The land surface influences the atmospheric boundary layer (ABL) through its impacts on the partitioning of available energy into evaporation and warming. Previous research on understanding this complex link focused mainly on site-scale flux observations, gridded satellite observations, climate modeling, and machine-learning experiments. Observational evidence of land surface conditions, among which soil moisture, impacting ABL properties at intermediate landscape scales is lacking. Here, we use a combination of global weather balloon soundings, satellite-observed soil moisture, and a coupled land-atmosphere model to infer the soil moisture impact on the ABL. The inferred relationship between soil moisture and surface flux partitioning reflects distinctive energy- and water-limited regimes, even at the landscape scale. We find significantly different behavior between those two regimes, associating dry conditions with on average warmer (≈3 K), higher (≈400 m) and drier (≈1 kPa) afternoon ABLs than wet conditions. This evidence of land–atmosphere coupling from globally distributed atmospheric measurements highlights the need for an accurate representation of land–atmosphere coupling into climate models and their climate change projections.

陆地表面通过影响大气边界层（ABL），将其影响到将可用能量分配为蒸发和变暖。先前关于了解此复杂链接的研究主要集中在站点规模的通量观测，网格化卫星观测，气候建模和机器学习实验。缺乏土地表面状况的观察证据，其中土壤湿度影响中等景观尺度下的ABL特性。在这里，我们结合使用了全球气象气球探测，卫星观测的土壤湿度和耦合的陆-气模型来推断土壤湿度对ABL的影响。推断的土壤水分与地表通量分配之间的关系反映了独特的能量和水限制机制，即使在景观尺度上也是如此。我们发现这两种方案之间的行为存在显着差异，将干燥条件与平均ABL相比，平均湿度更高（≈3K），下午更高（≈400m）和更干燥（≈1kPa）。来自全球分布的大气测量的陆-气耦合证据表明，需要准确地将陆-气耦合表示为气候模型及其气候变化预测。