Swarnima SINGH, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, U.P., India, India
Climate science is a data-intensive subject. A recent surge in research with big data analytics and data mining is trying to fulfil the existing gaps in the understanding of complex climatic changes. The study investigates climate and climate change scenario modeling of the western Himalayan region. It thrusts upon the causes of climatic variability in AEZs of the study region to determine the baseline of climatic changes by creating a methodology for the baseline and simulated spatio-temporal precipitation and temperature trends for impact analysis. The regional climate has been scaled down built on the Global Circulation Model (GCMs) downscaling for regional adaptive responses on the WRF model, based NOAA-NCEP-EMC-ESRL-NCAR partnership. The downscaling methodology (shepherd method) has been used on IMD, AIRS and TRMM combined interpolated gridded data to generate climate change scenarios for 2020, 2050 and 2080 for temperature and precipitation. The IMD, TRMM and AIRS data grid assessments of the western Himalayan region were quite harmonized. The analysis is shaped by GHGs emissions preceded from Intergovernmental Panel on Climate Change-Special Emission Scenario (IPCC-SRES) change modeling mechanism to understand the persistent GHG emissions at or above current rates in the baseline and emission scenario for further warming during the 21st century.
Mots clés : Regional downscaling|WRF model |Emission scenarios |Simulations |climate change impact
A104817SS