Open AccessImpact of Assimilation of Satellite Retrieved Ocean Surface Winds on the Tropical Cyclone Simulations Over the North Indian Ocean
Author(s) -
Bhate Jyoti,
Munsi Arpita,
Kesarkar Amit,
Kutty Govindan,
Deb Sanjib K.
Publication year - 2021
Publication title -
earth and space science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.843
H-Index - 23
ISSN - 2333-5084
DOI - 10.1029/2020ea001517
Subject(s) - tropical cyclone , scatterometer , climatology , rainband , typhoon , environmental science , data assimilation , eye , sea surface temperature , satellite , geology , meteorology , wind speed , oceanography , geography , aerospace engineering , engineering
The study intends to examine the impact of assimilation of ocean surface winds on the simulation of the tropical cyclones Ockhi, Mekunu, and Luban formed over the north Indian Oceans. We have conducted two assimilation experiments, cyclic control (CyclicCntl) and Hybrid, using the Weather Research and Forecast model. The CyclicCntl experiment and Hybrid experiment are the analysis generated without and with adding ocean surface winds, respectively. The ocean surface winds from Ocean Scatterometer, Advanced Scatterometer, and Windsat are assimilated using the ensemble three‐dimensional variational assimilation technique. The analysis generated by Hybrid and CyclicCntl is compared with the ocean surface winds observations from buoys, and it is found that the assimilation of ocean surface winds reduces the root mean square error between observation and analysis for zonal and meridional winds by 2–3 m s −1 (42%) compared to CyclicCntl simulations. The comparison with the International Best Track Archive for Climate Stewardship locations of cyclones derived from the analyses indicates that track error is maximum in genesis and landfall stage for both the Hybrid and CyclicCntl experiments, and the average track error is less than 80 km for the three cyclones. In a Hybrid experiment, during the intensifications from deep depression to the very severe cyclonic storm, the wind speed enhancement is dominant over the southeast and northwest sectors of the eyewall regions and subsequently in the rainband region. Thus, the assimilation of ocean surface winds from the three sensors improves the prediction of intensity and the evolution of tropical cyclones in general.