A 10% increase in global land evapotranspiration from 2003 to 2019

We calculate an ensemble of global land evapotranspiration (ET) for 2003 to 2019 over global land using a water-budget approach. We use 4 publicly available precipitation datasets (GPCPv2.3, MERRA-2, ERA-5 and NOAA-NCEP), 5 discharge estimates (JRA-55, and 4 independently calculated ocean -mass balance global discharge estimates) and water storage change derived from the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) missions. We calculate 20 different estimates of global land evapotranspiration using all combinations of the precipitation and discharge datasets, and one estimate of total water storage change (computed using backward difference method and the GRACE/GRACE-FO total water storage change from JPLRL06). The data is presented as a timeseries from 2003 to 2019 at a monthly time step (in units of mm per year). We also provide an estimate of monthly uncertainty based on error in the precipitation data sets (defined as the standard deviation across the precipitation data), error in discharge (defined as standard deviation across the discharge data) and error in the water storage change (this is calculated using the GRACE formal error product) as well as the total error (from summing in quadrature the mean component errors) ('Global-land-ET-error-budget'). The primary dataset is an estimate for all land areas including the ice-sheets ('Global-land-ET'). We also provide two separate estimates of global land ET that: i) do not include the contribution of the ice sheets (Greenland and Antarctica) ('Global-land-ET-without-icesheets'), ii) do not include the contribution of Antarctica ('Global-land-ET-without-Antarctica'). For each ensemble member of ET, the data variable contains the name of the precipitation data set and discharge data set used. We also include the data that has been smoothed and gap filled using bootstrapping methods ('Global-land-ET-smoothing-bootstrap'). All data is monthly and in units of mm/year. We also include the global discharge ocean mass balance estimates that were used to estimate global land evapotranspiration. The data set of global discharge is available for 2002 to 2019 using an ocean mass balance approach. The data was created using ocean altimetry (AVISO/DUACS), ocean steric information (EN4), combined with ocean precipitation (GPCPv2.2, CMAP), ocean evaporation (OAFLUX), and also estimates of precipitation - evaporation calculated from ocean atmospheric moisture budget (MERRA-2, ERA-5). The discharge includes runoff from all land masses including the ice sheets. The data was created by H. Chandanpurkar, and is an updated version from Chandanpurkar et al. (2017). Details are available at: Chandanpurkar, H. A., Reager, J. T., Famiglietti, J. S., & Syed, T. H. (2017). Satellite-and reanalysis-based mass balance estimates of global continental discharge (1993–2015). Journal of Climate, 30(21), 8481-8495.我们采用水量平衡法，计算得到2003至2019年全球陆面蒸散发（evapotranspiration, ET）的集合数据集。本研究使用了4套公开可用的降水数据集（GPCPv2.3、MERRA-2、ERA-5和NOAA-NCEP）、5套径流估算结果（JRA-55，以及4套独立计算的洋质量平衡全球径流估算结果），以及来自重力恢复与气候实验（Gravity Recovery and Climate Experiment, GRACE）及GRACE后续（GRACE-Follow On, GRACE-FO）任务的水储量变化数据。我们通过降水与径流数据集的所有组合方式，计算得到20组全球陆面蒸散发估算结果，以及1组总水储量变化估算结果（采用后向差分法，结合JPLRL06版本的GRACE/GRACE-FO总水储量变化数据）。本数据集以2003至2019年的月尺度时间序列形式发布，单位为毫米每年（mm/年）。我们还提供了基于各数据集误差的月尺度不确定性估算：包括降水数据集误差（定义为各降水数据集间的标准差）、径流误差（定义为各径流数据集间的标准差）、水储量变化误差（采用GRACE正式误差产品计算），以及通过各分量误差正交求和得到的总误差（对应数据集'Global-land-ET-error-budget'）。核心数据集为涵盖所有陆地区域（包括冰盖）的全球陆面蒸散发估算结果（'Global-land-ET'）。此外还提供两类独立的全球陆面蒸散发估算结果：① 不含冰盖（格陵兰与南极）贡献的结果（'Global-land-ET-without-icesheets'）；② 不含南极贡献的结果（'Global-land-ET-without-Antarctica'）。对于每个蒸散发集合成员，数据变量中会标注所用的降水数据集与径流数据集名称。我们还提供了采用自助法（bootstrapping）进行平滑与间隙填充后的数据集（'Global-land-ET-smoothing-bootstrap'）。所有数据均为月尺度数据，单位为mm/年。此外还包含了用于估算全球陆面蒸散发的全球径流洋质量平衡估算结果。该全球径流数据集的时间跨度为2002至2019年，采用洋质量平衡法构建，其制作采用了海洋测高数据（AVISO/DUACS）、海洋比容信息（EN4），结合海洋降水数据（GPCPv2.2、CMAP）、海洋蒸发数据（OAFLUX），以及基于海洋大气水汽预算计算的降水-蒸发差值（MERRA-2、ERA-5）。该径流包含所有陆块（包括冰盖）的径流。本数据集由H. Chandanpurkar制作，是Chandanpurkar等人（2017）研究的更新版本。详细信息可参见：Chandanpurkar, H. A., Reager, J. T., Famiglietti, J. S., & Syed, T. H. (2017). 基于卫星与再分析数据的全球大陆径流质量平衡估算（1993–2015）. 《气候杂志》, 30(21), 8481-8495.