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Abstract The ocean coastal‐shelf‐slope ecosystem west of the Antarctic Peninsula (WAP) is a biologically productive region that could potentially act as a large sink of atmospheric carbon dioxide. The duration of the sea‐ice season in the WAP shows large interannual variability. However, quantifying the mechanisms by which sea ice impacts biological productivity and surface dissolved inorganic carbon (DIC) remains a challenge due to the lack of data early in the phytoplankton growth season. In this study, we implemented a circulation, sea‐ice, and biogeochemistry model (MITgcm‐REcoM2) to study the effect of sea ice on phytoplankton blooms and surface DIC. Results were compared with satellite sea‐ice and ocean color, and research ship surveys from the Palmer Long‐Term Ecological Research (LTER) program. The simulations suggest that the annual sea‐ice cycle has an important role in the seasonal DIC drawdown. In years of early sea‐ice retreat, there is a longer growth season leading to larger seasonally integrated net primary production (NPP). Part of the biological uptake of DIC by phytoplankton, however, is counteracted by increased oceanic uptake of atmospheric CO2. Despite lower seasonal NPP, years of late sea‐ice retreat show larger DIC drawdown, attributed to lower air‐sea CO2fluxes and increased dilution by sea‐ice melt. The role of dissolved iron and iron limitation on WAP phytoplankton also remains a challenge due to the lack of data. The model results suggest sediments and glacial meltwater are the main sources in the coastal and shelf regions, with sediments being more influential in the northern coast.
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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
Abstract. The West Antarctic Peninsula (WAP) is a rapidly warming region, withsubstantial ecological and biogeochemical responses to the observed changeand variability for the past decades, revealed by multi-decadal observationsfrom the Palmer Antarctica Long-Term Ecological Research (LTER) program. Thewealth of these long-term observations provides an important resource forecosystem modeling, but there has been a lack of focus on the developmentof numerical models that simulate time-evolving plankton dynamics over theaustral growth season along the coastal WAP. Here, we introduce aone-dimensional variational data assimilation planktonic ecosystem model (i.e., theWAP-1D-VAR v1.0 model) equipped with a modelparameter optimization scheme. We first demonstrate the modified and newlyadded model schemes to the pre-existing food web and biogeochemicalcomponents of the other ecosystem models that WAP-1D-VAR model was adaptedfrom, including diagnostic sea-ice forcing and trophic interactions specificto the WAP region. We then present the results from model experiments wherewe assimilate 11 different data types from an example Palmer LTER growthseason (October 2002–March 2003) directly related to corresponding modelstate variables and flows between these variables. The iterative dataassimilation procedure reduces the misfits between observationsand model results by 58 %, compared to before optimization, via an optimized set of12 parameters out of a total of 72 free parameters. The optimized model resultscapture key WAP ecological features, such as blooms during seasonal sea-iceretreat, the lack of macronutrient limitation, and modeled variables andflows comparable to other studies in the WAP region, as well as severalimportant ecosystem metrics. One exception is that the model slightlyunderestimates particle export flux, for which we discuss potentialunderlying reasons. The data assimilation scheme of the WAP-1D-VAR modelenables the available observational data to constrain previously poorlyunderstood processes, including the partitioning of primary production bydifferent phytoplankton groups, the optimal chlorophyll-to-carbon ratio ofthe WAP phytoplankton community, and the partitioning of dissolved organiccarbon pools with different lability. The WAP-1D-VAR model can besuccessfully employed to link the snapshots collected by the available datasets together to explain and understand the observed dynamics along thecoastal WAP.
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- Award ID(s):
- 2026045
- PAR ID:
- 10320136
- Date Published:
- Journal Name:
- Geoscientific Model Development
- Volume:
- 14
- Issue:
- 8
- ISSN:
- 1991-9603
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/gmd-14-4939-2021
