Articles | Volume 14, issue 8
Geosci. Model Dev., 14, 4939–4975, 2021
https://doi.org/10.5194/gmd-14-4939-2021
Geosci. Model Dev., 14, 4939–4975, 2021
https://doi.org/10.5194/gmd-14-4939-2021
Development and technical paper
12 Aug 2021
Development and technical paper | 12 Aug 2021

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

Hyewon Heather Kim et al.

Related authors

Modeling polar marine ecosystem functions guided by bacterial physiological and taxonomic traits
Hyewon Heather Kim, Jeff S. Bowman, Ya-Wei Luo, Hugh W. Ducklow, Oscar M. Schofield, Deborah K. Steinberg, and Scott C. Doney
Biogeosciences, 19, 117–136, https://doi.org/10.5194/bg-19-117-2022,https://doi.org/10.5194/bg-19-117-2022, 2022
Short summary

Related subject area

Biogeosciences
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022,https://doi.org/10.5194/gmd-15-8473-2022, 2022
Short summary
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022,https://doi.org/10.5194/gmd-15-8453-2022, 2022
Short summary
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022,https://doi.org/10.5194/gmd-15-8377-2022, 2022
Short summary
Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022,https://doi.org/10.5194/gmd-15-8153-2022, 2022
Short summary
Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022,https://doi.org/10.5194/gmd-15-7809-2022, 2022
Short summary

Cited articles

Armstrong, R. A.: Optimality-based modeling of nitrogen allocation and photo acclimation in photosynthesis, Deep-Sea Res. II, 53, 513–531, 2006. 
Bertilsson, S., Berglund, O., Karl, D. M., and Chisholm, S. W.: Elemental composition of marine Prochlorococcus and Synechococcus: Implications for the ecological stoichiometry of the sea, Limnol. Oceanogr., 48, 1721–1731, https://doi.org/10.4319/lo.2003.48.5.1721, 2003. 
Biddanda, B. and Benner, R.: Carbon, nitrogen and carbohydrate fluxes during the production of particulate and dissolved organic matter by marine phytoplankton, Limnol. Oceanogr., 42, 506–518, 1997. 
Bird, D. F. and Karl, D. M.: Uncoupling of bacteria and phytoplankton during the austral spring bloom in Gerlache Strait, Antarctic Peninsula, Aquat. Microb. Ecol., 19, 13–27, https://doi.org/10.3354/ame019013, 1999. 
Bjørnsen, P. K.: Phytoplankton exudation of organic matter: Why do healthy cells do it?, Limnol. Oceanogr., 33, 151–154, 1988. 
Download
Short summary
The West Antarctic Peninsula (WAP) is a rapidly warming region, revealed by multi-decadal observations. Despite the region being data rich, there is a lack of focus on ecosystem model development. Here, we introduce a data assimilation ecosystem model for the WAP region. Experiments by assimilating data from an example growth season capture key WAP features. This study enables us to glue the snapshots from available data sets together to explain the observations in the WAP.