Articles | Volume 19, issue 12
https://doi.org/10.5194/gmd-19-5601-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-5601-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
29 Jun 2026
Development and technical paper |
| 29 Jun 2026
| 29 Jun 2026
Simultaneous versus sequential estimation of biogeochemical and physical parameters in coupled marine ecosystem models
Mechanical Engineering Department, University of Alaska Anchorage, Anchorage, AK, USA
Paul M. Rady Department of Mechanical Engineering, University of Colorado, Boulder, CO, USA
Mary E. McGuinn
Paul M. Rady Department of Mechanical Engineering, University of Colorado, Boulder, CO, USA
Vanasse Hangen Brustlin, Williamsburg, VA, USA
Katherine M. Smith
Los Alamos National Laboratory, Los Alamos, NM, USA
Nadia Pinardi
Department of Physics and Astronomy, University of Bologna, Bologna, IT
Kyle E. Niemeyer
School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, USA
Nicole S. Lovenduski
Department of Atmospheric and Oceanic Sciences and Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO, USA
Peter E. Hamlington
Paul M. Rady Department of Mechanical Engineering, University of Colorado, Boulder, CO, USA
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Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
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Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Dylan Schlichting, Katherine Smith, Mark Petersen, Robert Hetland, Kyle Hinson, and Darren Engwirda
EGUsphere, https://doi.org/10.5194/egusphere-2026-1567, https://doi.org/10.5194/egusphere-2026-1567, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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River plumes can strongly influence coastal dynamics but are poorly resolved in global ocean models. Building on a companion study, we perform high-resolution simulations of the Mississippi–Atchafalaya (M-A) plume with the Model for Prediction Across Scales–Ocean (MPAS-O), a global model, and compare with a limited-domain Regional Ocean Modeling System configuration. MPAS-O qualitatively captures the M-A plume seasonality but fails to generate realistic eddies on the Texas–Louisiana shelf.
Kyle E. Hinson, Dylan R. Schlichting, Robert D. Hetland, Darren Engwirda, Katherine M. Smith, Mark R. Petersen, and Kaila Uyeda
EGUsphere, https://doi.org/10.5194/egusphere-2026-1566, https://doi.org/10.5194/egusphere-2026-1566, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Physical dynamics of ocean flows at fine spatial scales are challenging for regional and global scale ocean models due to high computational effort associated with smaller grid cell sizes. We compared two ocean models: a regional model (ROMS; Regional Ocean Modeling System) and global model (MPAS-O; Model for Prediction Across Scales – Ocean) across a range of resolutions (10 km to 100 m) in an idealized domain, and found that their similarities may hold promise for future coupling between them.
Mark R. Petersen, Xylar S. Asay-Davis, Alice M. Barthel, Carolyn Branecky Begeman, Siddhartha Bishnu, Steven R. Brus, Philip W. Jones, Hyun-Gyu Kang, Youngsung Kim, Azamat Mametjanov, Brian J. O'Neill, James R. Overfelt, Kieran K. Ringel, Katherine M. Smith, Sarat Sreepathi, Luke P. Van Roekel, and Maciej Waruszewski
Geosci. Model Dev., 19, 3569–3594, https://doi.org/10.5194/gmd-19-3569-2026, https://doi.org/10.5194/gmd-19-3569-2026, 2026
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Ocean models are used to predict currents, temperature, and salinity of the earth's oceans, much like weather forecasting. As supercomputer hardware changes with evolving technology, models must be updated, and sometimes rewritten. Here we document Omega, a new ocean model that was designed to run on the world's fastest supercomputers. Testing shows that Omega accurately solves the model equations, and runs efficiently on many different computer architectures, including exascale computers.
Rita Lecci, Robyn Gwee, Kun Yan, Sanne Muis, Nadia Pinardi, Jun She, Martin Verlaan, Simona Masina, Wenshan Li, Hui Wang, Salvatore Causio, Antonio Novellino, Marco Alba, Etiënne Kras, Sandra Gaytan Aguilar, and Jan-Bart Calewaert
Nat. Hazards Earth Syst. Sci., 26, 1767–1783, https://doi.org/10.5194/nhess-26-1767-2026, https://doi.org/10.5194/nhess-26-1767-2026, 2026
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This study explored how sea level is changing along the China-Europe Sea Route. By combining satellite and in-situ observations with advanced modeling, the research identified ongoing sea level rise and an increasing frequency of extreme water level events in some regions. These findings underscore the importance of continued monitoring and provide useful knowledge to support long-term planning, coastal resilience, and informed decision-making.
Jacopo Alessandri, Giulia Bonino, Tomas Lovato, Momme Butenschön, Lorenzo Mentaschi, Giorgia Verri, Ivan Federico, and Nadia Pinardi
EGUsphere, https://doi.org/10.5194/egusphere-2026-1119, https://doi.org/10.5194/egusphere-2026-1119, 2026
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Coastal seas are strongly shaped by complex coastlines, shallow depths, and inputs from rivers, which influence marine life and water quality. This study introduces a new high-resolution modelling system that combines ocean circulation and marine ecosystem processes on unstructured grids. Applied to the northern Adriatic Sea, the model realistically captures seasonal changes in key biogeochemical variables, offering improved tools to support coastal environmental management.
Italo dos Reis Lopes, Ivan Federico, Michalis Vousdoukas, Luisa Perini, Salvatore Causio, Giovanni Coppini, Maurilio Milella, Nadia Pinardi, and Lorenzo Mentaschi
Nat. Hazards Earth Syst. Sci., 26, 811–825, https://doi.org/10.5194/nhess-26-811-2026, https://doi.org/10.5194/nhess-26-811-2026, 2026
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We improved a computer model to simulate coastal flooding by including temporary barriers like sand dunes. We tested it where sand dunes are built seasonally to protect the shoreline for two real storms: one that broke through the dunes and another where dunes held strong. Our model showed how important it is to design these defenses carefully since even if a small part of a dune fails, a major flooding can happen. Overall, our work helps create better tools to manage and protect coastal areas.
Mahmud Hasan Ghani, Nadia Pinardi, Antonio Navarra, Lorenzo Mentaschi, Silvia Bianconcini, Francesco Maicu, and Francesco Trotta
Ocean Sci., 22, 427–441, https://doi.org/10.5194/os-22-427-2026, https://doi.org/10.5194/os-22-427-2026, 2026
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Using the same sea surface temperature and the same bulk formula but different atmospheric reanalysis and analysis surface-variable datasets, we show that a higher-resolution dataset is crucial for evaluating the heat-budget closure hypothesis in the Mediterranean Sea. For the first time, we investigate the impact of extreme heat-loss events in the Mediterranean Sea by computing the long-term, basin-averaged mean heat budget.
Paolo Oddo, Mario Adani, Francesco Carere, Andrea Cipollone, Anna Chiara Goglio, Eric Jansen, Ali Aydogdu, Francesca Mele, Italo Epicoco, Jenny Pistoia, Emanuela Clementi, Nadia Pinardi, and Simona Masina
Geosci. Model Dev., 19, 423–445, https://doi.org/10.5194/gmd-19-423-2026, https://doi.org/10.5194/gmd-19-423-2026, 2026
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This study present a data assimilation system that combines ocean observational data with ocean model results to better understand the ocean and predict its future state. The method uses a three dimensional incremental variational approach focusing on the physical relationships between all the state vector variables errors. Testing in the Mediterranean Sea showed that a complex sea level operator based on a barotropic model works best.
Joshua Coupe, Nicole S. Lovenduski, Luise S. Gleason, Michael N. Levy, Kristen Krumhardt, Keith Lindsay, Charles Bardeen, Clay Tabor, Cheryl Harrison, Kenneth G. MacLeod, Siddhartha Mitra, and Julio Sepúlveda
Geosci. Model Dev., 18, 8217–8234, https://doi.org/10.5194/gmd-18-8217-2025, https://doi.org/10.5194/gmd-18-8217-2025, 2025
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We have developed a new feature in the atmosphere and ocean components of the Community Earth System Model version 2 by implementing ultraviolet (UV) radiation inhibition of photosynthesis of four marine phytoplankton functional groups represented in the Marine Biogeochemistry Library. The new feature is tested with varying levels of UV radiation, and it will enable an analysis of an asteroid impact’s effect on the ozone layer and how that affects the base of the marine food web.
Seimur Shirinov, Ivan Federico, Simone Bonamano, Salvatore Causio, Nicolás Biocca, Viviana Piermattei, Daniele Piazzolla, Jacopo Alessandri, Lorenzo Mentaschi, Giovanni Coppini, Marco Marcelli, and Nadia Pinardi
Nat. Hazards Earth Syst. Sci., 25, 3737–3758, https://doi.org/10.5194/nhess-25-3737-2025, https://doi.org/10.5194/nhess-25-3737-2025, 2025
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This research investigates how seagrass meadows attenuate coastal waves. Our methodology integrates site measurements with numerical simulations, revealing that plant flexibility and seasonal growth cycles are crucial factors that enhance model fidelity for predicting wave damping. These insights aid ecosystem-based coastal protection and conservation of these vital habitats. Future work should address current–sediment–vegetation interactions for a more complete hydrodynamic understanding.
Malik J. Jordan, Emily F. Klee, Peter E. Hamlington, Nicole S. Lovenduski, and Kyle E. Niemeyer
EGUsphere, https://doi.org/10.5194/egusphere-2025-2901, https://doi.org/10.5194/egusphere-2025-2901, 2025
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We developed a method to simplify complex ocean biogeochemical models so they can run faster in computer simulations without losing important details. By adapting techniques from combustion science, we created smaller versions of a large ocean model that still accurately represent key changes in ocean biology and chemistry. This work helps make detailed ocean simulations more efficient, supporting better understanding of ocean health and climate.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
José A. Jiménez, Gundula Winter, Antonio Bonaduce, Michael Depuydt, Giulia Galluccio, Bart van den Hurk, H. E. Markus Meier, Nadia Pinardi, Lavinia G. Pomarico, and Natalia Vazquez Riveiros
State Planet, 3-slre1, 3, https://doi.org/10.5194/sp-3-slre1-3-2024, https://doi.org/10.5194/sp-3-slre1-3-2024, 2024
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The Knowledge Hub on Sea Level Rise (SLR) has done a scoping study involving stakeholders from government and academia to identify gaps and needs in SLR information, impacts, and policies across Europe. Gaps in regional SLR projections and uncertainties were found, while concerns were raised about shoreline erosion and emerging problems like saltwater intrusion and ineffective adaptation plans. The need for improved communication to make better decisions on SLR adaptation was highlighted.
Nadia Pinardi, Bart van den Hurk, Michael Depuydt, Thorsten Kiefer, Petra Manderscheid, Lavinia Giulia Pomarico, and Kanika Singh
State Planet, 3-slre1, 2, https://doi.org/10.5194/sp-3-slre1-2-2024, https://doi.org/10.5194/sp-3-slre1-2-2024, 2024
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The Knowledge Hub on Sea Level Rise (KH-SLR), a joint effort between JPI Climate and JPI Oceans, addresses the critical need for science-based information on sea level changes in Europe. The KH-SLR actively involves stakeholders through a co-design process discussing the impacts, adaptation planning, and policy requirements related to SLR in Europe. Its primary output is the KH Assessment Report (KH-AR), which is described in this volume.
Bart van den Hurk, Nadia Pinardi, Alexander Bisaro, Giulia Galluccio, José A. Jiménez, Kate Larkin, Angélique Melet, Lavinia Giulia Pomarico, Kristin Richter, Kanika Singh, Roderik van de Wal, and Gundula Winter
State Planet, 3-slre1, 1, https://doi.org/10.5194/sp-3-slre1-1-2024, https://doi.org/10.5194/sp-3-slre1-1-2024, 2024
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The Summary for Policymakers compiles findings from “Sea Level Rise in Europe: 1st Assessment Report of the Knowledge Hub on Sea Level Rise”. It covers knowledge gaps, observations, projections, impacts, adaptation measures, decision-making principles, and governance challenges. It provides information for each European basin (Mediterranean, Black Sea, North Sea, Baltic Sea, Atlantic, and Arctic) and aims to assist policymakers in enhancing the preparedness of European coasts for sea level rise.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
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Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Bethany McDonagh, Emanuela Clementi, Anna Chiara Goglio, and Nadia Pinardi
Ocean Sci., 20, 1051–1066, https://doi.org/10.5194/os-20-1051-2024, https://doi.org/10.5194/os-20-1051-2024, 2024
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Tides in the Mediterranean Sea are typically of low amplitude, but twin experiments with and without tides demonstrate that tides affect the circulation directly at scales away from those of the tides. Analysis of the energy changes due to tides shows that they enhance existing oscillations, and internal tides interact with other internal waves. Tides also increase the mixed layer depth and enhance deep water formation in key regions. Internal tides are widespread in the Mediterranean Sea.
Roberta Benincasa, Giovanni Liguori, Nadia Pinardi, and Hans von Storch
Ocean Sci., 20, 1003–1012, https://doi.org/10.5194/os-20-1003-2024, https://doi.org/10.5194/os-20-1003-2024, 2024
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Ocean dynamics result from the interplay of internal processes and external inputs, primarily from the atmosphere. It is crucial to discern between these factors to gauge the ocean's intrinsic predictability and to be able to attribute a signal under study to either external factors or internal variability. Employing a simple analysis, we successfully characterized this variability in the Mediterranean Sea and compared it with the oceanic response induced by atmospheric conditions.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
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Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
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Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Geneviève W. Elsworth, Nicole S. Lovenduski, Kristen M. Krumhardt, Thomas M. Marchitto, and Sarah Schlunegger
Biogeosciences, 20, 4477–4490, https://doi.org/10.5194/bg-20-4477-2023, https://doi.org/10.5194/bg-20-4477-2023, 2023
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Anthropogenic climate change will influence marine phytoplankton over the coming century. Here, we quantify the influence of anthropogenic climate change on marine phytoplankton internal variability using an Earth system model ensemble and identify a decline in global phytoplankton biomass variance with warming. Our results suggest that climate mitigation efforts that account for marine phytoplankton changes should also consider changes in phytoplankton variance driven by anthropogenic warming.
Giovanni Coppini, Emanuela Clementi, Gianpiero Cossarini, Stefano Salon, Gerasimos Korres, Michalis Ravdas, Rita Lecci, Jenny Pistoia, Anna Chiara Goglio, Massimiliano Drudi, Alessandro Grandi, Ali Aydogdu, Romain Escudier, Andrea Cipollone, Vladyslav Lyubartsev, Antonio Mariani, Sergio Cretì, Francesco Palermo, Matteo Scuro, Simona Masina, Nadia Pinardi, Antonio Navarra, Damiano Delrosso, Anna Teruzzi, Valeria Di Biagio, Giorgio Bolzon, Laura Feudale, Gianluca Coidessa, Carolina Amadio, Alberto Brosich, Arnau Miró, Eva Alvarez, Paolo Lazzari, Cosimo Solidoro, Charikleia Oikonomou, and Anna Zacharioudaki
Ocean Sci., 19, 1483–1516, https://doi.org/10.5194/os-19-1483-2023, https://doi.org/10.5194/os-19-1483-2023, 2023
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The paper presents the Mediterranean Forecasting System evolution and performance developed in the framework of the Copernicus Marine Service.
István Dunkl, Nicole Lovenduski, Alessio Collalti, Vivek K. Arora, Tatiana Ilyina, and Victor Brovkin
Biogeosciences, 20, 3523–3538, https://doi.org/10.5194/bg-20-3523-2023, https://doi.org/10.5194/bg-20-3523-2023, 2023
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Despite differences in the reproduction of gross primary productivity (GPP) by Earth system models (ESMs), ESMs have similar predictability of the global carbon cycle. We found that, although GPP variability originates from different regions and is driven by different climatic variables across the ESMs, the ESMs rely on the same mechanisms to predict their own GPP. This shows that the predictability of the carbon cycle is limited by our understanding of variability rather than predictability.
Umesh Pranavam Ayyappan Pillai, Nadia Pinardi, Ivan Federico, Salvatore Causio, Francesco Trotta, Silvia Unguendoli, and Andrea Valentini
Nat. Hazards Earth Syst. Sci., 22, 3413–3433, https://doi.org/10.5194/nhess-22-3413-2022, https://doi.org/10.5194/nhess-22-3413-2022, 2022
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The study presents the application of high-resolution coastal modelling for wave hindcasting on the Emilia-Romagna coastal belt. The generated coastal databases which provide an understanding of the prevailing wind-wave characteristics can aid in predicting coastal impacts.
Julian Quick, Ryan N. King, Garrett Barter, and Peter E. Hamlington
Wind Energ. Sci., 7, 1941–1955, https://doi.org/10.5194/wes-7-1941-2022, https://doi.org/10.5194/wes-7-1941-2022, 2022
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Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of alignment with the incoming wind, thereby steering wakes away from downstream turbines. Trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present an optimization approach for efficiently exploring the trade-offs between power and loading during wake steering.
Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, https://doi.org/10.5194/gmd-15-6451-2022, 2022
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The Earth system changes over a range of time and space scales, and some of these changes are predictable in advance. Short-term weather forecasts are most familiar, but recent work has shown that it is possible to generate useful predictions several seasons or even a decade in advance. This study focuses on predictions over intermediate timescales (up to 24 months in advance) and shows that there is promising potential to forecast a variety of changes in the natural environment.
Giorgio Micaletto, Ivano Barletta, Silvia Mocavero, Ivan Federico, Italo Epicoco, Giorgia Verri, Giovanni Coppini, Pasquale Schiano, Giovanni Aloisio, and Nadia Pinardi
Geosci. Model Dev., 15, 6025–6046, https://doi.org/10.5194/gmd-15-6025-2022, https://doi.org/10.5194/gmd-15-6025-2022, 2022
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The full exploitation of supercomputing architectures requires a deep revision of the current climate models. This paper presents the parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). Optimized numerical libraries were used to partition the model domain and solve the sparse linear system of equations in parallel. The performance assessment demonstrates a good level of scalability with a realistic configuration used as a benchmark.
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Short summary
The parameters that control a model's behavior determine its ability to represent a system. In this work, multiple cases test how to estimate the parameters of a model with components corresponding to both the physics and the chemical and biological processes (i.e. the biogeochemistry) of the ocean. While demonstrating how to approach this problem type, the results show estimating both sets of parameters simultaneously is better than estimating the physics then the biogeochemistry separately.
The parameters that control a model's behavior determine its ability to represent a system. In...
