Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment

Abstract

Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by bias-corrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty.

Keywords: climate impact; evaporation; global hydrology; global warming.

Fig. 1.

Percentage change in the occurrence of days under drought conditions for the period 2070–2099 relative to 1976–2005, based on a multimodel ensemble MME experiment under RCP8.5 from five global climate models and seven global impact models: MME Mean change (Left) and associated signal-to-noise ratio (S2N, MME mean change divided by its inter-quartile range, Right). See Methods for definition of drought, S2N, and masking procedure.

Fig. 2.

Mean change in drought severity (Change in GDI, y axis) as measured by the daily global deficit index (GDI) for the period 2070–2099 relative to 1976–2005 based on a multimodel ensemble MME experiment calculated over the whole year (Left), December to February (DJF, Center), and June to August (JJA, Right). Changes are given for each MME member and are organized by radiative forcing (from left to right: RCP2.6, R2; RCP4.5, R4; RCP6.0, R6; RCP8.5, R8). In each RCP panel, results are organized according to driving GCMs from left to right: HadGEM2-ES, IPSLCM5-ARL, MIROC-ESM-CHEM, GFDL-ESM2M, and NorESM1-M. CO₂ effect in GIMs is described as color: black/open symbols, no CO₂; cyan/filled symbols, CO₂. GIMs are indicated by symbols: up triangle, HO8; circle, JULES; x, Mac-PDM.09; +, MPI-HM; pentagon, PRCGLOB-WB; down triangle, VIC; square, WBM.

Fig. 3.

Cumulative density functions (CDFs) of daily global deficit index (GDI) calculated over 30-y periods (1976-2005 for historical forcing and 2070–2099 for RCP forcings) for each multimodel ensemble member.

Fig. 4.

Cumulative density functions (CDFs) of daily global deficit index (GDI) calculated over 30-y periods (1976-2005 for historical forcing and 2070–2099 for RCP forcings) from runs using HadGEM2-ES forcing. (A) Models that include water and energy balances, shown for historical (Hist) and RCP8.5 (R8.5) forcings. (B) and (C) Models that include the dynamic responses of vegetation to CO₂ and climate, shown for historical (Hist), RCP2.6 (R2.6) and RCP8.5 (R8.5) forcings. Results are shown separately for runs that were forced by time-varying CO₂ concentration (CO₂) and with CO₂ concentration held constant after the year 2000 (noCO₂). (B) shows results for JULES, (C) shows results for LPJmL. Note that all CDFs in this figure sample a smaller set of locations than those in Fig. 3.

Fig. 5.

Mean percentage changes in regional deficit index (RDI) between 30-y simulations of reference (1976-2005) and future (2070-2099) under RCP8.5 for 17 world regions. Values are averaged over all of the MME members (All), by GCMs, and by GIMs. JULES includes CO₂ and vegetation effects. See SI Text and ref. for GEO region descriptions and acronyms.