Recent global decline in rainfall interception loss due to altered rainfall regimes
Xu Lian1, Wenli Zhao2, Pierre Gentine2,3
1Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA. xl3179@columbia.edu.
Nature Communications
|December 10, 2022
Summary
Evaporative loss of interception (Ei) is a key water balance component. Our study quantifies global Ei using machine learning, revealing declining trends due to changing rainfall patterns.
Area of Science:
- Hydrology
- Climate Science
- Machine Learning Applications
Background:
- Evaporative loss of interception (Ei) is the initial process during rainfall.
- Its contribution to large-scale surface water balance remains underexplored.
- Understanding Ei is crucial for accurate hydrological modeling.
Purpose of the Study:
- To develop a method for inferring Ei from flux tower data.
- To quantify global Ei and its trends from 2000-2020.
- To investigate the drivers of Ei changes, focusing on rainfall characteristics.
Main Methods:
- Utilized physics-informed hybrid machine learning models.
- Trained models on flux tower evapotranspiration data under wet versus dry conditions.
- Forced models with satellite and reanalysis data for global estimation.
Main Results:
- Global average Ei is 84.1 ± 1.8 mm/year, representing 8.6 ± 0.2% of total rainfall.
- Rainfall frequency and intensity were identified as key regulators of Ei.
- Global Ei and its fraction of precipitation (Ei/P) declined by 4.9% and 6.7% respectively since 2000 due to less frequent, more intense rain.
Conclusions:
- The study provides the first observationally constrained global estimate of Ei.
- Changing rainfall patterns (less frequent, more intense) are decreasing Ei globally.
- This shift favors soil moisture and runoff but increases flood risks.
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