Quasi-Global (50° S–50° N) of Soil Moisture and Precipitation Extremes

Clarifying the interplay between extreme soil moisture (SM) and precipitation (P) is imperative to understand the impacts of extreme events on ecosystems in a changing climate. However, the detailed relationships, pathways, and quantitative characterization of SM-P extremes at a quasi-global (50° S–50° N) scale remain unclear. Here, we systematically evaluated the co-occurrence and temporal dependencies of SM-P extremes from 2000 to 2022, quantified their synchronous probability, used statistical modeling to reveal the directional pathways among evapotranspiration (ET), P, and SM, and detected long-term trends in P and SM extremes. Our results show a significant increase in the co-occurrence frequency of SM-P extremes globally, with strong spatiotemporal co-occurrence patterns. A lower conditional probability (62%) of extreme SM anomalies was observed within a short term (34 days) after P extremes occurred, while a significantly higher conditional probability (88%) of P extremes was found following extreme SM anomalies. Path analysis (structural equation modeling) indicates a strong direct positive pathway from P to SM, whereas SM influences P indirectly through ET. Compared to satellite-based observations, the BCC-ESM1 model within the CMIP6 framework reproduces the synchrony of SM-P extremes reasonably well, offering a feasible alternative for predicting SM-P relationships in regions lacking satellite observations and aiding future projections of their trends. Our study broadens the perspective on land–atmosphere interactions and coupling mechanisms, providing a solid theoretical basis for predicting and managing the effects of extreme events on ecosystems.

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Publication Details

Journal
Hydrology
Published
2026-02-09
DOI
https://doi.org/10.3390/hydrology13020067
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

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article

Quasi-Global (50° S–50° N) of Soil Moisture and Precipitation Extremes

Z. li, Wenfu Yang, Aoqi Shi, Wenwen Wang et al.
Hydrology
Soil Moisture and Remote Sensing
article

Quasi-Global (50° S–50° N) of Soil Moisture and Precipitation Extremes

Z. li, Wenfu Yang, Aoqi Shi, Wenwen Wang, Wenmin Zhang, Taoyu Jin, Jun Liu
article en

Abstract

Clarifying the interplay between extreme soil moisture (SM) and precipitation (P) is imperative to understand the impacts of extreme events on ecosystems in a changing climate. However, the detailed relationships, pathways, and quantitative characterization of SM-P extremes at a quasi-global (50° S–50° N) scale remain unclear. Here, we systematically evaluated the co-occurrence and temporal dependencies of SM-P extremes from 2000 to 2022, quantified their synchronous probability, used statistical modeling to reveal the directional pathways among evapotranspiration (ET), P, and SM, and detected long-term trends in P and SM extremes. Our results show a significant increase in the co-occurrence frequency of SM-P extremes globally, with strong spatiotemporal co-occurrence patterns. A lower conditional probability (62%) of extreme SM anomalies was observed within a short term (34 days) after P extremes occurred, while a significantly higher conditional probability (88%) of P extremes was found following extreme SM anomalies. Path analysis (structural equation modeling) indicates a strong direct positive pathway from P to SM, whereas SM influences P indirectly through ET. Compared to satellite-based observations, the BCC-ESM1 model within the CMIP6 framework reproduces the synchrony of SM-P extremes reasonably well, offering a feasible alternative for predicting SM-P relationships in regions lacking satellite observations and aiding future projections of their trends. Our study broadens the perspective on land–atmosphere interactions and coupling mechanisms, providing a solid theoretical basis for predicting and managing the effects of extreme events on ecosystems.

HydrologyVol. 13(2)
Ministry of Natural Resources (CN), China Coal Research Institute (China) (CN), East China Normal University (CN), Taiyuan University of Technology (CN)
European Space Agency, ShanXi Science and Technology Department
Climate action
Openalex Percentile: Top 66%
Soil Moisture and Remote Sensing
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