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 5 description of the environmental controls on phen...

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Published in:Biogeosciences
Main Authors: Forkel, M., Carvalhais, N., Schaphoff, S., Bloh, W., Migliavacca, M., Thurner, M., Thonicke, K.
Format: Article in Journal/Newspaper
Language:unknown
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/11858/00-001M-0000-001A-1EFA-F
http://hdl.handle.net/11858/00-001M-0000-001A-1EFE-7
http://hdl.handle.net/11858/00-001M-0000-0024-9032-5
http://hdl.handle.net/21.11116/0000-0004-40F3-1
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spelling ftpubman:oai:pure.mpg.de:item_2048248 2023-08-20T03:59:21+02:00 Identifying environmental controls on vegetation greenness phenology through model-data integration Forkel, M. Carvalhais, N. Schaphoff, S. Bloh, W. Migliavacca, M. Thurner, M. Thonicke, K. 2014 application/pdf http://hdl.handle.net/11858/00-001M-0000-001A-1EFA-F http://hdl.handle.net/11858/00-001M-0000-001A-1EFE-7 http://hdl.handle.net/11858/00-001M-0000-0024-9032-5 http://hdl.handle.net/21.11116/0000-0004-40F3-1 unknown info:eu-repo/semantics/altIdentifier/doi/10.5194/bg-11-7025-2014 http://hdl.handle.net/11858/00-001M-0000-001A-1EFA-F http://hdl.handle.net/11858/00-001M-0000-001A-1EFE-7 http://hdl.handle.net/11858/00-001M-0000-0024-9032-5 http://hdl.handle.net/21.11116/0000-0004-40F3-1 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/3.0/ Biogeosciences info:eu-repo/semantics/article 2014 ftpubman https://doi.org/10.5194/bg-11-7025-2014 2023-08-01T23:36:58Z 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 5 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 to enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenol10 ogy 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 en15 vironmental 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 20 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 25 a new generation of phenology modules in DGVMs in order to correctly reproduce observed ... Article in Journal/Newspaper albedo Arctic Tundra Max Planck Society: MPG.PuRe Arctic Browning ENVELOPE(164.050,164.050,-74.617,-74.617) Biogeosciences 11 23 7025 7050
institution Open Polar
collection Max Planck Society: MPG.PuRe
op_collection_id ftpubman
language unknown
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 5 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 to enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenol10 ogy 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 en15 vironmental 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 20 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 25 a new generation of phenology modules in DGVMs in order to correctly reproduce observed ...
format Article in Journal/Newspaper
author Forkel, M.
Carvalhais, N.
Schaphoff, S.
Bloh, W.
Migliavacca, M.
Thurner, M.
Thonicke, K.
spellingShingle Forkel, M.
Carvalhais, N.
Schaphoff, S.
Bloh, W.
Migliavacca, M.
Thurner, M.
Thonicke, K.
Identifying environmental controls on vegetation greenness phenology through model-data integration
author_facet Forkel, M.
Carvalhais, N.
Schaphoff, S.
Bloh, W.
Migliavacca, M.
Thurner, M.
Thonicke, K.
author_sort Forkel, M.
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
publishDate 2014
url http://hdl.handle.net/11858/00-001M-0000-001A-1EFA-F
http://hdl.handle.net/11858/00-001M-0000-001A-1EFE-7
http://hdl.handle.net/11858/00-001M-0000-0024-9032-5
http://hdl.handle.net/21.11116/0000-0004-40F3-1
long_lat ENVELOPE(164.050,164.050,-74.617,-74.617)
geographic Arctic
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op_source Biogeosciences
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http://hdl.handle.net/11858/00-001M-0000-001A-1EFE-7
http://hdl.handle.net/11858/00-001M-0000-0024-9032-5
http://hdl.handle.net/21.11116/0000-0004-40F3-1
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op_doi https://doi.org/10.5194/bg-11-7025-2014
container_title Biogeosciences
container_volume 11
container_issue 23
container_start_page 7025
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