WAP-1D-VAR v1.0: development and evaluation of a one-dimensional variational data assimilation model for the marine ecosystem along the West Antarctic Peninsula
The West Antarctic Peninsula (WAP) is a rapidlywarming region, with substantial ecological and biogeochemical responses to the observed change and variability for the past decades, revealed by multidecadal observationsfrom the Palmer Antarctica Long-Term Ecological Research (LTER) program. The wealt...
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W&M ScholarWorks
2021
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Online Access: | https://scholarworks.wm.edu/vimsarticles/2182 https://doi.org/10.5194/gmd-14-4939-2021 https://scholarworks.wm.edu/context/vimsarticles/article/3183/viewcontent/gmd_14_4939_2021.pdf https://scholarworks.wm.edu/context/vimsarticles/article/3183/filename/0/type/additional/viewcontent/gmd_14_4939_2021_supplement.pdf |
Summary: | The West Antarctic Peninsula (WAP) is a rapidlywarming region, with substantial ecological and biogeochemical responses to the observed change and variability for the past decades, revealed by multidecadal observationsfrom the Palmer Antarctica Long-Term Ecological Research (LTER) program. The wealth of these long-term observations provides an important resource for ecosystem modeling, but there has been a lack of focus on the development of numerical models that simulate time-evolving plankton dynamics over the austral growth season along the coastal WAP. Here, we introduce a one dimensional variational data assimilation planktonic ecosystem model (i.e., the WAP-1D-VAR v1.0 model) equipped with a model parameter optimization scheme. We first demonstrate the modified and newly added model schemes to the pre-existing food web and biogeochemical components of the other ecosystem models that WAP-1D-VAR model was adapted from, including diagnostic sea-ice forcing and trophic interactions specific to the WAP region. We then present the results from model experiments where we assimilate 11 different data types from an example Palmer LTER growth season (October 2002–March 2003) directly related to corresponding model statevariables and flows between these variables. |
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