Observational evidence of regional increasing hot extreme accelerated by surface energy partitioning

Abstract Land-atmosphere interactions play an important role in the changes of extreme climates, especially hot spots land-atmosphere coupling. One linkages is coupling between air temperature and surface energy fluxes associated with soil moisture variability, vegetation change, human water/land management. However, existing studies on are mainly based parameterized solution climate model, which might not dynamically reflect all partitioning due to effects physiological control In this study, for first time, we used daily weather observations identify where (i.e., 99th percentile maximum temperature, Tq99th) rises faster than local mean (Tmean) during 1975–2017. Furthermore, analyzed relationship trends relative average (?Tq99th/?Tmean) evaporative fraction (?EF), i.e., ratio latent heat flux available energy, using long-term sensible informed by atmospheric boundary layer theory, machine learning, ground-based towers stations. Hot increase ?Tq99th/?Tmean identified be Europe, southwestern North America, Northeast Asia, Southern Africa. The detected significant negative correlations ?EF suggested that hotspot regions typically affected annual/summer dryness. Our observation-driven findings have great implications providing realistic observational evidences change accelerated partitioning.