Climatology and trends of summer high temperature days in India during 1969–2013

Jaswal, A. K.; Rao, P. Chandrasekhara; Singh, Virendra

doi:10.1007/s12040-014-0535-8

Cited by 47 publications

(36 citation statements)

References 45 publications

(41 reference statements)

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“…Four recent studies investigated trends in heat waves in India (Pai et al, 2013;Jaswal et al, 2015;Rohini et al, 2016;Wehner et al, 2016). Using the IMD definitions, Pai et al (2013) studied the trend in (severe) heat waves over India using station data from 1961 to 2010.…”

Section: Introductionmentioning

confidence: 99%

“…neglecting the cooling effects of perspiration). This criterion is used by Jaswal et al (2015), who use a threshold of 37 • C during the summer season March-June. Using data from 1969 to 2013, their findings indicate that long period trends show an increase in summer high-temperature days in north, west, and south regions and a decrease in north-central and east regions.…”

Section: Introductionmentioning

confidence: 99%

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Extreme heat in India and anthropogenic climate change

Oldenborgh

Philip

Kew

et al. 2018

Nat. Hazards Earth Syst. Sci.

125

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Abstract. On 19 May 2016 the afternoon temperature reached 51.0 • C in Phalodi in the northwest of India -a new record for the highest observed maximum temperature in India. The previous year, a widely reported very lethal heat wave occurred in the southeast, in Andhra Pradesh and Telangana, killing thousands of people. In both cases it was widely assumed that the probability and severity of heat waves in India are increasing due to global warming, as they do in other parts of the world. However, we do not find positive trends in the highest maximum temperature of the year in most of India since the 1970s (except spurious trends due to missing data). Decadal variability cannot explain this, but both increased air pollution with aerosols blocking sunlight and increased irrigation leading to evaporative cooling have counteracted the effect of greenhouse gases up to now. Current climate models do not represent these processes well and hence cannot be used to attribute heat waves in this area.The health effects of heat are often described better by a combination of temperature and humidity, such as a heat index or wet bulb temperature. Due to the increase in humidity from irrigation and higher sea surface temperatures (SSTs), these indices have increased over the last decades even when extreme temperatures have not. The extreme air pollution also exacerbates the health impacts of heat. From these factors it follows that, from a health impact point of view, the severity of heat waves has increased in India.For the next decades we expect the trend due to global warming to continue but the surface cooling effect of aerosols to diminish as air quality controls are implemented. The expansion of irrigation will likely continue, though at a slower pace, mitigating this trend somewhat. Humidity will probably continue to rise. The combination will result in a strong rise in the temperature of heat waves. The high humidity will make health effects worse, whereas decreased air pollution would decrease the impacts.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extreme heat in India and anthropogenic climate change

Oldenborgh

Philip

Kew

et al. 2018

Nat. Hazards Earth Syst. Sci.

125

View full text Add to dashboard Cite

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“…Both cities are located on the tropics. Extreme temperature has been recorded with 47.9°C in Nagpur during May 2013 (http://timesofindia.indiatimes.co m/city/nagpur/Nagpur-records-all-time-high-temperature-at-47-9-C/articleshow/20216419.cms) and 49°C in Chandrapur during June 2007 (Jaswal et al, 2015). Nagpur is recognized as the second green and clean city in India (http://pdf.…”

Section: Location and Datamentioning

confidence: 99%

Exceedance Analysis of PM10 Concentration in Central Indian City: Predicting Gap between Two Exceedances

Chelani

2015

Aerosol Air Qual. Res.

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In this study the gap between the two exceedances is analyzed using time series analysis. The time series of PM 10 (particulate matter of size less than 10 micron) observed during 2005-2013 in two cities; Nagpur and Chandrapur in central India is considered. Higher PM 10 concentration is observed in Chandrapur as compared to Nagpur. Exponential relationship is observed between the average time between the two exceedances and annual average PM 10 concentration. This information along with the PM 10 concentration prediction model is utilized to predict the average number of observations between the two exceedances for the following year. k-nearest neighbor approach is used for forecasting PM 10 concentration which enabled estimating the average number of observations between two exceedances using exponential relationship. The approach can be used for estimating the average number of observations between the two exceedances over a year, which can further be utilized to make appropriate decision to control and manage high particulate matter pollution in an area.

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“…However, the studies related to extreme temperature variation over India are very limited (Chaudhury et al 2000;Pai et al 2004Pai et al , 2013Sinha Ray and De 2003;Rao et al 2004Rao et al , 2005Pal and Al-Tabbaa 2010;Kothawale et al 2010;Dash and Mamgain 2011;Revadekar et al 2012;Jaswal et al 2015). Extreme maximum and minimum temperatures over India showed increasing trend in the south and decreasing trend in the north (Sinha Ray and De 2003;Jain and Kumar 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Revadekar et al (2012) studied the observed and future changes in temperature extreme over India and found increase in intensity and frequency of hot events and decrease in frequency of cold events. Pai et al (2013) have found significant long term increasing trends in heat wave days over India during 1961. Jaswal et al (2015 have found increase in summer high temperature days (days with daily maximum temperature above 37°C) over India by 3, 5, and 18 % in northern, western, and southern regions and decrease by 4 and 9 % in north-central and eastern regions, respectively, for the period 1969-2013.…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal variation in daily temperature indices in summer and winter seasons over India (1969–2012)

Kumar

Jaswal

Mohapatra

et al. 2016

Theor Appl Climatol

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Spatial and temporal variations in summer and winter extreme temperature indices are studied by using daily maximum and minimum temperatures data from 227 surface meteorological stations well distributed over India for the period 1969-2012. For this purpose, time series for six extreme temperature indices namely, hot days (HD), very hot days (VHD), extremely hot days (EHD), cold nights (CN), very cold nights (VCN), and extremely cold nights (ECN) are calculated for all the stations. In addition, time series for mean extreme temperature indices of summer and winter seasons are also analyzed. Study reveals high variability in spatial distribution of threshold temperatures of extreme temperature indices over the country. In general, increasing trends are observed in summer hot days indices and decreasing trends in winter cold night indices over most parts of the country. The results obtained in this study indicate warming in summer maximum and winter minimum temperatures over India. Averaged over India, trends in summer hot days indices HD, VHD, and EHD are significantly increasing (+1.0, +0.64, and +0.32 days/decade, respectively) and winter cold night indices CN, VCN, and ECN are significantly decreasing (−0.93, −0.47, and −0.15 days/decade, respectively). Also, it is observed that the impact of extreme temperature is higher along the west coast for summer and east coast for winter.

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Climatology and trends of summer high temperature days in India during 1969–2013

Cited by 47 publications

References 45 publications

Extreme heat in India and anthropogenic climate change

Extreme heat in India and anthropogenic climate change

Exceedance Analysis of PM10 Concentration in Central Indian City: Predicting Gap between Two Exceedances

Spatial and temporal variation in daily temperature indices in summer and winter seasons over India (1969–2012)

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