Identifying environmental controls on vegetation greenness phenology through model–data integration

Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenol...

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Main Authors: M. Forkel, N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner, K. Thonicke
Format: Article
Language:English
Published: Copernicus Publications 2014-12-01
Series:Biogeosciences
Online Access:http://www.biogeosciences.net/11/7025/2014/bg-11-7025-2014.pdf
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spelling doaj-8ad9a83583db4772aa886defcd1435c22020-11-24T23:20:08ZengCopernicus PublicationsBiogeosciences1726-41701726-41892014-12-0111237025705010.5194/bg-11-7025-2014Identifying environmental controls on vegetation greenness phenology through model–data integrationM. Forkel0N. Carvalhais1S. Schaphoff2W. v. Bloh3M. Migliavacca4M. Thurner5K. Thonicke6Max-Planck-Institute for Biogeochemistry, Department for Biogeochemical Integration, Hans-Knöll-Str. 10, 07745 Jena, GermanyMax-Planck-Institute for Biogeochemistry, Department for Biogeochemical Integration, Hans-Knöll-Str. 10, 07745 Jena, GermanyPotsdam Institute for Climate Impact Research, Earth System Analysis, Telegraphenberg A31, 14473 Potsdam, GermanyPotsdam Institute for Climate Impact Research, Earth System Analysis, Telegraphenberg A31, 14473 Potsdam, GermanyMax-Planck-Institute for Biogeochemistry, Department for Biogeochemical Integration, Hans-Knöll-Str. 10, 07745 Jena, GermanyMax-Planck-Institute for Biogeochemistry, Department for Biogeochemical Integration, Hans-Knöll-Str. 10, 07745 Jena, GermanyPotsdam Institute for Climate Impact Research, Earth System Analysis, Telegraphenberg A31, 14473 Potsdam, GermanyExisting dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness.http://www.biogeosciences.net/11/7025/2014/bg-11-7025-2014.pdf
collection DOAJ
language English
format Article
sources DOAJ
author M. Forkel
N. Carvalhais
S. Schaphoff
W. v. Bloh
M. Migliavacca
M. Thurner
K. Thonicke
spellingShingle M. Forkel
N. Carvalhais
S. Schaphoff
W. v. Bloh
M. Migliavacca
M. Thurner
K. Thonicke
Identifying environmental controls on vegetation greenness phenology through model–data integration
Biogeosciences
author_facet M. Forkel
N. Carvalhais
S. Schaphoff
W. v. Bloh
M. Migliavacca
M. Thurner
K. Thonicke
author_sort M. Forkel
title Identifying environmental controls on vegetation greenness phenology through model–data integration
title_short Identifying environmental controls on vegetation greenness phenology through model–data integration
title_full Identifying environmental controls on vegetation greenness phenology through model–data integration
title_fullStr Identifying environmental controls on vegetation greenness phenology through model–data integration
title_full_unstemmed Identifying environmental controls on vegetation greenness phenology through model–data integration
title_sort identifying environmental controls on vegetation greenness phenology through model–data integration
publisher Copernicus Publications
series Biogeosciences
issn 1726-4170
1726-4189
publishDate 2014-12-01
description Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness.
url http://www.biogeosciences.net/11/7025/2014/bg-11-7025-2014.pdf
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