Editors’ Highlights are summaries of recent papers by AGU’s journal editors.
Source: Water Resources Research

The development of a high resolution, high fidelity digital twin of Earth hydrology has been a major challenge for decades. In a new study, Tang et al. [2023] address one of the most important issues in achieving this goal, namely understanding the propagation of meteorological uncertainties to the variables of a hydrological model.

This fundamental modeling component is often neglected in hydrologic studies because of the lack of probabilistic meteorological products. The EM-Earth product (Tang et al., 2022) provides a new way to clarify how these uncertainties affect important hydrologic fluxes and states such as runoff and soil moisture, and help to understand the scale effects of these uncertainties. The advantage of EM-Earth over other existing products is that it uses a coherent atmospheric reanalysis (ERA5) merged with existing meteorological observations to provide global gridded meteorological estimates and uncertainties.

In this study, this probabilistic 25-member ensemble was used for the above purpose in a comprehensive sample of 289 cryosphere river basins. Among the main findings of this study is that “the uncertainties in precipitation and temperature lead to substantial uncertainties in hydrological model outputs, some of which exceed 100% of the magnitude of the output variables themselves”. This clearly indicates the urgent need to shift to probabilistic forcings for impact studies in water resources.

This study looked at how uncertain weather conditions like precipitation and temperature can affect different areas in boreal basins. The authors used a gridded probabilistic meteorological ensemble called EM-Earth to figure this out. They estimated these two meteorological forcings and showed how they propagate into the key hydrological fluxes. Credit: Tang et al. [2023], Figure 2

The pioneering work of this study is essential to our understanding of uncertainty propagation in hydrologic models and is therefore of great relevance and interest for future studies.

Citation: Tang, G., Clark, M. P., Knoben, W. J. M., Liu, H., Gharari, S., Arnal, L., et al. (2023). The impact of meteorological forcing uncertainty on hydrological modeling: A global analysis of cryosphere basins. Water Resources Research, 59, e2022WR033767. https://doi.org/10.1029/2022WR033767

—Luis Samaniego, Associate Editor, Water Resources Research

Text © 2023. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

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