Accurately evaluating land surface models is crucial for reliable climate forecast and water resource management. We proposed a new evaluation metric that avoids some traditional metrics' flaws by focusing on accuracy, variability, and pattern similarity. This work offers a more reliable alternative to evaluate land surface models, supporting better decisions in land surface model development.

Flux tower data are widely recognized as benchmarking data for land surface models, but insufficient emphasis on and deficiency in site attribute data limits their true value. We collect site-observed vegetation, soil, and topography data from various sources. The final dataset encompasses 90 sites globally, with relatively complete site attribute data and high-quality flux validation data. This work has provided more reliable site attribute data, benefiting land surface model development.

In this study we performed high-resolution climate model simulations for the hyper-arid Atacama Desert for the mid-Pliocene (3.2 Ma). The aim is to uncover the atmospheric processes that are involved in the enhancement of strong rainfall events during this period. We find that strong upper-level moisture fluxes (so-called moisture conveyor belts) originating in the tropical eastern Pacific are the main driver for increased rainfall in the mid-Pliocene.

Sand and dust emission are usually investigated by wind-tunnel experiments. However, wind-tunnel flows are usually neutrally stratified without large eddies, which typically develop in the convective atmospheric boundary layer. Here we proposed a novel technique by deploying a piece of randomly fluttering cloth in a wind tunnel to generate the large eddies and found them to enhance the entrainment of sand and dust particles, which explains why large eddies are important to aeolian entrainment.

Through a series of numerical experiments using the large-eddy-simulation model, we have developed an improved particle deposition scheme that takes into account transient wind shear fluctuations. Statistical analysis of the simulation results shows that the shear stress can be well approximated by a Weibull distribution and that the new scheme provides more accurate predictions than the conventional scheme, particularly under weak wind conditions and strong convective atmospheric conditions.