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Journal of Geophysical Research Biogeosciences
Article . 2019 . Peer-reviewed
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Global Variability of Simulated and Observed Vegetation Growing Season

Authors: Andrea Alessandri; Andrea Alessandri; Silvio Gualdi; Stefano Materia; Antonio Bombelli; Daniele Peano; Alessio Collalti; +1 Authors

Global Variability of Simulated and Observed Vegetation Growing Season

Abstract

AbstractVegetation phenology and its variability have substantial influence on land‐atmosphere interaction, and changes in growing season length are additional indicators of climate change impacts on ecosystems. For these reasons, global land surface models are routinely evaluated in order to assess their ability to reproduce the observed phenological variability. In this work, we present a new approach that integrates a wider spectrum of growing season modes, in order to better describe the observed variability in vegetation growing season onset and offset, as well as assess the ability of state‐of‐the‐art land surface models to capture this variability at the global scale. The method is applied to the Community Land Model version 4.5 (CLM4.5) simulations and LAI3g satellite observation. The comparison between data and model outputs shows that CLM4.5 is capable of reproducing the growing season features in the Northern Hemisphere midlatitude and high latitude, but also displays its limitations in areas where water availability acts as the main driver of vegetation phenological activity. Besides, the new approach allows evaluating land surface models in capturing multigrowing‐season phenology. In this regard, CLM4.5 proves its ability in reproducing the two‐growing‐season cycles in the Horn of Africa. In general, the new methodology expands the area of analysis from northern midlatitude and high latitude to the global continental areas and allows to assess the vegetation response to the ongoing climate change in a larger variety of ecosystems, ranging from semiarid regions to rain forests, passing through temperate deciduous and boreal evergreen forests.

Country
Italy
Keywords

Vegetation, Phenology, Climate Change, Model

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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25
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