{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:31:08Z","timestamp":1772253068667,"version":"3.50.1"},"reference-count":55,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T00:00:00Z","timestamp":1643241600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003629","name":"Korea Meteorological Administration","doi-asserted-by":"publisher","award":["KMA2017-02410"],"award-info":[{"award-number":["KMA2017-02410"]}],"id":[{"id":"10.13039\/501100003629","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2019R1F1A1058620"],"award-info":[{"award-number":["NRF-2019R1F1A1058620"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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\u2013height 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.<\/jats:p>","DOI":"10.3390\/rs14030605","type":"journal-article","created":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T22:01:57Z","timestamp":1643320917000},"page":"605","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Forecast Characteristics of Radar Data Assimilation Based on the Scales of Precipitation Systems"],"prefix":"10.3390","volume":"14","author":[{"given":"Jeong-Ho","family":"Bae","sequence":"first","affiliation":[{"name":"National Typhoon Center, Korea Meteorological Administration, Seogwipo 63614, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6133-6040","authenticated-orcid":false,"given":"Ki-Hong","family":"Min","sequence":"additional","affiliation":[{"name":"School of Earth System Sciences, Kyungpook National University, Daegu 41566, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1175\/2007MWR2123.1","article-title":"Scale-Selective Verification of Rainfall Accumulations from High-Resolution Forecasts of Convective Events","volume":"136","author":"Roberts","year":"2008","journal-title":"Mon. Weather Rev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1809","DOI":"10.1175\/JAMC-D-14-0243.1","article-title":"Variational Assimilation of Cloud Liquid\/Ice Water Path and Its Impact on NWP","volume":"54","author":"Chen","year":"2015","journal-title":"J. Appl. Meteorl. Climatol."},{"key":"ref_3","unstructured":"Bouttier, F. (2009). Fine Scale Versus Large Scale Data Assimilation\u2014A Discussion. Fifth WMO Symposium on Data Assimilation, WMO World Weather Research Programme. Available online: https:\/\/www.researchgate.net\/publication\/268376800_Fine_scale_versus_large_scale_data_assimilation_-a_discussion."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1175\/JAMC-D-12-0120.1","article-title":"Indirect assimilation of radar reflectivity with WRF 3D-Var and its impact on prediction of four summertime convective events","volume":"52","author":"Wang","year":"2013","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2224","DOI":"10.1175\/MWR-D-12-00168.1","article-title":"Radar data assimilation with WRF 4D-Var. Part I: System development and preliminary testing","volume":"141","author":"Wang","year":"2013","journal-title":"Mon. Weather Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1175\/MWR-D-16-0092.1","article-title":"The development of a terrain-resolving scheme for the forward model and its adjoint in the four-dimensional Variational Doppler Radar Analysis System (VDRAS)","volume":"145","author":"Tai","year":"2017","journal-title":"Mon. Weather Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1175\/1520-0493(2004)132<1238:IOIEAO>2.0.CO;2","article-title":"Impacts of initial estimate and observations on the convective-scale data assimilation with an ensemble Kalman filter","volume":"132","author":"Zhang","year":"2004","journal-title":"Mon. Weather Rev."},{"key":"ref_8","unstructured":"Zhang, J. (1999). Moisture and Diabatic Initialization Based on Radar and Satellite Observation. [Ph.D. Thesis, University of Oklahoma]."},{"key":"ref_9","first-page":"185","article-title":"ADAS cloud analysis. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ","volume":"79","author":"Zhang","year":"1998","journal-title":"Am. Meteorol. Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1642","DOI":"10.1175\/1520-0469(1997)054<1642:DAMRFD>2.0.CO;2","article-title":"Dynamical and microphysical retrieval from doppler radar observations using a cloud model and its adjoint. Part I: Model development and simulated data experiments","volume":"54","author":"Sun","year":"1997","journal-title":"J. Atmos. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1175\/1520-0469(1998)055<0835:DAMRFD>2.0.CO;2","article-title":"Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part2: Retrieval experiments of an observed Florida convective storm","volume":"55","author":"Sun","year":"1998","journal-title":"J. Atmos. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1175\/MWR3092.1","article-title":"3DVAR and cloud analysis with WSR-88D level-II data for the prediction of the Fort Worth, Texas, tornadic thunderstorms. Part I: Cloud analysis and its impact","volume":"134","author":"Hu","year":"2006","journal-title":"Mon. Weather Rev."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1175\/1520-0450(2003)042<0129:IOCAON>2.0.CO;2","article-title":"Impact of cloud analysis on numerical weather prediction in the Galician region of Spain","volume":"42","author":"Souto","year":"2003","journal-title":"J. Appl. Meteorol."},{"key":"ref_14","first-page":"492","article-title":"A study on severe heavy rainfall in north China during the 1990s (in Chinese)","volume":"10","author":"Sun","year":"2005","journal-title":"Clim. Environ. Res."},{"key":"ref_15","first-page":"4","article-title":"Assimilation of radar reflectivity data using a diabatic digital filter within the Rapid Update Cycle","volume":"Volume 8","author":"Weygandt","year":"2008","journal-title":"Proceedings of the 12th conference on IOAS-AOLS"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1007\/s00376-010-0035-y","article-title":"Observation and Numerical Simulations with Radar and Surface Data Assimilation for Heavy Rainfall over Central Korea","volume":"28","author":"Ha","year":"2011","journal-title":"Adv. Atmos. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1175\/2009MWR3086.1","article-title":"A multi-case comparative assessment of the ensemble Kalman filter for assimilation of radar observations. Part II: Short-range ensemble forecasts","volume":"138","author":"Aksoy","year":"2010","journal-title":"Mon. Weather Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3381","DOI":"10.1175\/MWR3471.1","article-title":"Multiple-radar data assimilation and short range quantitative precipitation forecasting of a squall line observed during IHOP 2002","volume":"135","author":"Xiao","year":"2007","journal-title":"Mon. Weather Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3081","DOI":"10.1175\/MWR3021.1","article-title":"A comparison between the 4DVAR and the ensemble Kalman filter techniques for radar data assimilation","volume":"133","author":"Caya","year":"2005","journal-title":"Mon. Weather Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2287","DOI":"10.1175\/MWR-D-12-00005.1","article-title":"Impact of Microphysics Scheme Complexity on the Propagation of Initial Perturbations","volume":"140","author":"Wang","year":"2012","journal-title":"Mon. Weather Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"815910","DOI":"10.1155\/2013\/815910","article-title":"WRF-ARW Variational Storm-Scale Data Assimilation: Current Capabilities and Future Developments","volume":"2013","author":"Sun","year":"2013","journal-title":"Adv. Meteorol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1175\/2010MWR3438.1","article-title":"Ensemble kalman filter assimilation of radar observations of the 8 May 2003 Oklahoma city supercell: Influences of reflectivity observations on storm-scale analyses","volume":"139","author":"Dowell","year":"2011","journal-title":"Mon. Weather Rev."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1002\/qj.2751","article-title":"Assimilation of 3D radar reflectivities with an ensemble Kalman filter on the convective scale","volume":"142","author":"Bick","year":"2016","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1710","DOI":"10.1175\/MWR2946.1","article-title":"Maximum likelihood ensemble filter: Theoretical aspects","volume":"133","author":"Zupanski","year":"2005","journal-title":"Mon. Weather Rev."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2403","DOI":"10.1175\/JAS-D-15-0311.1","article-title":"OSSEs for an Ensemble 3DVAR Data Assimilation System with Radar Observations of Convective Storms","volume":"73","author":"Gao","year":"2016","journal-title":"J. Atmos. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Lee, J.-W., Min, K.-H., Lee, Y.-H., and Lee, G. (2020). X-Net-Based radar data assimilation study over the Seoul metropolitan area. Remote Sens., 12.","DOI":"10.3390\/rs12050893"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1175\/2008BAMS2562.1","article-title":"High-resolution radar data assimilation for Hurricane Isabel (2003) at landfall","volume":"89","author":"Zhao","year":"2008","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1175\/JAS-D-11-0162.1","article-title":"Assimilation of reflectivity data in a convective-scale, cycled 3D-VAR framework with hydrometeor classification","volume":"69","author":"Gao","year":"2012","journal-title":"J. Atmos. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1175\/MWR2898.1","article-title":"Ensemble Kalman filter assimilation of Doppler radar data with a compressible nonhydrostatic model: OSS experiments","volume":"133","author":"Tong","year":"2005","journal-title":"Mon. Weather Rev."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1007\/s00703-019-0657-2","article-title":"High-resolution modeling study of an isolated convective storm over Seoul Metropolitan area","volume":"131","author":"Lee","year":"2019","journal-title":"Meteorol. Atmos. Phys."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1175\/JAMC-D-15-0010.1","article-title":"Constraining a 3DVAR Radar Data Assimilation System with Large-Scale Analysis to Improve Short-Range Precipitation Forecasts","volume":"55","author":"Vendrasco","year":"2016","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4011","DOI":"10.1175\/2009MWR2839.1","article-title":"Assimilation of Doppler radar data with WRF 3DVAR: Evaluation of its potential benefits to quantitative precipitation forecasting through observing system simulation experiments","volume":"137","author":"Sugimoto","year":"2009","journal-title":"Mon. Weather Rev."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1175\/JAM2248.1","article-title":"Assimilation of doppler radar observations with a regional 3DVAR system: Impact of doppler velocities on forecasts of a heavy rainfall case","volume":"44","author":"Xiao","year":"2005","journal-title":"J. Appl. Meteorol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3087","DOI":"10.1175\/MWR-D-14-00345.1","article-title":"A Comparison of Multiscale GSI-Based EnKF and 3DVar Data Assimilation Using Radar and Conventional Observations for Midlatitude Convective-Scale Precipitation Forecasts","volume":"143","author":"Johnson","year":"2015","journal-title":"Mon. Weather Rev."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1175\/JAS-D-15-0184.1","article-title":"The Implementation of the Ice-Phase Microphysical Process into a Four-Dimensional Variational Doppler Radar Analysis System (VDRAS) and Its Impact on Parameter Retrieval and Quantitative Precipitation Nowcasting","volume":"73","author":"Chang","year":"2016","journal-title":"J. Atmos. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Lai, A., Min, J., Gao, J., Ma, H., Cui, C., Xiao, Y., and Wang, Z. (2020). Assimilation of Radar Data, Pseudo Water Vapor, and Potential Temperature in a 3DVAR Framework for Improving Precipitation Forecast of Severe Weather Events. Atmosphere, 11.","DOI":"10.3390\/atmos11020182"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1002\/qj.3679","article-title":"Reflectivity and velocity radar data assimilation for two flash flood events in central Italy, A comparison between 3D and 4D variational methods","volume":"146","author":"Mazzarella","year":"2019","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1175\/MWR-D-19-0045.1","article-title":"Predictability of Deep Convection in Idealized and Operational Forecasts: Effects of Radar Data Assimilation, Orography, and Synoptic Weather Regime","volume":"148","author":"Bachmann","year":"2020","journal-title":"Mon. Weather Rev."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1571","DOI":"10.1175\/WAF-D-14-00095.1","article-title":"Evaluation of WRF cloud microphysics scheme using radar observations","volume":"30","author":"Min","year":"2015","journal-title":"Wea. Forecast."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.1256\/003590002320373337","article-title":"The interaction between model resolution, observation resolution and observation density in data assimilation: An one-dimensional study","volume":"128","author":"Liu","year":"2002","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_41","unstructured":"Ochotta, T., Gebhardt, C., Bondarenko, V., Saupe, D., and Wergen, W. (2007, January 14\u201318). On thinning methods for data assimilation of satellite observations. Proceedings of the 87th AMS Annual Meeting, San Antonio, TX, USA. Available online: https:\/\/ams.confex.com\/ams\/87ANNUAL\/techprogram\/paper_118511.htm."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1217","DOI":"10.1007\/s00376-015-4092-0","article-title":"Identification and removal of non-meteorological echoes in dual-polarization radar data based on a fuzzy logic algorithm","volume":"32","author":"Ye","year":"2015","journal-title":"Adv. Atmos. Sci."},{"key":"ref_43","unstructured":"Huffman, G.J., Stocker, E.F., Bolvin, D.T., Nelkin, E.J., and Tan, J. (2019). GPM IMERG Final Precipitation L3 Half Hourly 0.1 Degree x 0.1 Degree V06, Goddard Earth Sciences Data and Information Services Center (GES DISC)."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Das, M.K., Das, S., and Rahman, M. (2015). Chapter 5. Simulation of Mesoscale Convective Systems Associated with Squalls Using 3DVAR Data Assimilation over Bangladesh. High-Impact Weather Events over the SAARC Region, Springer.","DOI":"10.1007\/978-3-319-10217-7_5"},{"key":"ref_45","first-page":"87","article-title":"A Description of the Advanced Research WRF Version","volume":"3","author":"Skamarock","year":"2015","journal-title":"Natl. Cent. Atmos. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1175\/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2","article-title":"A three dimensional (3DVAR) data assimilation system for use with MM5: Implementation and initial results","volume":"132","author":"Barker","year":"2004","journal-title":"Mon. Weather Rev."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1175\/BAMS-D-11-00167.1","article-title":"Coauthors. The Weather Research and Forecasting (WRF) Model\u2019s Community Variational\/Ensemble Data Assimilation System: WRFDA","volume":"93","author":"Barker","year":"2012","journal-title":"Bull. Am. Meteorl. Soc."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Jang, S., Lim, K.-S.S., Ko, J., Kim, K., Lee, G., Cho, S.-J., Ahn, K.-D., and Lee, Y.-H. (2021). Revision of WDM7 Microphysics Scheme and Evaluation for Precipitating Convection over the Korean Peninsula. Remote Sens., 13.","DOI":"10.3390\/rs13193860"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1007\/s13143-011-0001-3","article-title":"Role of convective parameterization in simulations of heavy precipitation systems at grey-zone resolutions case studies","volume":"47","author":"Yu","year":"2011","journal-title":"Asia-Pac. J. Atmos. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1007\/s11069-018-3218-y","article-title":"A preliminary evaluation of the necessity of using a cumulus parameterization scheme in high-resolution simulations of Typhoon Haiyan 2013","volume":"92","author":"Li","year":"2018","journal-title":"Nat. Hazards"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1007\/s13143-018-0081-4","article-title":"Effects of Resolution, Cumulus Parameterization Scheme, and Probability Forecasting on Precipitation Forecasts in a High-Resolution Limited-Area Ensemble Prediction System","volume":"54","author":"On","year":"2018","journal-title":"Asia-Pac. J. Atmos. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1175\/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2","article-title":"The National Meteorological Center\u2019s spectral statistical-interpolation analysis system","volume":"120","author":"Parrish","year":"1992","journal-title":"Mon. Weather Rev."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1175\/MWR-D-12-00120.1","article-title":"Regional Comparison of GOES Cloud-Top Properties and Radar Characteristics","volume":"141","author":"Mecikalski","year":"2013","journal-title":"Mon. Weather Rev."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1941","DOI":"10.1175\/1520-0493(1995)123<1941:TDKAME>2.0.CO;2","article-title":"Three-Dimensional Kinematic and Microphysical Evolution of Florida Cumulonimbus. Part 2: Frequency Distributions of Vertical Velocity, Reflectivity, and Differential Reflectivity","volume":"123","author":"Yuter","year":"2013","journal-title":"Mon. Weather Rev."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1175\/2009WAF2222267.1","article-title":"Toward improved convection-allowing ensembles: Model physics sensitivities and optimizing probabilistic guidance with small ensemble membership","volume":"25","author":"Schwartz","year":"2010","journal-title":"Wea. Forecast."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/605\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:08:44Z","timestamp":1760134124000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/605"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,27]]},"references-count":55,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14030605"],"URL":"https:\/\/doi.org\/10.3390\/rs14030605","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints202111.0450.v1","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,27]]}}}