Articles | Volume 14, issue 8
https://doi.org/10.5194/gmd-14-5049-2021
https://doi.org/10.5194/gmd-14-5049-2021
Development and technical paper
 | 
13 Aug 2021
Development and technical paper |  | 13 Aug 2021

Optical model for the Baltic Sea with an explicit CDOM state variable: a case study with Model ERGOM (version 1.2)

Thomas Neumann, Sampsa Koponen, Jenni Attila, Carsten Brockmann, Kari Kallio, Mikko Kervinen, Constant Mazeran, Dagmar Müller, Petra Philipson, Susanne Thulin, Sakari Väkevä, and Pasi Ylöstalo

Related authors

Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024,https://doi.org/10.5194/gmd-17-1689-2024, 2024
Short summary
A regional pCO2 climatology of the Baltic Sea from in situ pCO2 observations and a model-based extrapolation approach
Henry C. Bittig, Erik Jacobs, Thomas Neumann, and Gregor Rehder
Earth Syst. Sci. Data, 16, 753–773, https://doi.org/10.5194/essd-16-753-2024,https://doi.org/10.5194/essd-16-753-2024, 2024
Short summary
Ocean models as shallow sea oxygen deficiency assessment tools: from research to practical application
Sarah Piehl, René Friedland, Thomas Neumann, and Gerald Schernewski
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-152,https://doi.org/10.5194/bg-2023-152, 2023
Revised manuscript not accepted
Short summary
The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment
Matthias Gröger, Manja Placke, H. E. Markus Meier, Florian Börgel, Sandra-Esther Brunnabend, Cyril Dutheil, Ulf Gräwe, Magnus Hieronymus, Thomas Neumann, Hagen Radtke, Semjon Schimanke, Jian Su, and Germo Väli
Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022,https://doi.org/10.5194/gmd-15-8613-2022, 2022
Short summary
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

Related subject area

Biogeosciences
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024,https://doi.org/10.5194/gmd-17-7317-2024, 2024
Short summary
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024,https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024,https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024,https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024,https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary

Cited articles

Asmala, E., Autio, R., Kaartokallio, H., Pitkänen, L., Stedmon, C. A., and Thomas, D. N.: Bioavailability of riverine dissolved organic matter in three Baltic Sea estuaries and the effect of catchment land use, Biogeosciences, 10, 6969–6986, https://doi.org/10.5194/bg-10-6969-2013, 2013. a
Attila, J., Koponen, S., Kallio, K., Lindfors, A., Kaitala, S., and Ylöstalo, P.: MERIS Case II water processor comparison on coastal sites of the northern Baltic Sea, Remote Sens. Environ., 128, 138–149, https://doi.org/10.1016/j.rse.2012.07.009, 2013. a
Brockmann, C., Doerffer, R., Peters, M., Stelzer, K., Embacher, S., and Ruescas, A.: Evolution of the C2RCC neural network for Sentinel 2 and 3 for the retrieval of ocean colour products in normal and extreme optically complex waters, website, available at: http://step.esa.int/docs/extra/Evolution%20of%20the%20C2RCC_LPS16.pdf (last access: 7 July 2020), 2016. a
Cahill, B., Schofield, O., Chant, R., Wilkin, J., Hunter, E., Glenn, S., and Bissett, P.: Dynamics of turbid buoyant plumes and the feedbacks on near-shore biogeochemistry and physics, Geophys. Res. Lett., 35, L10605, https://doi.org/10.1029/2008GL033595, 2008. a
Dutkiewicz, S., Hickman, A. E., Jahn, O., Gregg, W. W., Mouw, C. B., and Follows, M. J.: Capturing optically important constituents and properties in a marine biogeochemical and ecosystem model, Biogeosciences, 12, 4447–4481, https://doi.org/10.5194/bg-12-4447-2015, 2015. a, b, c
Download
Short summary
The Baltic Sea is heavily impacted by surrounding land. Therefore, the concentration of colored dissolved organic matter (CDOM) of terrestrial origin is relatively high and impacts the light penetration depth. Estimating a correct light climate is essential for ecosystem models. In this study, a method is developed to derive riverine CDOM from Earth observation methods. The data are used as boundary conditions for an ecosystem model, and the advantage over former approaches is shown.