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Multi-model hydrological reference dataset over continental Europe and an African basin.

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|September 17, 2024
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Summary

This study introduces a new hydrological dataset to assess land surface and hydrologic model (LSM/HM) uncertainty. It aims to foster collaboration between Earth Observation (EO) and LSM/HM communities for consistent terrestrial Essential Climate Variables (ECVs).

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Area of Science:

  • Earth System Science
  • Hydrology
  • Climate Science
  • Remote Sensing

Background:

  • Essential Climate Variables (ECVs) are crucial for scientific and policy decisions.
  • Terrestrial ECVs are not yet treated in an integrated manner by Earth Observation (EO) and Land Surface and Hydrologic Model (LSM/HM) communities.
  • Greater collaboration between EO and LSM/HM communities is needed for consistent terrestrial ECVs at regional and continental scales.

Purpose of the Study:

  • To introduce a new hydrological reference dataset for assessing LSM/HM simulation uncertainty.
  • To provide a benchmark for generating consistent terrestrial ECVs through the integration of EO products.
  • To foster collaboration between EO and LSM/HM communities.

Main Methods:

  • Compilation of 19 state-of-the-art LSM/HM simulations.
  • Simulations provided on a daily time step, covering Europe (Rhine, Po basins) and Africa (Tugela basin).
  • Uniform formatting for cross-simulation comparisons and validation with discharge, evapotranspiration, soil moisture, and total water storage anomaly observations.

Main Results:

  • A comprehensive hydrological reference dataset is established.
  • The dataset represents the current state-of-the-art in LSM/HM simulations.
  • Simulations are validated against multiple terrestrial hydrological observations.

Conclusions:

  • The developed dataset is a valuable tool for assessing LSM/HM uncertainty.
  • It serves as a benchmark for generating consistent terrestrial ECVs.
  • The dataset supports policy development and promotes integration between EO and LSM/HM communities.