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TCSIF: a Temporally Consistent Global Global Ozone Monitoring Experiment-2A (GOME-2A) Solar-Induced Chlorophyll Fluorescence Dataset with the Correction of Sensor Degradation

EARTH SYSTEM SCIENCE DATA(2024)

International Research Center of Big Data for Sustainable Development Goals

Cited 0|Views9
Abstract
Satellite-based solar-induced chlorophyll fluorescence (SIF) serves as a valuable proxy for monitoring the photosynthesis of vegetation globally. The Global Ozone Monitoring Experiment-2A (GOME-2A) SIF product has gained widespread popularity, particularly due to its extensive global coverage since 2007. However, serious temporal degradation of the GOME-2A instrument is a problem, and there is currently a lack of time-consistent GOME-2A SIF products that meet the needs of temporal trend analysis. In this paper, the GOME-2A instrument's temporal degradation was first calibrated using a pseudo-invariant method, which revealed 16.21 % degradation of the GOME-2A radiance at the near-infrared (NIR) band from 2007 to 2021. Based on the calibration results, the temporal degradation of the GOME-2A radiance spectra was successfully corrected by using a fitted quadratic polynomial function whose determination coefficient (R2) was 0.851. Next, a data-driven algorithm was applied for SIF retrieval at the 735–758 nm window. Also, a photosynthetically active radiation (PAR)-based upscaling model was employed to upscale the instantaneous clear-sky observations to monthly average values to compensate for the changes in cloud conditions and atmospheric scattering. Accordingly, a global temporally consistent GOME-2A SIF dataset (TCSIF) for 2007 to 2021 with the correction of temporal degradation was successfully generated, and the spatiotemporal pattern of global SIF was then investigated. Corresponding trend maps of the global temporally consistent GOME-2A SIF showed that 62.91 % of vegetated regions underwent an increase in SIF, and the global annual averaged SIF exhibited a trend of increasing by 0.70 % yr−1 during the 2007–2021 period. The TCSIF dataset is available at https://doi.org/10.5281/zenodo.8242928 (Zou et al., 2023).
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要点】:本文提出了一种生成时间一致性GOME-2A太阳能诱导叶绿素荧光(SIF)数据集的方法,通过校正传感器退化问题,实现了2007至2021年全球范围内的高质量SIF监测。

方法】:采用伪不变方法校准GOME-2A仪器的时间退化,利用拟合的二次多项式函数校正辐射光谱退化,并通过数据驱动算法进行SIF的检索,以及使用PAR基础的放大模型将瞬时观测值扩展到月平均值。

实验】:通过上述方法生成了TCSIF数据集,并分析了2007至2021年全球SIF的时空模式,结果显示62.91%的植被区域SIF增加,全球年均SIF呈现每年0.70%的增长趋势。数据集可通过https://doi.org/10.5281/zenodo.8242928获取。