Improvement in the Estimation of Daily Net Surface Radiation in China
Publication: Journal of Irrigation and Drainage Engineering
Volume 147, Issue 3
Abstract
Earth’s surface net radiation () governs sensitive and latent heat fluxes, plant photosynthesis, and the terrestrial carbon cycle. However, records are scarce in China. The accurate quantification of is therefore of great importance. The is the difference between net shortwave (incoming) and net longwave radiation (outgoing), and the Food and Agricultural Organization of the United Nations (FAO) 56 Penman-Monteith (FAO-56 PM) method has been widely used to estimate . However, site-specific calibrations of parameters are required for the FAO-56 PM method. Thereby, an improved estimation in China was done by (1) quantifying the spatial and temporal variations of surface albedo to better estimate net shortwave radiation and (2) recalibrating the parameters of FAO-56 PM method based on in situ observations to better estimate net longwave radiation. Results indicate that the monthly value of surface albedo over the course of a year is U-shaped, and the minimum value appears in the boreal growing season (April to September). The monthly surface albedo during the nongrowing season was best fit by a latitude-dependent quadratic function. By better accuracy in the estimation of net shortwave and longwave radiation, results at 31 validation stations indicated that the improved FAO-56 PM method enhanced the accuracy of estimated by 33% (the median Nash-Sutcliffe coefficient increased from 0.6 to 0.8) when compared to the default FAO-56 PM method. The improved method developed in this study has universal applicability in data-scarce regions in China and elsewhere, which is valuable for various practical applications including evapotranspiration simulation, hydrological modeling, and agricultural crop planning and management.
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Data Availability Statement
All data used during the study are available online in accordance with funder data retention policies. Solar radiation datasets related to this manuscript are hosted at the National Meteorological Information Center of the China Meteorological Administration and can be found at http://data.cma.cn/data/cdcdetail/dataCode/RADI_MUL_CHN_DAY.html.
Routine meteorological datasets related to this manuscript are also hosted at the National Meteorological Information Center of the China Meteorological Administration and can be found at http://data.cma.cn/data/cdcdetail/dataCode/SURF_CLI_CHN_MUL_DAY_V3.0.html. The code used in this study is available from the corresponding author upon request.
Acknowledgments
This work is financially supported by the National Key Research and Development Program of China (Grant Nos. 2016YFC0402706 and 2016YFC0402710); National Natural Science Foundation of China (Grant No. 51909057); Macau Science and Technology Development Fund (Grant No. 0045/2018/AFJ); and China Postdoctoral Science Foundation (Grant No. 2017M610292). We acknowledge Jorge Luis Peña-Arancibia and Manikanda Bharath Karuppasamy for the language proofreading. We also acknowledge the two anonymous reviewers,the associate editor, and the chief editor for their valuable comments.
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Journal of Irrigation and Drainage Engineering
Volume 147 • Issue 3 • March 2021
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© 2021 American Society of Civil Engineers.
History
Received: Sep 20, 2019
Accepted: Oct 12, 2020
Published online: Jan 8, 2021
Published in print: Mar 1, 2021
Discussion open until: Jun 8, 2021
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