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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

Author

Listed:
  • R. K. Mall

    (Banaras Hindu University)

  • Nidhi Singh

    (Banaras Hindu University)

  • K. K. Singh

    (India Meteorological Department)

  • Geetika Sonkar

    (Banaras Hindu University)

  • Akhilesh Gupta

    (Department of Science and Technology)

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 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.

Suggested Citation

  • R. K. Mall & Nidhi Singh & K. K. Singh & Geetika Sonkar & Akhilesh Gupta, 2018. "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, Springer, vol. 149(3), pages 503-515, August.
  • Handle: RePEc:spr:climat:v:149:y:2018:i:3:d:10.1007_s10584-018-2255-6
    DOI: 10.1007/s10584-018-2255-6
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    References listed on IDEAS

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    1. Naresh Soora & P. Aggarwal & Rani Saxena & Swaroopa Rani & Surabhi Jain & Nitin Chauhan, 2013. "An assessment of regional vulnerability of rice to climate change in India," Climatic Change, Springer, vol. 118(3), pages 683-699, June.
    2. Elizabeth J. Kendon & Nigel M. Roberts & Hayley J. Fowler & Malcolm J. Roberts & Steven C. Chan & Catherine A. Senior, 2014. "Heavier summer downpours with climate change revealed by weather forecast resolution model," Nature Climate Change, Nature, vol. 4(7), pages 570-576, July.
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    4. Birthal, P.S. & Khan, T.M. & Negi, D.S. & Agarwal, S., 2014. "Impact of Climate Change on Yields of Major Food Crops in India: Implications for Food Security," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 27(2).
    5. Xuan Yang & Zhan Tian & Laixiang Sun & Baode Chen & Francesco N. Tubiello & Yinlong Xu, 2017. "The impacts of increased heat stress events on wheat yield under climate change in China," Climatic Change, Springer, vol. 140(3), pages 605-620, February.
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