Articles | Volume 11, issue 3
https://doi.org/10.5194/gmd-11-915-2018
© Author(s) 2018. 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-11-915-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
12 Mar 2018
Model description paper |
| 12 Mar 2018
| 12 Mar 2018
Modular System for Shelves and Coasts (MOSSCO v1.0) – a flexible and multi-component framework for coupled coastal ocean ecosystem modelling
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht Zentrum
für Material- und Küstenforschung, 21502 Geesthacht, Germany
Richard Hofmeister
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht Zentrum
für Material- und Küstenforschung, 21502 Geesthacht, Germany
Institute for Hydrobiology and Fisheries Science, Universität Hamburg, 22767 Hamburg, Germany
Knut Klingbeil
Department of Physical Oceanography and Instrumentation,
Leibniz-Institute for Baltic Sea Research, 18119 Rostock-Warnemünde, Germany
now at: Department of Mathematics, University of Hamburg, 20146 Hamburg, Germany
M. Hassan Nasermoaddeli
Section Estuary Systems I, Bundesanstalt für Wasserbau, 22559 Hamburg, Germany
now at: Landesbetrieb Straßen, Brücken und Gewässer, Freie und Hansestadt Hamburg, 20097 Hamburg, Germany
Onur Kerimoglu
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht Zentrum
für Material- und Küstenforschung, 21502 Geesthacht, Germany
Hans Burchard
Department of Physical Oceanography and Instrumentation,
Leibniz-Institute for Baltic Sea Research, 18119 Rostock-Warnemünde, Germany
Frank Kösters
Section Estuary Systems I, Bundesanstalt für Wasserbau, 22559 Hamburg, Germany
Kai W. Wirtz
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht Zentrum
für Material- und Küstenforschung, 21502 Geesthacht, Germany
Related authors
Hao-Cheng Yu, Yinglong Joseph Zhang, Lars Nerger, Carsten Lemmen, Jason C. S. Yu, Tzu-Yin Chou, Chi-Hao Chu, and Chuen-Teyr Terng
EGUsphere, https://doi.org/10.5194/egusphere-2022-114, https://doi.org/10.5194/egusphere-2022-114, 2022
Preprint archived
Short summary
Short summary
We develop a new data assimilative approach by combining two parallel frameworks: PDAF and ESMF. This allows maximum flexibility and easy implementation of data assimilation for fully coupled earth system model applications. It is also validated by using a simple benchmark and applied to a realistic case simulation around Taiwan. The real case test shows significant improvement for temperature, velocity and surface elevation before, during and after typhoon events.
Angelica Feurdean, Boris Vannière, Walter Finsinger, Dan Warren, Simon C. Connor, Matthew Forrest, Johan Liakka, Andrei Panait, Christian Werner, Maja Andrič, Premysl Bobek, Vachel A. Carter, Basil Davis, Andrei-Cosmin Diaconu, Elisabeth Dietze, Ingo Feeser, Gabriela Florescu, Mariusz Gałka, Thomas Giesecke, Susanne Jahns, Eva Jamrichová, Katarzyna Kajukało, Jed Kaplan, Monika Karpińska-Kołaczek, Piotr Kołaczek, Petr Kuneš, Dimitry Kupriyanov, Mariusz Lamentowicz, Carsten Lemmen, Enikö K. Magyari, Katarzyna Marcisz, Elena Marinova, Aidin Niamir, Elena Novenko, Milena Obremska, Anna Pędziszewska, Mirjam Pfeiffer, Anneli Poska, Manfred Rösch, Michal Słowiński, Miglė Stančikaitė, Marta Szal, Joanna Święta-Musznicka, Ioan Tanţău, Martin Theuerkauf, Spassimir Tonkov, Orsolya Valkó, Jüri Vassiljev, Siim Veski, Ildiko Vincze, Agnieszka Wacnik, Julian Wiethold, and Thomas Hickler
Biogeosciences, 17, 1213–1230, https://doi.org/10.5194/bg-17-1213-2020, https://doi.org/10.5194/bg-17-1213-2020, 2020
Short summary
Short summary
Our study covers the full Holocene (the past 11 500 years) climate variability and vegetation composition and provides a test on how vegetation and climate interact to determine fire hazard. An important implication of this test is that percentage of tree cover can be used as a predictor of the probability of fire occurrence. Biomass burned is highest at ~ 45 % tree cover in temperate forests and at ~ 60–65 % tree cover in needleleaf-dominated forests.
Derek T. Robinson, Alan Di Vittorio, Peter Alexander, Almut Arneth, C. Michael Barton, Daniel G. Brown, Albert Kettner, Carsten Lemmen, Brian C. O'Neill, Marco Janssen, Thomas A. M. Pugh, Sam S. Rabin, Mark Rounsevell, James P. Syvitski, Isaac Ullah, and Peter H. Verburg
Earth Syst. Dynam., 9, 895–914, https://doi.org/10.5194/esd-9-895-2018, https://doi.org/10.5194/esd-9-895-2018, 2018
Short summary
Short summary
Understanding the complexity behind the rapid use of Earth’s resources requires modelling approaches that couple human and natural systems. We propose a framework that comprises the configuration, frequency of interaction, and coordination of communication between models along with eight lessons as guidelines to increase the success of coupled human–natural systems modelling initiatives. We also suggest a way to expedite model coupling and increase the longevity and interoperability of models.
Robert Lepper, Leon Jänicke, Ingo Hache, Christian Jordan, and Frank Kösters
EGUsphere, https://doi.org/10.5194/egusphere-2024-283, https://doi.org/10.5194/egusphere-2024-283, 2024
Short summary
Short summary
Coastal environments are often sheltered by intertidal flats and salt-marshes. These environments are at severe risk from drowning under sea level rise. Recent analyses in the Wadden Sea demonstrated tidal flats grew faster than the local mean sea level contrary to expectation. We found that tidal high and low water increased proportionally with SLR while coastal bathymetry evolution caused spatially-varying tidal adaptation with sharp increase-decrease edges at the coast.
Pia Kolb, Anna Zorndt, Hans Burchard, Ulf Gräwe, and Frank Kösters
Ocean Sci., 18, 1725–1739, https://doi.org/10.5194/os-18-1725-2022, https://doi.org/10.5194/os-18-1725-2022, 2022
Short summary
Short summary
River engineering measures greatly changed tidal dynamics in the Weser estuary. We studied the effect on saltwater intrusion with numerical models. Our analysis shows that a deepening of the navigation channel causes saltwater to intrude further into the Weser estuary. This effect is mostly masked by the natural variability of river discharge. In our study, it proved essential to recalibrate individual hindcast models due to differences in sediments, bed forms, and underlying bathymetric data.
Hao-Cheng Yu, Yinglong Joseph Zhang, Lars Nerger, Carsten Lemmen, Jason C. S. Yu, Tzu-Yin Chou, Chi-Hao Chu, and Chuen-Teyr Terng
EGUsphere, https://doi.org/10.5194/egusphere-2022-114, https://doi.org/10.5194/egusphere-2022-114, 2022
Preprint archived
Short summary
Short summary
We develop a new data assimilative approach by combining two parallel frameworks: PDAF and ESMF. This allows maximum flexibility and easy implementation of data assimilation for fully coupled earth system model applications. It is also validated by using a simple benchmark and applied to a realistic case simulation around Taiwan. The real case test shows significant improvement for temperature, velocity and surface elevation before, during and after typhoon events.
Vera Fofonova, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021, https://doi.org/10.5194/gmd-14-6945-2021, 2021
Short summary
Short summary
We present a test case of river plume spreading to evaluate coastal ocean models. Our test case reveals the level of numerical mixing (due to parameterizations used and numerical treatment of processes in the model) and the ability of models to reproduce complex dynamics. The major result of our comparative study is that accuracy in reproducing the analytical solution depends less on the type of applied model architecture or numerical grid than it does on the type of advection scheme.
Qing Li, Jorn Bruggeman, Hans Burchard, Knut Klingbeil, Lars Umlauf, and Karsten Bolding
Geosci. Model Dev., 14, 4261–4282, https://doi.org/10.5194/gmd-14-4261-2021, https://doi.org/10.5194/gmd-14-4261-2021, 2021
Short summary
Short summary
Different ocean vertical mixing schemes are usually developed in different modeling framework, making the comparison across such schemes difficult. Here, we develop a consistent framework for testing, comparing, and applying different ocean mixing schemes by integrating CVMix into GOTM, which also extends the capability of GOTM towards including the effects of ocean surface waves. A suite of test cases and toolsets for developing and evaluating ocean mixing schemes is also described.
Robert Hagen, Andreas Plüß, Romina Ihde, Janina Freund, Norman Dreier, Edgar Nehlsen, Nico Schrage, Peter Fröhle, and Frank Kösters
Earth Syst. Sci. Data, 13, 2573–2594, https://doi.org/10.5194/essd-13-2573-2021, https://doi.org/10.5194/essd-13-2573-2021, 2021
Short summary
Short summary
We established an open-access, integrated marine data collection for 1996 to 2015 in the German Bight as a database of scientific, economic, and governmental interest. This paper presents data for tidal elevation, depth-averaged current velocity, bottom shear stress, depth-averaged salinity, and wave parameters and spectra at a high temporal and spatial resolution. Data are additionally processed into meaningful parameters (i.e., tidal characteristic values, e.g., tidal range) for accessibility.
Onur Kerimoglu, Yoana G. Voynova, Fatemeh Chegini, Holger Brix, Ulrich Callies, Richard Hofmeister, Knut Klingbeil, Corinna Schrum, and Justus E. E. van Beusekom
Biogeosciences, 17, 5097–5127, https://doi.org/10.5194/bg-17-5097-2020, https://doi.org/10.5194/bg-17-5097-2020, 2020
Short summary
Short summary
In this study, using extensive field observations and a numerical model, we analyzed the physical and biogeochemical structure of a coastal system following an extreme flood event. Our results suggest that a number of anomalous observations were driven by a co-occurrence of peculiar meteorological conditions and increased riverine discharges. Our results call for attention to the combined effects of hydrological and meteorological extremes that are anticipated to increase in frequency.
Angelica Feurdean, Boris Vannière, Walter Finsinger, Dan Warren, Simon C. Connor, Matthew Forrest, Johan Liakka, Andrei Panait, Christian Werner, Maja Andrič, Premysl Bobek, Vachel A. Carter, Basil Davis, Andrei-Cosmin Diaconu, Elisabeth Dietze, Ingo Feeser, Gabriela Florescu, Mariusz Gałka, Thomas Giesecke, Susanne Jahns, Eva Jamrichová, Katarzyna Kajukało, Jed Kaplan, Monika Karpińska-Kołaczek, Piotr Kołaczek, Petr Kuneš, Dimitry Kupriyanov, Mariusz Lamentowicz, Carsten Lemmen, Enikö K. Magyari, Katarzyna Marcisz, Elena Marinova, Aidin Niamir, Elena Novenko, Milena Obremska, Anna Pędziszewska, Mirjam Pfeiffer, Anneli Poska, Manfred Rösch, Michal Słowiński, Miglė Stančikaitė, Marta Szal, Joanna Święta-Musznicka, Ioan Tanţău, Martin Theuerkauf, Spassimir Tonkov, Orsolya Valkó, Jüri Vassiljev, Siim Veski, Ildiko Vincze, Agnieszka Wacnik, Julian Wiethold, and Thomas Hickler
Biogeosciences, 17, 1213–1230, https://doi.org/10.5194/bg-17-1213-2020, https://doi.org/10.5194/bg-17-1213-2020, 2020
Short summary
Short summary
Our study covers the full Holocene (the past 11 500 years) climate variability and vegetation composition and provides a test on how vegetation and climate interact to determine fire hazard. An important implication of this test is that percentage of tree cover can be used as a predictor of the probability of fire occurrence. Biomass burned is highest at ~ 45 % tree cover in temperate forests and at ~ 60–65 % tree cover in needleleaf-dominated forests.
Johannes Pein, Annika Eisele, Richard Hofmeister, Tina Sanders, Ute Daewel, Emil V. Stanev, Justus van Beusekom, Joanna Staneva, and Corinna Schrum
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-265, https://doi.org/10.5194/bg-2019-265, 2019
Revised manuscript not accepted
Short summary
Short summary
The Elbe estuary is subject to vigorous tidal forcing from the sea side and considerable biological inputs from the land side. Our 3D numerical coupled physical-biogeochemical integrates these forcing signals and provides highly realistic hindcasts of the associated dynamics. Model simulations show that the freshwater part of Elbe estuary is inhabited by plankton. According to simulations these organism play a key role in converting organic inputs into nitrate, the major inorganic nutrient.
Marvin Lorenz, Knut Klingbeil, Parker MacCready, and Hans Burchard
Ocean Sci., 15, 601–614, https://doi.org/10.5194/os-15-601-2019, https://doi.org/10.5194/os-15-601-2019, 2019
Short summary
Short summary
Estuaries are areas where riverine and oceanic waters meet and mix. The exchange flow of an estuary describes the water properties of the inflowing and outflowing water. These can be described by simple bulk values for volume fluxes and salinities. This work focuses on the numerics of one computational method for these values, the Total Exchange Flow. We show that only the so-called dividing salinity method is able to reliably calculate the correct values, even for complex situations.
Derek T. Robinson, Alan Di Vittorio, Peter Alexander, Almut Arneth, C. Michael Barton, Daniel G. Brown, Albert Kettner, Carsten Lemmen, Brian C. O'Neill, Marco Janssen, Thomas A. M. Pugh, Sam S. Rabin, Mark Rounsevell, James P. Syvitski, Isaac Ullah, and Peter H. Verburg
Earth Syst. Dynam., 9, 895–914, https://doi.org/10.5194/esd-9-895-2018, https://doi.org/10.5194/esd-9-895-2018, 2018
Short summary
Short summary
Understanding the complexity behind the rapid use of Earth’s resources requires modelling approaches that couple human and natural systems. We propose a framework that comprises the configuration, frequency of interaction, and coordination of communication between models along with eight lessons as guidelines to increase the success of coupled human–natural systems modelling initiatives. We also suggest a way to expedite model coupling and increase the longevity and interoperability of models.
Onur Kerimoglu, Richard Hofmeister, Joeran Maerz, Rolf Riethmüller, and Kai W. Wirtz
Biogeosciences, 14, 4499–4531, https://doi.org/10.5194/bg-14-4499-2017, https://doi.org/10.5194/bg-14-4499-2017, 2017
Short summary
Short summary
In this study, we present a coupled physical–biogeochemical model, in which the acclimation of autotrophs to their resource environment is resolved based on optimality arguments. The model is implemented in the southern North Sea, a shallow coastal system. Based on comparisons with multiple data sources, we show that the model can reproduce the variability in the system for the period 2000–2010 and analyze the mechanisms driving the large-scale, persistent coastal gradients in the system.
Burkard Baschek, Friedhelm Schroeder, Holger Brix, Rolf Riethmüller, Thomas H. Badewien, Gisbert Breitbach, Bernd Brügge, Franciscus Colijn, Roland Doerffer, Christiane Eschenbach, Jana Friedrich, Philipp Fischer, Stefan Garthe, Jochen Horstmann, Hajo Krasemann, Katja Metfies, Lucas Merckelbach, Nino Ohle, Wilhelm Petersen, Daniel Pröfrock, Rüdiger Röttgers, Michael Schlüter, Jan Schulz, Johannes Schulz-Stellenfleth, Emil Stanev, Joanna Staneva, Christian Winter, Kai Wirtz, Jochen Wollschläger, Oliver Zielinski, and Friedwart Ziemer
Ocean Sci., 13, 379–410, https://doi.org/10.5194/os-13-379-2017, https://doi.org/10.5194/os-13-379-2017, 2017
Short summary
Short summary
The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the heavily used German Bight in the North Sea. The automated observing and modelling system is designed to monitor real-time conditions, to provide short-term forecasts and data products, and to assess the impact of anthropogenically induced change.
Maria Moreno de Castro, Markus Schartau, and Kai Wirtz
Biogeosciences, 14, 1883–1901, https://doi.org/10.5194/bg-14-1883-2017, https://doi.org/10.5194/bg-14-1883-2017, 2017
Short summary
Short summary
Observations from different mesocosms exposed to the same treatment level typically show variability that hinders the detection of potential treatments effects. To unearth relevant sources of variability, we developed and performed a data-based model analysis that simulates uncertainty propagation. With this method we investigate the divergence in the outcomes due to the amplification of differences in experimentally unresolved ecological factors within replicates of the same treatment level.
Joeran Maerz, Richard Hofmeister, Eefke M. van der Lee, Ulf Gräwe, Rolf Riethmüller, and Kai W. Wirtz
Biogeosciences, 13, 4863–4876, https://doi.org/10.5194/bg-13-4863-2016, https://doi.org/10.5194/bg-13-4863-2016, 2016
Short summary
Short summary
We investigated sinking velocity (ws) of suspended particulate matter (SPM) in the German Bight. By inferring ws indirectly from an extensive turbidity data set and hydrodynamic model results, we found enhanced ws in a coastal transition zone. Combined with known residual circulation patterns, this led to a new conceptual understanding of the retention of fine minerals and nutrients in shallow coastal areas. The retention is likely modulated by algal excretions enhancing flocculation of SPM.
A. Plüß and F. Kösters
Adv. Geosci., 39, 61–68, https://doi.org/10.5194/adgeo-39-61-2014, https://doi.org/10.5194/adgeo-39-61-2014, 2014
Related subject area
Climate and Earth system modeling
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
CD-type discretization for sea ice dynamics in FESOM version 2
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)
Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach
Towards the definition of a solar forcing dataset for CMIP7
ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)
Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region
Constraining the carbon cycle in JULES-ES-1.0
The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2
GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data
The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation
Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1
Monsoon Mission Coupled Forecast System version 2.0: model description and Indian monsoon simulations
Exploring the ocean mesoscale at reduced computational cost with FESOM 2.5: efficient modeling strategies applied to the Southern Ocean
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid-ammonia nucleation
Truly conserving with conservative remapping methods
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia
Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc
Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts
Understanding changes in cloud simulations from E3SM version 1 to version 2
WRF (v4.0)–SUEWS (v2018c) coupled system: development, evaluation and application
Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a)
Deep learning model based on multi-scale feature fusion for precipitation nowcasting
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Getting the leaves right matters for estimating temperature extremes
The Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative: scientific objectives and experimental design
Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
Short summary
Short summary
Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
Short summary
Short summary
We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
Short summary
Short summary
Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
Short summary
Short summary
Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
Short summary
Short summary
Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
Short summary
Short summary
We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Short summary
This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
Short summary
Short summary
The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
Short summary
Short summary
This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
Short summary
Short summary
Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
Short summary
Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
Short summary
Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
Short summary
Short summary
This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
Short summary
Short summary
Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
Short summary
Short summary
Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
Short summary
Short summary
We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
Short summary
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
Short summary
Short summary
As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
Short summary
Short summary
In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
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
Short summary
This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
Short summary
Short summary
A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
Short summary
Short summary
Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
Short summary
Short summary
Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
Short summary
Short summary
The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
Short summary
Short summary
We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
Short summary
Short summary
This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
Short summary
Short summary
By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
Short summary
Short summary
We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
Short summary
Short summary
Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
Short summary
Short summary
We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
Short summary
Short summary
We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
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
Short summary
Short summary
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.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
Short summary
Short summary
This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
Short summary
Short summary
This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
Short summary
Short summary
The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
Short summary
Short summary
The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
Short summary
Short summary
Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Carl Svenhag, Moa Kristina Sporre, Tinja Olenius, Daniel Yazgi, Sara Marie Blichner, Lars Peter Nieradzik, and Pontus Roldin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2665, https://doi.org/10.5194/egusphere-2023-2665, 2024
Short summary
Short summary
Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we showed that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacted the number of particles in the air and clouds. It also changed the radiation balance in the same magnitude as man-made greenhouse emissions.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
Short summary
Short summary
Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
Short summary
Short summary
This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
Short summary
Short summary
We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
Short summary
Short summary
The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
Short summary
Short summary
We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
Short summary
Short summary
For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
Short summary
Short summary
Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
Short summary
Short summary
This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
Short summary
Short summary
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
Short summary
Short summary
Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
Short summary
Short summary
Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
Short summary
Short summary
Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Cited articles
Alexander, K. and Easterbrook, S. M.: The software architecture of climate
models: a graphical comparison of CMIP5 and EMICAR5 configurations, Geosci.
Model Dev., 8, 1221–1232, https://doi.org/10.5194/gmd-8-1221-2015, 2015. a
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2:
an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model
Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. a
Azhikodan, G. and Yokoyama, K.: Spatio-temporal variability of phytoplankton
(Chlorophyll-a) in relation to salinity, suspended sediment concentration,
and light intensity in a macrotidal estuary, Cont. Shelf Res., 126, 15–26,
https://doi.org/10.1016/j.csr.2016.07.006, 2016. a
Balaji, V., Adcroft, A., and Liang, Z.: Gridspec: A standard for the
description of grids used in Earth System models, Tech. rep., National
Oceanographic and Atmospheric Administration, Princeton, NJ, 2007. a
Balaji, V., Benson, R., Wyman, B., and Held, I.: Coarse-grained component
concurrency in Earth system modeling: parallelizing atmospheric radiative
transfer in the GFDL AM3 model using the Flexible Modeling System coupling
framework, Geosci. Model Dev., 9, 3605–3616,
https://doi.org/10.5194/gmd-9-3605-2016, 2016. a
Bayne, B. L., Iglesias, J., and Hawkins, A. J. S.: Feeding behaviour of the
mussel, Mytilus edulis: responses to variations in quantity and organic
content of the seston, J. Mar. Biol. Assoc. UK, 73, 813–829, 1993. a
Breugem, W. A. and Holthuijsen, L. H.: Generalized Shallow Water Wave Growth
from Lake George, J. Waterw. Port. C., 133, 173–182,
https://doi.org/10.1061/(ASCE)0733-950X(2007)133:3(173), 2007. a
Bruggeman, J. and Bolding, K.: A general framework for aquatic
biogeochemical models, Environ. Model. Softw., 61, 249–265,
https://doi.org/10.1016/j.envsoft.2014.04.002, 2014. a, b, c
Burchard, H. and Bolding, K.: GETM – a General Estuarine Transport Model.
Scientific Documentation, Tech. Rep. EUR 20253 EN, European Commission,
2002. a
Burchard, H., Bolding, K., and Villarreal, M. R.: GOTM – a General Ocean
Turbulence Model. Theory, implementation and test cases, Tech. Rep. EUR
18745 EN, European Commission, 1999. a
Burchard, H., Deleersnijder, E., and Meister, A.: Application of modified
Patankar schemes to stiff biogeochemical models for the water column, Ocean
Dynam., 55, 326–337, https://doi.org/10.1007/s10236-005-0001-x, 2005. a
Burchard, H., Bolding, K., Kühn, W., Meister, A., Neumann, T., and
Umlauf, L.: Description of a flexible and extendable
physical–biogeochemical model system for the water column, J. Marine Syst.,
61, 180–211, https://doi.org/10.1016/j.jmarsys.2005.04.011, 2006. a
Butenschön, M., Clark, J., Aldridge, J. N., Allen, J. I., Artioli, Y.,
Blackford, J., Bruggeman, J., Cazenave, P., Ciavatta, S., Kay, S., Lessin,
G., van Leeuwen, S., van der Molen, J., de Mora, L., Polimene, L., Sailley,
S., Stephens, N., and Torres, R.: ERSEM 15.06: a generic model for marine
biogeochemistry and the ecosystem dynamics of the lower trophic levels,
Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016,
2016. a
Cazenave, P. W., Torres, R., and Allen, J. I.: Unstructured grid modelling
of offshore wind farm impacts on seasonally stratified shelf seas, Prog.
Oceanogr., 145, 25–41, https://doi.org/10.1016/j.pocean.2016.04.004, 2016. a
Cossarini, G., Querin, S., Solidoro, C., Sannino, G., Lazzari, P., Di Biagio,
V., and Bolzon, G.: Development of BFMCOUPLER (v1.0), the coupling scheme
that links the MITgcm and BFM models for ocean biogeochemistry simulations,
Geosci. Model Dev., 10, 1423–1445, https://doi.org/10.5194/gmd-10-1423-2017,
2017. a
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new
version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10,
3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017. a
Daewel, U. and Schrum, C.: Simulating long-term dynamics of the coupled
North Sea and Baltic Sea ecosystem with ECOSMO II: Model description and
validation, J. Marine Syst., 119-120, 30–49,
https://doi.org/10.1016/j.jmarsys.2013.03.008, 2013. a
de Deckere, E. M. G. T., Tolhurst, T. J., and de Brouwer, J. F. C.:
Destabilization of cohesive intertidal sediments by infauna, Estuar. Coast.
Shelf S., 53, 665–669, https://doi.org/10.1006/ecss.2001.0811, 2001. a
de Laat, P. B.: Governance of open source software: state of the art, J.
Manage. Govern., 11, 165–177, https://doi.org/10.1007/s10997-007-9022-9, 2007. a
Dunlap, R.: Effective reuse of coupling technologies for Earth System
Models, PhD thesis, Georgia Institute of Technology, 2013. a
Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W.,
Shevliakova, E., Stouffer, R. J., Cooke, W., Dunne, K. A., Harrison, M. J.,
Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Phillipps, P. J., Sentman,
L. T., Samuels, B. L., Spelman, M. J., Winton, M., Wittenberg, A. T., and
Zadeh, N.: GFDL's ESM2 Global Coupled Climate–Carbon Earth System Models –
Part I: Physical Formulation and Baseline Simulation Characteristics, J.
Climate, 25, 6646–6665, https://doi.org/10.1175/JCLI-D-11-00560.1, 2012. a
ESMF Joint Specification Team: Earth System Modeling Framework User Guide
Version 6.3.0, Tech. rep., National Oceanic and Atmospheric Administration,
Boulder, CO, 2013. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R.
J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project
Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9,
1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Geyer, B.: High-resolution atmospheric reconstruction for Europe 1948–2012:
coastDat2, Earth Syst. Sci. Data, 6, 147–164, https://doi.org/10.5194/essd-6-147-2014,
2014. a
Gräwe, U., Holtermann, P., Klingbeil, K., and Burchard, H.: Advantages
of vertically adaptive coordinates in numerical models of stratified shelf
seas, Ocean Model., 92, 56–68, https://doi.org/10.1016/j.ocemod.2015.05.008, 2015. a
Harms, I.: Water mass transformation in the Barents Sea – application of
the Hamburg Shelf Ocean Model (HamSOM), ICES J. Mar. Sci., 54, 351–365,
https://doi.org/10.1006/jmsc.1997.0226, 1997. a
Hinners, J., Hofmeister, R., and Hense, I.: Modeling the Role of pH on
Baltic Sea Cyanobacteria, Life, 5, 1204–1217, https://doi.org/10.3390/life5021204,
2015. a
Hofmeister, R., Burchard, H., and Beckers, J.-M.: Non-uniform adaptive
vertical grids for 3D numerical ocean models, Ocean Model., 33, 70–86,
2010. a
Hofmeister, R., Lemmen, C., Kerimoglu, O., Wirtz, K. W., and Nasermoaddeli,
M. H.: The predominant processes controlling vertical nutrient and suspended
matter fluxes across domains – using the new MOSSCO system form coastal sea
sediments up to the atmosphere, in: 11th International Conference on
Hydroscience and Engineering, edited by: Lehfeldt, R. and Kopmann, vol. 28,
Hamburg, Germany, 2014. a, b
Hofmeister, R., Flöser, G., and Schartau, M.: Estuary-type circulation
as a factor sustaining horizontal nutrient gradients in freshwater-influenced
coastal systems, Geo.-Mar. Lett., 37, 179–192,
https://doi.org/10.1007/s00367-016-0469-z, 2017. a
Hu, F., Bolding, K., Bruggeman, J., Jeppesen, E., Flindt, M. R., van Gerven,
L., Janse, J. H., Janssen, A. B. G., Kuiper, J. J., Mooij, W. M., and Trolle,
D.: FABM-PCLake – linking aquatic ecology with hydrodynamics, Geosci. Model
Dev., 9, 2271–2278, https://doi.org/10.5194/gmd-9-2271-2016, 2016. a
Jaffrés, J. B. D.: The Oceanographic and Geochemical Effects of Mixed
Layer Depth Variability and Increasing Anthropogenic CO2 on the Inorganic
Carbon System of the Coral Sea, PhD thesis, James Cook University, 2011. a
Jagers, H. R. A. B.: Linking Data , Models and Tools: An Overview, in:
International Environmental Modelling and Software, edited by: Swayne, D. A.,
Yang, W., Voinov, A. A., Rizzoli, A., Filatova, T., Ottawa, Canada, 2010. a
Jöckel, P., Sander, R., Kerkweg, A., Tost, H., and Lelieveld, J.:
Technical Note: The Modular Earth Submodel System (MESSy) – a new approach
towards Earth System Modeling, Atmos. Chem. Phys., 5, 433–444,
https://doi.org/10.5194/acp-5-433-2005, 2005. a
Jones, P. W.: First- and Second-Order Conservative Remapping Schemes for
Grids in Spherical Coordinates, Mon. Weather Rev., 127, 2204–2210,
https://doi.org/10.1175/1520-0493(1999)127<2204:FASOCR>2.0.CO;2, 1999. a
Kerimoglu, O., Hofmeister, R., Maerz, J., Riethmüller, R., and Wirtz, K.
W.: The acclimative biogeochemical model of the southern North Sea,
Biogeosciences, 14, 4499–4531, https://doi.org/10.5194/bg-14-4499-2017, 2017. a, b, c, d
Kerkweg, A. and Jöckel, P.: The 1-way on-line coupled atmospheric
chemistry model system MECO(n) – Part 1: Description of the limited-area
atmospheric chemistry model COSMO/MESSy, Geosci. Model Dev., 5, 87–110,
https://doi.org/10.5194/gmd-5-87-2012, 2012. a
Klingbeil, K. and Burchard, H.: Implementation of a direct nonhydrostatic
pressure gradient discretisation into a layered ocean model, Ocean Model.,
65, 64–77, https://doi.org/10.1016/j.ocemod.2013.02.002, 2013. a
Krause, D. and Thörnig, P.: JURECA: General-purpose supercomputer at
Jülich Supercomputing Centre, J. Large-Scale Res. Fac. JLSRF, 2, A62,
https://doi.org/10.17815/jlsrf-2-121, 2016. a
Lorkowski, I., Pätsch, J., Moll, A., and Kühn, W.: Interannual
variability of carbon fluxes in the North Sea from 1970 to 2006 – Competing
effects of abiotic and biotic drivers on the gas-exchange of CO2, Estuar.
Coast. Shelf S., 100, 38–57, https://doi.org/10.1016/j.ecss.2011.11.037, 2012. a
Lovelock, J. E. and Margulis, L.: Atmospheric homeostasis by and for the
biosphere: the gaia hypothesis, Tellus, 26, 2–10,
https://doi.org/10.1111/j.2153-3490.1974.tb01946.x, 1974. a
Maerz, J., Verney, R., Wirtz, K. W., and Feudel, U.: Modeling flocculation
processes: Intercomparison of a size class-based model and a
distribution-based model, Cont. Shelf Res., 31, S84–S93,
https://doi.org/10.1016/j.csr.2010.05.011, 2011. a
Manabe, S.: Climate and the ocean circulation II. The atmospheric
circulation and the effect of heat transfer by ocean currents, Mon. Weather
Rev., 97, 775–805, 1969. a
Margalef, R.: On Certain Unifying Principles in Ecology, Am. Nat., 97,
357–374, https://doi.org/10.1086/282286, 1963. a
Meursedoif, Y.: ios: An efficient and highly configurable parallel output
library for climate modeling, in: Second Workshop on Coupling Technologies
for Earth System Models, Boulder, CO, USA, 20–22 February, 2013. a
Moghimi, S., Klingbeil, K., Gräwe, U., and Burchard, H.: A direct
comparison of a depth-dependent Radiation stress formulation and a Vortex
force formulation within a three-dimensional coastal ocean model, Ocean
Model., 70, 132–144, https://doi.org/10.1016/j.ocemod.2012.10.002, 2013. a
Nasermoaddeli, M. H., Lemmen, C., Hofmeister, R., Kösters, F., and
Klingbeil, K.: The Benthic Geoecology Model within the Modular System for
Shelves and Coasts (MOSSCO), in: 11th International Conference on
Hydroinformatics, New York City, USA, 17–21 August, 2014. a
Nasermoaddeli, M., Lemmen, C., Kösters, F., Stigge, G., Kerimoglu, O.,
Burchard, H., Klingbeil, K., Hofmeister, R., Kreus, M., and Wirtz, K.: A
model study on the large-scale effect of macrofauna on the suspended sediment
concentration in a shallow shelf sea, Estuar. Coast. Shelf S., in press,
https://doi.org/10.1016/j.ecss.2017.11.002, 2018. a, b, c, d, e
Partheniades, E.: Erosion and Deposition of Cohesive Soils, J. Hydr. Eng.
Div.-ASCE, 91, 105–139, 1965. a
Peckham, S. D.: The CSDMS Standard Names: Cross-Domain Naming Conventions
for Describing Process Models, Data Sets and Their Associated Variables, 7th
Int. Congress on Env. Modelling and Software, edited by: Ames, D. P., Quinn,
N. W. T., Rizzoli, A. E., International Environmental Modelling and Software
Society (iEMSs), San Diego, California, USA, 2014. a, b
Peckham, S. D., Hutton, E. W., and Norris, B.: A component-based approach to
integrated modeling in the geosciences: The design of CSDMS, Comput.
Geosci., 53, 3–12, https://doi.org/10.1016/j.cageo.2012.04.002, 2013. a, b, c, d
Pelupessy, I., van Werkhoven, B., van Elteren, A., Viebahn, J., Candy, A.,
Portegies Zwart, S., and Dijkstra, H.: The Oceanographic Multipurpose
Software Environment (OMUSE v1.0), Geosci. Model Dev., 10, 3167–3187,
https://doi.org/10.5194/gmd-10-3167-2017, 2017. a
Rew, R. and Davis, G.: NetCDF: An Interface for Scientific Data Access,
IEEE Comput. Graph., 10, 76–82, https://doi.org/10.1109/38.56302, 1990. a, b
Ruckelshaus, M., Klinger, T., Knowlton, N., and DeMaster, D. P.: Marine
Ecosystem-based Management in Practice: Scientific and Governance
Challenges, Bioscience, 58, 53–63, https://doi.org/10.1641/B580110, 2008. a
Scheliga, K. S., Pampel, H., Bernstein, E., Bruch, C., zu Castell, W.,
Diesmann, M., Fritzsch, B., Fuhrmann, J., Haas, H., Hammitzsch, M.,
Lähnemann, D., McHardy, A., Konrad, U., Scharnberg, G., Schreiber, A.,
and Steglich, D.: Helmholtz Open Science Workshop “Zugang zu und
Nachnutzung von wissenschaftlicher Software”#hgfos16, Tech. rep.,
Deutsches GeoForschungsZentrum GFZ, Potsdam, https://doi.org/10.2312/lis.17.01, 2016. a
Shang, Q. Q., Fang, H. W., Zhao, H. M., He, G. J., and Cui, Z. H.: Biofilm
effects on size gradation, drag coefficient and settling velocity of sediment
particles, Int. J. Sediment Res., 29, 471–480,
https://doi.org/10.1016/S1001-6279(14)60060-3, 2014. a
Shore, J.: Fail fast, IEEE Software, 21, 21–25,
https://doi.org/10.1109/MS.2004.1331296, 2004. a
Soetaert, K., Herman, P. M. J., and Middelburg, J. J.: Dynamic response of
deep-sea sediments to seasonal variations: A model, Limnol. Oceanogr., 41,
1651–1668, 1996. a
Suarez, M., Trayanov, A., da Silva, A., Hill, C., and Schopf, P.: An
Introduction to MAPL, Tech. rep., Goddard Fluid Dynamics Laboratory,
Princeton, NJ, 2007. a
Tansley, A. G.: The Use and Abuse of Vegetational Concepts and Terms,
Ecology, 16, 284–307, https://doi.org/10.2307/1930070, 1935. a
Theurich, G., DeLuca, C., Campbell, T., et al.: The Earth System Prediction
Suite: Toward a Coordinated U.S. Modeling Capability, B. Am. Meteorol. Soc.,
97, 1229–1247, https://doi.org/10.1175/BAMS-D-14-00164.1, 2016. a
Turuncoglu, U. U. and Sannino, G.: Validation of newly designed regional
earth system model (RegESM) for Mediterranean Basin, Clim. Dynam., 48,
2919–2947, https://doi.org/10.1007/s00382-016-3241-1, 2017. a
Turuncoglu, U. U., Giuliani, G., Elguindi, N., and Giorgi, F.: Modelling the
Caspian Sea and its catchment area using a coupled regional atmosphere-ocean
model (RegCM4-ROMS): model design and preliminary results, Geosci. Model
Dev., 6, 283–299, https://doi.org/10.5194/gmd-6-283-2013, 2013. a
Van Pham, T., Brauch, J., Dieterich, C., Frueh, B., and Ahrens, B.: New
coupled atmosphere-ocean-ice system COSMO-CLM/NEMO: assessing air temperature
sensitivity over the North and Baltic Seas, Oceanologia, 56, 167–189,
https://doi.org/10.5697/oc.56-2.167, 2014. a
van Rijn, L. C.: Unified View of Sediment Transport by Currents and Waves –
II: Suspended Transport, J. Hydraul. Eng., 133, 668–689,
https://doi.org/10.1061/(ASCE)0733-9429(2007)133:6(668), 2007. a
Vernadsky, V. I.: The Biosphere, Springer, 1998. a
Warner, J. C., Perlin, N., and Skyllingstad, E. D.: Using the Model Coupling
Toolkit to couple earth system models, Environ. Model. Softw., 23,
1240–1249, https://doi.org/10.1016/j.envsoft.2008.03.002, 2008. a
Warner, J. C., Armstrong, B., He, R., and Zambon, J. B.: Development of a
Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) Modeling
System, Ocean Model., 35, 230–244, https://doi.org/10.1016/j.ocemod.2010.07.010,
2010. a
Wirtz, K. W. and Kerimoglu, O.: Autotrophic Stoichiometry Emerging from
Optimality and Variable Co-limitation, Front. Ecol. Environ., 4, 131,
https://doi.org/10.3389/fevo.2016.00131, 2016. a
Yakushev, E. V., Protsenko, E. A., Bruggeman, J., Wallhead, P., Pakhomova, S.
V., Yakubov, S. Kh., Bellerby, R. G. J., and Couture, R.-M.: Bottom RedOx
Model (BROM v.1.1): a coupled benthic–pelagic model for simulation of water
and sediment biogeochemistry, Geosci. Model Dev., 10, 453–482,
https://doi.org/10.5194/gmd-10-453-2017, 2017. a
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M:
Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc.,
141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a
Short summary
To describe coasts in a computer model, many processes have to be represented, from the air to the water to the ocean floor, from different scientific disciplines. No existing computer model adequately addresses this complexity. We present the Modular System for Shelves and Coasts (MOSSCO), which embraces this diversity and flexibly connects several tens of individual process models. MOSSCO also makes it easier to bring local knowledge to the Earth system level.
To describe coasts in a computer model, many processes have to be represented, from the air to...
