Dataset Information

Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale.

ABSTRACT: Rainfall kinetic energy (RKE) constitutes one of the most critical factors that drive rainfall erosivity on surface soil. Direct measurements of RKE are limited, relying instead on the empirical relations between kinetic energy and rainfall intensity (KE-I relation), which have not been well regionalized for data-scarce regions. Here, we present the first global rainfall microphysics-based RKE (RKE_MPH) flux retrieved from radar reflectivity at different frequencies. The results suggest that RKE_MPH flux outperforms the RKE estimates derived from a widely used empirical KE-I relation (RKE_KE-I) validated using ground disdrometers. We found a potentially widespread underestimation of RKE_KE-I, which is especially prominent in some low-income countries with ~20% underestimation of RKE and the resultant rainfall erosivity. Given the evidence that these countries are subject to greater rainfall-induced soil erosion, these underestimations would mislead conservation practices for sustainable development of terrestrial ecosystems.

SUBMITTER: Dai Q

PROVIDER: S-EPMC10411884 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale.

Dai Qiang Q Zhu Jingxuan J Lv Guonian G Kalin Latif L Yao Yuanzhi Y Zhang Jun J Han Dawei D

Science advances 20230809 32

Rainfall kinetic energy (RKE) constitutes one of the most critical factors that drive rainfall erosivity on surface soil. Direct measurements of RKE are limited, relying instead on the empirical relations between kinetic energy and rainfall intensity (KE-I relation), which have not been well regionalized for data-scarce regions. Here, we present the first global rainfall microphysics-based RKE (RKEMPH) flux retrieved from radar reflectivity at different frequencies. The ...[more]

PMID: 37556540

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Dataset Information

Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale.

Publications

Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale.

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