Dynamic Scaling of the Generalized Complementary Relationship Improves Long-term Tendency Estimates in Land Evaporation

Most large-scale evapotranspiration(ET)estimation methods require detailed information of land use,land cover,and/or soil type on top of various atmospheric measurements.The complementary relationship of evaporation(CR)takes advantage of the inherent dynamic feedback mechanisms found in the soil−vegetation−atmosphere interface for its estimation of ET rates without the need of such biogeophysical data.ET estimates over the conterminous United States by a new,globally calibrated,static scaling(GCR-stat)of the generalized complementary relationship(GCR)of evaporation were compared to similar estimates of an existing,calibration-free version(GCR-dyn)of the GCR that employs a temporally varying dynamic scaling.Simplified annual water balances of 327 medium and 18 large watersheds served as ground-truth ET values.With long-term monthly mean forcing,GCR-stat(also utilizing precipitation measurements)outperforms GCR-dyn as the latter cannot fully take advantage of its dynamic scaling with such data of reduced temporal variability.However,in a continuous monthly simulation,GCR-dyn is on a par with GCR-stat,and especially excels in reproducing long-term tendencies in annual catchment ET rates even though it does not require precipitation information.The same GCR-dyn estimates were also compared to similar estimates of eight other popular ET products and they generally outperform all of them.For this reason,a dynamic scaling of the GCR is recommended over a static one for modeling long-term behavior of terrestrial ET.