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

• Published in: Geoscientific Model Development
• Main Authors: Kim, Hyewon Heather, Luo, Ya-Wei, Ducklow, Hugh W., Schofield, Oscar M. E., Steinberg, Deborah K., Doney, Scott C.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: European Geosciences Union 2021
• Subjects: Antarctic; Antarctic Peninsula; Austral; Antarc*; Antarctica; Sea ice
• Online Access: https://hdl.handle.net/1912/27711

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kim, H. H., Luo, Y.-W., Ducklow, H. W., Schofield, O. M., Steinberg, D. K., & Doney, S. C. 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. Geoscientific Model Development, 14(8), (2021): 4939–4975, https://doi.org/10.5194/gmd-14-4939-2021. The West Antarctic Peninsula (WAP) is a rapidly warming region, with substantial ecological and biogeochemical responses to the observed change and variability for the past decades, revealed by multi-decadal observations from 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 state variables and flows between these variables. The iterative data assimilation procedure reduces the misfits between observations and model results by 58 %, compared to before optimization, via an optimized set of 12 parameters out of a total of 72 free parameters. The optimized model results ...