Role of Resolution on Atmospheric Dynamics during Fani Cyclone in the Indian Subcontinent

Abstract

A persistent discrepancy between mathematically modeled atmospheric circulation and observed precipitation has become increasingly evident over recent decades. High-resolution numerical weather prediction (NWP) models offer a pathway to reduce this gap, yet their practical deployment is constrained by limited data availability, high computational cost, and reliance on traditional model verification measures. This study proposes an efficient NWP framework implemented on small-scale parallel computing systems using an adaptive grid-resolution strategy within the well-known Nonhydrostatic Icosahedral Atmospheric Model (NICAM), enabling global weather analysis. By systematically varying horizontal grid spacing, the approach identifies the minimum resolution required to reliably capture mesoscale variations in wind, temperature, and precipitation while maintaining computational efficiency for targeted forecasting objectives. Global cloud-resolving simulations using NICAM are conducted under low-pressure conditions characteristic of cyclone formation over the Indian subcontinent, with specific focus on Cyclone Fani. Results show that even at reduced resolution, the model reproduces key atmospheric dynamics, including temperature, pressure, wind velocity, and precipitation at both near-surface and upper-atmospheric levels. These findings indicate that reasonable coarse-resolution NICAM simulations executed on small-scale parallel computing systems can effectively capture the essential atmospheric circulation associated with Cyclone Fani, providing a computationally efficient alternative for high-resolution numerical weather prediction.