{"title":"CHiRAD: A high-resolution daily net radiation dataset for China generated using meteorological and albedo data","authors":"Ye Jing , Peng Bai , Zelong Yang","doi":"10.1016/j.jhydrol.2025.132854","DOIUrl":null,"url":null,"abstract":"<div><div>Surface net radiation (R<sub>n</sub>) is a key variable for studying the energy available at the Earth’s surface, essential in atmospheric, water, and carbon cycle research. Despite the existence of global R<sub>n</sub> products, they often encounter issues such as data gaps, low resolution, and significant uncertainty. In this study, we developed a high spatial resolution (0.05°×0.05°) daily R<sub>n</sub> dataset for China from 2000 to 2019 using routine meteorological data and remotely sensed albedo. To ensure the reliability of the dataset, we tested various net shortwave and longwave algorithms with ground-based measurements and selected an optimal combination to generate this dataset (hereafter named CHiRAD). Validation against R<sub>n</sub> observations from 43 flux towers across China demonstrated the remarkable accuracy of CHiRAD, with a Kling Gupta efficiency (KGE) of 0.81, a percentage of bias (Pbias) of 0.38 %, and a root mean square error (RMSE) of 37.10 W m<sup>−</sup>2. CHiRAD outperforms two commonly used R<sub>n</sub> products: ERA5-Land (KGE = 0.73, Pbias = -7.81 %, RMSE = 41.24 W m<sup>−2</sup>) and GLASS-AVHRR (KGE = 0.73, Pbias = 1.92 %, RMSE = 36.76 W m<sup>−2</sup>). This dataset, available at <span><span><u>https://doi.org/10.5281/zenodo.12605405</u></span><svg><path></path></svg></span>, offers valuable input for various land surface and hydrological models, with broad application in hydrology, climatology, ecology, and other related fields.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132854"},"PeriodicalIF":5.9000,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022169425001921","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
Surface net radiation (Rn) is a key variable for studying the energy available at the Earth’s surface, essential in atmospheric, water, and carbon cycle research. Despite the existence of global Rn products, they often encounter issues such as data gaps, low resolution, and significant uncertainty. In this study, we developed a high spatial resolution (0.05°×0.05°) daily Rn dataset for China from 2000 to 2019 using routine meteorological data and remotely sensed albedo. To ensure the reliability of the dataset, we tested various net shortwave and longwave algorithms with ground-based measurements and selected an optimal combination to generate this dataset (hereafter named CHiRAD). Validation against Rn observations from 43 flux towers across China demonstrated the remarkable accuracy of CHiRAD, with a Kling Gupta efficiency (KGE) of 0.81, a percentage of bias (Pbias) of 0.38 %, and a root mean square error (RMSE) of 37.10 W m−2. CHiRAD outperforms two commonly used Rn products: ERA5-Land (KGE = 0.73, Pbias = -7.81 %, RMSE = 41.24 W m−2) and GLASS-AVHRR (KGE = 0.73, Pbias = 1.92 %, RMSE = 36.76 W m−2). This dataset, available at https://doi.org/10.5281/zenodo.12605405, offers valuable input for various land surface and hydrological models, with broad application in hydrology, climatology, ecology, and other related fields.
期刊介绍:
The Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology and hydrogeology. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, hydraulics, agrohydrology, geomorphology, soil science, instrumentation and remote sensing, civil and environmental engineering are included. Social science perspectives on hydrological problems such as resource and ecological economics, environmental sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site.