Research Article: Drought risk assessment under climate change is sensitive to methodological choices for the estimation of evaporative demand

Date Published: March 16, 2017

Publisher: Public Library of Science

Author(s): Candida F. Dewes, Imtiaz Rangwala, Joseph J. Barsugli, Michael T. Hobbins, Sanjiv Kumar, Maite deCastro.


Several studies have projected increases in drought severity, extent and duration in many parts of the world under climate change. We examine sources of uncertainty arising from the methodological choices for the assessment of future drought risk in the continental US (CONUS). One such uncertainty is in the climate models’ expression of evaporative demand (E0), which is not a direct climate model output but has been traditionally estimated using several different formulations. Here we analyze daily output from two CMIP5 GCMs to evaluate how differences in E0 formulation, treatment of meteorological driving data, choice of GCM, and standardization of time series influence the estimation of E0. These methodological choices yield different assessments of spatio-temporal variability in E0 and different trends in 21st century drought risk. First, we estimate E0 using three widely used E0 formulations: Penman-Monteith; Hargreaves-Samani; and Priestley-Taylor. Our analysis, which primarily focuses on the May-September warm-season period, shows that E0 climatology and its spatial pattern differ substantially between these three formulations. Overall, we find higher magnitudes of E0 and its interannual variability using Penman-Monteith, in particular for regions like the Great Plains and southwestern US where E0 is strongly influenced by variations in wind and relative humidity. When examining projected changes in E0 during the 21st century, there are also large differences among the three formulations, particularly the Penman-Monteith relative to the other two formulations. The 21st century E0 trends, particularly in percent change and standardized anomalies of E0, are found to be sensitive to the long-term mean value and the amplitude of interannual variability, i.e. if the magnitude of E0 and its interannual variability are relatively low for a particular E0 formulation, then the normalized or standardized 21st century trend based on that formulation is amplified relative to other formulations. This is the case for the use of Hargreaves-Samani and Priestley-Taylor, where future E0 trends are comparatively much larger than for Penman-Monteith. When comparing Penman-Monteith E0 responses between different choices of input variables related to wind speed, surface roughness, and net radiation, we found differences in E0 trends, although these choices had a much smaller influence on E0 trends than did the E0 formulation choices. These methodological choices and specific climate model selection, also have a large influence on the estimation of trends in standardized drought indices used for drought assessment operationally. We find that standardization tends to amplify divergences between the E0 trends calculated using different E0 formulations, because standardization is sensitive to both the climatology and amplitude of interannual variability of E0. For different methodological choices and GCM output considered in estimating E0, we examine potential sources of uncertainty in 21st century trends in the Standardized Precipitation Evapotranspiration Index (SPEI) and Evaporative Demand Drought Index (EDDI) over selected regions of the CONUS to demonstrate the practical implications of these methodological choices for the quantification of drought risk under climate change.

Partial Text

Drought is a major climatic phenomenon affecting socio-ecological systems worldwide through scarcity of available water [1,2]. This scarcity generally arises from a sustained and extended period of precipitation deficiency, such as in the 2012–2016 California drought, but it often is initially set off and further intensified by increased water demand by the atmosphere and society [3–5]. In this paper we focus on atmospheric evaporative demand (i.e., “the thirst of the atmosphere”), which represents the amount of water that would evaporate from the earth’s surface and be transpired by plants if water availability were not a limiting factor (e.g., [6]).

In this study we evaluated how different methodological and dataset choices in the estimation of evaporative demand yield different assessments of temporal and spatial variability in E0 and trends in 21st century drought risk. First, we evaluated these differential responses across three of the more widely used formulations for E0 estimations: Penman-Monteith, Hargreaves-Samani, and Priestley-Taylor. Our analysis shows that Penman-Monteith provides a more physically robust treatment of E0 across the CONUS. This formulation gives a more spatially heterogeneous realization of E0 because it is more sensitive to the variations in turbulent fluxes (driven by wind speed and surface roughness) and relative humidity. Penman-Monteith also facilitates a more physically robust depiction of the amplitude of interannual variability relative to the other two methods, whose interannual variabilities are much lower, particularly Priestley-Taylor. We also find regional patterns to this enhanced interannual variability in Penman-Monteith, such as in the Great Plains and southwestern US, which is corroborated by pan evaporation observations. This feature is not reproduced by Hargreaves-Samani and Priestley-Taylor. Previous studies have also shown a greater importance of drivers like wind speed and relative humidity in these regions in driving interannual variability in E0 [5,72,88]. Therefore, the application of Penman-Monteith for E0 estimation would especially be critical for regions where the influence of these drivers is strong.




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