Impact of radiation variations on temporal upscaling of instantaneous Solar-Induced Chlorophyll Fluorescence
Impact of radiation variations on temporal upscaling of instantaneous Solar-Induced Chlorophyll Fluorescence
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DOI：
10.1016/j.agrformet.2022.109197
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发表时间：
2022-12
影响因子：
6.2
通讯作者：
Rui Cheng;P. Köhler;C. Frankenberg
中科院分区：
文献类型：
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作者：
Rui Cheng;P. Köhler;C. Frankenberg
太阳诱导的叶绿素荧光(SIF)已越来越多地被用作衡量植被生产力的新指标。几个星载仪器可以在不同的天桥时间反演SIF，这使得解释变得复杂，因为SIF是由采集时间吸收的光合作用有效辐射(PAR)驱动的。为了便于传感器之间的比较，基于卫星的SIF被提升为具有日长修正系数(DC)的日平均值。在传统的DC计算中，一天的光强是用太阳天顶角(SZA)的余弦来近似的，忽略了大气消光和地形影响的变化。在这里，我们使用再分析PAR数据进行DC计算，以分别评估大气消光和漫射辐射的影响。我们发现，对于平坦的表面，简单的SZA方法是一个可靠的近似，其中大气对DC的总体影响不到10%，因为直接PAR和漫射PAR的大的单独影响部分地相互补偿。在更长的时间尺度上，由于卫星数据的云过滤，可能存在采样(晴朗的天空)偏差。我们发现，在亚马逊地区，真实的月平均面值可能比有云过滤的日子低25%，这可能会导致同样顺序的季节性SIF偏差。在一天中影响平价的另一个因素是地形。对于复杂地形，DC表达式中的直射光需要对曲面坡度进行校正。例如，在美国加利福尼亚州的圣加布里埃尔山脉，对于强烈倾斜的表面，修改后的DC变化高达500%。这一修改对于空间分辨率较高的卫星仪器尤其重要，因为这些仪器的表面坡度不是平均的，可能会对反射率和SIF产生重大影响。总体而言，我们改进的DC校正和平均策略可以帮助卫星SIF解释以及在广泛的时空尺度和天桥时间范围内的相互比较。
Solar-Induced Chlorophyll Fluorescence (SIF) has been increasingly used as a novel proxy for vegetation productivity. Several space-borne instruments can retrieve SIF at varying overpass time, which complicates the interpretation as SIF is driven by absorbed Photosynthetically Active Radiation (PAR) at the acquisition time. To facilitate comparisons across sensors, satellite-based SIF is upscaled to daily averages with a length-of-day correction factor (DC). In conventional DC calculations, the light intensity over a day is approximated geometrically by the cosine of the Solar Zenith Angle (SZA), neglecting changes in atmospheric extinction and topographic effects. Here, we use reanalysis PAR data for DC calculations to evaluate the impact of atmospheric extinction and diffuse radiation individually. We find that the simple SZA approach is a reliable approximation for flat surfaces, where the overall atmospheric impact on DC is less than 10% as large individual effects on direct and diffuse PAR partially compensate each other. At longer time-scales, a sampling (clear sky) bias might exist due to cloud-filtering of satellite data. We find that in the Amazon the true monthly mean PAR can be 25% lower than the one for cloud-filtered days, potentially inducing seasonal SIF biases on the same order. An additional factor impacting PAR during a day is topography. For complex terrain, direct light in the DC expression requires a correction for surface slopes. For example in the San Gabriel Mountains, California, USA, the modified DC is changed by as much as 500% for strongly tilted surfaces. This modification is especially important for satellite instruments with fine spatial resolutions, where surface slopes are not averaged out and can have a substantial impact on reflectance and SIF. Overall, our refined DC-corrections and averaging strategy can help satellite SIF interpretation as well as intercomparisons over a wide range of spatio-temporal scales and overpass times.