Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data
文献类型：期刊论文
| 作者 | Lu, N (Lu, Ning)4; Tang, WJ (Tang, Wenjun)2,3; Qin, J (Qin, Jun)2; Yang, K (Yang, Kun)2,3; Liu, SM (Liu, Shaomin)1; Niu, XL (Niu, Xiaolei)2; Tang, WJ |
| 刊名 | ATMOSPHERIC CHEMISTRY AND PHYSICS
 |
| 出版日期 | 2016 |
| 卷号 | 16期号:4页码:2543-2557 |
| 关键词 | Photosynthetically Active Radiation Global Data Sets Neural-network Shortwave Radiation Optical-properties Satellite Data Irradiance China Algorithm Products |
| DOI | 10.5194/acp-16-2543-2016 |
| 文献子类 | Article |
| 英文摘要 | Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100Wm(-2) for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0Wm(-2) (or 3.5 %) and 98.5Wm(-2) (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8Wm(-2) (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2Wm(-2) (or 19.1 %) and 22.1Wm(-2) (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km. |
| 学科主题 | 自然地理学 |
| 语种 | 英语 |
| WOS记录号 | WOS:000372971500042 |
| 源URL | [http://ir.itpcas.ac.cn/handle/131C11/7870]  |
| 专题 | 青藏高原研究所_图书馆 |
| 通讯作者 | Tang, WJ |
| 作者单位 | 1.Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China 2.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing 100101, Peoples R China 3.Chinese Acad Sci, CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, N ,Tang, WJ ,Qin, J ,et al. Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2016,16(4):2543-2557. |
| APA | Lu, N .,Tang, WJ .,Qin, J .,Yang, K .,Liu, SM .,...&Tang, WJ.(2016).Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data.ATMOSPHERIC CHEMISTRY AND PHYSICS,16(4),2543-2557. |
| MLA | Lu, N ,et al."Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data".ATMOSPHERIC CHEMISTRY AND PHYSICS 16.4(2016):2543-2557. |
入库方式： OAI收割
来源：青藏高原研究所
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