2019
DOI: 10.1029/2019jd030642
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Impact of SCATSat‐1 Retrieved Wind Vectors on Short‐Range WRF Model Predictions Over the South Asia Region

Abstract: The Indian Space Research Organization launched SCATterometer Satellite-1 (SCATSat1) satellite by PSLV-C35 on 26 September 2016 from Sriharikota. In this study, SCATSat-1 retrieved winds are assimilated in the regional atmospheric model subsequent to preliminary evaluation of SCATSat-1 retrieved winds against National Centers for Environmental Prediction final analyses. The Weather Research and Forecasting (WRF) model and its three-and four-dimensional variational (3D-Var and 4D-Var) data assimilation system a… Show more

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Cited by 9 publications
(2 citation statements)
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“…They show that the impact of SCATSAT‐1 wind assimilation on track and intensity prediction is slightly better in 4DVAR than in 3DVAR. Our results are in line with the results of P. Kumar and Gairola (2019). Gao et al.…”
Section: Resultssupporting
confidence: 93%
See 1 more Smart Citation
“…They show that the impact of SCATSAT‐1 wind assimilation on track and intensity prediction is slightly better in 4DVAR than in 3DVAR. Our results are in line with the results of P. Kumar and Gairola (2019). Gao et al.…”
Section: Resultssupporting
confidence: 93%
“…The decrement in the RMSE confirms that the assimilation is reducing the error in the analysis with respect to observations. P. Kumar and Gairola (2019) found that by assimilation of SCATSAT‐1 wind in the WRF model using a three‐dimensional variational data assimilation method (3DVAR), analysis bias (observation‐analysis, O‐A) becomes smaller than first‐guess bias (observation‐back ground, O‐B). The root mean square difference (RMSD) reduces from 2.04 to 1.23 m s −1 for zonal wind and 2.02 to 1.23 m s −1 for meridional wind.…”
Section: Resultsmentioning
confidence: 99%