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Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation

Earth Sciences

Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation

G. Konapala, A. K. Mishra, et al.

This groundbreaking research by Goutam Konapala, Ashok K. Mishra, Yoshihide Wada, and Michael E. Mann explores how seasonal and annual precipitation patterns affect water availability across global regions. Using non-parametric analysis, the study reveals dramatic variations in precipitation and evaporation, offering crucial insights into future water resource management.

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Playback language: English
Abstract
Both seasonal and annual mean precipitation and evaporation influence patterns of water availability impacting society and ecosystems. Existing global climate studies rarely consider such patterns from a non-parametric statistical standpoint. Here, we employ a non-parametric analysis framework to analyze seasonal hydroclimatic regimes by classifying global land regions into nine regimes using late 20th century precipitation means and seasonality. These regimes are used to assess implications for water availability due to concomitant changes in mean and seasonal precipitation and evaporation changes using CMIP5 model future climate projections. Out of 9 regimes, 4 show increased precipitation variation, while 5 show decreased evaporation variation coupled with increasing mean precipitation and evaporation. Increases in projected seasonal precipitation variation in already highly variable precipitation regimes gives rise to a pattern of "seasonally variable regimes becoming more variable". Regimes with low seasonality in precipitation, instead, experience increased wet season precipitation.
Publisher
Nature Communications
Published On
Jun 23, 2020
Authors
Goutam Konapala, Ashok K. Mishra, Yoshihide Wada, Michael E. Mann
Tags
precipitation
evaporation
hydroclimatic regimes
water availability
climate projections
seasonality
non-parametric analysis
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