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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Surface albedo is an essential parameter in many solar radiation applications. Although several models are available, it remains debatable whether they are applicable to other locations. Using long-term daily measurements of radiation acquired by observational networks in China, this study examined the applicability of six existing albedo models: Ineichen model (IeM), Gueymard model (GM), Dong model (DeM), Iziomon-Mayer model (IMM), Morton model (MM), and Zhou model (ZeM). The evaluation results of model performance through statistical analysis showed that among the available ground albedo models, ZeM had the best overall performance at 12 selected stations, IeM was shown to provide acceptable estimations for locations where albedo records are readily available. The statistical results of individual station have shownthat the number of input parameters is not the only key factor for determining the predictive performance of ground albedo models. In other words, a simple model has potential for accurate estimation of ground albedo with appropriate model parameters. Therefore, the simple two-parameter DeM was selected to re-calibrate with in-situ radiometric measurements, which can be adopted as a surrogate for ZeM to predict surface albedo in China.

Details

Title
Evaluation of Ground-Based Models for Estimating Surface Albedo with In-Situ Radiometric Measurements across China
Author
Chen, Gang 1   VIAFID ORCID Logo  ; Zhou, Mi 2 ; Gu, Shixiang 1 ; Chen, Jinming 1 ; Wu, Lei 1 

 Water Resources Research Center, Department of Planning, Yunnan Survey and Design Institute of Water Conservancy and Hydropower, Kunming 650021, China; [email protected] (S.G.); [email protected] (J.C.); [email protected] (L.W.) 
 State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; [email protected] 
First page
412
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
20734433
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2642338117
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.