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Evaluating the performance of RegCM4.0 climate model for climate change impact assessment on wheat and rice crop in diverse agro-climatic zones of Uttar Pradesh, India

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Abstract

The paper aims to explore the biasness in the RegCM climate model outputs for diverse agro-climatic zones of Uttar Pradesh, India, with emphasis on wheat (Rabi growing season) and rice (Kharif growing season) yields with and without bias correction using quantile mapping approach for the baseline period of 1971–2000. The result shows that RCM highly underestimated the maximum and minimum temperature. There exists a bias towards lower precipitation in annual and Kharif and higher in Rabi along with strikingly low intense warm (maximum temperature > 45 °C and 40 °C) and high cold events (maximum temperature < 20 °C and minimum temperature < 5 °C) in the RCM simulation and biased towards low extreme rainfall > 50 mm/day. Bias correction through quantile mapping approach, however, showed excellent agreement for annual and seasonal maximum and minimum temperature and satisfactory for extreme temperatures but drastically failed to correct rainfall. The study also quantified the biasness in the simulated potential, irrigated, and rainfed wheat and rice yield using DSSAT (Decision Support System for Agro-technology Transfer) crop model by employing observed, RCM baseline, and RCM baseline bias-corrected weather data. The grain yields of RCM-simulated wheat and rice were high while the bias-corrected yield has shown good agreement with corresponding observed yield. Future research must account for the development of more reliable RCM models and explicitly bias correction method in specific to complement future analysis.

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Acknowledgements

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.

Funding

The authors thank the Climate Change Programme, Department of Science and Technology, New Delhi, for financial support.

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Authors and Affiliations

  1. DST-Mahamana Centre of Excellence in Climate Change Research, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, 221005, India

    R. K. Mall, Nidhi Singh & Geetika Sonkar

  2. Agromet Division, India Meteorological Department, New Delhi, India

    K. K. Singh

  3. Department of Science and Technology, New Delhi, India

    Akhilesh Gupta

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  1. R. K. Mall
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  2. Nidhi Singh
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  5. Akhilesh Gupta
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Correspondence to R. K. Mall.

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Mall, R.K., Singh, N., Singh, K.K. et al. Evaluating the performance of RegCM4.0 climate model for climate change impact assessment on wheat and rice crop in diverse agro-climatic zones of Uttar Pradesh, India. Climatic Change 149, 503–515 (2018). https://doi.org/10.1007/s10584-018-2255-6

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