DST - Mahamana Centre of Excellence in Climate Change Research (MCECCR) is an initiative taken at BHU under Prime Minister's National Action Plan on Climate Change. The centre started in May 2017 funded by the Department of Science and Technology, Government of India to develop fundamental understanding of the climate change and deducing its impact on the water, health and agricultural sectors from local to global scales. The primary goal of the centre is to develop infrastructure facilities for climate simulation modeling, to understand climatic impacts and vulnerability assessment of agriculture, water, health, socio-economic sector and to develop proper adaptation and mitigation strategies.
Impact of climate change on sugarcane crop was assessed using the CANEGRO-Sugarcane model in diverse agro-climatic zones of the Uttar Pradesh. The results showed that Stalk Fresh Mass is projected to increase by 3–39% (rainfed) and 7–47% (irrigated) in 2040–2060 relative to 1971–2000. Similarly, Sucrose Mass is projected to decrease by 9–69% (rainfed) and 6–37% (irrigated). The findings suggest the development of efficient water use, heat-tolerant cane variety and improved farm management strategies in the near future to assist the sugar industry and to adapt to the changing climate in northern India.
Sonkar et al., 2020
Conclusive evidence of the negative impact of rising temperature on wheat yield was reported for India. The impact was inconsistent spatially. One degree increase in mean temperature resulted a 7% decrease in wheat yield over India which varied disproportionally across the wheat growing zones within a range of -9% (peninsular zone, PZ) to 4% (northern hills zone, NHZ).
Sonkar et al., 2019
Increase in daily mean temperature was strongly associated with excess mortality in Varanasi, both during summer (5.61%) and winter (1.50%). Daily mortality was found to be increased by 12% due to heat wave. The study is first to present the increase in mortality with decrease in diurnal temperature variation. Increase in mortality was high during summer compared to winter. Similarly, risk ratio was high due to heat wave compared to cold spell.
Singh et al., 2019
Science of the Total Environment
The performance and validation of regional climate model (RegCM-4.3) simulation of Indian summer monsoon rainfall (ISMR) have been conducted with a futuristic view of climate change study with the convective parameterization schemes (CPSs) over the different homogeneous regions of India. Performance and validation of RegCM-4.3 in capturing regionalized rainfall of Indian subcontinent was assessed and various best performing parameterization schemes of RegCM-4.3 were identified to simulate the rainfall over different regions of India. The overall diversification of simulation depending upon the topographical difference of Indian subcontinent causes the regionalize difference in simulating monsoon rainfall over the Indian subcontinent.
Bhatla et al., 2020
Theoretical and Applied Climatology
The results obtained from this study are used to evaluate the activity of initial conditions of zonal wind circulation speed, which causes an increase in the uncertainty of regional model output over the region under investigation. Further, the results showed that the EIN15 zonal wind circulation lacks sufficient speed over the specified region in a particular time, which was carried forward by the RegCM output and leads to a disrupted regional simulation in the climate model.
Ghosh et al., 2019
Theoretical and Applied Climatology
We assessed the existing status and scope of DRR including CCA in development projects across South Asia, so that an effective and achievable deliberation may be made to regional policymakers. The project inventory was diverse in nature with respect to location, scale, sectoral focus, and strategic importance. Bangladesh, India, and Bhutan were found to be proactive in implementing DRR- and CCA-related projects. Meta-analysis suggests an urgent need for an individual and collaborative convergence of processes for DRR and CCA through policies, plans, strategies, and programs.
Mall et al., 2019
International Journal of Disaster Risk Science
Smoke injection height varied considerably during rice (October-November: 0.71±0.65km) and wheat (April-may: 2.34±1.34km) residue burning period with a significant positive correlation with prevailing boundary layer. Besides, despite travelling efficiently to free troposphere, major proportion of smoke AOD (50-80%) continue to remain close to the surface (less than 3km).
Vinjamuri et al., 2020
Short-term variations in aerosol climatology during extreme biomass burning emissions over Indo-Gangetic Plain, and thereby to regional climate were investigated. Columnar aerosol loading increased significantly, with presence of absorbing aerosols having low aerosol layer height. A strong short-wave aerosol radiative forcing and heating rate (4.3 K day-1) during extreme biomass burning emissions over Varanasi was evident.
Singh et al., 2018
Atmospheric Chemistry and Physics
A comparatively high aerosol loading (AOD: 0.50±0.25) was evident over Indo-Gangetic Plain (IGP) with a statistically insignificant increasing trend of 0.002 year-1. 2. The incremental AOD trends are more pronounced over central to lower IGP. A distinct “aerosol pool” region over eastern part of Ganges plain was identified, where meteorology, topography, and aerosol sources favor the persistence of airborne particulates.
Kumar et al., 2018
The study addresses the performance analysis of reference evapotranspiration (ETo) estimated from NASA/POWER, National Center for Environmental Prediction (NCEP) global reanalysis data before and after dynamical downscaling through the Weather Research and Forecasting (WRF) model. The state-of-the-art Hamon’s and Penman-Monteith’s methods were utilized for the ETo estimation in the Northern India. The results indicated that after WRF downscaling, there was some marginal improvement found in the ETo as compared to the without downscaling datasets. However, a better performance was found in the case of NASA/POWER datasets In overall, the results indicated that the NASA/POWER and WRF downscaled data can be used for ETo estimation, especially in the ungauged areas. However, NASA/POWER is recommended as the ETo calculations are less computationally expensive and easily available than performing WRF simulations.
Srivastava et al., 2020
Theoretical and Applied Climatology
The study explores the relation between the long-term rainfall (1992–2014) and the corresponding water table variation over the Varanasi district. The district experienced an annual rainfall average of 876 mm during the study period. In the recent decade (2003–2014), the amount of annual rainfall and rainy days declined by 42 mm and 8 days, respectively, were compared with previous decade (1992–2002). The water table fluctuation had also shown decreasing trend in the recent decade and were compared with the previous decade. The frequent fluctuations in rainfall anomaly and water table fluctuation had been related to El Nino and La Nina events to study the impact of these events at regional scale. The intense cultivation of water intensive crops as well as rainfall variation was found to be one of the major causes behind the water table fluctuation in the study area.
Dey et al. 2020
Arabian Journal of Geosciences
Revised Universal Soil Loss Equation, rainfall climatology from merged IMD gauge-TRMM (1998–2015) and soil hydraulic parameters were integrated to delineate the highly susceptible zones of the Kosi River Basin (KRB), Bihar, India for soil erosion assessment and watershed prioritization. ROSETTA model and the analytical hierarchy process based on multi-criteria evaluation method (AHP-MCE) was employed to assign the weighting to each factor (Soil erosion. Weighted overlay analysis is performed to generate the watershed prioritization map for soil and water conservation. The findings suggest that the sub-watersheds 5, 8 and 7 required utmost attention and conservative measures because of their high erodibility characteristics.
Pradhan et al., 2018
This work aims to explore the biasness in the RegCM climate model outputs for diverse agro climatic zones of Uttar Pradesh, India emphasizing on wheat and rice yields with and without bias corrected data for the baseline period of 1971–2000. Bias correction approach showed good agreement for the annual and seasonal maximum and minimum temperatures. The CERES-Wheat and CERES-Rice models embedded in DSSAT (Decision Support System for Agro-technology Transfer) were used to quantify the biasness in the simulated potential, irrigated, and rainfed wheat and rice yield. The RCM-simulated wheat and rice yield were high while the bias-corrected yield has shown good agreement with the observed yield.
Mall et al., 2018