VODCA2GPP - A new global, long-term (1988-2020) GPP dataset from microwave remote sensing

Benjamin Wild
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引用次数: 2

Abstract

Abstract. Long-term global monitoring of terrestrial Gross Primary Production (GPP) is crucial for assessing ecosystem response to global climate change. In recent years and decades, great advances in estimating GPP on a global level have been made and many global GPP datasets have been published. These global data records are either based on observations from optical remote sensing, are upscaled from in situ measurements, or rely on process-based models. The different estimation approaches are well established within the scientific community but also exhibit significant discrepancies among each other. Here, we introduce the new VODCA2GPP dataset, which utilizes microwave remote sensing estimates of Vegetation Optical Depth (VOD) to estimate GPP on a global scale. VODCA2GPP is able to complement existing products with long-term GPP estimates covering the period 1988–2020. VODCA2GPP applies a previously developed carbon sink-driven approach (Teubner et al., 2019, 2021) to estimate GPP from the Vegetation Optical Depth Climate Archive (Zotta et al., in prep.; Moesinger et al., 2020), which merges VOD observations from multiple sensors into one long-running, coherent data record. VODCA2GPP was trained and evaluated against FLUXNET in situ observations of GPP and assessed against largely independent state-of-the art GPP datasets (MODIS GPP, FLUXCOM GPP, and GPP estimates from the TRENDY-v7 model ensemble). These assessments show that VODCA2GPP exhibits very similar spatial patterns compared to existing GPP datasets across all biomes but with a consistent positive bias. In terms of temporal dynamics, a high agreement was found for regions outside the humid tropics, with median correlations around 0.75. Concerning anomalies from the long-term climatology, VODCA2GPP correlates well with MODIS and TRENDY-v7 GPP (Pearson’s r: 0.53 and 0.61) but less with FLUXCOM GPP (Pearson’s r: 0.29). A trend analysis for the period 1988–2019 did not exhibit a significant trend in VODCA2GPP on a global scale but rather suggests regionally differing long-term changes in GPP. Significant similar increases of global GPP that were found for VODCA2GPP, MODIS GPP, and the TRENDY-v7 ensemble for the shorter overlapping observation period (2003–2015) supports the theory of elevated CO2 uptake potentially induced by increased atmospheric CO2 concentrations and the associated rising temperatures. The VODCA2GPP dataset is available at TU Data ( https://doi.org/10.48436/1k7aj-bdz35 ; Wild et al., 2021).
VODCA2GPP -一个新的全球长期(1988-2020)微波遥感GPP数据集
摘要陆地初级生产总值(GPP)的长期全球监测对于评估生态系统对全球气候变化的响应至关重要。近年来和几十年来,在全球水平估算GPP方面取得了很大进展,并发表了许多全球GPP数据集。这些全球数据记录要么是基于光学遥感观测,要么是根据原位测量放大的,要么依赖基于过程的模型。不同的估计方法在科学界得到了很好的确立,但彼此之间也表现出显著的差异。在此,我们介绍了新的VODCA2GPP数据集,该数据集利用微波遥感估计植被光学深度(VOD)来估计全球范围内的GPP。VODCA2GPP能够以涵盖1988-2020年期间的长期GPP估算来补充现有产品。VODCA2GPP应用先前开发的碳汇驱动方法(Teubner等人,2019年,2021年)从植被光学深度气候档案(Zotta等人,准备;Moesinger et al., 2020),该方法将来自多个传感器的VOD观测结果合并为一个长期运行的连贯数据记录。根据FLUXNET对GPP的现场观测对VODCA2GPP进行了训练和评估,并根据基本独立的最先进的GPP数据集(MODIS GPP、FLUXCOM GPP和TRENDY-v7模型集合估计的GPP)进行了评估。这些评估表明,与所有生物群系的现有GPP数据集相比,VODCA2GPP显示出非常相似的空间格局,但存在一致的正偏差。就时间动态而言,在湿润热带以外的地区发现了高度一致性,中位数相关性约为0.75。关于长期气候学异常,VODCA2GPP与MODIS和TRENDY-v7 GPP (Pearson’s r: 0.53和0.61)的相关性较好,但与FLUXCOM GPP的相关性较差(Pearson’s r: 0.29)。1988-2019年期间的趋势分析并未显示出全球范围内VODCA2GPP的显著趋势,而是表明GPP的区域差异长期变化。在较短的重叠观测期内(2003-2015年),在VODCA2GPP、MODIS GPP和TRENDY-v7集合中发现的全球GPP显著增加支持了二氧化碳吸收量增加可能是由大气二氧化碳浓度增加和相关温度上升引起的理论。VODCA2GPP数据集可在TU Data (https://doi.org/10.48436/1k7aj-bdz35;Wild et al., 2021)。
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