Modelling for science, for a better future - some recent outcomes

On the build-up of dust aerosols and possible indirect effect during Indian summer monsoon break spells using recent satellite observations of aerosols and cloud properties

by Arya V. B., Sajani Surendran and Kavirajan Rajendran

Abstract
Association of higher (lower) rainfall with lower (higher) Aerosol Optical Depth (AOD) is consistent with the understanding that increased washout (build-up) and shorter (longer) life-time of aerosols occur in wetter (drier) conditions. Given the life-time of aerosols, it is imperative to examine how aerosols impact active/break (wetter/drier than normal) spells, the prominent intraseasonal variability (ISV) of Indian summer monsoon (ISM), through their composite analysis using recent satellite observations of aerosols and cloud properties, circulation and rainfall. Dust aerosols can act as CCN and participate efficiently in cloud processes during active phase. During breaks, build-up of desert dust transported by prevalent circulation, is associated with lower cloud effective radius implying aerosols’ indirect effect where they can inhibit cloud growth in the presence of reduced moisture and decrease precipitation efficiency/rainfall. Correspondingly, correlation albeit small, between intraseasonal anomalies of AOD and rainfall is negative, when AOD leads rainfall by 3–5 days implying that indirect aerosols impact is effective during breaks, though it is not the dominant responsible factor. During breaks, lower shortwave flux at top of atmosphere hints at dust-induced semi-direct effect. As breaks are permanent features of ISM, incorporation of dust-induced feedbacks in models, is essential for improved ISV simulation and ISM prediction.

Citation: Arya V. B., Sajani Surendran and Kavirajan Rajendran. On the build-up of dust aerosols and possible indirect effect during Indian summer monsoon break spells using recent satellite observations of aerosols and cloud properties. J. Earth Syst. Sci., 130, 42 (2021).

Source: https://doi.org/10.1007/s12040-020-01526-6

Evaluating the Spatial Distribution of WRF-Simulated Rainfall, 2-m Air Temperature, and 2-m Relative Humidity over the Urban Region of Bangalore, India

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