Global Characterization of the Varying Responses of the Standardized Precipitation Evapotranspiration Index to Atmospheric Evaporative Demand

Abstract

The standardized precipitation evapotranspiration index (SPEI) is one of the well‐established drought metrics worldwide. It is simply computed using precipitation and atmospheric evaporative demand (AED) data. Although AED is considered a key driver of drought variability worldwide, it could have less impact on drought in specific regions and for particular times as a function of the magnitude of precipitation. Specifically, the influence of the AED might overestimate drought severity during both normal and humid periods, resulting in “false alarms” about drought impacts on physical and human environments. Here, we provided a global characterization of the sensitivity of the SPEI to changes of the AED. Results demonstrate that the contribution of AED to drought severity is largely impacted by the spatial and temporal variability of precipitation. Specifically, the impact of AED on drought severity was more pronounced during periods of low precipitation, compared to wet periods. Interestingly, drought severity in humid regions (as revealed by SPEI) also showed low sensitivity to AED under drier conditions. These results highlight the skill of SPEI in identifying the role of AED in drought evolution, especially in arid and semiarid regions whose climate is characterized typically by low precipitation. This advantage was also evident for humid environments, where SPEI did not overestimate drought severity due to the increased AED. These findings highlight the broader applicability of SPEI to accurately characterize drought severity worldwide.

Flash Drought Response to Precipitation and Atmospheric Evaporative Demand in Spain

“…To analyze the role of precipitation deficits and atmospheric evaporative demand (AED) positive anomalies in the development of flash drought events in Spain, we calculated the sensitivity of SPEI to the AED at a short time scale (1-month) and compared it with the total frequency of flash drought events recorded in each month of the year in the period from 1961 to 2018. The sensitivity of SPEI to AED differs between climate conditions [9,17]. The SPEI is based on standardization of the climate balance (D) resulting from differences between precipitation and AED (D = P − AED), making it possible to quantify the contribution of precipitation and AED to the variability of SPEI values, following the methodology proposed by Tomas-Burguera et al [9].…”

“…The sensitivity of SPEI to AED differs between climate conditions [9,17]. The SPEI is based on standardization of the climate balance (D) resulting from differences between precipitation and AED (D = P − AED), making it possible to quantify the contribution of precipitation and AED to the variability of SPEI values, following the methodology proposed by Tomas-Burguera et al [9]. Thus, using the precipitation and AED series employed to compute SPEI, we calculated the partial derivatives of the climate balance (D) to determinate the relative contribution of both variables in each month over the period 1961-2018.…”

“…Precipitation is the most important factor in the development of droughts [9]. However, the occurrence of flash droughts has been commonly related to drastic increases in AED and the associated land-atmosphere feedbacks (e.g., increased land evapotranspiration) that can trigger or reinforce drought conditions [10].…”

The evolution of climatic drought studies in Spain over the last few decades

“…This index has gained use globally during the last decade, with advantages over other indices in drought quantification (Vicente-Serrano et al, 2012a) and provides a suitable response to the spatial and temporal variability of precipitation and AED (Vicente-Serrano et al, 2015c). In the SPEI, the main influence of the AED is recorded during low precipitation periods and regions (Tomas-Burguera et al, 2020); it also provides a good characterization of the tails of the distribution of the variable (Vicente-Serrano and Beguería, 2016), thus enabling robust temporal and spatial comparability of drought severity.…”

“…Turco et al (2017) analyzed summer drought predictability and compared statistical and dynamic models, and although they showed a source of predictability, they suggested that this is mostly attributable to the observed initial conditions and mainly as a consequence of the autoregressive character of droughts, which limit any practi-cal operability of the forecasts. Thus, the ability of possible drought forecasting is restricted to the AED component (Solaraju-Murali et al, 2019), which has little influence on drought severity in comparison to precipitation (Tomas-Burguera et al, 2020).…”