Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Clim Change
Impact Factor: 6.099

Unraveling the influence of atmospheric evaporative demand on drought and its response to climate change

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract This review examines the role of the atmospheric evaporative demand (AED) in drought. AED is a complex concept and here we discuss possible AED definitions, the subsequent metrics to measure and estimate AED, and the different physical drivers that control it. The complex influence of AED on meteorological, environmental/agricultural and hydrological droughts is discussed, stressing the important spatial differences related to the climatological conditions. Likewise, AED influence on drought has implications regarding how different drought metrics consider AED in their attempts to quantify drought severity. Throughout the article, we assess literature findings with respect to: (a) recent drought trends and future projections; (b) the several uncertainties related to data availability; (c) the sensitivity of current drought metrics to AED; and (d) possible roles that both the radiative and physiological effects of increasing atmospheric CO2 concentrations may play as we progress into the future. All these issues preclude identifying a simple effect of the AED on drought severity. Rather it calls for different evaluations of drought impacts and trends under future climate scenarios, considering the complex feedbacks governing the climate system. This article is categorized under: Paleoclimates and Current Trends > Earth System Behavior
Simplified scheme showing the diverse effects of the AED on environmental/agricultural and hydrological systems. Numbers mean different effects on drought severity: (1) increase AED increases water stress, (2) increase AED has little/no impacts, and (3) increase AED has indirect positive effects
[ Normal View | Magnified View ]
(a) Evolution of mean climate balances (precipitation minus AED) from a CMIP5 multi‐model average for RCPs 4.5 and 8.5. The AED was obtained by means of the FAO‐56 Penman–Monteith equation (including the data sources and Rn component approaches reported in Figure caption) and also considering the CO2 physiological effect on stomatal conductance according to Y. Yang et al. (). (b) Percentage of the world showing negative climate balances (precipitation minus AED) and (c) first column: spatial distribution of the mean annual climate balances for the period 2071–2100 and second column: difference between 2071–2100 and 1971–2000
[ Normal View | Magnified View ]
(a) Top row: Evolution of annual AED and precipitation using GISS‐E2‐H model for the RCP8.5 scenario simulations from 2005 to 2100 and for the historic simulations from 1950 to 2005 for a humid region in east USA (88.75°W, 38.75°N). AED was calculated using the FAO‐56 Penman–Monteith equation and also considering the CO2 physiological effect according to Y. Yang et al. (). Second row: Evolution of the difference between annual precipitation and AED. Third row: Evolution of the 12‐month SPEI considering the two methods to calculate the AED. Bottom row: Density plots for the annual P‐AED for 1950–2000 and 2050–2100. (b) Same as (a) but for a semi‐arid region in the western USA (111.25°W, 36.25°N)
[ Normal View | Magnified View ]
(a) Spatial distribution of the annual mean AED (in mm) obtained from the FAO‐56 Penman–Monteith equation for 2071–2100 from a multi‐model CMIP5 mean for the RCP4.5 and 8.5 scenarios. The figure also shows AED averages for both scenarios but also considering the possible CO2 physiological effect on stomata conductance according to the equation proposed by Y. Yang et al. (). (b) Spatial distribution of the absolute mean difference between the AED calculated for 2071–2100 and 1981–2010. (c) Evolution of the mean AED considering the two RCP scenarios and also the role of CO2 atmospheric concentrations between 1950 and 2100. From 1950 to 2005, a multi‐mean model of the historical simulation is used, and from 2005 to 2100 the 4.5 and 8.5 RCPs projections were used. The CMIP5 models used here were: CCSM4, CSIRO MR3‐6‐0, GFDL‐ESM26, GFDL‐ESM2M, IPSL‐CM5A‐LR, MIROC5, MIROC ESM CHEM, MIROC ESM and MRI‐CGCM3
[ Normal View | Magnified View ]
(a) Spatial distribution of the trend in 12‐month SPI (in number of standard deviations between 1979 and 2017 using the entire time series and a linear regression analysis. (b) same as (a) but for the SPEI, (c) SPEI minus SPI changes in arid and semi‐arid regions (defined as regions with long‐term AED minus long‐term precipitation between 500 and 2,500 mm/year). (d) same as (a) but considering the SPI values below −0.84, (e) same as (b) but considering the SPEI values below −0.84, (f) same as (c) but considering the changes in the values below −0.84. (g) same as (a) but considering the magnitude of the drought events obtained from 3‐month SPI series identified with a threshold below −0.84. (h) same as (b) but considering the magnitude of the drought events obtained from 3‐month SPEI series identified with a threshold below −0.84. (i) same as (c) but considering the changes in the magnitude of the drought events
[ Normal View | Magnified View ]
(a) Large figure: Spatial distribution of the magnitude of change in the annual AED between 1979 and 2017 (mm/39 years). Small figures: Difference with observations considering the different X variables involved in the calculations as constant (full trend‐trend with X held constant). AED was calculated using the FAO‐56 Penman–Monteith equation (R. G. Allen et al., ), forced with data from the CRU TS v. 3.26 for maximum and minimum air temperature and from ERA‐Interim reanalysis (Dee et al., ) for relative humidity (which was calculated from Tdew and mean temperature; see Vicente‐Serrano, Nieto, et al., ), downward solar radiation was used to calculate the net radiation (Rn) following the FAO‐56 recommendations (R. G. Allen et al., ) and wind speed. (b) Evolution of the global average annual AED based on observations (black line) and considering the different variables as constant
[ Normal View | Magnified View ]
(a) News from Italy, France, Spain, and Belgium stressing the severity of the drought conditions during the summer of 2017. (b) Spatial distribution of the 6‐month (i.e., calculated for the current month and the five preceding months) SPI and SPEI in Western Europe between May 2017 and August 2017. The monthly precipitation data were obtained from the Global Precipitation Climatology Centre (GPCC) (https://www.dwd.de/EN/ourservices/gpcc/gpcc.html) and the AED was calculated from ERA‐Interim reanalysis output as detailed in Figure caption
[ Normal View | Magnified View ]
(a) Top: Spatial distribution of the coefficient of variation (denoted as C.V. in the figures) of annual precipitation and AED. Bottom: The sensitivity of drought to the temporal variability of the precipitation and AED. This sensitivity is measured by means of the correlation coefficient between 12‐month Standardized Precipitation Evapotranspiration Index (SPEI) and the series of precipitation and AED. (b) Relationship between the spatial distribution of the sensitivity of SPEI to precipitation and to AED as a function of the United Nations Environmental Programme (UNEP) Aridity Index (long‐term annual precipitation/long‐term annual AED). Low values represent stronger aridity. Precipitation is sourced from CRU TS v. 3.26 (Harris, Jones, Osborn, & Lister, ) and AED has been calculated by the FAO‐56 Penman–Monteith equation (R. G. Allen et al., ) using data from the CRU TS v. 3.26 for maximum and minimum air temperature and from ERA‐Interim reanalysis (Dee et al., ) for relative humidity (which was obtained from Tdew and mean temperature, see Vicente‐Serrano, Nieto, et al., ), downward solar radiation was used to calculate the net radiation (Rn) following the FAO‐56 recommendations (R. G. Allen et al., ) and wind speed. Analysis covers 1979–2017
[ Normal View | Magnified View ]

Browse by Topic

Paleoclimates and Current Trends > Earth System Behavior

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts