A benchmark dataset for global evapotranspiration estimation based on FLUXNET2015 from 2000 to 2022 (V1.0)

Our released data mainly contains four types of data:

(1) Half-hourly or hourly gap-filled LE data: The data are well gap-filled LE data using the novel bias-corrected RF algorithm. In the filenames, “HH” or “HR” indicate half-hourly or hourly scale data, respectively. The time information in the data files includes a pair of timestamps consistent with those in FLUXNET2015. The data are recorded at local time. The start time is “2000-02-18, 00:00:00”, and the end time is the same as the observation time at each site. For the quality control flags (QC), a value of 0 indicates observed data, while 1 indicates gap-filled data.

(2) Prolonged daily LE data: This dataset provides the prolonged daily LE data using the novel bias-corrected RF algorithm. The seamless data covers the period from February 18, 2000, to December 31, 2022. For the prolonged part, the quality flag is set to 2. The rest data is consistent with the aggregated daily LE data.

(3) Aggregated daily, monthly and yearly LE data: The hourly dataset is aggregated from the gap-filled half-hourly data to a daily scale. The start time is “2000-02-18”, and the end time is the same as the observation time at each site. Data quality control flags are also provided, with the values representing the percentage of hourly observations for each day. The monthly and yearly LE data are aggregated from the prolonged daily LE data. Quality control flags represent the proportion of days with more than 90% of hourly observations in a given month or a given year. No distinction is made between prolonged data and data with complete missing observations within a day. The start time for the monthly data is March 2000, and that for the yearly data is 2001.

All files are formatted as csv files. NDVI and debiased reference variables from ERA5-Land are also provided.

For more details of our data, please refer to a companion research article submitted to ESSD. Li, W., Yao, Z., Qu, Y., Yang, H., Song, Y., Song, L., Wu, L., and Cui, Y.: A benchmark dataset for global evapotranspiration estimation based on FLUXNET2015 from 2000-2022, Earth Syst. Sci. Data, under review, 2024.