{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T10:28:13Z","timestamp":1766485693690,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,12,29]],"date-time":"2018-12-29T00:00:00Z","timestamp":1546041600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Beijing Science &amp; Technology Commission","award":["Grant No. Z161100001116098"],"award-info":[{"award-number":["Grant No. Z161100001116098"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Due to the availability of observations and the effectiveness of bias correction, it is still a challenge to assimilate data from the polar orbit satellites into a limited-area and frequently updated model. This study assessed the initial application of satellite radiance data from multiple platforms in the Rapid-refresh Multi-scale Analysis and Prediction System (RMAPS). Satellite radiance data from the advanced microwave sounding unit-A (AMSU-A) and microwave humidity sounding (MHS) were used. Two 12-day retrospective runs were conducted to evaluate the impact of assimilating satellite radiance data on 0\u201324 h forecasts using RMAPS. The forecasts, initialized from analyses with and without satellite radiance data, were verified against observations. The results showed that satellite radiance data from AMSU-A and MHS had a positive impact on the initial conditions and the forecasts of RMAPS, even over the relatively data-rich area of North China. Compared to the control run that only assimilated conventional observations, an improvement of about 36.8% can be obtained for the temperature bias between 300 hPa and 850 hPa and 0.65% for the average RMSE. Satellite radiance observations from 1200 UTC contribute relatively significantly (77.8%) to the bias improvement of the initial temperature field. For the wind at 10 m, the bias and root-mean-square error (RMSE) both had a reduction for the 0\u201312 h forecast range. An improvement can be also found for the skill score of the 3-h accumulated rainfall below 10.0 mm in the first 12 h of the forecast range. There was a slight improvement in the skill score of the 6-h accumulated rainfall above 50 mm over North China, with a 20.7% improvement for the first 12 h of the forecast. The inclusion of satellite radiance observations was found to be beneficial for the initial temperature, which consequently improved the forecast skill of the 0\u201312 h range in the RMAPS.<\/jats:p>","DOI":"10.3390\/rs11010054","type":"journal-article","created":{"date-parts":[[2018,12,31]],"date-time":"2018-12-31T07:22:30Z","timestamp":1546240950000},"page":"54","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["An Assessment of Satellite Radiance Data Assimilation in RMAPS"],"prefix":"10.3390","volume":"11","author":[{"given":"Yanhui","family":"Xie","sequence":"first","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]},{"given":"Shuiyong","family":"Fan","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]},{"given":"Min","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6163-2912","authenticated-orcid":false,"given":"Jiancheng","family":"Shi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Joint Center for Global Change Studies (JCGCS), Beijing 100875, China"}]},{"given":"Jiqin","family":"Zhong","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]},{"given":"Xinyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,29]]},"reference":[{"key":"ref_1","unstructured":"Bjerknes, V. (1911). Dynamic Meteorology and Hydrography. Part II: Kinematics, Carnegie Institute of Washington."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s13351-016-5114-2","article-title":"On the assimilation of satellite sounder data in cloudy skies in numerical weather prediction models","volume":"30","author":"Li","year":"2016","journal-title":"J. Meteorol. Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1002\/wea.736","article-title":"From Observations to Forecasts\u2014Part 8: The use of satellite observations in numerical weather prediction","volume":"66","author":"Collard","year":"2011","journal-title":"Weather"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Kalnay, E. (2003). Atmospheric Modeling, Data Assimilation and Predictability, Cambridge University Press.","DOI":"10.1017\/CBO9780511802270"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1002\/qj.366","article-title":"Monitoring the observation impact on the short-range forecast","volume":"135","author":"Cardinali","year":"2010","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3331","DOI":"10.1175\/MWR-D-12-00232.1","article-title":"The impact of MetOp and other satellite data within the Met Office global NWP system using an adjoint-based sensitivity method","volume":"141","author":"Joo","year":"2013","journal-title":"Mon. Weather Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2551","DOI":"10.1256\/qj.01.206","article-title":"A note on the occurrence of cloud in meteorologically sensitive areas and the implications for advanced infrared sounders","volume":"128","author":"Mcnally","year":"2002","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1214","DOI":"10.1002\/qj.426","article-title":"The direct assimilation of cloud-affected satellite infrared radiances in the ECMWF 4D-Var","volume":"135","author":"McNally","year":"2009","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2287","DOI":"10.1175\/1520-0493(1998)126<2287:TUOTCC>2.0.CO;2","article-title":"The use of TOVS cloud-cleared radiances in the NCEP SSI analysis system","volume":"126","author":"Derber","year":"1998","journal-title":"Mon. Weather Rev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"13","DOI":"10.2174\/1874282300903010013","article-title":"Application of ATOVS Radiance with ARW WRF\/GSI Data Assimilation System in the Prediction of Hurricane Katrina","volume":"3","author":"Xu","year":"2009","journal-title":"Open Atmos. Sci. J."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Saunders, R., Matricardi, M., and Brunel, P. (1999). A Fast Radiative Transfer Model for Assimilation of Satellite Radiance Observations-RTTOV-5, European Centre for Medium-Range Weather Forecasts.","DOI":"10.1256\/smsqj.55614"},{"key":"ref_12","first-page":"1","article-title":"Community radiative transfer model (CRTM): Version 1","volume":"122","author":"Han","year":"2006","journal-title":"NOAA Tech. Rep."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1256\/qj.04.171","article-title":"The assimilation of AIRS radiance data at ECMWF","volume":"132","author":"McNally","year":"2006","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1175\/BAMS-D-11-00167.1","article-title":"The weather research and forecasting model\u2019s community variational\/ensemble data assimilation system: WRFDA","volume":"93","author":"Barker","year":"2012","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1002\/qj.2408","article-title":"Assimilation of SSMIS and ASCAT data and the replacement of highly uncertain estimates in the Environment Canada Regional Ice Prediction System","volume":"142","author":"Buehner","year":"2016","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1361","DOI":"10.1175\/MWR-D-13-00135.1","article-title":"Satellite radiance assimilation in the JMA operational mesoscale 4DVAR system","volume":"142","author":"Kazumori","year":"2014","journal-title":"Mon. Weather Rev."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1868","DOI":"10.1002\/qj.659","article-title":"Direct 4D-Var assimilation of all-sky radiance. Part I: Implementation","volume":"136","author":"Bauer","year":"2010","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4017","DOI":"10.1175\/MWR-D-12-00083.1","article-title":"Impact of assimilating AMSU-A radiances on forecasts of 2008 Atlantic tropical cyclones initialized with a limited-area ensemble kalman filter","volume":"140","author":"Liu","year":"2012","journal-title":"Mon. Weather Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1175\/WAF1025.1","article-title":"A two-season impact study of satellite and in situ data in the NCEP Global Data Assimilation System","volume":"22","author":"Zapotocny","year":"2007","journal-title":"Weather Forecast."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Lin, H., Weygandt, S.S., Lim, A.H.N., Hu, M., Brown, J.M., and Benjamin, S.G. (2017). Radiance preprocessing for assimilation in the Hourly Updating Rapid Refresh Mesoscale Model: A study using AIRS data. Weather Forecast., 32.","DOI":"10.1175\/WAF-D-17-0028.1"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1175\/1520-0493(1991)119<0734:UOFDDA>2.0.CO;2","article-title":"Use of four-dimensional data assimilation in a limited-area mesoscale model part II: Effects of data assimilation within the planetary boundary layer","volume":"119","author":"Stauffer","year":"1991","journal-title":"Mon. Weather Rev."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1002\/qj.49711247414","article-title":"Analysis methods for numerical weather prediction","volume":"112","author":"Lorenc","year":"1986","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1175\/MWR-D-13-00170.1","article-title":"The role of satellite data in the forecasting of Hurricane Sandy","volume":"142","author":"McNally","year":"2014","journal-title":"Mon. Weather Rev."},{"key":"ref_24","first-page":"451","article-title":"Assimilation of microwave radiance measurements over land and sea-ice in a regional weather model","volume":"Volume 5571","author":"Groverasmussen","year":"2004","journal-title":"Proceedings of the Remote Sensing of Clouds and the Atmosphere IX"},{"key":"ref_25","unstructured":"Lin, H., Weygandt, S.S., Back, A., Hu, M., Brown, J.M., and Alexander, C.R. (2018, January 3\u20134). Assimilation of Polar Orbiter and Geostationary Satellite Data in the RAP and HRRR models: Recent upgrades and ongoing work with new observation sets. Proceedings of the 25th Conference on Numerical Weather Prediction, Colorado B (Grand Hyatt Denver), Denver, CO, USA."},{"key":"ref_26","unstructured":"Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M.G., Huang, X.Y., Wang, W., and Powers, J.G. (2008). A Description of the Advanced Research WRF Version 3. NCAR Tech. Note."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Xie, Y.H., Shi, J.C., Fan, S.Y., Chen, M., Dou, Y.J., and Ji, D.B. (2018). Impact of radiance data assimilation on the prediction of heavy rainfall in RMAPS: A case study. Remote Sens., 10.","DOI":"10.3390\/rs10091380"},{"key":"ref_28","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. Wea. Rev."},{"key":"ref_29","first-page":"1783","article-title":"The ECMWF implementation of threedimensional variational assimilation (3D-Var). Part I: Formulation","volume":"124","author":"Courtier","year":"1998","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"3393","DOI":"10.1175\/1520-0493(1993)121<3393:IODAOI>2.0.CO;2","article-title":"Interactions of dynamics and observations in a four-dimensional variational data assimilation","volume":"121","author":"Thepaut","year":"1993","journal-title":"Mon. Weather Rev."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"10143","DOI":"10.1029\/94JC00572","article-title":"Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics","volume":"99","author":"Evensen","year":"1994","journal-title":"J. Geophys. Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"181","DOI":"10.2151\/jmsj1965.75.1B_181","article-title":"Unified notation for data assimilation: Operational, sequential and variational","volume":"75","author":"Ide","year":"1997","journal-title":"J. Meteorol. Soc. Jpn."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.1016\/j.jqsrt.2008.03.001","article-title":"Conversion issues between microwave radiance and brightness temperature","volume":"109","author":"Liu","year":"2008","journal-title":"J. Quant. Spectrosc. Radiat. Transf."},{"key":"ref_34","unstructured":"Goodrum, G., Kidwell, K.B., and Winston, W. (2000). NOAA KLM User\u2019s Guide Section 3.9, NOAA-NESDIS\/NCDC."},{"key":"ref_35","unstructured":"Amstrup, B. (2001). Impact of ATOVS AMSU-A Radiance Data in the DMI-HIRLAM 3D-Var Analysis and Forecasting System, Danish Meteorological Institute."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1175\/1520-0442(1996)009<0840:AOGMPU>2.0.CO;2","article-title":"Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions","volume":"9","author":"Xie","year":"1996","journal-title":"J. Clim."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1175\/1520-0434(1990)005<0570:TCSIAA>2.0.CO;2","article-title":"The critical success index as an indicator of warning skill","volume":"5","author":"Schaffer","year":"1990","journal-title":"Weather Forecast."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1002\/met.52","article-title":"Forecast verification: Current status and future directions","volume":"15","author":"Casati","year":"2008","journal-title":"Meteorol. Appl."},{"key":"ref_39","first-page":"1","article-title":"A bias correction scheme for simulated TOVS brightness temperatures","volume":"186","author":"Eyre","year":"1992","journal-title":"Tech. Memo. ECMWF"},{"key":"ref_40","first-page":"1453","article-title":"A satellite radiance bias correction scheme for data assimilation","volume":"127","author":"Harris","year":"2001","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_41","first-page":"631","article-title":"Adaptive bias correction for satellite data in a numerical weather prediction system","volume":"133","author":"McNally","year":"2010","journal-title":"Q. J. R. Meteorol. Soc."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/1\/54\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:36:40Z","timestamp":1760197000000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/1\/54"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,29]]},"references-count":41,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2019,1]]}},"alternative-id":["rs11010054"],"URL":"https:\/\/doi.org\/10.3390\/rs11010054","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,12,29]]}}}