Abstract
Abstract
Evapotranspiration (ET) is one of the most important yet highly uncertain components of the water cycle. Available modeled ET products do not necessarily agree with each other at various spatiotemporal scales, either due to limitations on input data and/or due to model assumptions and simplifications. Therefore, using the water budget equation to estimate ET has gained attention. However, numerous water budget combinations with large uncertainties are available, which increases ambiguity in choosing the best ET estimate. Here, the Kalman filter is employed to ingest 96 water budget-based ET estimates, and produce a global ET product with uncertainty
<
2
mm month−1, and capture the general spatiotemporal pattern of ET and the inter-annual variability over all continents. Since the water budget includes storage changes due to human interventions, our ET estimates are superior over regions with strong irrigation signals, such as the Ganges basin. We verify our claim by using a modified variable infiltration capacity model that also simulates irrigation activities. Our ET estimates have a global mean positive trend of
0.18
±
0.02
mm yr−1 with larger regional variations, which we discuss.