| Autor: |
Kumar, Prashant, Shukla, Munn V., Varma, A. K. |
| Předmět: |
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| Zdroj: |
Quarterly Journal of the Royal Meteorological Society; Jul2022, Vol. 148 Issue 746, p2532-2545, 14p |
| Abstrakt: |
The objective of this study is to explore and present a methodology to assimilate all‐sky water vapour (WV) radiance from Indian geostationary satellites (INSAT‐3D and INSAT‐3DR) in the Weather Research and Forecasting (WRF) model. For all‐sky assimilation, hydrometeors are considered as control variables by adding in background error covariance. Additionally, this study uses the application of Global Satellite based Inter‐Calibration System (GSICS) based bias correction mechanism on WV radiances before their assimilation. To fulfil these objectives, three sets of experiments have been performed with and without WV radiance assimilation for the month of July 2018 over the South Asia region. The impact assessment of assimilation has been performed by comparing radiative transfer (RT) model‐simulated analysed and predicted brightness temperature against independent satellite observations from SAPHIR (Sondeur Atmosphérique du Profil d'Humidité Intertropicale par Radiométrie) and MHS (Microwave Humidity Sounder) sensors. Results not only show the number of assimilated observations increased significantly (∼250%) in all‐sky assimilation compared to clear‐sky assimilation but also present that the all‐sky analyses are closer to actual satellite observations. Due to the multivariate nature of variational data assimilation, noteworthy changes are also noticed in hydrometeors analyses in all‐sky assimilation. The short‐range forecasts confirm the positive impact of all‐sky assimilation as compared to clear‐sky assimilation when verified against SAPHIR and MHS measurements. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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