Preprints
https://doi.org/10.5194/essd-2023-495
https://doi.org/10.5194/essd-2023-495
10 Jan 2024
 | 10 Jan 2024
Status: a revised version of this preprint was accepted for the journal ESSD and is expected to appear here in due course.

Satellite-based Near-Real-Time Global Daily Terrestrial Evapotranspiration Estimates

Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi

Abstract. Accurate and timely information on global terrestrial actual evapotranspiration (ET) is crucial in agriculture, water resource management and drought forecasting in a changing climate. While numerous satellite-based ET products have been developed in recent decades, few provide near-real-time global terrestrial ET estimates. The MOD16 ET dataset, currently updating at the fastest rate, still experiences a delay of over two weeks. This is because most satellite-based ET algorithms rely on meteorological data from land surface models or in situ measurements, which cannot be obtained in near-real-time, resulting in delays of more than two weeks. To expedite global ET data access, we developed the Moderate Resolution Imaging Spectroradiometer (MODIS) based Variation of Standard Evapotranspiration Algorithm (VISEA) to provide global daily ET data within a week of the actual measurements at a spatial resolution of 0.05°. The VISEA model incorporates several key components: (1) A vegetation index (VI)-temperature (Ts) triangle method to simulate air temperature (Ta), serves as a basis for calculating other meteorological parameters (e.g., water vapor deficit and wind speed); (2) A daily evaporation fraction (EF) method based on the decoupling parameter, converts satellite-based instantaneous observations into daily ET estimates; (3) A net radiation calculation program takes into account cloud coverage in the atmosphere's downward longwave radiation. The VISEA model is driven by shortwave radiation from the European Centre for Medium-range Weather Forecasts (ERA5-Land) and MODIS land products, e.g., surface reflectance, land surface temperature/emissivity, land cover products), vegetation indices, and albedo as inputs. To assess its accuracy, we compared VISEA-with measurements from 149 flux towers, five other satellite-based global ET products, and precipitation data from the Global Precipitation Climatology Centre (GPCC). The evaluations show that the near-real-time ET using VISEA performs with similar accuracy to other existing data products and offers a significantly shorter time frame for daily data availability. Over 12 landcover types, the mean R is about 0.6 with an RMSE of 1.4 mm day-1 at a daily scale. Furthermore, the consistent spatial patterns of multi-year average VISEA align closely with GPCC precipitation data, reaffirming the dataset's ability to accurately represent global terrestrial ET distribution. To emphasize the capabilities of the VISEA for drought monitoring, we analyzed the spatial and temporal variations of ET during a drought event and subsequent recovery with precipitation in the Yangtze River basin from August 28th to September 1st, 2022. The VISEA distinctly illustrated low ET levels (<0.2 mm day-1) across most areas of the Yangtze River Basin on August 28th, indicating the severity of the drought. Conversely, a noticeable increase in ET (>0.9 mm day-1) is observed on August 29th, signifying the retreat of the drought due to precipitation. The near-real-time global daily terrestrial ET estimates could be valuable for meteorology and hydrology applications requiring real-time data, particularly in coordinating relief efforts during droughts. The VISEA code and dataset are available at https://doi.org/10.11888/Terre.tpdc.300782 (Huang et al., 2023a).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-495', Mingliang Liu, 01 Feb 2024
    • AC1: 'Reply on RC1', Lei Huang, 20 Mar 2024
  • RC2: 'Comment on essd-2023-495', Seungcheol Oh, 05 Feb 2024
    • AC2: 'Reply on RC2', Lei Huang, 20 Mar 2024
  • RC3: 'Comment on essd-2023-495', Ren Wang, 11 Feb 2024
    • AC3: 'Reply on RC3', Lei Huang, 20 Mar 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-495', Mingliang Liu, 01 Feb 2024
    • AC1: 'Reply on RC1', Lei Huang, 20 Mar 2024
  • RC2: 'Comment on essd-2023-495', Seungcheol Oh, 05 Feb 2024
    • AC2: 'Reply on RC2', Lei Huang, 20 Mar 2024
  • RC3: 'Comment on essd-2023-495', Ren Wang, 11 Feb 2024
    • AC3: 'Reply on RC3', Lei Huang, 20 Mar 2024
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi

Data sets

Satellite-based Near-Real-Time Global Daily Terrestrial Evapotranspiration Estimates Lei Huang https://doi.org/10.11888/Terre.tpdc.300782

Model code and software

Satellite-based Near-Real-Time Global Daily Terrestrial Evapotranspiration Estimates Lei Huang https://doi.org/10.6084/m9.figshare.24647721.v1

Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi

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Short summary
Timely global terrestrial evapotranspiration (ET) data are crucial for water resource management and drought forecasting. This study introduces the VISEA algorithm, which integrates satellite data and shortwave radiation to provide daily 0.05° gridded near-real-time ET estimates. By employing a vegetation index-temperature method, this algorithm can estimate ET without requiring additional data. Evaluation results demonstrate VISEA's comparable accuracy with accelerated data availability.
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