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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/11470
Title: Evaluation of RegCM4 climate model for assessment of climate change impact on crop production
Authors: Singh N.
Mall R.K.
Sonkar G.
Singh K.K.
Gupta, Akhilesh Kumar
Published in: Mausam
Abstract: For evaluating the impacts of climate change on crop yields regional climate models (RCMs) are now considered better than general circulation models (GCMs). In order to assess what extent the climate output of RCM-RegCM4.0 is biased, this is analysed by comparing the base line simulated daily weather with the observed weather for the corresponding year (1971-2000) over Varanasi. The result shows that the RCM output is biased towards lower annual maximum and minimum temperature by 5.4 °C and 1.7 °C respectively. Seasonal analysis shows that the RCM output is underestimating the kharif (Rice) season maximum and minimum temperature by 3.0 °C and 1.5 °C respectively and the rabi (wheat) season maximum and minimum temperature by 6.7 °C and 1.4 °C respectively. The RCM output overestimates the annual and rabi rainfall while it underestimates kharif rainfall. It is also overestimating the annual, kharif and rabi season rainy days. Most importantly, model underestimates the extreme events, i.e., extreme temperature and heavy rainfall. The study also includes assessment of biasness in yields of wheat and rice simulated using CERES-wheat and CERES-rice crop models employing observed and RCM simulated weather data. Due to biasness in the extreme events in RCM baseline data the simulated wheat and rice grain yield during several years were overestimated compared to observed yield. The present RCM output is overestimating the different climatic variables in comparison to present observed climate for annual as well as seasonal. Therefore, framing of better management practices, mitigation programme and planning and policy making based on climate model output must ensure to get the reliable and validated RCM climate output. For that we need more precise and improved regional climate models through more research in climate modelling. © 2018, India Meteorological Department. All rights reserved.
Citation: Mausam (2018), 69(3): 387-398
URI: http://repository.iitr.ac.in/handle/123456789/11470
Issue Date: 2018
Publisher: India Meteorological Department
Keywords: Agriculture
Climate change
DSSAT
RegCM4.0
Rice
Wheat
ISSN: 2529416
Author Scopus IDs: 55257540000
8158084700
56197134600
57208749166
55491955100
Author Affiliations: Singh, N., DST-Mahamana Centre of Excellence in Climate Change Research, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, 221 005, India
Mall, R.K., DST-Mahamana Centre of Excellence in Climate Change Research, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, 221 005, India
Sonkar, G., DST-Mahamana Centre of Excellence in Climate Change Research, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, 221 005, India
Singh, K.K., India Meteorological Department, New Delhi, 110 003, India
Gupta, A., Department of Science and Technology, New Delhi, 110 016, India
Funding Details: Authors thank the Climate Change Programme, Department of Science and Technology, New Delhi, for financial support. We thankfully acknowledge India Meteorological Department New Delhi for providing observed rainfall and temperature data used in the study. We also thank the CCCR-IITM for RegCM outputs from the domain CORDEX-South Asia that was used in this study. The contents and views expressed in this research paper/article are the views of the authors and do not necessarily reflect the views of the organizations they belong to.
Corresponding Author: Mall, R.K.; DST-Mahamana Centre of Excellence in Climate Change Research, Institute of Environment and Sustainable Development, Banaras Hindu UniversityIndia; email: mall_raj@rediffmail.com
Appears in Collections:Journal Publications [ME]

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