Impact of INSAT-3D radiance data assimilation using WRF 3DVAR on simulation of Indian summer monsoon and high-resolution rainfall forecast over hilly terrain

Gogoi, Rekha Bharali; Kundu, Shyam Sundar; Raju, P. L. N.

doi:10.1007/s11069-021-04833-3

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“…Lekhadiya and Jana (2019) assimilated the temperature and relative humidity profile and reported an improved rainfall prediction. Gogoi et al (2021) suggested that the combination of INSAT‐3D imager and sounder data assimilation improved the forecast Indian summer monsoon rainfall over the northeastern region. However, the impact of the assimilation of derived INSAT‐3D sounding data for the prediction of TS over India is not well documented.…”

Section: Introductionmentioning

confidence: 99%

Enhanced prediction of premonsoon thunderstorms over eastern India through assimilation of INSAT‐3D sounding data

Priya,

Sasanka,

Osuri

2024

Quart J Royal Meteoro Soc

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The present study assesses the impact of Indian National Satellite 3D (INSAT‐3D)‐derived atmospheric (temperature and relative humidity) profiles on the simulation of severe thunderstorms over eastern India during the premonsoon season. Two sets of numerical experiments, without assimilation (CNTL) and with assimilation of INSAT‐3D profiles (INSAT) have been conducted using the three‐dimensional variational data assimilation system of the Weather Research and Forecasting model for 11 thunderstorm events. Analysis increments are positive with INSAT profile assimilation in the lower to middle atmosphere in the thunderstorm region. The errors in the initial fields have been reduced by approx. 50% after the assimilation. After assimilation, the predictions of the surface fields (2‐m temperature, 2‐m relative humidity, and 10‐m wind speed) have been improved at the mature stage (by 37%, 26%, and 15%) compared to the CNTL. Similar improvements are noticed in the vertical profiles of relative humidity and wind speed in the INSAT experiment. The time and magnitude of updrafts and downdrafts improved in INSAT. After assimilation, rainfall intensity improved in nine cases, and time improved in four cases out of 11. The Critical Success Index (False Alarm Rate) of the INSAT ranges from approx. 0.6–0.15 (∼0.37–0.48) for all thresholds, and are higher (lower) than the CNTL. The rainfall area is improved by 25% for light rainfall, 11% for moderate rainfall, and 2% for heavy rainfall in the INSAT over the CNTL experiment. Overall thunderstorm prediction has been improved with the assimilation of INSAT‐3D data. Thus, the study highlights the viability of INSAT‐3D profiles in improving thunderstorm predictions over eastern India.

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Section: Introductionmentioning

confidence: 99%