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Simulated Climate Change (2031-2060)

The simulated summer monsoon 2-m air temperature patterns are changing between 1976-2005 and 2031-2060 for the RCP4.5 scenario (Fig. 5). The ensemble mean of five-members indicate large increase of above 1.5 °C over the central and northern parts of India (Fig. 5a). The individual model simulations show very different response over India (Fig. 5b-f), with LMDZ4 (IPSL) indicating a warming that is above 2.0 °C higher than in RegCM445(GFDL) by middle of the twenty-first century for most parts of the country. The ensemble mean summer monsoon precipitation change for the same period indicates less than 25 % drying in the central and eastern parts of India and moistening of similar magnitude over the rest of India (Fig. 6a). However, for most parts of India, this ensemble mean change is not found to be statistically significant. Also some of the individual models indicate precipitation changes of similar magnitude with opposite sign in these regions (Fig. 6b-f). Further, these precipitation changes are also not statistically significant, implying that the CORDEX RCMs simulated change in summer monsoon precipitation over India are uncertain not only in magnitude but also in sign.

The analysis of the CORDEX multi-RCM temperature and precipitation projections for South Asia land areas for the period 1950-2100 (Fig. 7) shows that for RCP4.5 scenario the annual mean warming is likely to be in the range 1.0-2.0 °C by 2030, 1.8-3.0 °C by 2060 and 2.0-3.1 °C by 2090 relative to the 1976-2005 period (Fig. 7b). The summer monsoon precipitation projections for this region

Summer monsoon (JJAS) season mean 2-m air temperature

Fig. 5 Summer monsoon (JJAS) season mean 2-m air temperature (°C) changes in 2031-2060 with respect to 1976-2005 for the CORDEX South Asia simulations driven by CMIP5 AOGCM RCP4.5 scenario experiments a multi-model ensemble mean (ENSM) and b-f five different CORDEX RCMs listed in Table 1. Stippling denotes areas where the 30-year mean changes are not statistically significant at the 1 % level using Student’s t test

Summer monsoon (JJAS) season mean precipitation changes

Fig. 6 Summer monsoon (JJAS) season mean precipitation changes (%) in 2031-2060 with respect to 1976-2005 for the CORDEX South Asia simulations driven by CMIP5 AOGCM RCP4.5 scenario experiments a multi-model ensemble mean (ENSM) and b-f five different CORDEX RCMs listed in Table 1. Stippling denotes areas where the 30-year mean changes are not statistically significant at the 1 % level using Student’s t test

Time series for the period 1950-2100 of

Fig. 7 Time series for the period 1950-2100 of: 2-m temperature (°C) annual a mean and b change relative to 1976-2005; and precipitation (mm day-1) summer monsoon (JJAS) season c mean and d change relative to 1976-2005, averaged over land grid points in South Asia (60- 100°E, 5-35°N) for the five different CORDEX RCMs listed in Table 1

show large spread among the individual models for the entire analysis period (Fig. 7d) suggesting that these downscaled precipitation projections are not reliable.

The percentile distribution of near-surface air temperature or precipitation gives insight into the spatial and temporal patterns of their extremes (e.g. 90th percentile). The mid-term (2031-60) projections in the RCP4.5 scenario experiments for South Asia during summer monsoon months (June-September) are shown in Fig. 8 and Fig. 9, displaying mid-term changes in extreme temperature (Fig. 8) and precipitation (Fig. 9) for the CORDEX South Asia RCMs (right-hand panels) and their

Changes in the 90th percentile of the daily distribution of 2-m air temperature

Fig. 8 Changes in the 90th percentile of the daily distribution of 2-m air temperature (°C) during summer monsoon months (June-September) in the 30-year period 2031-2060 with respect to 1976-2005 for the five CORDEX South Asia simulations (right panels) driven by CMIP5 AOGCM RCP4.5 scenario experiments (left panels) listed in Table 1

Changes in the 90th percentile of the daily distribution of precipitation

Fig. 9 Changes in the 90th percentile of the daily distribution of precipitation (mm day-1) during summer monsoon months (June-September) in the 30-year period 2031-2060 with respect to 1976-2005 for the five CORDEX South Asia simulations (right panels) driven by CMIP5 AOGCM RCP4.5 scenario experiments (left panels) listed in Table 1

corresponding driving coarser resolution CMIP5 AOGCMs (left-hand panels) relative to the reference period 1976-2005. Most of the AOGCM projections (Fig. 8, left-hand panels) show a warming of 2-3 °C extending from the eastern region to the interior north India, with the highest changes of more than 3 °C over the eastern coast of India. The downscaled spatial patterns of the mid-term changes for the extreme temperatures in CORDEX South Asia RCMs indicate lesser summer monsoon seasonal warming over India (Fig. 8, right-hand panels). The mid-term changes in the summer monsoon precipitation for the downscaled CORDEX RCMs show different spatial patterns than that for their driving CMIP5 AOGCMs (Fig. 9). While most of the AOGCMs indicate an increase in extreme precipitation over central and peninsular India (Fig. 9, left-hand panels), the projected changes for few downscaled RCMs during the same period indicate decreases in extreme precipitation over central India (Fig. 9, right-hand panels).

Finally, it is noted that this small ensemble of five transient 140-year simulations samples only a small part of the total uncertainty range. However, it was shown that this small ensemble of climate change simulations were useful in order to demonstrate the uncertainties related to RCM formulation and boundary conditions in a physically consistent manner at the regional scale. A much larger ensemble containing more forcing AOGCMs, emission scenarios and ensemble members sampling the natural variability will be needed to explore the full uncertainty ranges. Therefore, the preliminary results presented here need to be updated for CORDEX South Asia using regional climate change metrics covering broader uncertainty ranges.

 
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