Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data
Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data
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利用结合 MODIS 和 MTSAT 数据得出的云参数反演高分辨率表面太阳辐射
DOI：
10.5194/acp-16-2543-2016
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发表时间：
2015-12
影响因子：
6.3
通讯作者：
Niu, Xiaolei
中科院分区：
文献类型：
--
作者：
Yang, Kun;Liu, Shaomin;Lu, Ning;Niu, Xiaolei
抽象。云参数（云掩模、有效粒子半径和液态/冰水路径）是估算地面太阳辐射（SSR）的重要输入。这些参数可以从中分辨率成像光谱仪获得高精度，但它们的时间分辨率太低，无法获得高时间分辨率的SSR反演。为了获得逐时云参数，人工神经网络（ANN）在这项研究中应用，以直接构建一个功能之间的关系，MODIS云产品和多功能运输卫星（MTSAT）地球同步卫星信号。此外，一个有效的参数化模式，SSR反演，驱动与MODIS大气和陆地产品时，其均方根误差（RMSE）约为100 W m-2的44个基线地面辐射网络（BSRN）站。一旦云参数和其他信息（如气溶胶，可降水量，臭氧）的估计输入到模式中，我们可以得到高时空分辨率的SSR。反演的SSR首次评估在中国海河流域的三个实验站的逐时辐射数据。每小时SSR估计的平均偏差误差（MBE）和RMSE分别为12.0 W m−2（或3.5%）和98.5 W m−2（或28.9%）。利用中国气象局（CMA）90个台站的日辐射资料对反演的SSR进行了评价。MBE为9.8 W m−2（或5.4%）;日和月平均SSR估计的RMSE分别为34.2 W m−2（或19.1%）和22.1 W m−2（或12.3%）。的精度是相当的，甚至高于其他两个辐射产品（玻璃和ISCCP-FD），本方法是更有效的计算，可以产生每小时SSR数据的空间分辨率为5公里。
Abstract. 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 100 W m−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 12.0 W m−2 (or 3.5 %) and 98.5 W m−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 9.8 W m−2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m−2 (or 19.1 %) and 22.1 W m−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.
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影响因子：
13.5
作者：
P. Wang;M. Sneep;J. Veefkind;P. Stammes;P. Levelt
通讯作者：
P. Wang;M. Sneep;J. Veefkind;P. Stammes;P. Levelt
影响因子：
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作者：
Jianping Huang;P. Minnis;B. Lin;Y. Yi;M. Khaiyer;R. Arduini;Alice Fan;G. Mace
通讯作者：
Jianping Huang;P. Minnis;B. Lin;Y. Yi;M. Khaiyer;R. Arduini;Alice Fan;G. Mace
一种简单有效的算法，用于根据对地静止卫星数据估算每日全球太阳辐射
影响因子：
9
作者：
Ning Lu;Jun Qin;Kun Yang;Jiulin Sun
通讯作者：
Jiulin Sun
影响因子：
--
作者：
N. Lu;Ronggao Liu;Jiyuan Liu;S. Liang
通讯作者：
N. Lu;Ronggao Liu;Jiyuan Liu;S. Liang
影响因子：
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作者：
Zhian Sun;Jing-miao Liu;X. Zeng;H. Liang
通讯作者：
Zhian Sun;Jing-miao Liu;X. Zeng;H. Liang