Atmospheric vapor pressure deficit (VPD) is a critical variable in determining plant photosynthesis. Synthesis of four global climate datasets reveals a sharp increase of VPD after the late 1990s. In response, the vegetation greening trend indicated by a satellite-derived vegetation index (GIMMS3g), which was evident before the late 1990s, was subsequently stalled or reversed. Terrestrial gross primary production derived from two satellite-based models (revised EC-LUE and MODIS) exhibits persistent and widespread decreases after the late 1990s due to increased VPD, which offset the positive CO2 fertilization effect. Six Earth system models have consistently projected continuous increases of VPD throughout the current century. Our results highlight that the impacts of VPD on vegetation growth should be adequately considered to assess ecosystem responses to future climate conditions.

No 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.

[1] Leaf area index (LAI) is a critical variable for land surface and climate modeling studies. Several global LAI products exist, and it is important to know how these products perform and what their uncertainties are. Five major global LAI products-MODIS, GEOV1, GLASS, GLOBMAP, and JRC-TIP-were compared between 2003 and 2010 at a 0.01 spatial resolution and with a monthly time step. The daily Land-SAF product was used as a regional reference in order to evaluate the performance of other global products in Africa. Cross-sensor LAI conversion equations were derived for different biome types. Product uncertainties were assessed by looking into the product quantitative quality indicators (QQIs) attached to MODIS, GEOV1, and JRC-TIP. MODIS, GEOV1, GLASS, and GLOBMAP are generally consistent and show strong linear relationships between the products (R 2 > 0.74), with typical deviations of < 0.5 for nonforest and < 1.0 for forest biomes. JRC-TIP, the only effective LAI product, is about half the values of the other LAI products. The average uncertainties and relative uncertainties are in the following order: MODIS (0.17, 11.5%) < GEOV1 (0.24, 26.6%) < Land-SAF (0.36, 37.8%) < JRC-TIP (0.43, 114.3%). The highest relative uncertainties usually appear in ecological transition zones. More than 75% of MODIS, GEOV1, JRC-TIP, and Land-SAF pixels are within the absolute uncertainty requirements (AE 0.5) set by the Global Climate Observing System (GCOS), whereas more than 78.5% of MODIS and 44.6% of GEOV1 pixels are within the threshold for relative uncertainty (20%). This study reveals the discrepancies mainly due to differences between definitions, retrieval algorithms, and input data. Future product development and validation studies should focus on areas (e.g., sparsely vegetated and savanna areas) and periods (e.g., winter time) with higher uncertainties. Citation: Fang, H., et al. (2013), Characterization and intercomparison of global moderate resolution leaf area index (LAI) products: Analysis of climatologies and theoretical uncertainties,