An assessment study on the impact of land use land cover on monsoon depressions over India

Abstract

This study investigates the influence of LULC representation on surface meteorological conditions associated with monsoon depressions (MDs) in the Advanced Research Weather Research and Forecasting (WRF) model. A total of 18 MDs were considered during 2007–2018, with a life period of at least two days. Two simulations are performed at a 5-km grid-spacing, ingesting the LULC from the United States Geological Survey (USGS) and National Remote Sensing Centre (NRSC) for each MD case. The urban area has been increased from 0.13% in USGS to 1.21% in NRSC over the north-central and east coastal states, reducing the soil moisture (SM) errors by 0.015 m3 m−3 (25%) in the NRSC run. The SM in the NRSC run has a correlation of 0.53, which is 15% higher than that in the USGS run. The NRSC has a larger forest area (22%) than the USGS (7%) over the north-western parts and some parts of Maharashtra, which helps increase latent heat flux (LHF) by 30 Wm−2. Verifying with ERA analysis, the USGS and the NRSC simulations underestimate the LHF in most parts of India and overestimate in orographic areas. The NRSC-simulation shows fewer improvements (<5%) in LHF across the central and southern areas, unlike in the East and West parts (>13%). The surface temperature, moisture, and rainfall have been noticeably improved in the NRSC run for day-2 and day-3 simulation, unlike in USGS, while they are comparable in day-1. The spatial error of rainfall increases with forecast length, with NRSC having 10–15% less error than the USGS run. Further, the NRSC run could identify the rainfall peaks of 3 mm h−1 with a mean error of 1.5 mm h−1 as compared to 2.2 mm h−1 error in the USGS. This study demonstrates the positive impact of NRSC-developed LULC in the MD simulations over India.