Global hydrological modeling is influenced by Meteorological uncertainty.
Editors’ Highlights are summaries of recent papers by AGU’s journal editors.
Rewritten: The publication “Water Resources Research” is the source.
Creating a precise and accurate digital model of Earth’s hydrology has been a significant hurdle for many years. In their recent research, Tang and colleagues [2023] tackle a crucial aspect of this task by examining how uncertainties in weather data affect the variables in a hydrological model.
The crucial modeling aspect is frequently disregarded in hydrological research due to the absence of probabilistic weather data. The EM-Earth product (Tang et al., 2022) offers a novel approach to elucidate the impact of these uncertainties on crucial hydrological processes, such as runoff and soil moisture, and aid in comprehending the scale effects of these uncertainties. What sets EM-Earth apart from other available products is its utilization of a unified atmospheric reanalysis (ERA5) combined with current meteorological data to generate global gridded estimates and associated uncertainties.
For this research, a 25-member group with probabilistic methods was utilized to examine 289 river basins in the cryosphere. One of the key conclusions was that variations in precipitation and temperature greatly affect the accuracy of hydrological model results, with some variations exceeding 100% of the actual output values. This highlights the importance of using probabilistic forces for assessing the impact on water resources.
The focus of this research was to examine the impact of unpredictable weather elements such as precipitation and temperature on various regions within boreal basins. To do this, the authors utilized a gridded probabilistic meteorological ensemble known as EM-Earth. By estimating these two meteorological factors, they were able to demonstrate how they influence important hydrological processes. Credit goes to Tang et al. [2023], Figure 2.
This study’s groundbreaking research is crucial for comprehending how uncertainty spreads in hydrologic models, making it highly relevant and intriguing 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
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