资源环境科技发展态势分析平台

As a key variable in the climate system, soil moisture (SM) plays a central role in the Earth's terrestrial water, energy, and biogeochemical cycles through its coupling with surface latent heat flux (LH). Despite the need to accurately represent SM/LH coupling in Earth system models, we currently lack quantitative, observation-based, and unbiased estimates of its strength. Here we utilize the triple-collocation (TC) approach introduced in Crow et al. (2015) to SM and LH products obtained from multiple satellite remote sensing platforms and land surface models (LSMs) to obtain unbiased global maps of SM/LH coupling strength. Results demonstrate that relative to coupling strength estimates acquired directly from remote sensing-based data sets, the application of TC generally enhances estimates of warm-season SM/LH coupling, especially in the western United States, the Sahel, central Asia, and Australia. However, relative to triple-collocation estimates, LSMs (still) overpredict SM/LH coupling strength along transitional climate regimes between wet and dry climates, such as the central Great Plains of North America, India, and coastal Australia. Specific climate zones with biased relations in LSMs are identified to geographically focus the reexamination of LSM parameterizations. TC-based coupling strength estimates are robust to our choice of LSM contributing SM and LH products to the TC analysis. Given their robustness, TC-based coupling strength estimates can serve as an objective benchmark for investigating model-predicted SM/LH coupling.

Plain Language Summary Physical models describing land-atmosphere coupling have been developed to help better understand the impact of local-, regional-, and global-scale climate on weather and the water cycle. However, verifying the accuracy of these models is challenging over sparsely instrumented areas. Here the strength of land-atmosphere coupling between soil moisture and terrestrial evapotranspiration is examined by combining multiple global-scale remote sensing and modeling products into a unified analysis. This analysis is unique in that it can be conducted globally and is unbiased by the presence of random errors in the remote sensing products. As such it provides the first robust estimate of the degree to which soil moisture and evapotranspiration are linked. Results show strong soil moisture/evapotranspiration coupling over the western United States, the African Sahel, central Asia, and Australia. However, they also demonstrate that most existing models are still overpredicting this coupling along transitional regions between wet and dry climates (like the Central Great Plains of North America, India, and coastal Australia). This work will help improve the representation of land-atmosphere coupling in models used to obtain future climate projections.