Land transpiration-evaporation partitioning errors responsible for modeled summertime warm bias in the central United States

• Published in: Nature communications Vol. 13; no. 1; p. 336
• Main Authors: Dong, Jianzhi, Lei, Fangni, Crow, Wade T.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 17.01.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 704/106/242; 704/242; Air temperature; Atmosphere; Atmospheric models; Bias; Canopies; Carbon dioxide; Evaporation; Evapotranspiration; Humanities and Social Sciences; Hypotheses; multidisciplinary; Partitioning; Physics; Remote sensing; Science; Science (multidisciplinary); Simulation; Soil moisture; Soil water storage; Summer; Transpiration; Water storage; Water stress; United States > US
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-021-27938-6

Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiment exhibit a well-known summertime warm bias in mid-latitude land regions – most notably in the central contiguous United States (CUS). The dominant source of this bias is still under debate. Using validated datasets and both coupled and off-line modeling, we find that the CUS summertime warm bias is driven by the incorrect partitioning of evapotranspiration (ET) into its canopy transpiration and soil evaporation components. Specifically, CMIP6 ESMs do not effectively use available rootzone soil moisture for summertime transpiration and instead rely excessively on shallow soil and canopy-intercepted water storage to supply ET. As such, expected summertime precipitation deficits in CUS induce a negative ET bias into CMIP6 ESMs and a corresponding positive temperature bias via local land-atmosphere coupling. This tendency potentially biases CMIP6 projections of regional water stress and summertime air temperature variability under elevated CO 2 conditions. Summertime warm bias in the central United States persists in Earth System Models. This bias is dominated by land physics related to transpiration and evaporation partitioning. Improved land physics can constrain projected climate uncertainty.