Sea surface temperature (SST) over Indian Ocean and Near Surface Temperature (TAS) over the Indian subcontinent are directly connected with circulation, winds, humidity, and precipitation over India. Increased SSTs & TAS are a major consequence of climate change driven by anthropogenic factors. Changes in SST and/or TAS can affect circulation patterns, which can impact the monsoons that are vital to the region.
We have previously carried out a D&A analysis of area averaged annual mean SST changes over four regions in the Indian Ocean (Bay of Bengal, Arabian Sea, Southwest Indian Ocean and Southeast Indian Ocean) using regression based optimal detection method of Allen & Tett (1999). Among the SST regions we found that the Bay of Bengal, Arabian Sea, and Southeast Indian Ocean have shown warming due to Anthropogenic causes over the last 50- and 100-year periods. However, over the more recent 20- and 30-year period, the warming was not inconsistent with natural variability.
In a second analysis of season-wise TAS changes over seven homogenous temperature zones in India, we found that in the Western Himalayas (all seasons except JJA), West Coast, and East Coast, anthropogenic influences have dominated the observed changes. The combination of all seven regions shows that over India, temperature changes have been dominated by anthropogenic forcings in all seasons except JJA.
In the current study, we merge the SSTs from the Indian Ocean and the TAS over land (36°S-42°N, 51°E-102°E at 3°X3° resolution) for 100-year (1906-2005) and 50-year (1956-2005) periods and carry out a D&A analysis of the merged data using two Optimal Fingerprint methods a) the regression based method of Allen & Tett (1999) and b) the method of Santer et al (2004). For the merged data, we use TAS observations from CRU 3.2.2, and multiple SST datasets (ERSST v3b & HadISST v1.1) along with model output from 7 models in the Coupled Model Intercomparison Project Phase-5 (CMIP5) database. Individual forcing runs such as the historicalGHG, historicalNat, historicalAnthro, historicalAA along with the combined forcing (historical) and control (piControl) runs.
Preliminary results indicate that the warming over this region is attributable to anthropogenic forcings (specifically Greenhouse gases) with a negligible contribution from natural forcings over the 100- & 50- year time periods. We explore the sensitivity of our results to observational uncertainty and D&A method used.
- Allen, Myles R., and Simon FB Tett. "Checking for model consistency in optimal fingerprinting." Climate Dynamics 15.6 (1999): 419-434.
- Santer, Benjamin D., et al. "Identification of anthropogenic climate change using a second generation reanalysis." Journal of Geophysical Research: Atmospheres 109.D21 (2004).