Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> As the theoretical upper bound of evapotranspiration (ET) or water use by ecosystems, potential ET (PET) has always been widely used as a variable linking a variety of disciplines, such as climatology, ecology, hydrology, and agronomy. However, substantial uncertainties exist in the current PET methods (e.g., empiric models and single-layer models) and datasets, because of unrealistic configurations of land surface and unreasonable parameterizations. Therefore, this study comprehensively considered interspecific differences in various vegetation-related parameters (e.g., plant stomatal resistance and CO<sub>2</sub> effects on stomatal resistance) to calibrate and parametrize the Shuttleworth-Wallace (SW) model for forests, shrubland, grassland and cropland. We derived the parameters using identified daily ET observations with no water stress (i.e., PET) at 96 eddy covariance (EC) sites across the globe. Model validations suggest that the calibrated model could be transferable from known observations to any location. Based on four popular meteorological datasets, relatively realistic canopy height and time-varying land use/land cover and Leaf Area Index, we generated a global 5 km ensemble mean monthly PET dataset that includes two components of potential transpiration (PT) and soil evaporation (PE) for the 1982–2015 time period. Using this new dataset, the climatological characteristics of PET partitioning and the spatio-temporal changes in PET, PE and PT were investigated. The global mean annual PET was 1200 mm with PT/PET of 40 % and PE/PET of 60 %, and moreover controlled by PT and PE over 43 % and 57 % of the globe, respectively. Globally, the annual PET and PT significantly (<em>p</em><0.05) increases by 1.25 mm/yr and 1.22 mm/yr over the last 34 years, followed by a slight increase in the annual PE. Overall, the annual PET changes over 53 % of the globe could be attributed to PT, and the rest to PE. The new PET dataset may be used by academic communities and various agencies to conduct climatological analyses, hydrological modelling, drought studies, agricultural water management, and biodiversity conservation. The dataset is available at <a href="https://doi.org/10.11888/Terre.tpdc.300193" target="_blank" rel="noopener">https://doi.org/10.11888/Terre.tpdc.300193</a> (Sun et al., 2023).
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