Preprints
https://doi.org/10.5194/hess-2022-79
https://doi.org/10.5194/hess-2022-79
 
01 Apr 2022
01 Apr 2022
Status: this preprint is currently under review for the journal HESS.

SMPD: A soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation

Kunlong He1,2, Wei Zhao1, Luca Brocca3, and Pere Quintana-Seguí4 Kunlong He et al.
  • 1Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
  • 2School of Energy and Power Engineering, Xihua University, Chengdu 610039, Sichuan, China
  • 3Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
  • 4Ebro Observatory (OE), Ramon Llull University – CSIC, Roquetes, Spain

Abstract. As a key component in the water and energy cycle, precipitation with high resolution and accuracy is of great significance for hydrological, meteorological, and ecological studies. However, current satellite-based precipitation products have a coarse spatial resolution (from 10 to 50 km) not meeting the needs of several applications (e.g., flash floods and landslides). The implementation of spatial downscaling methods can be a suitable approach to overcome this shortcoming. In this study, we developed a Soil Moisture-based Precipitation Downscaling (SMPD) method for spatially downscaling the Integrated Multi-satellitE Retrievals for GPM (IMERG) V06B daily precipitation product over a complex topographic and climatic area in southwestern Europe (Iberia Peninsula), in the period 2016–2018. By exploiting the soil water balance equation, high-resolution surface soil moisture (SSM) and Normalized Difference Vegetation Index (NDVI) products were used as auxiliary variables. The spatial resolution of the IMERG daily precipitation product was downscaled from 10 km to 1 km. An evaluation using 1027 rain gauge stations highlighted the good performance of the downscaled 1 km IMERG product compared to the original 10 km product, with a correlation coefficient of 0.61, root mean square error (RMSE) of 4.83 mm and a relative bias of 5 %. Meanwhile, the 1 km downscaled results can also capture the typical temporal and spatial variation behaviours of precipitation in the study area during dry and wet seasons. Overall, the SMPD method greatly improves the spatial details of the original 10 km IMERG product with also a slight enhancement of the accuracy. It shows good potential to be applied for the development of high quality and high-resolution precipitation products in any region of interest.

Kunlong He et al.

Status: open (until 12 Jun 2022)

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Kunlong He et al.

Kunlong He et al.

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Short summary
In this study, we developed a Soil Moisture-based Precipitation Downscaling (SMPD) method for spatially downscaling the GPM daily precipitation product by exploiting the connection between surface soil moisture and precipitation according to the soil water balance equation. Based on this method, the spatial resolution of the daily precipitation product was downscaled 1 km and the SMPD method shows good potentials for the development of high quality and high-resolution precipitation products.