Estimation of Downwelling Surface Longwave Radiation with the Combination of Parameterization and Artificial Neural Network from Remotely Sensed Data for Cloudy Sky Conditions
文献类型：期刊论文
| 作者 | Jiang, Yun1,4; Tang, Bo-Hui1,3; Zhao, Yanhong2 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2022-06-01 |
| 卷号 | 14期号:11页码:16 |
| 关键词 | downwelling surface longwave radiation GA-ANN MODIS ERA5 cloudy sky |
| DOI | 10.3390/rs14112716 |
| 通讯作者 | Tang, Bo-Hui(tangbh@kust.edu.cn) |
| 英文摘要 | This work proposes a new method for estimating downwelling surface longwave radiation (DSLR) under cloudy-sky conditions based on a parameterization method and a genetic algorithm-artificial neural network (GA-ANN) algorithm. The new method establishes a GA-ANN model based on simulated data, and then combines MODIS satellite data and ERA5 reanalysis data to estimate the DSLR. According to the validation results of the field sites, the bias and RMSE are -9.18 and 34.88 W/m(2), respectively. Compared with the existing research, the new method can achieve reasonable accuracy. Parameter analysis using independently simulated data shows that the near-surface air temperature (T-a) and cloud base height (CBH) have an important influence on DSLR estimation under cloudy-sky conditions. With an increase in CBH, DSLR gradually decreases; however, with an increase in T-a, DSLR shows a trend of gradual increase. When estimating DSLR under cloudy-sky conditions, under the influence of clouds, except for cirrus, the change in DSLRs with CBH and T-a is greater than 20 W/m(2). |
| WOS关键词 | CLEAR-SKY ; DOWNWARD RADIATION ; WAVE-RADIATION ; EDDY-COVARIANCE ; SATELLITE DATA ; MODIS ; IRRADIANCE ; SKIES ; FLUX |
| 资助项目 | National Natural Science Foundation of China[41871244] ; Platform Construction Project of High-Level Talent in KUST |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000808741300001 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China ; Platform Construction Project of High-Level Talent in KUST |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/179810]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tang, Bo-Hui |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.China Univ Min & Technol Beijing, Fac Earth Sci & Mapping Engn, Beijing 100083, Peoples R China 3.Kunming Univ Sci & Technol, Fac Land Resource Engn, Kunming 650093, Yunnan, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Jiang, Yun,Tang, Bo-Hui,Zhao, Yanhong. Estimation of Downwelling Surface Longwave Radiation with the Combination of Parameterization and Artificial Neural Network from Remotely Sensed Data for Cloudy Sky Conditions[J]. REMOTE SENSING,2022,14(11):16. |
| APA | Jiang, Yun,Tang, Bo-Hui,&Zhao, Yanhong.(2022).Estimation of Downwelling Surface Longwave Radiation with the Combination of Parameterization and Artificial Neural Network from Remotely Sensed Data for Cloudy Sky Conditions.REMOTE SENSING,14(11),16. |
| MLA | Jiang, Yun,et al."Estimation of Downwelling Surface Longwave Radiation with the Combination of Parameterization and Artificial Neural Network from Remotely Sensed Data for Cloudy Sky Conditions".REMOTE SENSING 14.11(2022):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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