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Understanding the Asian Water Tower requires a new precipitation observation strategy

<p>The Asian water tower (AWT) serves as the source of 10 major Asian river systems and supports the lives of ~2&nbsp;billion people. Obtaining reliable precipitation data over AWT is a prerequisite for understanding the water cycle within this pivotal region. Here, we quantitatively reveal that the &ldquo;observed&rdquo; precipitation over the AWT is considerably underestimated in view of observational evidence from three water cycle components, namely, evapotranspiration, runoff and accumulated snow. We found that three paradoxes appear if the so-called &ldquo;observed&rdquo; precipitation is corrected, namely, actual evapotranspiration exceeding precipitation, unrealistically high runoff coefficients, and accumulated snow water equivalent exceeding contemporaneous precipitation. We then explained the cause of precipitation underestimation from instrumental error caused by wind-induced gauge undercatch and the representativeness error caused by sparse-uneven gauge density and complexity of local surface conditions. These findings require us to rethink previous results related to the water cycle, and the study then introduced potential solutions.</p> <p>This provides the main dataset used in this study, including the observed precipitation, evapotranspiration, runoff, and snow water equivalent across AWT.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

Dataset details

Repository
zenodo
Published
May 29, 2024
License
cc-by-4.0
DOI
10.5281/zenodo.10695841

Scored with release 0.9.0

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