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

<div><p>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 21^st 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 21^st century, there are also large differences among the three formulations, particularly the Penman-Monteith relative to the other two formulations. The 21^st 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 21^st 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 21^st 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.</p></div

Historical mean E₀ across the different E₀ formulations.

<p>Climatological mean E₀ (mm) across the CONUS for the MJJAS period in GFDL-ESM2M (first three plots in left column) and CanESM2 (right column) as estimated by the Penman-Monteith (first row), Hargreaves-Samani (second row), and Priestley-Taylor (third row) formulations for the 1976–2005 period. The bottom left plot shows observed mean MJJAS pan evaporation across the CONUS from 228 stations which had at least 20 years of data between 1950 and 2001.</p

21^st century trends in E₀ across the different E₀ formulations.

<p>Trends in MJJAS E₀ projected from Penman-Monteith (green), Hargreaves-Samani (blue), and Priestley-Taylor (red) formulations driven by GFDL-ESM2M and CanESM2 data for the Northern Great Plains. The top row shows seasonal totals in mm, center row shows E₀ anomalies as % of the 1976–2005 mean, and bottom row shows standardized E₀ anomalies.</p

Projected changes (%) in E₀ by 2050 across the different E₀ formulations.

<p>Percent change in mean MJJAS E₀ from Penman-Monteith (top row), Hargreaves-Samani (center), and Priestley-Taylor (bottom) formulations for GFDL-ESM2M (left) and CanESM2 (right) by 2050 (2036–2065) relative to the historical (1976–2005) period. Grid cells where the change is not statistically significant (i.e., p > 0.05) are masked out in white.</p

Analysis summary.

<p>Analysis summary.</p

21^st century trends in EDDI and SPEI.

<p>Comparison of 12-week EDDI and SPEI computed with the three E₀ formulations for each day between 1950–2100 for GFDL-ESM2M and CanESM2 for the Northern Great Plains region. Daily EDDI or SPEI values are binned into specific percentile categories (spanning between driest and wettest categories) relative to the historical (1976–2005) distribution.</p

Uncertainties in changing drought risk by 2050 based on E₀ formulation and GCM selection.

<p>Comparison of changes in 12-week EDDI and SPEI values for August 31 by 2050 (relative to the 1976–2005 mean) between the two GCMs based on the different E₀ formulations considered in this study. Filled circles show the mean change, box plots show 25th, 50th and 75th percentiles, and whiskers show 5th and 95th percentiles. Confidence intervals shown here about the mean projected change are estimated based on Monte Carlo resampling. Positive changes in EDDI and negative changes in SPEI signify increases in drought intensity.</p

Projections of Mountain Snowpack Loss for Wolverine Denning Elevations in the Rocky Mountains

Abstract Future reduction in mountain snowpack due to anthropogenic climate change poses a threat to many snow‐adapted species worldwide. Mountain topography exerts a strong control on snowpack not only due to elevation but also through the effect of slope and aspect on the surface energy balance. We develop high‐resolution projections of snowpack in order to provide improved, physically based estimates of the spatial distribution of future snowpack to inform species conservation efforts for the wolverine (Gulo gulo) in two study areas in the Rocky Mountains: one in Montana with known den sites and one in Colorado with recent wolverine activity and potential for reintroduction. Here we assess springtime snowpack loss in actual and potential denning areas under five future climate scenarios for the mid‐21st century. Snowpack in April and May is likely to persist into the mid‐21st century in the upper half of current denning elevations in all but the warmest future climate scenario, while large declines are projected for the lower half of the denning elevations. We gain new insight into the influence of topographical aspect on future snowpack and quantify the potential for enhanced snow persistence on north and east facing slopes under future scenarios that is only revealed in simulations where terrain slopes are resolved

Global climate model specifications and sensitivities.

<p>Global climate model specifications and sensitivities.</p

Anatomy of an interrupted irrigation season: Micro-drought at the Wind River Indian Reservation

Drought is a complex phenomenon manifested through interactions between biophysical and social factors. At the Wind River Indian Reservation (WRIR) in west-central Wyoming, water shortages have become increasingly common since the turn of the 21st century. Here we discuss the 2015 water year as an exemplar year, which was characterized by wetter-than-normal conditions across the reservation and, according to the U.S. Drought Monitor, remained drought-free throughout the year. Yet parts of the reservation experienced harmful water shortages, or “micro-drought” conditions, during the growing season in 2015. In this assessment of the 2015 water year at the WRIR we: (1) describe the hydroclimatic and social processes under way that contributed to the 2015 water year micro-drought in the Little Wind Basin; (2) compare water availability conditions within and between other basins at the WRIR to illustrate how micro-droughts can result from social and environmental features unique to local systems; and (3) describe how a collaborative project is supporting drought preparedness at the WRIR. We combine a social science assessment with an analysis of the hydroclimate to deconstruct how shortages manifest at the WRIR. We provide insights from this study to help guide drought assessments at local scales. Keywords: Drought, Climate vulnerability, Drought preparedness, Indigenous adaptation, Co-productio