Detection and attribution of near surface temperature changes over homogenous temperature zones in India

Abstract:

The IPCC Fifth Assessment Report concluded, “More than half of the observed increase in global mean surface temperature (GMST) from 1951 to 2010 is very likely due to the observed anthropogenic increase in greenhouse gas (GHG) concentrations.” Detecting and attributing the changes over regional scales can provide more relevant information to policymakers at the national level but the low signal-to-noise ratios at smaller spatial scales make this a harder problem.

In this study, we analyze changes in temperature (annual and seasonal means of mean, minimum, and maximum temperatures) over 7 homogeneous temperature zones of India from 1901 -2005 using models from the CMIP5 database and multiple observational datasets (CRU-3.22, and IITM). We perform Detection and Attribution (D&A) analysis using fingerprint methods by defining a signal that concisely express both spatial and temporal changes found in the model runs with the CMIP5 individual forcing runs; greenhouse (historicalGHG), natural (historicalNat), anthropogenic (historicalAnthro), and anthropogenic aerosols (historicalAA). We are able to detect changes in annual mean temperature over many of the homogenous temperature zones as well as seasonal means in some of the homogenous zones. We quantify the contributions resulting from individual forcings in these cases. Preliminary results indicate large contributions from anthropogenic, forcings with a negligible contribution from natural forcings.