New Delhi [India], August 15 (ANI): The latest generation of climate models projects an increase in severity and frequency of very wet Indian summer monsoon seasons, a new study by scientists from the Potsdam Institute for Climate Impacts Research shows.
The South Asian monsoon affects the lives of more than one billion people and a changing monsoon might have tremendous consequences for millions of people faced with floods and landslides. The researchers find that very wet monsoon seasons are projected to occur 8 times more often in 2050-2100 compared to 1965-2015 under unabated climate change.
With modest mitigation efforts, this is reduced to a factor of 6 in the future period. Besides, this increase in frequency and intensity of extreme monsoon seasons is accompanied by a shift from days with light rainfall to days with moderate or heavy rainfall. Additionally, the number of wet days is projected to increase.
The particular character of the change depends on the determination of humankind to reduce carbon emissions and implement mitigation measures.
There have been numerous floods in recent years associated with the Indian summer monsoon (ISM) as a component of the South Asian monsoon, for example, the Mumbai floods in 2005, floods in Northwest India and Pakistan in 2010 as a response to a strong La Nina event or those in Kerala in 2018.
Since the 1980s, there have been more than 95,000 deaths associated with floods and landslides in the countries of the Indian subcontinent. Hunt and Menon (2020) found that the Kerala flooding event in 2018 could be 36 per cent more rainfall-intense under an RCP8.5 climate. Almazroui et al. (2021) projected an increase in the annual maximum consecutive 5-day precipitation in the Asian monsoon regions and derived a higher risk for extreme flooding in the Asian monsoon regions.
Given the agricultural yield's sensitivity to the monsoon rainfall variability and associated extremes, understanding how the ISM responds to global warming is also crucial for crop yields and food security in the region as well as for numerous other aspects of public and individual life, like water management or the country's economy.
The data from various phases of Coupled Model Intercomparison projects (CMIPs) has been widely used to examine the projected changes in the global climate as well as its different components such as the ISM. In the last generation of climate models - which were the basis of earlier studies on seasonal extremes - studies identified monsoon rainfall features that were not yet well represented in the CMIP5 models.
Recently, the data from the latest phase 6 of CMIP (CMIP6) has become available and it was confirmed that they bring relevant improvements regarding the ISM's characteristics. By updating deep convective schemes, modifying the indirect effects of aerosols in cloud formation as well as implementing finer resolutions, the models have undergone further improvements.
The improved model capacity in capturing the meridional moisture flux convergence might have contributed to the reduction in dry and wet biases in the Asian monsoon region as well as to the model's capacity in reproducing extreme precipitation (Dong & Dong, 2021). Nevertheless, other dynamics as the relationship between the ISM rainfall and the Equatorial Indian Ocean Oscillation are not yet fully captured adequately in many models. Given this relationship's crucial impact on the interannual variability of the ISM, also in this generation of CMIP, there still remains potential for further improvements.
There is a widespread agreement among global climate models that the rainfall during the ISM will increase throughout the 21st century. Using 32 models of the latest climate model generation (CMIP6), Katzenberger et al. (2021) quantified the projected summer monsoon rainfall increase to be between 9.7 per cent and 24.3 per cent by the end of the 21st century depending on the underlying emission scenario.
Also, a linear dependence of the ISM rainfall and the global temperature independent of the scenarios was found and estimated to be 0.33 mm/day per degree Celsius which corresponds to 5.4 per cent of the current annual rainfall. Thus, the rainfall of the ISM domain is more sensitive to rising global temperatures than global precipitation. In addition, an increase in the interannual variability of seasonal rainfall is projected, raising the amount of rainfall in some seasons even further.
While the literature on the projections of the ISM's interannual variability has been converging toward an intensifying tendency, the particular outcome for wet seasonal extremes had only drawn limited attention until recent years, which was the motivation for Kamizawa and Takahashi (2018) to use 22 CMIP5 models to address this research question.
In their study, the changes in the wettest (driest) and second wettest (driest) seasons between 2007-2031 and 2076-2100 were examined under the Representative Concentration Pathway 4.5 (RCP4.5). Most of the CMIP5 models projected that the wet seasonal extremes expand over the Indian subcontinent, but it has to be noted, that focusing on the maxima is a method highly susceptible to the bias of outliers.
These results coincide with the earlier study by Sharmila et al. (2015), who found that the years with strong monsoon rainfall are expected to increase in frequency as well as severity by the end of the 21st century but the results still had a very strong inter-model spread. Against this background and given the improvements in CMIP6 compared to CMIP5 as explained before, the results of CMIP6 regarding the seasonal extremes are of particular interest.
Additionally, Dong and Dong (2021) point out the improvements between CMIP5 and CMIP6 regarding the daily rainfall amount (exceeding 10 and 20 mm) which was an additional motivation for this study to also analyze the question of how the changes in seasonal rainfall translate to selected indices on the sub-seasonal scale.
Here, they use the data of 32 CMIP6 models in order to quantify the changes in seasonal rainfall extremes in India under different emission scenarios. They also analyze how these changes translate to the sub-seasonal scale, particularly changes in daily rainfall. In order to do so, they select six models with a better monsoon performance in the historical simulations in order to get an insight into their projections following the detailed evaluation provided by Rajendran et al. (2021).
Section 2 gives an overview of the underlying scenarios, the CMIP6 data, the definition of seasonal extremes and the characterization of daily rainfall as well as the selection criteria for the models. Section 3 gives a detailed insight into our results and in Section 4 these results are discussed in the context of similar studies. (ANI)