Assessment of Aerosol Optical Depth over Indian Subcontinent during COVID-19 lockdown (March–May 2020)
by Krushna Chandra Gouda, Iranna Gogeri & Aruna Singanahalli Thippa Reddy
The COVID-19 pandemic has created a major threat to human beings and huge losses over the globe. In order to control the pandemic spread, almost all parts of the world imposed lockdown. The imposed lockdown drastically impacted on reduction in the atmospheric pollutions and also resulted in net decrease in aerosol optical depth (AOD) in the atmosphere. In this study, the reduction in the AOD during the COVID-19 lockdown over the Indian subcontinent is being assessed using the moderate resolution imaging spectroradiometer (MODIS) satellite data available in Giovanni version 4.34 developed by NASA. The long-term mean analysis is computed considering 20 years (i.e., 2000–2019) data on Terra platform with a temporal resolution of daily and monthly and spatial resolution of 1 degree. The dataset of AOD with a temporal resolution of monthly was used for investigation of AOD anomaly for March, April and May 2020, and the seasonal variation (March to May 2020) is also assessed. Similarly, the daily scale dataset was used to investigate the percentage change in AOD during pre-lockdown and lockdown period with respect to long-term mean. The key findings in the present study show that reduction in AOD level over Indian subcontinent is approximately 14.75% during the lockdown period with spatial variation in the magnitude from region to region. The level of AOD is greatly reduced in the northern part of India (~ 22.53%), whereas changes in the southern part of India are much less (~ -0.31%); this may be due to ongoing anthropogenic activities during the lockdown period in this region. Furthermore, a positive AOD anomaly was observed in the eastern and central regions of India (i.e., over the states of Odisha, Chhattisgarh, Telangana, Jharkhand, West Bengal, Part of Maharashtra and Karnataka). However, negative AOD anomaly was observed in the north and northwest regions of India, whereas not much change in the AOD anomaly in other parts of the country. The overall assessment of the AOD level shows a net decrease over the Indian subcontinent during the lockdown period, i.e., March to May 2020. This kind of assessment study will surely help the government for the sustainable policy decisions for atmospheric pollution control by implementing proper lockdown procedures over various parts of the country.
Source: https://doi.org/10.1007/s10661-022-09855-3
Assessing the Impact of Parameter Sensitivity and Multi-Configurational Ensembles of WRF- Hydro Model on Simulated Hydro-Meteorological Variables—A Multifaceted Evaluation over Krishna River Basin of India
by Sumana Sarkar & P. Lakshmikanthan
Quantifying the variability of hydro-meteorological variables and various land-surface processes in response to the diverse sources of uncertainties arising from the structure of hydrological models, model parameters, calibration procedures, and schemes related to the various physical process representations is a significant scientific endeavour with important implications in hydrology. Sensitivity analysis is the only plausible way to provide valuable insights into how different parameters influence model outputs and helps evaluate the rationality of each model parameter. Hence, the present study employs sensitivity analysis for comprehensive evaluation of the impact of an enhanced hydrological parameterized and newly developed WRF-Hydro model towards the simulation of hydro-meteorological variables, in terms of model parameter uncertainty and structural variability. The study is carried out in the vicinity of the Krishna River basin in India with a sub grid-scale of 200 m. We evaluate the model's fidelity to accurately simulate streamflow and key hydrometeorological variables, including Evapotranspiration, soil moisture, and land heat and moisture fluxes, through a series of sensitivity experiments. These experiments quantify the impact of uncertainties related to land surface model parameterization, thresholds of model parameters, and structural configurations of the WRF-Hydro framework. The characteristics of the simulations thus generated have been validated against in-situ gauge data and remote sensing-based multi-platform observations, revealing a significant improvement in the simulation accuracy, with correlation coefficients exceeding 0.9 and 0.7 for soil moisture and soil temperature, respectively. Our findings show marked enhancement in the model’s predictive accuracy. By identifying the configurations with superior performance, this study provides practical insight for selecting optimal model parameterizations, thereby contributing to improving the hydro-meteorological forecasting frameworks and supporting better water management practices in regions with limited data availability.
Assessing the impact of modified LULC on extreme hydrological event over a complex terrain: A case study for kodagu 2018 flood event
by Sumana Sarkar and S.Himesh
Abstract
The livelihoods and biodiversity in the Kodagu district of Karnataka are greatly altered by the growing urbanization through huge deforestation. The changes in the Land Use and Land Cover (LULC) patterns have important implications on the heavy rainfall activity due to significant alterations in the spatial distribution of existing land-surface properties. Hence, in order to make region (like Kodagu) more climate resilient; it is utmost important to construct a novel coupled framework for hydro-meteorological prediction to assess the impact of changing LULC (degradation of forest cover owing to urban expansion) on extreme rainfall events. Only a well-calibrated, validated, and optimized coupled high-resolution hydrological-atmospheric modelling system can be one of the best tools to study such complex problems. Thus in the present study, we have enhanced the forecasting capability of the state-of-the-art Weather Research and Forecasting (WRF) model by coupling with a physically based, fully distributed, WRF-Hydro. The evaluation of the proposed model configurations (stand-alone and coupled mode) is done with respect to two LULC datasets (USGS, 1992: less urbanized scenario and ISRO, 2017: more urbanized scenario) to explore the underlying causes and hydrological responses behind the 2018 Kodagu flood event. The simulations have been contended with both the stand-alone and coupled WRF/WRF-hydro models with different LULC datasets and a comparative evaluation have been carried out. The simulated variables (rainfall, runoff, surface fluxes, and peak stream discharge) are evaluated and compared with observation to assess the impact of changing LULC pattern during the flood event.
Source: https://www.sciencedirect.com/science/article/abs/pii/S1364682622001341
Assessing the dynamics and thermodynamics of Monsoon onset: The impact of ENSO
by Smrutishree Lenka, K. C. Gouda, MOHAN T. S., Rani Devi and V. S. Prasad
This study examines the mechanisms involved in the onset and progression of the monsoon over the Indian subcontinent by analyzing key dynamical and thermodynamical processes. Additionally, it investigates the characteristics of monsoon onset during various ENSO phases. To achieve this, we utilized long-term observations and ERA5 reanalysis data to conduct a comprehensive study on the onset and related characteristics.
Results indicate that, a robust connection between the thermal gradient in both zonal and meridional directions and the corresponding vertical wind shear both across the active monsoon shear domain (MSD) and Kerala domain (KD). It is found that, this relationship varies across different time scales i.e., annual, seasonal (ISM-length), and onset pentad (p0), underscoring that the intensity of monsoon convection hinges on the thermal gradient and wind shear. The analysis concludes that presence of weak vertical wind shear, creates a stable state and the presence of a significant thermal gradient, characterized by minimal variations in wind speed and direction at different altitudes, are critical factors that facilitate the monsoon onset. Further, El Niño tends to increase wind shear over the Indian subcontinent and leads to a delayed monsoon onset. Elevated geopotential height during an El Niño year indicates the existence of a high-pressure region, which is an unfavorable condition for the onset of the monsoon. Analysis of temperature tendency equation exhibit a robust diabatic heating which is linked to a Gill-like Rossby wave response, initiating thermodynamic interactions with midlatitude westerly jet. Furthermore, this study also gives an indication of the influence of central pacific (CP) warming events and its influence on monsoon onset characteristics, which needs further exploration.
Page 28 of 33
