs are assimilated in parallel experiments: CTL, the same dataset assimilated in the NCEP operational analysis; CIMSS(h), hourly datasets processed by CIMSS; and CIMSS(h+RS), the dataset including AMVs from the rapid-scan mode. With an order of magnitude more AMV data assimilated, the CIMSS(h) analyses exhibit a superior track, intensity, and structure to CTL analyses. The corresponding 3-day ensemble forecasts initialized with CIMSS(h) yield smaller track and intensity errors than those initialized with CTL. During the period when rapid-scan AMVs are available, the CIMSS(h+RS) analyses offer additional modifications to the TC and its environment. In contrast to many members in the ensemble forecasts initialized from the CTL and CIMSS(h) analyses that predict an erroneous landfall in China, the CIMSS(h+RS) members capture recurvature, albeit prematurely. The results demonstrate the promise of assimilating enhanced AMV data into regional TC models. Further studies to identify optimal strategies for assimilating integrated full-resolution multivariate data from satellites are under way.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/HTGLS9FD/Wu et al_2014_Influence of Assimilating Satellite-Derived Atmospheric Motion Vector.pdf}
}

@article{zhao2021,
  title = {Impact of {{Assimilating High-Resolution Atmospheric Motion Vectors}} on {{Convective Scale Short-Term Forecasts}}: 1. {{Observing System Simulation Experiment}} ({{OSSE}})},
  shorttitle = {Impact of {{Assimilating High-Resolution Atmospheric Motion Vectors}} on {{Convective Scale Short-Term Forecasts}}},
  author = {Zhao, J. and Gao, Jidong and Jones, Thomas A. and Hu, Junjun},
  date = {2021},
  journaltitle = {Journal of Advances in Modeling Earth Systems},
  volume = {13},
  number = {10},
  pages = {e2021MS002484},
  issn = {1942-2466},
  doi = {10.1029/2021MS002484},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2021MS002484},
  urldate = {2022-04-10},
  abstract = {This research investigates to what extent the high-spatiotemporal-resolution Atmospheric Motion Vector (AMV) product derived from the new-generation Geostationary Operational Environmental Satellites-Series R can benefit convective-scale data assimilation (DA) and forecasts of potential high impact weather events. In the first part of this two-part study, the impact of AMV DA on convective-scale numerical weather prediction (NWP) is evaluated with an idealized supercell storm. The simulated AMV observations are synthesized from the idealized supercell storm generated by the Weather Research and Forecasting model and then the data are assimilated with a three-dimensional variational analysis and forecast system. A baseline DA experiment demonstrates that the wind errors within and around the storms are remarkably reduced by assimilating the AMV data, consequently enhancing the storm top-level divergence and low-level convergence signatures associated with two strong splitting supercells. Three sets of sensitivity experiments are then performed to test the impact of observation resolution, DA cycling frequency and horizontal correlation length scale respectively. Generally, assimilating higher-spatial-resolution AMVs at higher cycling frequency is able to produce reasonable divergence analysis as well as the subsequent 90 min forecasts. However, too frequent DA cycling tends to produce a warm bias and overestimate nonprecipitating hydrometeor and storm-relative helicity features, resulting in more spurious cells in the short-term forecasts. It is also found that the correlation length scale of 20 km produces the best results when assimilating the AMV data.},
  langid = {english},
  keywords = {Atmospheric Motion Vectors,GOES-R,Numerical Weather Prediction,OSSE},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021MS002484},
  file = {/home/pao/Zotero/zotero-library/storage/YBVGSRQN/Zhao et al_2021_Impact of Assimilating High-Resolution Atmospheric Motion Vectors on Convective.pdf}
}

@article{zhao2021a,
  title = {Impact of {{Assimilating High-Resolution Atmospheric Motion Vectors}} on {{Convective Scale Short-Term Forecasts}}: 2. {{Assimilation Experiments}} of {{GOES-16 Satellite Derived Winds}}},
  shorttitle = {Impact of {{Assimilating High-Resolution Atmospheric Motion Vectors}} on {{Convective Scale Short-Term Forecasts}}},
  author = {Zhao, J. and Gao, Jidong and Jones, Thomas A. and Hu, Junjun},
  date = {2021},
  journaltitle = {Journal of Advances in Modeling Earth Systems},
  volume = {13},
  number = {10},
  pages = {e2021MS002486},
  issn = {1942-2466},
  doi = {10.1029/2021MS002486},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2021MS002486},
  urldate = {2022-04-10},
  abstract = {Building on the results from the observing system simulation experiments in Part I, this study investigates the impact of assimilating Geostationary Operational Environmental Satellite-16 (GOES-16) derived atmospheric motion vector (AMV) data on the convective scale numerical weather prediction (NWP) by using the National Severe Storms Laboratory (NSSL) three-dimensional variational (3DVAR) data assimilation (DA) system. The benefit of the AMV DA for short-term severe weather forecast is assessed with three high-impact weather events that occurred in spring 2018 and 2019 over the Great Plains of the United States. The results show that the wind and equivalent potential temperature fields associated with the storm environment and the nearby ongoing convection are improved by the AMV DA, which yields better simulation of the boundaries and the subsequent forecasts of storm evolution. For the quasi-linear or mesoscale convective system, the assimilation of AMVs has a positive impact on the 0–3 h forecasts of composite reflectivity and accumulated precipitation in terms of the shape, location, and magnitude. However, the AMV DA has difficulty in capturing the sharp moisture gradient associated with the dryline and mostly underpredicts the associated scattered storms.},
  langid = {english},
  keywords = {3DVAR,Atmospheric Motion Vectors,GOES-16,Numerical Weather Prediction},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021MS002486},
  file = {/home/pao/Zotero/zotero-library/storage/LQEMI2ZC/Zhao et al_2021_Impact of Assimilating High-Resolution Atmospheric Motion Vectors on Convective.pdf}
}

@article{zhu2014,
  title = {Enhanced Radiance Bias Correction in the {{National Centers}} for {{Environmental Prediction}}'s {{Gridpoint Statistical Interpolation}} Data Assimilation System},
  author = {Zhu, Yanqiu and Derber, John and Collard, Andrew and Dee, Dick and Treadon, Russ and Gayno, George and Jung, James A.},
  date = {2014},
  journaltitle = {Quarterly Journal of the Royal Meteorological Society},
  volume = {140},
  number = {682},
  pages = {1479--1492},
  issn = {1477-870X},
  doi = {10.1002/qj.2233},
  url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.2233},
  urldate = {2020-06-04},
  abstract = {Radiance bias correction is an important and necessary step in the proper use of satellite observations in a data assimilation system. The original radiance bias-correction scheme used in the Gridpoint Statistical Interpolation (GSI) data assimilation system consists of two components: a variational air-mass dependent component and a scan-angle component. The air-mass component is updated within the GSI, while the scan-angle component is updated outside the GSI. This study examines and enhances several aspects of the radiance bias-correction problem. First, a modified pre-conditioning is applied to the bias-correction coefficients and the analysis variables to speed up convergence of the minimization process. A new procedure for applying the modified pre-conditioning in the GSI is utilized. Second, capabilities for detecting any new/missing/recovering radiance data and initializing the bias correction for new radiance data are implemented. A new scheme is proposed and employed to adjust the background-error variances for the bias-correction coefficients automatically, using an approximation of the analysis-error variances from the previous cycle, and to remove the pre-specified predictor scaling parameters. Finally, the capability to perform bias correction for passive channels within the GSI is developed with a new approach. The two-step bias-correction procedure originally used is replaced with a one-step variational bias-correction scheme within the GSI. Experiment results with the GSI-based hybrid ensemble-variational system show that using the modified pre-conditioning leads to a better convergence rate. Moreover, with the one-step scheme, the anomaly correlation of geopotential height at 500 mb is neutral in the Northern Hemisphere but improved in the Southern Hemisphere. The root-mean-square (RMS) error of wind is comparable to that of the two-step scheme and the biases of the global temperature 24 h and 48 h forecasts fitted to the rawinsonde are reduced.},
  langid = {english},
  keywords = {data assimilation,GSI,radiance bias correction},
  annotation = {\_eprint: https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2233},
  file = {/home/pao/Dropbox/Papers Zotero/Zhu/zhu_2014_enhanced_radiance_bias_correction_in_the_national_centers_for_environmental.pdf}
}

@article{zhu2016,
  title = {All-{{Sky Microwave Radiance Assimilation}} in {{NCEP}}’s {{GSI Analysis System}}},
  author = {Zhu, Yanqiu and Liu, Emily and Mahajan, Rahul and Thomas, Catherine and Groff, David and Van Delst, Paul and Collard, Andrew and Kleist, Daryl and Treadon, Russ and Derber, John C.},
  date = {2016-09-15},
  journaltitle = {Monthly Weather Review},
  shortjournal = {Mon. Wea. Rev.},
  volume = {144},
  number = {12},
  pages = {4709--4735},
  publisher = {{American Meteorological Society}},
  issn = {0027-0644},
  doi = {10.1175/MWR-D-15-0445.1},
  url = {https://journals.ametsoc.org/doi/full/10.1175/MWR-D-15-0445.1},
  urldate = {2020-06-04},
  abstract = {The capability of all-sky microwave radiance assimilation in the Gridpoint Statistical Interpolation (GSI) analysis system has been developed at the National Centers for Environmental Prediction (NCEP). This development effort required the adaptation of quality control, observation error assignment, bias correction, and background error covariance to all-sky conditions within the ensemble–variational (EnVar) framework. The assimilation of cloudy radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) microwave radiometer for ocean fields of view (FOVs) is the primary emphasis of this study.In the original operational hybrid 3D EnVar Global Forecast System (GFS), the clear-sky approach for radiance data assimilation is applied. Changes to data thinning and quality control have allowed all-sky satellite radiances to be assimilated in the GSI. Along with the symmetric observation error assignment, additional situation-dependent observation error inflation is employed for all-sky conditions. Moreover, in addition to the current radiance bias correction, a new bias correction strategy has been applied to all-sky radiances. In this work, the static background error variance and the ensemble spread of cloud water are examined, and the levels of cloud variability from the ensemble forecast in single- and dual-resolution configurations are discussed. Overall, the all-sky approach provides more realistic simulated brightness temperatures and cloud water analysis increments, and improves analysis off the west coasts of the continents by reducing a known bias in stratus. An approximate 10\% increase in the use of AMSU-A channels 1–5 and a 12\% increase for channel 15 are also observed. The all-sky AMSU-A radiance assimilation became operational in the 4D EnVar GFS system upgrade of 12 May 2016.},
  file = {/home/pao/Dropbox/Papers Zotero/Zhu/zhu_2016_all-sky_microwave_radiance_assimilation_in_ncep’s_gsi_analysis_system.pdf;/home/pao/Zotero/zotero-library/storage/M3GVHDTE/Zhu et al_2016_All-Sky Microwave Radiance Assimilation in NCEP’s GSI Analysis System.pdf}
}

@article{zhu2019,
  title = {The {{Impact}} of {{Satellite Radiance Data Assimilation}} within a {{Frequently Updated Regional Forecast System Using}} a {{GSI-based Ensemble Kalman Filter}}},
  author = {Zhu, Kefeng and Xue, Ming and Pan, Yujie and Hu, Ming and Benjamin, Stanley G. and Weygandt, Stephen S. and Lin, Haidao},
  date = {2019-12},
  journaltitle = {Advances in Atmospheric Sciences},
  shortjournal = {Adv. Atmos. Sci.},
  volume = {36},
  number = {12},
  pages = {1308--1326},
  issn = {0256-1530, 1861-9533},
  doi = {10.1007/s00376-019-9011-3},
  url = {http://link.springer.com/10.1007/s00376-019-9011-3},
  urldate = {2020-05-21},
  abstract = {A regional ensemble Kalman filter (EnKF) data assimilation (DA) and forecast system was recently established based on the Gridpoint Statistical Interpolation (GSI) analysis system. The EnKF DA system was tested with continuous threehourly updated cycles followed by 18-h deterministic forecasts from every three-hourly ensemble mean analysis. Initial tests showed negative to neutral impacts of assimilating satellite radiance data due to the improper bias correction procedure. In this study, two bias correction schemes within the established EnKF DA system are investigated and the impact of assimilating additional polar-orbiting satellite radiance is also investigated. Two group experiments are conducted. The purpose of the first group is to evaluate the bias correction procedure. Two online bias correction methods based on GSI 3DVar and EnKF algorithms are used to assimilate AMSU-A radiance data. Results show that both variational and EnKF-based bias correction procedures effectively reduce the observation and background radiance differences, achieving positive impacts on forecasts. With proper bias correction, we assimilate full radiance observations including AMSU-A, AMSU-B, AIRS, HIRS3/4, and MHS in the second group. The relative percentage improvements (RPIs) for all forecast variables compared to those without radiance data assimilation are mostly positive, with the RPI of upper-air relative humidity being the largest. Additionally, precipitation forecasts on a downscaled 13-km grid from 40-km EnKF analyses are also improved by radiance assimilation for almost all forecast hours.},
  langid = {english},
  file = {/home/pao/Zotero/zotero-library/storage/RQFFCFEQ/Zhu et al. - 2019 - The Impact of Satellite Radiance Data Assimilation.pdf}
}