Abstract
Leaf Area Index (LAI) represents the total surface area of leaves above a unit area of ground and is a key variable in any vegetation model, as well as in climate models. New high resolution LAI satellite data is now available covering a period of several decades. This provides a unique opportunity to validate LAI estimates from multiple vegetation models. The objective of this paper is to compare new, satellite-derived LAI measurements with modeled output for the Northern Hemisphere. We compare monthly LAI output from eight land surface models from the TRENDY compendium with satellite data from an Artificial Neural Network (ANN) from the latest version (third generation) of GIMMS AVHRR NDVI data over the period 1986–2005. Our results show that all the models overestimate the mean LAI, particularly over the boreal forest. We also find that seven out of the eight models overestimate the length of the active vegetation-growing season, mostly due to a late dormancy as a result of a late summer phenology. Finally, we find that the models report a much larger positive trend in LAI over this period than the satellite observations suggest, which translates into a higher trend in the growing season length. These results highlight the need to incorporate a larger number of more accurate plant functional types in all models and, in particular, to improve the phenology of deciduous trees.
Highlights
Leaf Area Index (LAI) is the number of leaf layers per unit area in an ecosystem
All of the models overestimate mean LAI, LAI trend and interannual variability (IAV) over the high-latitude Northern Hemisphere compared to the satellite observations (Figure 2)
When the same methodology used to calculate the LAI-growing period was applied to gross primary productivity (GPP), we found that the dormancy began at 277 ± 7 days in the models, which is remarkably earlier than previously predicted by LAI (315 ± 10 days), even on the low-north latitudes
Summary
Leaf Area Index (LAI) is the number of leaf layers per unit area in an ecosystem. It is widely used in the coupling of land surface and atmospheric processes, such as radiation, precipitation interception [1]and gas exchange [2]. Leaf Area Index (LAI) is the number of leaf layers per unit area in an ecosystem It is widely used in the coupling of land surface and atmospheric processes, such as radiation, precipitation interception [1]. LAI is a key variable of energy and water balance calculations in vegetation models [4] It influences numerous model outputs such as net primary productivity (NPP), evapotranspiration (ET), the fraction of the light being absorbed by plants (FAPAR) and nutrient dynamics [5]. Land Surface Models (LSMs) have different approaches for calculating LAI, and while the use of plant functional types (PFTs) is widespread [6], there are important differences in the number of simulated PFTs, their spatial distribution and the representation of vegetation dynamics [7]
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