Implication of climate variable selections on the uncertainty of reference crop evapotranspiration projections propagated from climate variables projections under climate change

Abstract

The projection of reference crop evapotranspiration (ETo) based on global climate models (GCMs) is an important task in many fields under climate change background. However, ETo projections are typically hindered by the limited data availability or high uncertainty of the GCM-projected climate variable for ETo calculation (e.g., radiation and wind speed). In the current study, we investigate how the selection of climate variables for ETo calculation would influence the reliability and uncertainty of the ETo projections. Based on the Penman-Monteith (P-M) formula and the missing variable estimation approaches provided by FAO, five variable selection schemes (VSs) that select different subsets of the climate variables for ETo calculation are established. Four emission scenarios, five GCMs and four statistical downscaling approaches were adopted, and their uncertainty contributions were quantified by analyses of variation (ANOVA) approach. Results show that, among the climate variables except air temperature, shortwave radiation caused the lowest uncertainty to the projected ETo, and is thus suggested as the most suitable variable to be considered for ETo projections. In most areas, wind speed and relative humidity are determined as marginal variables for their limited influences in ETo projections, yet in some complex-terrain regions, wind speed could propagate considerable uncertainty to the projected ETo. Differences in GCMs is the major source of uncertainty in ETo projections, while the emission scenario generally ranked as second. Statistical downscaling approaches contribute limited uncertainty (below 10%) to ETo projections. Above all, this study shows the applicability of using the missing value estimation approaches for the FAO56 P-M formula to perform future ETo projection, for the practices with limited GCM data availability, and can serve as the reference for selecting suitable variables for ETo forecasting in applications.