Inconsistencies of interannual variability and trends in long‐term satellite leaf area index products

Abstract

Understanding the long-term performance of global satellite leaf area index (LAI) products is important for global change research. However, few effort has been devoted to evaluating the long-term time series consistencies of LAI products. This study compared four long-term LAI products (GLASS, GLOBMAP, LAI3g, and TCDR) Accepted ArticleThis article is protected by copyright. All rights reserved. LAI3g an increasing trend. GEOV1, MERIS, and MODIS C6 also exhibited an increasing trend, but to a much smaller extent than that from LAI3g. During both periods, the R 2 of detrended anomalies between the four long-term LAI products were smaller than 0.4 for most regions. Interannual variabilities of the four long-term LAI products were considerably different over the two periods, and the differences followed the order GLASS > LAI3g > TCDR > GLOBMAP. Uncertainty variations quantified by a collocation error model followed the same order. Our results indicate that the four long-term LAI products were neither intraconsistent over time nor inter-consistent with each other. These inconsistencies may be due to NOAA satellite orbit changes and MODIS sensor degradation. Caution should be used in the interpretation of global changes derived from the four long-term LAI products.

An Overview of Global Leaf Area Index (LAI): Methods, Products, Validation, and Applications

“…Long‐term spatiotemporal patterns and the main strengths and weaknesses of each data set need to be identified and compared with modeling results. The AVHRR orbit change and sensor degradation are two important sources of inconsistency (Jiang et al, ; Mao et al, ; Zaichun Zhu, Piao, et al, ). Further efforts should be made to reprocess and reanalyze the historical archives of AVHRR sensors to ensure compatibility and consistency with current records (GCOS, ).…”

“…The greening trend in Eurasia is more obvious than that in North America (Kai Yan et al, ). The amplitude of greening in China is about 24% higher than the global value (0.070 per decade vs. 0.053 per decade; Jiang et al, ; Piao et al, ). The greening trend is largely explained by the climate change, CO 2 fertilization, atmospheric nitrogen deposition, and longer high‐latitude growing seasons (Piao et al, ; Zaichun Zhu, Piao, et al, ).…”

“…The greening trend is largely explained by the climate change, CO 2 fertilization, atmospheric nitrogen deposition, and longer high‐latitude growing seasons (Piao et al, ; Zaichun Zhu, Piao, et al, ). Differences exist among the LAI products in calculating the interannual variability and long‐term trend, especially at regional scales (Fang, Jiang, et al, ; Jiang et al, ; Piao et al, ). Differences also exist in the predicted LAI using various process models (Mahowald et al, ).…”

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region

“…However, a relatively large discrepancy among these long‐term LAI products has also been reported in some recent studies (Xiao et al, ; Zhu et al, ). Therefore, the uncertainty of LAI data itself (Jiang et al, ) should be considered when evaluating model performances.…”

Global vegetation variability and its response to elevated CO<sub>2</sub>, global warming, and climate variability – a study using the offline SSiB4/TRIFFID model and satellite data

“…It should be pointed out that although there is general consistency between the satellite-based LAI products, large relative uncertainties were identified (Jiang et al, 2017). 25…”