EGU2020-5539
https://doi.org/10.5194/egusphere-egu2020-5539
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Heat Events in the Indian Subcontinent under a warming climate scenario: Detection and its Drivers

Kapoor Ritika1,2, Enrico Scoccimarro1, Carmen Alvarez-Castro1, Stefano Materia1, and Silvio Gualdi1,3
Kapoor Ritika et al.
  • 1Euro-Mediterranean Center on Climate Change (CMCC), Climate Simulation & Predictions - CSP, BOLOGNA, Italy
  • 2Ca Foscari University, Venice, Italy
  • 3Istituto Nazionale di Geofisica e Vulcanologia (INGV)

Global temperatures have shown a warming trend over the last century, mainly as a result of anthropogenic activities. Rising temperatures are a potential cause for increase of extreme climate events, such as heat waves, both in severity and frequency. Under an increasing extreme event scenario, the world population of mid- and low-latitude countries is more vulnerable to heat related mortality and morbidity. In India, the events occurred in recent years have made this vulnerability clear, since the numbers of heat related deaths are on a rise.

Over India, the heat waves occur during the months of April to June and can impact various sectors including health, agriculture, ecosystems and the national economy. In May 2015, a severe heat wave due to the delayed onset of southwest monsoon affected parts of south-eastern India, which claimed more than 2500 lives.

Preliminary results show the prevalence of Heat events in North-West, Central and South-Eastern regions of India during the pre-monsoon (March, April, May) and transitional (May, June, July) months. We consider the Heat Index (HI), a combination of temperature and relative humidity, also known as apparent temperature, gives an insight into the discomfort because of increment in humidity, that reduces the efficiency of body’s cooling mechanism as it blocks evaporation. Thus, along with temperature anomalies, humidity also plays a role in transitional period.

Heatwaves over India are known to be linked with El-Niño-Southern Oscillation or ENSO, but some studies indicated that the processes generating heat waves over northwest-central and coastal eastern India could be linked to anomalous blocking over North Atlantic and to the cooling over central and east equatorial Pacific. While other studies demonstrated that anomalous persistent high-pressure systems, supplemented with clear skies and depleted soil moisture, are primarily responsible for the occurrence of heat waves over India.

The changes in the frequency and intensity of extreme events have profound impact on human society and the natural environment. The heat stress and underlying anomalous conditions can exacerbate an increase in the number of deaths. While global heat wave and health impact research is prolific in some regions, the global population most incline to risk of death and conspicuous harm caused by extreme heat is under-represented. Heat wave and health impact research are needed in regions where this impact is expected to be most severe.

How to cite: Ritika, K., Scoccimarro, E., Alvarez-Castro, C., Materia, S., and Gualdi, S.: Heat Events in the Indian Subcontinent under a warming climate scenario: Detection and its Drivers, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5539, https://doi.org/10.5194/egusphere-egu2020-5539, 2020

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Presentation version 2 – uploaded on 04 May 2020
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  • CC1: Comment on EGU2020-5539, Clemens Schwingshackl, 05 May 2020

    Thank you for this interesting study, Ritika. I have a short comment on the use of simplified WBGT (which I assume you did because it is also used in Brouillet et al., 2019). According to results from Lemke and Kjellstrom (2012, doi:10.2486/indhealth.MS1352) and my own research, using simplified WBGT should rather be avoided as the origin of the formula is not really clear and when comparing it to other methods to calculate WBGT it can give very different results. I would thus suggest to follow the definition of WBGT as weighted mean between dry-bulb and wet-bulb temperature. One simple option to calculate wet-bulb temperature is the method from Stull (2011), which was, e.g., used in this presentation: https://presentations.copernicus.org/EGU2020/EGU2020-9704_presentation.pdf.
    But there are also other formulations available, e.g., Davies-Jones (2008, doi:10.1175/2007MWR2224.1).

  • AC1: Comment on EGU2020-5539, Kapoor Ritika, 05 May 2020

    Dear Clemens, thank you for your comment. I had referred to the formulations of Monteiro, J. M., & Caballero, R. (2019) where they talk how their formula gives similar results to Davies-Jones (2008). The spatial pattern of WBGT over India in the paper Monteiro, J. M., & Caballero, R. (2019) were similar to Brouillet et al., 2019 pattern. The values were somewhat different and the simplified WBGT could be the reason behind it. I would take in consideration your study and comment . Thanks again :)

     

    • CC2: Reply to AC1, Ana Casanueva, 05 May 2020

      Nice work Kapoor. I agree with Clemens that there are other indices which seem more appropiate than the simplified WBGT.

      In case you want to try others, I implemented an R package with a set of heat stress indices, most based on temperature and humidity/dew point, but there is one with wind speed and solar radiation (WBGT): https://github.com/anacv/HeatStress

  • AC2: Comment on EGU2020-5539, Kapoor Ritika, 05 May 2020

    Dear Ana, thank you for the R package  link. Yes, I will also conduct some calculations on the WBGT formulations as Clemens and you suggested , in addition to the simplified WBGT.

     

Presentation version 1 – uploaded on 03 May 2020 , no comments