Topographic radiation modeling and spatial scaling of clear-sky land surface longwave radiation over rugged terrain
Topographic radiation modeling and spatial scaling of clear-sky land surface longwave radiation over rugged terrain
复制标题
崎岖地形上晴空地表长波辐射的地形辐射建模和空间缩放
DOI：
10.1016/j.rse.2015.10.026
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发表时间：
2016
影响因子：
13.5
通讯作者：
Chen Ling
中科院分区：
文献类型：
--
作者：
Yan Guangjian;Wang Tianxing;Jiao Zhonghu;Mu Xihan;Zhao Jing;Chen Ling
长波辐射(5-100亿μm)是地球辐射收支的关键组成部分。现有的大多数基于卫星的反演算法只适用于平坦的表面，没有考虑地形的影响。这会导致严重的错误。同时，遥感数据的空间分辨率是固定的，很难将卫星产生的长波辐射与不同尺度上运行的不同陆地模型联系起来。这些不足导致迫切需要对长波辐射进行地形建模和空间尺度研究。本文提出了一个长波地形辐射模式(LWTRM)，它量化了地形崎岖地区所有可能的辐射影响因素。基于人工神经网络(ANN)和辐射传输模拟，提出了一种从MODIS数据中同时提取长波辐射多分量的混合方法。然后，通过耦合ANN输出和LWTRM，得到地形校正的长波辐射。在此基础上，提出了长波辐射的一般放大策略。结果表明：(1)LWTRM和提升尺度策略都是有效的，并且在崎岖的地区效果良好；(2)基于人工神经网络的方法可以产生更高精度的长波辐射(RMSE<；=23W/m2，BIAS<；=9.0W/m2)。更重要的是，它可以同时以一致的方式获得长波辐射的多个分量；(3)在山区，如果忽略地形影响，无论是从空间分布还是从具体数值上都无法准确表征辐射，例如，长波净通量的诱导误差可达100W/m2；(4)在选定的研究区域内，地形影响在大约5公里的空间尺度下是不能忽略的。
Longwave radiation (5–100 μm) is a critical component of the Earth's radiation budget. Most of the existing satellite-based retrieval algorithms are valid only for flat surfaces without accounting for topographic effects. This causes significant errors. Meanwhile, the fixed spatial resolution of remote sensing data makes it difficult to link the satellite-derived longwave radiation to different land models running on various scales. These deficiencies result in an urgent need for topographic modeling and spatial scaling studies of longwave radiation. In this paper, a longwave topographic radiation model (LWTRM) is proposed that quantifies all possible radiation-affecting factors over rugged terrain. For driving the LWTRM, a hybrid method for simultaneously deriving multiple components of longwave radiation from MODIS data is suggested based on artificial neuron networks (ANN) and the radiative transfer simulation. Topographically corrected longwave radiation is then derived by coupling the ANN outputs and LWTRM. Based on this, a general upscaling strategy for longwave radiation is presented. The results demonstrate that: (1) both the proposed LWTRM and the upscaling strategy are rather effective and work well over rugged areas; (2) the ANN-based retrieval method can produce longwave radiation with better accuracy(RMSE < 23 W/m2, bias < 9 W/m2). More importantly, it can simultaneously derive multiple components of longwave radiation in a consistent manner; (3) over mountainous areas, the radiation cannot be accurately characterized in terms of either spatial distribution or specific values if topographic effects are neglected, for instance, the induced error can reach up to 100 W/m2for the longwave net flux; and (4) the topographic effects cannot be ignored below spatial scale of approximately 5 km in the selected study area.
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5.2
作者：
R. Dubayah;V. V. Katwijk-V.
通讯作者：
R. Dubayah;V. V. Katwijk-V.
影响因子：
5.2
作者：
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