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Satellite-derived quantification of the diurnal and annual dynamics of land surface temperature
Remote Sensing of Environment ( IF 11.1 ) Pub Date : 2021-08-14 , DOI: 10.1016/j.rse.2021.112642
Panagiotis Sismanidis 1, 2 , Benjamin Bechtel 2 , Iphigenia Keramitsoglou 1 , Frank Göttsche 3 , Chris T. Kiranoudis 1, 4
Affiliation  

The diurnal and annual cycles of Earth drive the land surface temperature (LST) variations in space and time but their combined effects are conveyed differently from place to place as a function of climate, local weather conditions, and surface characteristics. Fitting a model of the diurnal or annual LST cycle (DTC and ATC, respectively) to satellite data yields several parameters that summarize the thermal dynamics of each pixel. These parameters are distinct for each place and reveal how the ATC and DTC differ between pixels. Currently, due to the lack of LST with high spatial and temporal resolution, it is impossible to characterize both cycles at kilometer or sub-kilometer scale. This work addresses this problem and presents a method for simultaneously quantifying the annual and diurnal LST dynamics at kilometer scale. The proposed method is based on Annual Cycle Parameters (ACP) retrieved from geostationary satellite data for every 30 min between 00:00 and 23:30 local time and uses statistical downscaling to enhance their coarse spatial resolution. We apply our method to continental Europe for the period 2009–2013 and validate it using independent ACP retrieved from satellite and in-situ LST. Our results reveal how the climate and surface conditions influence the shape of the ACP diurnal profiles over Europe and illustrate for the first time the excellent agreement between satellite-derived ACP and ACP derived from in-situ LST. Even though our method is limited by the spatial coverage of the geostationary data, it provides a novel way for describing Earth's thermal response to solar heating.



中文翻译:

地表温度日变化和年变化的卫星衍生量化

地球的昼夜循环和年循环驱动着地表温度 (LST) 在空间和时间上的变化,但它们的综合影响因气候、当地天气条件和地表特征的不同而因地而异。将昼夜或年度 LST 循环(分别为 DTC 和 ATC)的模型拟合到卫星数据会产生几个参数,这些参数总结了每个像素的热动态。这些参数对于每个地方都是不同的,并揭示了像素之间的 ATC 和 DTC 有何不同。目前,由于缺乏具有高空间和时间分辨率的 LST,不可能在公里或亚公里尺度上表征这两个周期。这项工作解决了这个问题,并提出了一种在公里尺度上同时量化年度和昼夜 LST 动态的方法。所提出的方法基于从当地时间 00:00 到 23:30 之间每 30 分钟从地球静止卫星数据中检索到的年度周期参数 (ACP),并使用统计降尺度来提高其粗略的空间分辨率。我们在 2009-2013 年期间将我们的方法应用于欧洲大陆,并使用从卫星和原位 LST 检索到的独立 ACP 对其进行验证。我们的研究结果揭示了气候和地表条件如何影响欧洲 ACP 昼夜剖面的形状,并首次说明卫星衍生的 ACP 与原位 LST 衍生的 ACP 之间的极好一致性。尽管我们的方法受到地球静止数据空间覆盖范围的限制,但它提供了一种描述地球对太阳加热的热响应的新方法。

更新日期:2021-08-15
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