Missing pieces to modeling the Arctic-Boreal puzzle
© 2018 The Author(s). Published by IOP Publishing Ltd. NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses....
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Language: | English |
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ftcdlib:qt4q97v4zq 2023-05-15T14:25:16+02:00 Missing pieces to modeling the Arctic-Boreal puzzle Fisher, JB Hayes, DJ Schwalm, CR Huntzinger, DN Stofferahn, E Schaefer, K Luo, Y Wullschleger, SD Goetz, S Miller, CE Griffith, P Chadburn, S Chatterjee, A Ciais, P Douglas, TA Genet, H Ito, A Neigh, CSR Poulter, B Rogers, BM Sonnentag, O Tian, H Wang, W Xue, Y Yang, ZL Zeng, N Zhang, Z 2018-02-01 application/pdf http://www.escholarship.org/uc/item/4q97v4zq english eng eScholarship, University of California qt4q97v4zq http://www.escholarship.org/uc/item/4q97v4zq public Fisher, JB; Hayes, DJ; Schwalm, CR; Huntzinger, DN; Stofferahn, E; Schaefer, K; et al.(2018). Missing pieces to modeling the Arctic-Boreal puzzle. Environmental Research Letters, 13(2). doi:10.1088/1748-9326/aa9d9a. UCLA: Retrieved from: http://www.escholarship.org/uc/item/4q97v4zq ABoVE arctic arctic boreal vulnerability experiment boreal model requirements uncertainty article 2018 ftcdlib https://doi.org/10.1088/1748-9326/aa9d9a 2018-07-13T22:58:41Z © 2018 The Author(s). Published by IOP Publishing Ltd. NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented. Article in Journal/Newspaper Arctic Arctic permafrost University of California: eScholarship Arctic Environmental Research Letters 13 2 020202 |
institution |
Open Polar |
collection |
University of California: eScholarship |
op_collection_id |
ftcdlib |
language |
English |
topic |
ABoVE arctic arctic boreal vulnerability experiment boreal model requirements uncertainty |
spellingShingle |
ABoVE arctic arctic boreal vulnerability experiment boreal model requirements uncertainty Fisher, JB Hayes, DJ Schwalm, CR Huntzinger, DN Stofferahn, E Schaefer, K Luo, Y Wullschleger, SD Goetz, S Miller, CE Griffith, P Chadburn, S Chatterjee, A Ciais, P Douglas, TA Genet, H Ito, A Neigh, CSR Poulter, B Rogers, BM Sonnentag, O Tian, H Wang, W Xue, Y Yang, ZL Zeng, N Zhang, Z Missing pieces to modeling the Arctic-Boreal puzzle |
topic_facet |
ABoVE arctic arctic boreal vulnerability experiment boreal model requirements uncertainty |
description |
© 2018 The Author(s). Published by IOP Publishing Ltd. NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented. |
format |
Article in Journal/Newspaper |
author |
Fisher, JB Hayes, DJ Schwalm, CR Huntzinger, DN Stofferahn, E Schaefer, K Luo, Y Wullschleger, SD Goetz, S Miller, CE Griffith, P Chadburn, S Chatterjee, A Ciais, P Douglas, TA Genet, H Ito, A Neigh, CSR Poulter, B Rogers, BM Sonnentag, O Tian, H Wang, W Xue, Y Yang, ZL Zeng, N Zhang, Z |
author_facet |
Fisher, JB Hayes, DJ Schwalm, CR Huntzinger, DN Stofferahn, E Schaefer, K Luo, Y Wullschleger, SD Goetz, S Miller, CE Griffith, P Chadburn, S Chatterjee, A Ciais, P Douglas, TA Genet, H Ito, A Neigh, CSR Poulter, B Rogers, BM Sonnentag, O Tian, H Wang, W Xue, Y Yang, ZL Zeng, N Zhang, Z |
author_sort |
Fisher, JB |
title |
Missing pieces to modeling the Arctic-Boreal puzzle |
title_short |
Missing pieces to modeling the Arctic-Boreal puzzle |
title_full |
Missing pieces to modeling the Arctic-Boreal puzzle |
title_fullStr |
Missing pieces to modeling the Arctic-Boreal puzzle |
title_full_unstemmed |
Missing pieces to modeling the Arctic-Boreal puzzle |
title_sort |
missing pieces to modeling the arctic-boreal puzzle |
publisher |
eScholarship, University of California |
publishDate |
2018 |
url |
http://www.escholarship.org/uc/item/4q97v4zq |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arctic permafrost |
genre_facet |
Arctic Arctic permafrost |
op_source |
Fisher, JB; Hayes, DJ; Schwalm, CR; Huntzinger, DN; Stofferahn, E; Schaefer, K; et al.(2018). Missing pieces to modeling the Arctic-Boreal puzzle. Environmental Research Letters, 13(2). doi:10.1088/1748-9326/aa9d9a. UCLA: Retrieved from: http://www.escholarship.org/uc/item/4q97v4zq |
op_relation |
qt4q97v4zq http://www.escholarship.org/uc/item/4q97v4zq |
op_rights |
public |
op_doi |
https://doi.org/10.1088/1748-9326/aa9d9a |
container_title |
Environmental Research Letters |
container_volume |
13 |
container_issue |
2 |
container_start_page |
020202 |
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1766297698948874240 |