Human influence on sub-regional surface air temperature change over India
R Dileepkumar1, Krishna AchutaRao2, T Arulalan1,3
1Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India.
Scientific Reports
|June 14, 2018
Summary
Human activities, primarily greenhouse gases, are driving temperature increases in India. Other factors like aerosols and land use partially offset these changes, impacting regional climate adaptation.
Area of Science:
- Climate Science
- Atmospheric Science
- Environmental Science
Background:
- Global Mean Surface Temperature is rising due to human activities.
- Regional climate change detection and attribution (D&A) is complex due to internal variability, forcing uncertainties, model errors, and observational limitations.
- Understanding regional temperature changes is crucial for societal impacts and adaptation strategies.
Purpose of the Study:
- To investigate the causes of annual and seasonal surface air temperature (TAS) changes over India.
- To perform a detection and attribution (D&A) analysis for regional climate change in India.
- To assess the influence of anthropogenic forcings on India's temperature trends.
Main Methods:
- Utilized two observational datasets for India.
- Analyzed results from a multi-model archive of forced and unforced climate simulations.
- Employed optimal fingerprinting methods and various temporal-averaging techniques for D&A analysis.
Main Results:
- Robustly attributed surface air temperature (TAS) changes over India from 1956-2005.
- Identified greenhouse gases as the primary anthropogenic forcing responsible for observed warming.
- Found that aerosols and land use land cover change partially offset the warming effect of greenhouse gases.
Conclusions:
- Anthropogenic forcing, dominated by greenhouse gases, is the main driver of observed temperature changes in India.
- Regional D&A studies are essential for understanding climate change impacts and informing adaptation policies.
- Future research should continue to refine regional climate models and observational data.
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