Abstract
Abstract. The present study focuses on identifying the parameters from the Weather Research and Forecasting (WRF) model that strongly influence the simulation of tropical cyclones over the Bay of Bengal (BoB) region. Three global sensitivity analysis (SA) methods, namely, the Morris One-at-A-Time (MOAT), multivariate adaptive regression splines (MARS), and surrogate-based Sobol', are employed to identify the most sensitive parameters out of 24 tunable parameters corresponding to seven parameterization schemes of the WRF model. Ten tropical cyclones across different categories, such as cyclonic storms, severe cyclonic storms, and very severe cyclonic storms over BoB between 2011 and 2018, are selected in this study. The sensitivity scores of 24 parameters are evaluated for eight meteorological variables. The parameter sensitivity results are consistent across three SA methods for all the variables, and 8 out of the 24 parameters contribute 80 %–90 % to the overall sensitivity scores. It is found that the Sobol' method with Gaussian progress regression as a surrogate model can produce reliable sensitivity results when the available samples exceed 200. The parameters with which the model simulations have the least RMSE values when compared with the observations are considered the optimal parameters. Comparing observations and model simulations with the default and optimal parameters shows that simulations with the optimal set of parameters yield a 16.74 % improvement in the 10 m wind speed, 3.13 % in surface air temperature, 0.73 % in surface air pressure, and 9.18 % in precipitation simulations compared to the default set of parameters.
Highlights
The Indian subcontinent is vulnerable to tropical cyclones which develop in the North Indian Ocean (NIO) that consists of the Arabian Sea and the Bay of Bengal (BoB)
A close observation of Fig. 3 reveals that the variables outgoing longwave radiation flux (OLR) and downward shortwave radiation flux (DSWRF) have the highest sensitivity to just one parameter each, whereas the remaining variables exhibit the highest sensitivity to at least two parameters
The present study evaluated the sensitivity of the eight meteorological variables, namely, surface wind speed, surface air temperature, surface air pressure, precipitation, planetary boundary layer height, downward shortwave radiation flux, downward longwave radiation flux, and outgoing longwave radiation flux, to 24 tunable parameters for the simulations of 10 tropical cyclones over the BoB region
Summary
The Indian subcontinent is vulnerable to tropical cyclones which develop in the North Indian Ocean (NIO) that consists of the Arabian Sea and the Bay of Bengal (BoB). These cyclones invariably cause widespread destruction to life and property. An extensive study conducted using the past 30 years of data suggests that the severity of extremely severe cyclonic storms (ESCSs) over NIO increased by 26 %. The observed statistics reveal that the duration of the ESCS stage and maximum wind speeds of ESCSs have shown an increasing trend, and the landfall category was very severe (Singh et al, 2021a). Singh et al (2019) showed that the present warming climate impacts the formation and Published by Copernicus Publications on behalf of the European Geosciences Union
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