DST - Mahamana Centre of Excellence in Climate Change Research (MCECCR)

District and Block level AAS Bulletins of Varanasi district of Vindhyan Agro-climatic Zone of East Uttar Pradesh.

Mahamana Centre of Excellence in Climate Change Research (MCECCR)

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.

Coordinator's Message

Prof. Rajesh Kumar Mall

Principal Investigator,
Institute of Environment & Sustainable Development
Banaras Hindu University, India

Welcome to DST - Mahamana Centre of Excellence in Climate Change Research (MCECCR). The main goal of this Center is to develop a holistic approach for solving climate change related problems and impact assessment.

Academic Events

04 August

2022

Setting up of Dakshin Gangotri at Antarctica : A Miracle & Climate Change

DST-MCECCR Lecture Series Entitled "Setting up of Dakshin Gangotri at Antarctica : A Miracle & Climate Change" by Prof. Harsh Gupta
23 July

2022

Climate in Himalaya : Challenges for Sustainable Development

DST-MCECCR Lecture Series Entitled "Climate in Himalaya : Challenges for Sustainable Development" by Prof. A. P. Dimiri
6 June

2022

Planet Earth Needs Risk Resilient Infrastructures Under Climate Change Scenario

DST-MCECCR Lecture Series Entitled "Planet Earth Needs Risk Resilient Infrastructures Under Climate Change Scenario" by Dr. O. P. Mishra
17 May

2022

Groundwater Variability Across India, Under Contrasting Human And Natural Conditions

DST-MCECCR Lecture Series Entitled "Groundwater Variability Across India, Under Contrasting Human And Natural Conditions" by Dr. V. M. Tiwari
14 May

2022

Climate Research in India: Current Status and Way Forward

DST-MCECCR Lecture Series Entitled "Climate Research in India: Current Status and Way Forward" by Dr. Akhilesh Gupta
21 Apr.

2022

Career Help Desk By An Expert Reviewer

DST-MCECCR Lecture Series Entitled "Career Help Desk By An Expert Reviewer" by Prof. Gordana Medunic
10 Aug.

2021

Climate Research 2.0: A Framework for Climate Studies for The Decade

DST-MCECCR Lecture Series Entitled "Climate Research 2.0: A Framework for Climate Studies for The Decade" by Prof. Dev Niyogi
15 - 16 Mar.

2021

Online workshop on Species Distribution Modelling Using R

Training program of Species Distribution Modelling Using R
27 - 31 Jan.

2020

2nd National workshop on Techniques in Hyperspectral Data Analysis and Processing

Training Programme on Hyperspectral Data Analysis and Processing
22 April

2019

Launch of High Performance Computing

Launch of HPC in DST - Mahamana Centre of Excellence in Climate Change Research, IESD, BHU.
21 - 31 Jan.

2019

Crop Simulation Modelling and its Application

Advance Training Programme on "Crop Simulation Modelling and its application".
18-19 May

2017

Piloting Climate Outlook Forums (PCOF) at State level

Piloting Climate Outlook Forums (PCOF) at State level – Eastern Uttar Pradesh, India DST- Mahamana Centre of Excellence in Climate Change Research, Banaras Hindu University, Varanasi.
23 Feb.

2017

Climate Change Research in India : Progress

Brainstorming Meeting on “CLIMATE CHANGE RESEARCH IN INDIA: PROGRESS, CHALLENGES AND WAY FORWARD” at BHU, Varanasi.
21 April

2014

Simulation Modelling and Climate Change

National Workshop on 'Simulation Modelling and Climate Change' ,IESD, BHU, Varanasi, India.

Quick Links

Department of Science and Technology, New Delhi

India Meteorological Department (IMD), New Delhi

National Institute of Disaster Management, New Delhi

National Institute of Oceanography (NIO), Goa

Indian Institute of Tropical Meteorology(IITM), Pune

Central Ground Water Authority (CGWA), New Delhi

Indian Agricultural Research Institute (IARI), New Delhi

International Centre for Theoretical Physics, Italy

University of Florida, USA

Purdue University, US

Indian Institute of Technology, Delhi

Indian Institute of Technology, Kanpur

Indian Institute of Technology, Madras

Indian Institute of Technology, Kharagpur

Indian Institute of Technology, Bhubaneswar

Indian Institute of Technology (BHU), Varanasi

Indian Institute of Technology, Roorkee

Banaras Hindu University, Varanasi

Tweets by mceccr

Mission Statement

Education / Training

To develop an interdisciplinary curriculum including special courses for undergraduate, postgraduate & doctoral students

Research Centre

To undertake high-impact, multi-disciplinary problem driven research for end-to-end solutions to climate change.

Human Resource Development

To establish a multi-disciplinary research to fill the gap of climate change and to build long-term scientific capacity, systems for study of regional climate change and future.

Government and Industry Interaction

To provide critical assessments regarding Government policies and provide support in decision making.
To serve public as well as private sector entities catering to clean energy, climate advisories and services.

Research Highlights

The study identifies three prominent heat wave (HW) prone regions i.e., Northwestern, Central and South-Central India, and found a Spatio-temporal shift in the occurrence of HW events with a significantly increasing trend, highest being in West Madhya Pradesh (0.80 events/year), while a significantly decreasing trend was observed over eastern region i.e., Gangetic West Bengal (-0.13events/year). Severe Heat wave (SHW) events showed a southward expansion and a spatial surge during the decades of 2001-2010 and 2010-2016. Additionally, correlation between HW/SHW events and observed mortality reveals that the eastern coastal states i.e., Odisha and Andhra Pradesh show a significant positive correlation of 0.62 and 0.73 respectively.

Singh et al., 2021
International Journal of Climatology

The evidence of effect of multiple air pollutants e.g., aerosols (black carbon, BC; PM2.5 and PM10) and trace gases (NO2, SO2 and O3) on all-cause premature mortality was established over central Indo-Gangetic Plain (IGP). Statistically significant impact of BC aerosols (4.95%), followed by NO2 (2.38%) and PM2.5 (1.06%) on mortality was noted, particularly for elderly and children. Individual effects of air pollutants increased in presence of other pollutants. The distributed lag nonlinear model showed significant lag effect of pollutants up to 5 days. The exposure-response curves for individual air pollutants were mostly linear.

Singh et al., 2021
Atmospheric Environment

IAerosol climatology during typical haze dominating period was explored using several EOS products from 2010 - 2020. Comparatively high aerosol loading with dominance of fine and UV-absorbing aerosol are noted across the Indo-Gangetic plain (AOD:0.58; UVAI:0.74) against weak UV-absorbing fine aerosols over Southeast Asia (AOD:0.26; UVAI:0.07). Urban hotspots across IGP (except Dhaka) denote a spatially consistent minor increasing trend in AOD (0.2-1.8x10-2year-1) while increase in UVAI is more prominent over upper IGP. Smoke aerosols are more UV-absorbing across South Asia compared to Southeast Asia. At upper atmosphere (>4km) dust aerosols clearly dominate across the IGP. Smoke & urban aerosols are abundant over SEA.

Banerjee et al., 2021
JGR-Atmosphere

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
Environmental pollution

Increasing trend of DTR (0.038_C/decade) during 1951–2016, and a decreasing trend (−0.02_C/decade) during the recent period (1991–2016) across the different agro-climatic zones (ACZs) of India. Increasing trend was noted for Tmax (0.078_C/decade, significant), Tmin (0.049_C/decade) during 1951–2016 and Srad (0.10 MJ/m2/day/decade) during 1984–2016. Decreasing trend in DTR was accounted for much increase in Tmin (0.210_C/decade) during 1991–2016. There were also interesting spatial differences found with the ACZs in the north-west, parts of Gangetic plain, north-east, and central India exhibiting negative DTR trends.

Mall et al. 2021
International journal of climatology

It is the first study to evaluate performance of eight CORDEX-SA regional climate models for simulating heat waves over India. In the present study, Regional Climate Models (RCMs) namely, CCAM and RegCM, from Coordinated Regional Climate Downscaling Experiments (CORDEX) for South Asia (SA) are evaluated for simulating heat waves (March–June) over India in comparison with observations from India Meteorological Department (IMD). LMDZ4 and GFDL-ESM2M were found to be best-performing models in significantly reproducing the heat wave frequency and spatial variability in closer proximity with observations over India amongst all models after bias correction. The study suggests a way forward to assess RCMs performance in extreme weather analysis in future projections.

Singh et al., 2021
Atmospheric Research

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

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
Sugar Tech.

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
Environmental Pollution

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

As soil erosion is an integral element for sustainable agricultural and environmental development, this study aims to investigate the impact of rainfall and land use/land cover changes in the current and future scenarios (1981 – 2040) to further deduce the soil erosion losses using the state-of-the-art Revised Universal Soil Loss Equation (RUSLE), Cellular Automata Markov Chain (CA-Markov) and machine learning models. In total seven CMIP5 model projections viz Ensemble mean, MRI-CGCM3, INMCM4, canESM2, MPI-ESM-LR, GFDL-ESM2M and GFDL-CM3 of rainfall were used in model development and comparison. As a result, we have generated an integrated framework for the prediction of soil erosion rates over Mahi River Basin.

Maurya et al. 2021
Journal of Hydrology

A comprehensive evaluation of multi-satellite satellite precipitation products are undertaken against ground-measured Indian Meteorological Department (IMD) precipitation data to estimate and forecast the meteorological drought in the Bundelkhand region of Central India. The high-resolution CHIRPS data showed the closest agreement with the IMD precipitation and well captured the drought characteristics. The Standardized Precipitation Index (SPI) identified seven major droughts events during the period of 1981 to 2016. The forecasting result showed a reasonably good agreement with the observed datasets with the one-month lead time.

Pandey et al. 2020
Geocarto International

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

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
Climatic Change

Thematic Areas

Simulation Modeling

Evaluation of Climate Models - understanding model performance and constraining uncertainty in climate models.
Recognizing the uncertainty in role of aerosols on climate change for improved climate modeling

Climatic Impact and Vulnerability Assessment

Water - Integrated water resource management in the context of climate variations.
Health - Assess the individual and synergistic impact of climate change, air quality and extreme events on human health.
Agriculture - Assesment of crop production and climatic risk using the crop simulation models.

Socio-Economic Issues

Community based management
Economics of Climate Change - Adaptation and Mitigation
Climate Change and Human Security: Resilience and Response
Water security, Food Security, Energy Security, Health security leading to national security.