TY - JOUR
T1 - SMPD
T2 - A soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation
AU - He, Kunlong
AU - Zhao, Wei
AU - Brocca, Luca
AU - Quintana-Seguí, Pere
N1 - Funding Information:
National Natural Science Foundation of China (grant 42071349-42222109)
Funding Information:
This research has been supported by the National Natural Science Foundation of China (grant nos. 42071349 and 42222109), and the Sichuan Province Science and Technology Support Program (grant no. 2020JDJQ0003).
Funding Information:
This research was partially funded as part of the National Natural Science Foundation of China (grant nos. 42071349 and 42222109), Sichuan Science and Technology Program (Grant No. 2020JDJQ0003), the West Light Foundation of the Chinese Academy of Sciences, and the project PRIMA PCI2020-112043 funded by MCIN/AEI/10.13039/501100011033. We thank the Spanish State Meteorological Agency (AEMET) for sharing daily precipitation data with this project.
Publisher Copyright:
© 2023 Copernicus GmbH. All rights reserved.
PY - 2023/1/10
Y1 - 2023/1/10
N2 - As a key component in the water and energy cycle, estimates of 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 50ĝ€¯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 multisatellite retrievals for global precipitation measurement (IMERG) V06B daily precipitation product over a complex topographic and climatic area in southwestern Europe (Iberian 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 to 1ĝ€¯km. An evaluation using 1027 rain gauge stations highlighted the good performance of the downscaled 1ĝ€¯km IMERG product compared to the original 10ĝ€¯km product, with a correlation coefficient of 0.61, root mean square error (RMSE) of 4.83ĝ€¯mm and a relative bias of 5ĝ€¯%. Meanwhile, the 1ĝ€¯km downscaled results can also capture the typical temporal and spatial variation behaviors of precipitation in the study area during dry and wet seasons. Overall, the SMPD method greatly improves the spatial details of the original 10ĝ€¯km IMERG product also with a slight enhancement of accuracy. It shows good potential to be applied for the development of high-quality and high-resolution precipitation products in any region of interest.
AB - As a key component in the water and energy cycle, estimates of 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 50ĝ€¯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 multisatellite retrievals for global precipitation measurement (IMERG) V06B daily precipitation product over a complex topographic and climatic area in southwestern Europe (Iberian 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 to 1ĝ€¯km. An evaluation using 1027 rain gauge stations highlighted the good performance of the downscaled 1ĝ€¯km IMERG product compared to the original 10ĝ€¯km product, with a correlation coefficient of 0.61, root mean square error (RMSE) of 4.83ĝ€¯mm and a relative bias of 5ĝ€¯%. Meanwhile, the 1ĝ€¯km downscaled results can also capture the typical temporal and spatial variation behaviors of precipitation in the study area during dry and wet seasons. Overall, the SMPD method greatly improves the spatial details of the original 10ĝ€¯km IMERG product also with a slight enhancement of accuracy. It shows good potential to be applied for the development of high-quality and high-resolution precipitation products in any region of interest.
UR - http://www.scopus.com/inward/record.url?scp=85147330644&partnerID=8YFLogxK
U2 - 10.5194/hess-27-169-2023
DO - 10.5194/hess-27-169-2023
M3 - Article
AN - SCOPUS:85147330644
SN - 1027-5606
VL - 27
SP - 169
EP - 190
JO - Hydrology and Earth System Sciences
JF - Hydrology and Earth System Sciences
IS - 1
ER -