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2021-05-21

修改日期:

2021-10-23

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利用MODIS多通道反照率产品估算OCO-2氧气A吸收带陆表反照率的方法研究
杨洁, 李四维, 王庆鑫
武汉大学
摘要:

在基于OCO-2卫星氧气A吸收带观测的云反演中,陆表反射是重要的干扰因素,其强度主要由陆表反照率决定。然而,目前尚无卫星产品能提供OCO-2云反演所需的氧气A吸收带陆表反照率,为此本文提出基于MODIS多通道黑空/白空反照率的OCO-2氧气A吸收带陆表反照率估算方法。该方法顾及地表覆盖类型对波段间转换陆表反照率的影响,在不同时间和不同空间上测试的相关系数均超过0.93,均方根误差为0.026。其中,MODIS反照率数据的质量是决定多通道模型转换精度的最重要因素。当输入最佳质量的MODIS反照率时,OCO-2氧气A吸收带陆表反照率估值的均方根误差略优于0.02,随着MODIS反照率数据质量的下降,估值的均方根误差逐渐增大至超过0.05。

A method for estimating the land surface albedo of OCO-2 oxygen A-band based on MODIS/MCD43C3
Abstract:

The land surface reflection depends largely on the land surface albedo and interferes with retrieving the cloud geometrical thickness from the OCO-2 oxygen A-band observations due to its second-strongest reflection after the cloud. However, no product can provide the land surface albedo of the OCO-2 oxygen A-band required for the retrieval. Therefore, the accurate estimation of the land surface albedo is necessary and beneficial to the retrieval quality. In this study, we proposed an idea of estimating the land surface albedo in the oxygen A-band from the multi-channel black/white albedos from MODIS/MCD43C3 products. Although the estimation (MODIS → OCO-2) is land-cover-type-related, the comparison based on the Shannon entropy proved that the multi-channel albedo data contains the type information and sufficient to achieve the same accuracy as the land-cover-type-involved estimation. In addition, we implement the estimation model by BP neural network, and the accuracy is consistent with that of the analysis based on the Shannon entropy. We verified the multi-channel-based estimation model by the tests in different times and different spaces whose coefficients of determination were all over 0.9 and whose root-mean-squared errors were 0.026. In addition, the multi-channel-based model was always superior to the single-channel linear model on all land cover types, whether applied to the best performing type of the barren or sparsely vegetated, or the worse performing type of the snow and ice. The quality of the MODIS albedo data is the most important for the accuracy of estimation. The root-mean-squared error with the best inputs was slightly better than 0.02 and increased to more than 0.05 as the quality of the inputs decreased. The method of estimating the land surface albedo in the OCO-2 oxygen A-band from MODIS multi-channel black/white albedo data is feasible and can resist disturbance caused by unknown land cover type. The estimation accuracy depends mainly on the quality of the input MODIS albedo data.

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