Publications

Kadaverugu, R (2023). A comparison between WRF-simulated and observed surface meteorological variables across varying land cover and urbanization in south-central India. EARTH SCIENCE INFORMATICS.

Abstract
Changes in land use and land cover (LULC) and urbanization affect the regional energy balance. Accurate estimation of the earth's surface skin temperature and surface thermodynamic variables (temperature, T and relative humidity, RH) is essential to understand regional climate change better. The present study examined the agreeability between the Weather Research and Forecasting (WRF) model simulated surface skin temperature (TSK) and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-derived land surface temperature (LST) over heterogeneous LULC (built-up, crop land, forest cover, and barren land) in south-central India. Model performance metrics were computed for daytime and nighttime surface temperatures in January, May, and July 2021, representing winter, summer, and monsoon seasons. Further, the study compared the WRF-simulated near-surface (2 m from surface) T and RH with the observed hourly data from 20 locations in south-central India representing Tier-I, Tier-II, and Tier-III cities (high to low urbanization) to understand the effect of urbanization. Results indicate an overall high correlation (r > 0.9) between WRF-TSK and MODIS-LST. Nighttime correlations (r > 0.55) are relatively good enough for crop and forest land-use group than daytime simulations. In general, the correlation between TSK and LST is relatively poor for barren and built-up land-use groups during all three seasons (for both daytime and nighttime). Similarly, the WRF-simulated T and RH also differ considerably from the observed data in high and moderately dense urban locations, and the seasonal biases are predominant, especially during summer and winter. The WRF-simulated surface variables are a reasonable alternative in the absence of satellite-observed or surface-measured data in better understanding the environmental processes. However, the trends in the surface meteorological variables needs to be interpreted by duly considering the impact of land use and urbanization.

DOI:
10.1007/s12145-022-00927-z

ISSN:
1865-0481