Present and future projections of heatwave hazard-risk over India: A regional earth system model assessment

Dubey, Aditya Kumar; Lal, Preet; Kumar, Pankaj; Kumar, Amit; Dvornikov, Anton Y.

doi:10.1016/j.envres.2021.111573

Cited by 45 publications

(19 citation statements)

References 57 publications

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“…In order to facilitate adaptive planning for such inclement events, it is imperative that a detailed quantitative analysis of projected heatwaves is carried out for India. A few studies (Murari et al ., 2015; Dubey et al ., 2021) have addressed the issue of projected heatwaves in India, however the present study adds to the body of knowledge by accounting for spatial variation, associated uncertainties, risk attribution and finally introduces the computation of the cost of climate inaction (in the context of heatwave).…”

Section: Introductionmentioning

confidence: 99%

Trends, intensification, attribution and uncertainty of projected heatwaves in India

Chowdhury

2022

Intl Journal of Climatology

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This study investigates the projected heatwaves for India using 0.25° × 0.25° summer mean temperature data from Coupled Model Intercomparison Project (CMIP) 5 and 6 simulations for 2016–2100. The heatwaves were delineated using count and density‐based indices. A new approach of using medians of past as threshold for computing projected variables was introduced to amplify the footprint of the warming signal on the heatwaves. Further, spatio‐climatic heterogeneity of India was accounted through optimizing climatic zones using the fuzzy c‐mean clustering technique. Temporal homogeneity, trend, intensification and attribution of the heatwave variables were computed and analysed. Additionally, the scenario uncertainty was partitioned from the internal climatic variability, and consequently the variables were modelled within a probabilistic framework. Within this probabilistic framework, a novel concept of intensification ratio was introduced to capture the cost of climate action/inaction on heatwaves in India. All the heatwave variables except heatwave count have breaks in homogeneity between 2045 and 2055 and show predominantly increasing trends. While heatwave count shows an intensification of 4–6 times over the past, with 70% of the intensification being attributable to climate change, for other variables, the figures are 35–30 times and 95%. The scenario uncertainty surpasses the internal climatic variability around 2050. The probabilistic framework yields normalized values of uncertainty mostly below 0.5, enhancing the applicability of the results. Finally, the intensification ratio shows that climate inaction will intensify the heatwaves for ~75% of India by ~50–100%. The intensification of heatwave density over its count and relative accentuation of heatwaves resulting from climate inaction are the major takeaways from this study.

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Section: Introductionmentioning

confidence: 99%

Trends, intensification, attribution and uncertainty of projected heatwaves in India

Chowdhury

2022

Intl Journal of Climatology

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“…따라서 폭염 위험을 평가할 경우, 지역별 기후, 환경, 사회 등의 다양한 요인들을 고려해야 한다. 다양한 선행 연구사례에서는 어떤 재난 현상 에 대한 위험을 위해, 노출, 취약의 함수로 설명하였다 (Papathoma-Koehle et al, 2016;Savic et al, 2018;Kim et al, 2019;Yamagata et al, 2019;Yin et al, 2020;Dubey et al, 2021). 본 연구에서는 일 최고기온과 행정구역별 폭염 취약정도 를 고려해 우리나라의 지역별 일 단위 폭염위험지수를 개발 하였고, 이를 활용한 위기경보 발령 기준을 제안하였다.…”

Section: 서 론unclassified

Development of Heatwave Crisis Alert Standard for Administrative Districts Using Heatwave Risk Index

Kim¹,

Yeom²,

Song³

et al. 2022

J. Korean Soc. Hazard Mitig

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The current heatwave crisis alert system considers the daily maximum temperature alone; therefore, the present study proposed a new method for estimating the daily heatwave crisis alert level. Specifically, the heatwave risk index was calculated by combining regional vulnerability, as estimated using principal component analysis, and normalized daily maximum temperature. The crisis alert level was classified according to the risk index value using the natural breaks method. The correlation coefficient between the heatwave risk index and heat-related morbidity rate was approximately 0.4. In addition, analysis of variance confirmed significant differences in the heat-related morbidity rate among different crisis alert levels. The current method is limited in that it does not take into account the various regional environmental characteristics, which may results in an ambiguous alert standard; however, this shortcoming may be resolved using the proposed heatwave risk index. Therefore, the results of the present study may be valuable for risk assessment and management in Korea.

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“…However, it is computationally expensive, and alternatively, high-resolution RESM can be used at a less computational cost. Various RESM having varying complexities have been developed and employed to explore the understanding of atmospheric and oceanic variability over different regions of the globe and suggest improvements (Sein et al, 2015;Wang et al, 2015;Dubey et al, 2021;Mishra et al, 2021aMishra et al, , 2021bSaharwardi et al, 2021;Kumar et al, 2022;Mishra et al, 2022aMishra et al, , 2022bMishra et al, , 2022c. Kumar et al (2022) demonstrated that dynamical and thermodynamical processes including the upper tropospheric circulation associated with the Indian summer monsoon employing the same model used in this study.…”

Section: Introductionmentioning

confidence: 99%

Regional earth system model for CORDEX‐South Asia: A comparative assessment of RESM and ESM over the tropical Indian Ocean

Kumar

Mallick

Mishra

et al. 2022

Intl Journal of Climatology

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Understanding climate variability requires good quality high resolution spatially and temporally varying ocean fields due to its decisive role in regulating the region's climate, including the Indian summer monsoon. In this regard, we employed a new high-resolution regional earth system model (RESM), namely ROM over CORDEX South Asia. We demonstrated the performance of the RESM and its added value over the global earth system model, namely MPI-ESM, in simulating the hydrographic characteristics and associated mechanism over the tropical Indian Ocean (TIO). ROM shows better skill than MPI-ESM in simulating the near-surface and subsurface characteristics of the ocean. However, larger added values are noticed for subsurface (>350 m) thermal structure. MPI-ESM's cold sea surface temperature (SST) bias is reduced in ROM which is associated with weaker winds, anomalous cyclonic wind stress curl, enhanced stratifications, and a shallower mixed layer, resulting in greater upper-ocean heating. The reduced SST bias is also consistent with improved ocean meridional heat transport (OMHT) in ROM. For example, reduced southward export of OMHT over the Arabian Sea increases the surface warming by 4%, reducing the RMSE by 0.2-0.6 C and becoming closer to observation. The anomalous cyclonic wind stress curl, in turn, caused mixed layer stratifications in the western Indian Ocean. The advective heat transfer from the south-eastern Indian Ocean to the western Indian Ocean reduced oceanic cooling by vertical processes, overcame the cooling by the net loss of surface heat fluxes, and favoured the TIO's surface warming.

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Present and future projections of heatwave hazard-risk over India: A regional earth system model assessment

Cited by 45 publications

References 57 publications

Trends, intensification, attribution and uncertainty of projected heatwaves in India

Trends, intensification, attribution and uncertainty of projected heatwaves in India

Development of Heatwave Crisis Alert Standard for Administrative Districts Using Heatwave Risk Index

Regional earth system model for CORDEX‐South Asia: A comparative assessment of RESM and ESM over the tropical Indian Ocean

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