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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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 Browning |
geographic_facet |
Arctic Browning |
genre |
albedo Arctic Tundra |
genre_facet |
albedo Arctic Tundra |
op_source |
Biogeosciences |
op_relation |
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 |
op_rights |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/3.0/ |
op_doi |
https://doi.org/10.5194/bg-11-7025-2014 |
container_title |
Biogeosciences |
container_volume |
11 |
container_issue |
23 |
container_start_page |
7025 |
op_container_end_page |
7050 |
_version_ |
1774712359189741568 |