Assimilation of All Sky Infrared Radiance from INSAT-3D/3DR Satellite in
the WRF Model
Abstract
The all-sky Infrared (IR) radiance assimilation from geostationary
satellites has been a prime research area in the numerical weather
prediction (NWP) modeling. In this study, the variational data
assimilation system of the weather research and forecasting (WRF) model
has been customized to assimilate all-sky assimilation of water vapour
(WV) radiance from Imager onboard two geostationary Indian National
Satellites (INSAT-3D and INSAT-3DR). This study also integrated
different hydrometeors (like cloud, rain, ice, snow and graupel) as
control variables in the WRF variation assimilation system. To do this,
parallel experiments were performed by carrying out model simulations
with and without INSAT WV radiance assimilation during July 2018.
Results of these simulations suggested that the WRF model analyses for
all-sky assimilation are closer to the brightness temperature
(TB) of channel-1 (183.31 ± 0.2 GHz) of SAPHIR
(Sondeur Atmosphérique du Profil d’Humidité Intertropicale par
Radiométrie) sensor onboard Megha-Tropiques satellite and channel-3
(183.31 ± 1.0 GHz) of MHS (Microwave Humidity Sounder) sensor onboard
National Oceanic and Atmospheric Administration (NOAA-18/19) and
Meteorological Operational Satellite (MetOp-A/B/C) satellites.
Furthermore, noteworthy changes are noticed in hydrometeors analyses
with all-sky assimilation and the number of assimilated observations are
increased significantly (around 2.5 times). The short-range predictions
from all-sky assimilation runs revealed notable positive impact as
compared to clear-sky assimilation runs when verified with SAPHIR and
MHS TB, and NCEP (National Centers for
Environmental Prediction) final analysis.