by Kantha Rao Bhimala, Krushna Chandra Gouda & S. Himesh 

The present study evaluates the skill of the Weather Research and Forecasting (WRF) model to simulate high-resolution rainfall, 2-m air temperature (T2m), and 2-m relative humidity (RH2m) over the metropolitan city of Bangalore, India. The novelty of the present study is that the WRF model simulations were carried out for ten different rain intensities during the monsoon season and compared with in situ observations from a high-density rain gauge network (81 rain gauge stations) and automatic weather stations (AWS) located over Bangalore. Our analysis shows that the model underestimated (bias score < 1) rainfall for most (87%) of the stations, and the model accuracy in the forecasting of rainfall was more than 70% for 16% of stations in the city. The RMSE values ranged between 18 and 28 mm/day for most of the rainfall events. Our analysis also found that the underestimation of the convective available potential energy (CAPE < 2000 J/kg) may be a possible reason for the simulation of low-intensity rainfall (< 10 mm/day) in most of the stations in Bangalore. In the case of T2m and RH2m simulations, the model closely matched the observed values [bias: T2m (−1 °C to 1 °C), Rh2m (0–10%)] for most of the AWS, while the model showed cold (−4.5 °C) and moist bias (19%) for the industrial area of Begur station. Proper representation of the urban morphology, air pollution, and anthropogenic heat data in the WRF modeling system may improve the model skill to capture the spatial variability in rainfall, T2m, and RH2m over highly urbanized cities in India.

Source: https://doi.org/10.1007/s00024-021-02676-4