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- W4221024028 endingPage "106130" @default.
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- W4221024028 abstract "The present study investigates the impact of assimilation of satellite derived soil wetness data from Advanced Scatterometer (ASCAT) on simulation of inland moving monsoon depressions (MDs) over Indian region using high resolution NCUM-R forecasting system. The simplified Extended Kalman Filter (sEKF) based Land Surface Data Assimilation (LSDA) system is used to create land surface soil moisture initial conditions for NCUM-R by assimilating ASCAT soil moisture (SM) along with screen level observations. Two numerical experiments, namely CTL (incorporating only screen level observations in LSDA) and ASCAT (assimilating both ASCAT SM and screen level observations in LSDA) are carried out to update the model soil moisture initial conditions. Identical atmospheric initial condition prepared considering the 4DVAR data assimilation technique is used in both experiments. The results of this study show that the assimilation of remotely sensed SM has a beneficial impact on MD simulation, its movement, structure and associated precipitation. The analysis increment of fluxes from ASCAT experiment clearly shows properly coupled positive feedback between land and atmosphere. SM in the vicinity of MD is considerably improved in the ASCAT analysis as compared to the CTL analysis and is well correlated with the observed rainfall over the regions. The root mean square error of top layer SM is decreased by 5 to 15% in ASCAT analyses compared to CTL analyses. The land-atmosphere coupling feedback is investigated by using Dirmeyer's indices, it is noticed that the precipitation modulated by the latent heat flux is higher in ASCAT simulation than in the CTL simulation. This improvement is due to the proper representation of surface conditions by assimilating the satellite SM observations into LSDA. The contribution of individual terms of vorticity equation and total vorticity tendency is considerably well represented in ASCAT experiment as compared to the CTL experiment during the various phases of MD. Overall, this study indicates that the use of ASCAT SM in the preparation of soil moisture initial conditions helps to improve the forecast of MDs by the regional NWP system." @default.
- W4221024028 created "2022-04-03" @default.
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- W4221024028 date "2022-07-01" @default.
- W4221024028 modified "2023-10-17" @default.
- W4221024028 title "Improving the prediction of monsoon depressions by assimilating ASCAT soil moisture in NCUM-R modeling system" @default.
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- W4221024028 doi "https://doi.org/10.1016/j.atmosres.2022.106130" @default.
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