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

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 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.

Fig. 1. Classification of the precipitation regimes.

a Spatial distribution of precipitation regimes based on the percentile (Pr_i) thresholds concept using mean apportionment entropy (AE) and annual precipitation P during the 1971–2000 reference period. b Percentage of land occupied by each regime. c Precipitation climatology of the spatially aggregated monthly rainfall climatology for regimes H_PL_AE, H_PH_AE, L_PH_AE, L_PL_AE. These regimes are selected as they represent boundary case scenarios. H, M, and L represent high moderate and low values, respectively.

Fig. 2. Trends in precipitation and evaporation totals and seasonality.

Theil-sen slopes of a total annual precipitation (TOT_P) and total annual evaporation (TOT_E) magnitudes, and b precipitation apportionment entropy (AE_P) and evaporation apportionment entropy AE_E. The error bars surrounding the point estimates represent the 95% confidence interval of the CMIP5 multimodel ensemble. H, M, and L represent high moderate and low values, respectively.

Fig. 3. Future monthly water availability.

a BMA ensemble monthly projected (RCP 2.6, RCP 4.5, and RCP 8.5) of available water (2070–2099) and historical (1971–2000) scenarios. Where, H, M, and L abbreviate high moderate and low values, respectively. Whereas, apportionment entropy is abbreviated as AE and annual precipitation as P.

Fig. 4. Projected seasonal changes in precipitation, evaporation, and available water.

Relative changes in future precipitation and evaporation during the wet (three-month average with maximum precipitation in a year) and dry seasons (three-month average with minimum precipitation in a year) derived based on the CMIP5 scenario relative to the historical period (1971–2000). The error bars surrounding the point estimates represent the 95% confidence interval of the CMIP5 multimodel ensemble. H, M, and L abbreviate high moderate and low values, respectively. Whereas, apportionment entropy is abbreviated as AE and annual precipitation as P.