Analysis of CMIP6 Simulations in the Indian Summer Monsoon Period 1979-2014

Authors

  • Dr. Lakshmana Rao Vennapu Dept. of Meteorology and Oceanography, Andhra University, Visakhapatnam, India Author
  • Dr. Krishna Dora Babu Kotti Dept. of Geography, School of Distance Education, Andhra University, Visakhapatnam, India Author
  • Dr. Sravani Alanka Flood Meteorological Office, Meteorological Centre Hyderabad, IMD India. Author
  • Pavan Krishnudu Badireddi Ideal Institute of Technology, JNTUK, Kakinada, East Godavari, India. Author

DOI:

https://doi.org/10.46488/NEPT.2024.v24i01.B4215

Keywords:

Global Climate, Monsoon, Coupled Model, Climate Change

Abstract

The monsoon system in India plays a pivotal role in shaping the country's climate. Recent studies have indicated that the increasing variability of monsoons is attributable to climate change, resulting in prolonged periods of drought and excessive rainfall. Understanding, analyzing, and forecasting monsoons is crucial for socioeconomic sustainability and communities’ overall well-being. Climate forecasts, which project future Earth climates typically up to  2100, rely on models such as the Couple Model Intercomparison Project (CMIP). However, confidence in these forecasts remains low due to the limitations of global climate models, particularly in terms of capturing the intricacies of monsoon dynamics, notably from June to September. To address this issue, researchers have examined precipitation simulations under various future scenarios using both CMIP5 and the latest CMIP6 models. Evaluating the performance of these models from 1979 to 2014, particularly in simulating mean precipitation and temperature, has revealed improvements in multi-model ensembles (MME), highlighting advancements in monsoon characteristics. By comparing the CMIP5 and CMIP6 models, researchers have identified the most reliable models for climate downscaling research, which can provide more accurate predictions of regional climate changes, thereby offering valuable insights for enhancing climate modeling in the Indian subcontinent.

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