首页 >  2019, Vol. 23, Issue (5) : 924-934

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DOI:

10.11834/jrs.20198033

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2018-01-24

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基于葵花-8卫星大气产品的地表下行短波辐射计算
1.中国科学院遥感与数字地球研究所 遥感科学国家重点实验室, 北京 100101;2.中国科学院大学 资源与环境学院, 北京 100049;3.内蒙古师范大学 地理科学学院, 呼和浩特 010022;4.中国矿业大学 环境与测绘学院, 徐州 221116;5.中国科学院大学 电子电气与通信工程学院, 北京 100049
摘要:

地表下行短波辐射DSSR(Downward Surface Shortwave Radiation)的准确估算在气候变化研究和地表太阳能估算等领域具有重要作用。新一代静止气象卫星葵花-8(Himawari-8)具有高达10 min的对地观测能力,为DSSR近实时估算提供了新机遇。然而,日本宇宙航空研究开发机构(JAXA)对外公开的葵花-8辐射产品中,没有将其反演的云、气溶胶产品作为DSSR的输入参数,从而没有形成一整套的DSSR估算算法流程,缺乏产品输出的一致性。大气中的云、气溶胶是DSSR的重要影响因子,本文重点考虑云、气溶胶对太阳辐射的影响,基于大气辐射传输模式RSTAR构建了DSSR查找表,开发了DSSR的快速计算方法,进而将JAXA葵花-8二级云、气溶胶产品(光学厚度,粒子有效半径等)作为快速化计算方法的输入参量,计算得到了DSSR。通过与JAXA葵花-8二级DSSR产品(JAXA DSSR)对比,发现两者具有很好的空间一致性。为了进一步评价本文的DSSR计算精度,分别选取了陆地(Yonsei)和海洋(0n_165e)的观测数据验证了2016年4、7、10和12月本文计算的DSSR和同时期的JAXA DSSR产品,验证结果显示两者的DSSR在两个观测站点均具有非常高的相关性(全天空、晴空和云天条件下的相关系数R均大于0.88)。在两个站点云天条件下的验证结果中,考虑了云相态并在冰云模型中使用了非球形冰晶粒子(六棱柱)来计算DSSR,获得了比JAXA DSSR更小的偏差。本文提出的快速化计算方法能快速准确地计算DSSR,可为计算地表辐射收支等研究提供重要数据支撑。

Estimation of downward surface shortwave radiation from Himawari-8 atmospheric products
Abstract:

Downward Surface Shortwave Radiation (DSSR) estimated from satellite measurements is crucial in climate change study and clean energy applications. The Advanced Himawari Imager (AHI) onboard the new generation geostationary satellite Himawari-8 provides an unprecedented opportunity for the near real-time estimation of DSSR, with a spatial resolution of 5 km and a temporal resolution of 10 min over the full disk regions. To meet the requirements of fast and accurate estimation of DSSR from Himawari-8, this study proposed a Look-Up Table (LUT) method to estimate the DSSR from Himawari-8/AHI level 2 (L2) atmospheric products.
We first investigate the sensitivities of DSSR to solar geometry (solar zenith angle), atmosphere conditions (aerosol optical depth, cloud optical depth, and cloud effective radius), and surface condition (surface albedo) basing on the atmospheric radiative transfer model. Then, LUTs for clear and cloudy skies are generated based on the sensitivity results. Finally, the DSSR is estimated with the inputs of Himawari-8 L2 aerosol and cloud products released by JAXA on the basis of LUTs previously created.
As an experiment, DSSR results are estimated using our algorithm at 02:00 UTC on April 1, 2016 and compared with the JAXA Himawari-8 L2 DSSR product. The comparison shows that our DSSR estimates are consistent with the operational DSSR results over the full disk regions. To further validate our DSSR estimates, we compare our results and the operational DSSR results with ground-based measurements at Yonsei site (land) and 0n_165e site (sea) in April, July, October, and December 2016. The correlation coefficients (R) derived from ground measurements and these two DSSR results are larger than 0.88 for all types of sky conditions. With the scattering properties of non-spherical (hexagon) ice cloud particles included, the biases of our DSSR estimates in the validation with ground measurements at two sites are lower than the operational DSSR results.
This study developed an LUT-based method to estimate DSSR with inputs of Himawari-8 L2 atmospheric products (including aerosol and cloud products, and other auxiliary data such as solar zenith angle in L1 product). The estimated DSSR was validated against both land and sea sites of ground observed DSSR, with RMSEs of 94.13 Wm−2, 62.92 Wm−2, and 110.60 Wm−2 for all types of sky conditions at Yonsei, and RMSEs of 123.86 Wm−2, 105.33 Wm−2 and 151.44 Wm−2 for all types of sky conditions at sea site 0n_165e. Furthermore, the correlation coefficients (R) of our DSSR estimation from the land and sea sites were greater than 0.88 for all sky conditions. These validation results suggested that our DSSR estimation with Himawari-8 atmospheric products works well and can thus be further used in land surface radiation budget research and solar energy application after improvements on the current algorithm.

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