the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Estimating changes of temperatures and precipitation extremes in India using the Generalized Extreme Value (GEV) distribution
Abstract. Changes in extreme temperature and precipitation may give some of the largest significant societal and ecological impacts. For changes in the magnitude of extreme temperature and precipitation over India, we used a statistical model of generalized extreme value (GEV) distribution. The GEV statistical distribution is a time-dependent distribution with different time scales of variability bounded by a precipitation, maximum (Tmax), and minimum (Tmin) temperature extremes and also assessed their possibility changes are evaluated and quantified over India is presented. The GEV-based method is applied on both precipitation and temperature extremes over India during the 20th and 21st centuries using multiple coupled climate models taking an interest in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and observational datasets. The regional means of historical warm extreme temperatures are 34.89, 36.42, and 38.14 °C for three different (10, 20, and 50-year) periods, respectively; whereas the cold extreme mean temperatures are 7.75, 4.19, and −1.57 °C. It indicates that 20th century cold extreme temperatures have relatively larger variations than the warm extremes. As for the future, the CMIP5 models of warm extreme regional mean values increase from 0.33 to 0.75 °C in all return periods (10-, 20-, and 50-year periods), while in the case of cold extreme means values vary between 0.58 and 2.29 °C. In the future, cold extreme values have a larger increasing rate over the northwest, northeast, some parts of north-central, and Inter Peninsula regions. The CRU precipitation extremes are larger than the historical extreme precipitation in all three (10, 20, and 50-year) return-periods.
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RC1: 'Review', Anonymous Referee #1, 11 Dec 2018
- AC1: 'Reviewer1 Replies', Pangaluru Kishore, 04 Mar 2019
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RC2: 'Review of Pangaluru et al', Anonymous Referee #2, 13 Jan 2019
- AC2: 'Reviewer2 Replies', Pangaluru Kishore, 04 Mar 2019
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RC1: 'Review', Anonymous Referee #1, 11 Dec 2018
- AC1: 'Reviewer1 Replies', Pangaluru Kishore, 04 Mar 2019
-
RC2: 'Review of Pangaluru et al', Anonymous Referee #2, 13 Jan 2019
- AC2: 'Reviewer2 Replies', Pangaluru Kishore, 04 Mar 2019
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Cited
5 citations as recorded by crossref.
- Seasonal extreme rainfall variability over India and its association with surface air temperature D. Sardana et al. 10.1007/s00704-022-04045-0
- CMIP6 Model Evaluation for Mean and Extreme Precipitation Over India P. Kushwaha et al. 10.1007/s00024-023-03409-5
- Employing the generalized Pareto distribution to analyze extreme rainfall events on consecutive rainy days in Thailand's Chi watershed: implications for flood management T. Phoophiwfa et al. 10.5194/hess-28-801-2024
- Daily Precipitation and Temperature Extremes in Southern Italy (Calabria Region) G. Prete et al. 10.3390/atmos14030553
- Assessing coincidence probability for extreme precipitation events in the Jinsha River basin S. Zhu et al. 10.1007/s00704-019-03009-1