1、Assimilation of Ocean Surface Wind Data by the HY-2B Satellitein GRAPES:Impacts on Analyses and ForecastsJincheng WANG1,2,Xingwei JIANG*3,4,Xueshun SHEN1,2,Youguang ZHANG3,4,Xiaomin WAN1,2,Wei HAN1,2,and Dan WANG1,21CMA Earth System Modeling and Prediction Center,China Meteorological Administration,
2、Beijing 100081,China2National Meteorology Center,China Meteorological Administration,Beijing 100081,China3Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou),Guangzhou 511458,China4National Satellite Ocean Application Service,Beijing 100081,China(Received 25 October 2021;revised
3、7 April 2022;accepted 6 May 2022)ABSTRACTThe ocean surface wind (OSW)data retrieved from microwave scatterometers have high spatial accuracy andrepresent the only wind data assimilated by global numerical models on the ocean surface,thus playing an important role inimproving the forecast skills of g
4、lobal medium-range weather prediction models.To improve the forecast skills of theGlobal/Regional Assimilation and Prediction System Global Forecast System(GRAPES_GFS),the HY-2B OSW data isassimilated into the GRAPES_GFS four-dimensional variational assimilation(4DVAR)system.Then,the impacts of theH
5、Y-2B OSW data assimilation on the analyses and forecasts of GRAPES_GFS are analyzed based on one-monthassimilation cycle experiments.The results show that after assimilating the HY-2B OSW data,the analysis errors of thewind fields in the lower-middle troposphere (1000600 hPa)of the tropics and the s
6、outhern hemisphere (SH)aresignificantly reduced by an average rate of about 5%.The impacts of the HY-2B OSW data assimilation on the analysisfields of wind,geopotential height,and temperature are not solely limited to the boundary layer but also extend throughoutthe entire troposphere after about tw
7、o days of cycling assimilation.Furthermore,assimilating the HY-2B OSW data cansignificantly improve the forecast skill of wind,geopotential height,and temperature in the troposphere of the tropics andSH.Key words:HY-2B,ocean surface wind,4DVAR,GRAPES-GFS,medium-range weather forecastCitation:Wang,J.
8、C.,X.W.Jiang,X.S.Shen,Y.G.Zhang,X.M.Wan,W.Han,and D.Wang,2023:Assimilation ofocean surface wind data by the HY-2B satellite in GRAPES:Impacts on analyses and forecasts.Adv.Atmos.Sci.,40(1),4461,https:/doi.org/10.1007/s00376-022-1349-2.Article Highlights:The impacts of the HY-2B OSW data assimilation
9、(in 4DVAR)on the global analysis fields are not limited to theboundary layer.The OSW data assimilation impacts on analysis can extend to the whole troposphere after about two days of cyclingassimilation and then remain stable.The OSW data provide a significant positive impact on the GRAPES_GFS forec
10、ast skill in the troposphere of the tropicsand the southern hemisphere.1.IntroductionThe Global Data Assimilation System(GDAS)is oneof the core components of the global numerical weather pre-diction(NWP)system,which provides the initial conditionfor integrating an NWP model.Presently,two main catego
11、riesof observational data can be assimilated into the GDAS,1)conventional observational data,including surface observa-tions,upper-air observations,aircraft-based observations,and ship observations,and 2)observations that are gatheredby remote sensing satellites,which are mainly comprised ofthe brig
12、htness temperature data of the polar-orbiting and geo-stationary satellites,the refractivity data of the Global Naviga-tion Satellite System-Radio Occultation (GNSS-RO),andthe cloud-derived wind data retrieved from the polar-orbitingand geostationary satellites.The satellite observations effec-tivel
13、y fill the shortage of conventional observational data*Corresponding author:Xingwei JIANGEmail:ADVANCES IN ATMOSPHERIC SCIENCES,VOL.40,JANUARY 2023,4461 Original Paper Institute of Atmospheric Physics/Chinese Academy of Sciences,and Science Press and Springer-Verlag GmbH Germany,part of Springer Nat
14、ure 2023over the ocean and thus significantly improve the skill ofglobal numerical weather forecasts.Satellite observationsare playing an increasingly important role in promoting thedevelopment of todays NWP(Cardinali,2009).Despite a growing amount of satellite observations,themost collected variabl
15、e by satellite observations is the bright-ness temperature(mass field).The number of wind(motionfield)observations is relatively lower over the ocean,withonly the atmospheric motion vectors(AMVs)data availablein cloud regions (Feng and Wang,2019).Becausegeostrophic balance between the motion field a
16、nd the massfield is not satisfied in tropical regions,the existing dataassimilation algorithm is incapable of deriving the high preci-sion motion field from the observational data of the massfield,which limits the accuracy of the initial condition poten-tially leading to poor forecasting skill for typhoon and otherdisastrous weather events in the tropics.To remedy the lackof wind observations over the ocean,the microwave scat-terometer was developed to observe the ocean surface wind(OSW)(Figa-Sa
