Impact assessment of 3D-var data assimilation on simulation of tropical cyclones using WRF

Abstract

The combination of data from the Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) satellites provide measurements in frequency channels 23-183 GHz, which allow the estimation of vertical profiles of atmospheric temperature and humidity. These measurements play a significant role in numerical weather prediction models, improving initial conditions during tropical cyclone development. In the present study, measurements from AMSU-A and MHS have been assimilated in the Weather Research and Forecasting (WRF) model through the 3D-variational (3D-var) data assimilation technique using the Gridpoint Statistical Interpolation (GSI) analysis system. The assimilation impact has been assessed on super cyclonic storm Amphan and severe cyclonic storm Nisarga, which formed over the Bay of Bengal (BoB) and the Arabian Sea (AS), respectively. To investigate their impact, a series of experiments are conducted with and without assimilation of AMSU-A and MHS observations from each day’s initial condition for both cyclones. The track and landfall errors of all the experiments are computed against the best track position provided by the India Meteorological Department (IMD). The results indicate that the assimilation of AMSU-A and MHS observations led to an improvement in track errors of about 11 to 35% for Amphan and 6 to 20% for Nisarga for 12 to 72 h lead times. Furthermore, the assimilation of AMSU-A and MHS observations helped to improve the simulation of landfall position and time. The evaluation of maximum sustained surface wind, central pressure, and rainfall against the observations demonstrates the positive impact of the assimilated observations on the performance of the WRF model.