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

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

Reanalysis data are being increasingly used as gridded weather data sources for assessing crop-reference evapotranspiration (ET0) in irrigation water-budget analyses at regional scales. This study assesses the performances of ET0 estimates based on weather data, respectively produced by two high-resolution reanalysis datasets: UERRA MESCAN-SURFEX (UMS) and ERA5-Land (E5L). The study is conducted in Campania Region (Southern Italy), with reference to the irrigation seasons (April–September) of years 2008–2018. Temperature, wind speed, vapor pressure deficit, solar radiation and ET0 derived from reanalysis datasets, were compared with the corresponding estimates obtained by spatially interpolating data observed by a network of 18 automatic weather stations (AWSs). Statistical performances of the spatial interpolations were evaluated with a cross-validation procedure, by recursively applying universal kriging or ordinary kriging to the observed weather data. ERA5-Land outperformed UMS both in weather data and ET0 estimates. Averaging over all 18 AWSs sites in the region, the normalized BIAS (nBIAS) was found less than 5% for all the databases. The normalized RMSE (nRMSE) for ET0 computed with E5L data was 17%, while it was 22% with UMS data. Both performances were not far from those obtained by kriging interpolation, which presented an average nRMSE of 14%. Overall, this study confirms that reanalysis can successfully surrogate the unavailability of observed weather data for the regional assessment of ET0.

Comparison of ERA5-Land and UERRA MESCAN-SURFEX Reanalysis Data with Spatially Interpolated Weather Observations for the Regional Assessment of Reference Evapotranspiration

Reference grass evapotranspiration with reduced data sets: Parameterization of the FAO Penman-Monteith temperature approach and the Hargeaves-Samani equation using local climatic variables

Reference crop evapotranspiration (ET
 o) is a critically important parameter for climatological, hydrological and agricultural management. The FAO56 Penman-Monteith (PM) equation has been recommended as the standardized ET
 o (ET
 o,s) equation, but it has a high requirements of climatic data. There is a practical need for finding a best alternative method to estimate ET
 o in the regions where full climatic data are lacking. A comprehensive comparison for the spatiotemporal variations, relative errors, standard deviations and Nash-Sutcliffe efficacy coefficients of monthly or annual ET
 o,s and ET
 o,i (i = 1, 2, …, 10) values estimated by 10 selected methods (i.e., Irmak et al., Makkink, Priestley-Taylor, Hargreaves-Samani, Droogers-Allen, Berti et al., Doorenbos-Pruitt, Wright and Valiantzas, respectively) using data at 552 sites over 1961–2013 in mainland China. The method proposed by Berti et al. (2014) was selected as the best alternative of FAO56-PM because it was simple in computation process, only utilized temperature data, had generally good accuracy in describing spatiotemporal characteristics of ET
 o,s in different sub-regions and mainland China, and correlated linearly to the FAO56-PM method very well. The parameters of the linear correlations between ET
 o of the two methods are calibrated for each site with the smallest determination of coefficient being 0.87.

/pdf/the-best-alternative-for-estimating-reference-crop-hyar7g14cc.pdf

The best alternative for estimating reference crop evapotranspiration in different sub-regions of mainland China.

Short-term forecasting of daily reference evapotranspiration using the Penman-Monteith model and public weather forecasts

Accuracy of reference evapotranspiration (ETo) estimates under data scarcity scenarios in the Iberian Peninsula

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Accuracy of reference evapotranspiration (ETo) estimates under data scarcity scenarios in the Iberian Peninsula