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Spatiotemporal Variations of Precipitation and Temperatures Under CORDEX Climate Change Projections: A Case Study of Krishna River Basin, India

  • Shaik RehanaEmail author
  • Galla Sireesha Naidu
  • Nellibilli Tinku Monish
Chapter

Abstract

The Earth’s climate is not static; it changes according to the natural and anthropogenic climate variability. Anthropogenic forcing due to increase of greenhouse gases in the atmosphere has driven changes in climate variables globally. Changes in climatological variables have severe impact on global hydrological cycle affecting the severity and occurrence of natural hazards such as floods and droughts. Estimation of projections under climate signals with statistical and dynamic downscaling models and integration with water resource management models for the impact assessment have gained much attention. The fine-resolution climate change predictions of dynamic regional climate model (RCM) outputs, which include regional parameterization, have been widely applied in the hydrological impact assessment studies. Advancement of the Coordinated Regional Downscaling Experiment (CORDEX) program has enabled the use of RCMs in regional impact assessment which has progressed in recent years. CORDEX model outputs were considered to be valuable in terms of establishing large ensembles of climate projections based on regional climate downscaling all over the world. However, the simulations of RCM outputs have to be evaluated to check the reliability in reproducing the observed climate variability over a region. The present study demonstrates the use of bias-corrected CORDEX model simulation in analyzing the regional-scale climatology at river basin scale, Krishna river basin (KRB), India. The precipitation and temperature simulations from CORDEX models with RCP 4.5 were evaluated for the historical data for the period of 1965 to 2014 with India Meteorological Department (IMD) gridded rainfall and temperature data sets cropped over the basin. The projected increase of precipitation under climate signals was predicted to be from 74.4 to 136.7 mm over KRB for the future time period of 2041–2060 compared to the observed periods of 1966–2003. About 1.06 °C to 1.35 °C of increase in temperatures was predicted for the periods of 2021–2040 and 2041–2060, respectively, compared to the observed period of 1966–2014 over KRB. The climate variable projections obtained based on RCM outputs can provide insights toward the variations of water-energy variables and consequent impact on basin yields and losses in river basin management.

Keywords

Bias correction Dynamic downscaling Hydrology Regional circulation model (RCM) General circulation model (GCM) 

Notes

Acknowledgments

The research work presented in the manuscript is funded by Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India through Start-up Grant for Young Scientists (YSS) Project no. YSS/2015/002111.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Shaik Rehana
    • 1
    Email author
  • Galla Sireesha Naidu
    • 1
  • Nellibilli Tinku Monish
    • 1
  1. 1.Spatial InformaticsInternational Institute of Information TechnologyHyderabadIndia

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