On the heat waves over India and their future projections under different SSP scenarios from CMIP6 models
Thirteen Coupled Model Intercomparison Project phase 6 (CMIP6) models were employed to simulate mean, maximum, and minimum temperature across 7 homogenous temperature regions of India for both annual and summer season (June, July, and August (JJA)). The model fidelity was assessed by comparing them...
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Veröffentlicht in: | International journal of climatology 2024-03, Vol.44 (3), p.973-995 |
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Zusammenfassung: | Thirteen Coupled Model Intercomparison Project phase 6 (CMIP6) models were employed to simulate mean, maximum, and minimum temperature across 7 homogenous temperature regions of India for both annual and summer season (June, July, and August (JJA)). The model fidelity was assessed by comparing them with observed Climate Research Unit temperature dataset. The JJA multi‐model ensemble for the present (1981–2014) suggests large warm biases in the temperature. Although the models could simulate the spatial variability of the mean and maximum temperature over most of the homogeneous regions, they do not compare well for representing the temporal variability. We also found, that although different individual models have strengths and weaknesses in representing spatial and temporal temperature characteristics over India, a few of the models perform better than the others. For example, CNRM‐CM6 could better represent the spatial temperature patterns however they struggle in capturing the temporal variability. HadGEM3‐GC31‐LL, KACE‐1‐0G, and UKESM1‐0‐LL are comparably the best‐performing models for temporal temperature features over India. The annual maximum temperature during far future period is projected to increase by 1.5°C, 2.3°C, and 4.1°C for Socioeconomic Pathways (SSPs) SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5 respectively. At regional scales, JJA mean temperature for SSP5‐8.5 revealed significant increases in Interior Peninsula (3.8°C), Western Himalaya (5.6°C), Northwest (3.9°C), West Coast (3.6°C), East Coast (3.6°C), Northeast (3.6°C), and North Central (3.8°C), highlighting the Western Himalaya's heightened sensitivity. Further, heat wave frequency is projected to rise, with the northern territories (NW, NC, NE, and part of IP) most affected, anticipating week‐long heat waves affecting around 50% of India's population under stronger SSPs. Such unprecedented impacts seem to be less profound in case of abatement scenarios such as the SSP1‐2.6. Our findings support the urgent need for more ambitious mitigation and adaptation strategies to alleviate the public health impacts of climate change.
In near and far future the heat wave over homogeneous temperature zones over India is highly likely to increase. The figure shows the heat wave duration index with reference to the mean of the summer season (where TX > TXnorm +5°C for 7 consecutive days) difference compared to the ensemble mean of the historical period (1984–2014) for SSP1‐2.6 (a), (b), SSP2‐4.5 (c), (d) an |
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ISSN: | 0899-8418 1097-0088 1097-0088 |
DOI: | 10.1002/joc.8367 |