Future Global Lake Evaporation

The data contains grided mean annual lake evaporation data derived from the Lake, Ice, Snow, and Sediment Simulator (LISSS) simulations. It includes three primary variables: mean evaporation forced by reanalysis–observation (RO) datasets, mean evaporation driven by global climate models (GCMs) historic data, and mean evaporation driven by GCMs under the RCP8.5 scenario. The RO evaporation represents the average output from LISSS simulations forced with the CRU (Viovy, 2018) and Princeton (Sheffield et al., 2006) datasets, while the GCM driven evaporation reflects the mean of simulations forced with GFDL-ESM2M and GISS-E2R CMIP5 models. This dataset facilitates comparison of historical and projected lake evaporation patterns under high-emissions climate scenarios.本数据集包含基于湖泊、冰盖、积雪与沉积物模拟器（Lake, Ice, Snow, and Sediment Simulator, LISSS）模拟得到的格网化年平均湖泊蒸发量数据。其包含三类核心变量：由再分析-观测（reanalysis–observation, RO）数据集驱动的平均蒸发量、由全球气候模型（global climate models, GCMs）历史数据驱动的平均蒸发量，以及RCP8.5情景下由GCMs驱动的平均蒸发量。其中RO蒸发量代表以CRU（Viovy, 2018）与Princeton（Sheffield et al., 2006）数据集为强迫场的LISSS模拟结果的平均值，而GCM驱动的蒸发量则反映了以GFDL-ESM2M和GISS-E2R CMIP5模式为强迫场的模拟结果的平均值。本数据集可用于对比高排放气候情景下的历史与预估湖泊蒸发格局。