Abstract
Abstract Understanding the relationship between soil moisture (SM) and latent heat flux (LE) is crucial for forecasting seasonal extremes like heat waves and droughts and grasping long-term climate systems. Despite its importance, substantial disparities exist among various models’ interpretations of this relationship. This study defines four SM-LE indicators: wilting point, critical SM, saturated LE, and SM-LE slope, characterizing SM-LE regimes and corresponding breakpoints delineating the regimes using segmented regression and scrutinizes model disparities by contrasting conventional coupled simulations with matching offline land model (LM) simulations within the CMIP6 framework. It is revealed that those indicators have lower variability among ensemble members from the same model than among different models. Moreover, all indicators except for SM-LE slope demonstrate strong correlations between the coupled and uncoupled simulations using the same LMs. While the spatial distributions of breakpoint values correspond only moderately well with the indicators’ values, they improve after adjusting for model atmospheric biases of precipitation and downward radiation. The impact of the atmospheric fields on the four SM-LE indicators is well correlated between the coupled and offline experiments, except for the relationship between precipitation and the wilting point. Consequently, this indicates a significant constraint of the SM-LE relationship in coupled model simulations determined by the LM's behavior. Thus, one may determine much about the land-atmosphere coupling behavior parsimoniously in a model system without running the fully coupled model, justifying a hierarchical approach for model development and assessment.
Published Version
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