Estimation of rainfall erosivity based on WRF-derived raindrop size distributions

Dai, Qiang; Zhu, Jingxuan; Zhang, Shuliang; Zhu, Shaonan; Han, Dawei; Lv, Guonian

doi:https://doi.org/10.5194/hess-24-5407-2020

Articles | Volume 24, issue 11

https://doi.org/10.5194/hess-24-5407-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-24-5407-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 11

Research article

|

17 Nov 2020

Research article |

| 17 Nov 2020

Estimation of rainfall erosivity based on WRF-derived raindrop size distributions

Qiang Dai, Jingxuan Zhu, Shuliang Zhang, Shaonan Zhu, Dawei Han, and Guonian Lv

Data sets

MIDAS UK Hourly Rainfall Data Met Office https://catalogue.ceda.ac.uk/uuid/bbd6916225e7475514e17fdbf11141c1

Chilbolton Facility for Atmospheric and Radio Research (CFARR) Disdrometer Data Science and Technology Facilities Council, Chilbolton Facility for Atmospheric and Radio Research, Natural Environment Research Council, and C. L. Wrench https://catalogue.ceda.ac.uk/uuid/aac5f8246987ea43a68e3396b530d23e

Short summary

Rainfall is a driving force that accounts for a large proportion of soil loss around the world. Most previous studies used a fixed rainfall–energy relationship to estimate rainfall energy, ignoring the spatial and temporal changes of raindrop microphysical processes. This study proposes a novel method for large-scale and long-term rainfall energy and rainfall erosivity investigations based on rainfall microphysical parameterization schemes in the Weather Research and Forecasting (WRF) model.