Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-4663-2020
© Author(s) 2020. 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-13-4663-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
02 Oct 2020
Model description paper |
| 02 Oct 2020
| 02 Oct 2020
Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 1: Implementation and model behaviour
Markus Pahlow
CORRESPONDING AUTHOR
GEOMAR Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany
Chia-Te Chien
GEOMAR Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany
Lionel A. Arteaga
Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA
present address: NASA Global Modeling and Assimilation Office, Universities Space Research Association, Columbia, MD, USA
Andreas Oschlies
GEOMAR Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany
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Jaard Hauschildt, Soeren Thomsen, Vincent Echevin, Andreas Oschlies, Yonss Saranga José, Gerd Krahmann, Laura A. Bristow, and Gaute Lavik
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Mariana Hill Cruz, Iris Kriest, Yonss Saranga José, Rainer Kiko, Helena Hauss, and Andreas Oschlies
Biogeosciences, 18, 2891–2916, https://doi.org/10.5194/bg-18-2891-2021, https://doi.org/10.5194/bg-18-2891-2021, 2021
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Chia-Te Chien, Markus Pahlow, Markus Schartau, and Andreas Oschlies
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Sabine Mathesius, Julia Getzlaff, Heiner Dietze, Andreas Oschlies, and Markus Schartau
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Iris Kriest, Paul Kähler, Wolfgang Koeve, Karin Kvale, Volkmar Sauerland, and Andreas Oschlies
Biogeosciences, 17, 3057–3082, https://doi.org/10.5194/bg-17-3057-2020, https://doi.org/10.5194/bg-17-3057-2020, 2020
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Fabian Reith, Wolfgang Koeve, David P. Keller, Julia Getzlaff, and Andreas Oschlies
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Tronje P. Kemena, Angela Landolfi, Andreas Oschlies, Klaus Wallmann, and Andrew W. Dale
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Daniela Niemeyer, Iris Kriest, and Andreas Oschlies
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Yonss Saranga José, Lothar Stramma, Sunke Schmidtko, and Andreas Oschlies
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-155, https://doi.org/10.5194/bg-2019-155, 2019
Revised manuscript accepted for BG
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In situ observations along the Peruvian and Chilean coasts have exhibited variability in the water column oxygen concentration. This variability, which is attributed to the El Niño Southern Oscillation (ENSO), might have implication on the vertical extension of the Eastern Tropical South Pacific (ETSP) oxygen minimum zone. Here using a coupled physical-biogeochemical model, we provide new insights into how ENSO variability affects the vertical extension of the oxygen-poor waters of the ETSP.
Olaf Duteil, Andreas Oschlies, and Claus W. Böning
Biogeosciences, 15, 7111–7126, https://doi.org/10.5194/bg-15-7111-2018, https://doi.org/10.5194/bg-15-7111-2018, 2018
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Oxygen-depleted regions of the Pacific Ocean are currently expanding, which is threatening marine habitats. Based on numerical simulations, we show that the decrease in the intensity of the trade winds and the subsequent slowdown of the oceanic currents lead to a reduction in oxygen supply. Our study suggests that the prevailing positive conditions of the Pacific Decadal Oscillation since 1975, a major source of natural variability, may explain a significant part of the current deoxygenation.
Marine Bretagnon, Aurélien Paulmier, Véronique Garçon, Boris Dewitte, Séréna Illig, Nathalie Leblond, Laurent Coppola, Fernando Campos, Federico Velazco, Christos Panagiotopoulos, Andreas Oschlies, J. Martin Hernandez-Ayon, Helmut Maske, Oscar Vergara, Ivonne Montes, Philippe Martinez, Edgardo Carrasco, Jacques Grelet, Olivier Desprez-De-Gesincourt, Christophe Maes, and Lionel Scouarnec
Biogeosciences, 15, 5093–5111, https://doi.org/10.5194/bg-15-5093-2018, https://doi.org/10.5194/bg-15-5093-2018, 2018
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In oxygen minimum zone, the fate of the organic matter is a key question as the low oxygen condition would preserve the OM and thus enhance the biological carbon pump while the high microbial activity would foster the remineralisation and the greenhouse gases emission. To investigate this paradigm, sediment traps were deployed off Peru. We pointed out the influence of the oxygenation as well as the organic matter quantity and quality on the carbon transfer efficiency in the oxygen minimum zone.
Volkmar Sauerland, Ulrike Löptien, Claudine Leonhard, Andreas Oschlies, and Anand Srivastav
Geosci. Model Dev., 11, 1181–1198, https://doi.org/10.5194/gmd-11-1181-2018, https://doi.org/10.5194/gmd-11-1181-2018, 2018
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We present a concept to prove that a parametric model is well calibrated, i.e., that changes of its free parameters cannot lead to a much better model–data misfit anymore. The intention is motivated by the fact that calibrating global biogeochemical ocean models is important for assessment and inter-model comparison but computationally expensive.
Nadine Mengis, David P. Keller, and Andreas Oschlies
Earth Syst. Dynam., 9, 15–31, https://doi.org/10.5194/esd-9-15-2018, https://doi.org/10.5194/esd-9-15-2018, 2018
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The Systematic Correlation Matrix Evaluation (SCoMaE) method applies statistical information to systematically select, transparent, nonredundant indicators for a comprehensive assessment of the Earth system state. We show that due to changing climate forcing, such as anthropogenic climate change, the ad hoc assessment indicators might need to be reevaluated. Within an iterative process, this method would allow us to select scientifically consistent and societally relevant assessment indicators.
Karin F. Kvale, Samar Khatiwala, Heiner Dietze, Iris Kriest, and Andreas Oschlies
Geosci. Model Dev., 10, 2425–2445, https://doi.org/10.5194/gmd-10-2425-2017, https://doi.org/10.5194/gmd-10-2425-2017, 2017
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James C. Orr, Raymond G. Najjar, Olivier Aumont, Laurent Bopp, John L. Bullister, Gokhan Danabasoglu, Scott C. Doney, John P. Dunne, Jean-Claude Dutay, Heather Graven, Stephen M. Griffies, Jasmin G. John, Fortunat Joos, Ingeborg Levin, Keith Lindsay, Richard J. Matear, Galen A. McKinley, Anne Mouchet, Andreas Oschlies, Anastasia Romanou, Reiner Schlitzer, Alessandro Tagliabue, Toste Tanhua, and Andrew Yool
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The Ocean Model Intercomparison Project (OMIP) is a model comparison effort under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Its physical component is described elsewhere in this special issue. Here we describe its ocean biogeochemical component (OMIP-BGC), detailing simulation protocols and analysis diagnostics. Simulations focus on ocean carbon, other biogeochemical tracers, air-sea exchange of CO2 and related gases, and chemical tracers used to evaluate modeled circulation.
Daniela Niemeyer, Tronje P. Kemena, Katrin J. Meissner, and Andreas Oschlies
Earth Syst. Dynam., 8, 357–367, https://doi.org/10.5194/esd-8-357-2017, https://doi.org/10.5194/esd-8-357-2017, 2017
Markus Schartau, Philip Wallhead, John Hemmings, Ulrike Löptien, Iris Kriest, Shubham Krishna, Ben A. Ward, Thomas Slawig, and Andreas Oschlies
Biogeosciences, 14, 1647–1701, https://doi.org/10.5194/bg-14-1647-2017, https://doi.org/10.5194/bg-14-1647-2017, 2017
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Plankton models have become an integral part in marine ecosystem and biogeochemical research. These models differ in complexity and in their number of parameters. How values are assigned to parameters is essential. An overview of major methodologies of parameter estimation is provided. Aspects of parameter identification in the literature are diverse. Individual findings could be better synthesized if notation and expertise of the different scientific communities would be reasonably merged.
Yonss Saranga José, Heiner Dietze, and Andreas Oschlies
Biogeosciences, 14, 1349–1364, https://doi.org/10.5194/bg-14-1349-2017, https://doi.org/10.5194/bg-14-1349-2017, 2017
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This study aims to investigate the diverse subsurface nutrient patterns observed within anticyclonic eddies in the upwelling system off Peru. Two simulated anticyclonic eddies with opposing subsurface nitrate concentrations were analysed. The results show that diverse nutrient patterns within anticyclonic eddies are related to the presence of water mass from different origins at different depths, responding to variations in depth of the circulation strength at the edge of the eddy.
Iris Kriest, Volkmar Sauerland, Samar Khatiwala, Anand Srivastav, and Andreas Oschlies
Geosci. Model Dev., 10, 127–154, https://doi.org/10.5194/gmd-10-127-2017, https://doi.org/10.5194/gmd-10-127-2017, 2017
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Global biogeochemical ocean models are subject to a high level of parametric uncertainty. This may be of consequence for their skill with respect to accurately describing features of the present ocean and their sensitivity to possible environmental changes. We present the first results from a framework that combines an offline biogeochemical tracer transport model with an estimation of distribution algorithm, calibrating six biogeochemical model parameters against observed oxygen and nutrients.
Fabian Reith, David P. Keller, and Andreas Oschlies
Earth Syst. Dynam., 7, 797–812, https://doi.org/10.5194/esd-7-797-2016, https://doi.org/10.5194/esd-7-797-2016, 2016
Bei Su, Markus Pahlow, and Andreas Oschlies
Biogeosciences, 13, 4985–5001, https://doi.org/10.5194/bg-13-4985-2016, https://doi.org/10.5194/bg-13-4985-2016, 2016
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Previously identified positive feedbacks within the nitrogen cycle in the eastern tropical South Pacific (ETSP) have challenged our understanding of the observed dynamics and stability of the nitrogen inventory. We present a box model analysis of the biological and biogeochemical relations in the ETSP among nitrogen deposition, benthic denitrification and phosphate regeneration. Our results suggest dominant stabilizing feedbacks tending to keep a balanced nitrogen inventory in the ETSP.
Carolin R. Löscher, Hermann W. Bange, Ruth A. Schmitz, Cameron M. Callbeck, Anja Engel, Helena Hauss, Torsten Kanzow, Rainer Kiko, Gaute Lavik, Alexandra Loginova, Frank Melzner, Judith Meyer, Sven C. Neulinger, Markus Pahlow, Ulf Riebesell, Harald Schunck, Sören Thomsen, and Hannes Wagner
Biogeosciences, 13, 3585–3606, https://doi.org/10.5194/bg-13-3585-2016, https://doi.org/10.5194/bg-13-3585-2016, 2016
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The ocean loses oxygen due to climate change. Addressing this issue in tropical ocean regions (off Peru and Mauritania), we aimed to understand the effects of oxygen depletion on various aspects of marine biogeochemistry, including primary production and export production, the nitrogen cycle, greenhouse gas production, organic matter fluxes and remineralization, and the role of zooplankton and viruses.
I. Kriest and A. Oschlies
Geosci. Model Dev., 8, 2929–2957, https://doi.org/10.5194/gmd-8-2929-2015, https://doi.org/10.5194/gmd-8-2929-2015, 2015
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We use a global model of oceanic P, N, and O2 cycles to investigate consequences of uncertainties in description of organic matter sinking, remineralization, denitrification, and N2-Fixation. After all biogeochemical and physical processes have been spun-up into a dynamically consistent steady-state, particle sinking and oxidant affinities of aerobic and anaerobic remineralization determine the extent of oxygen minimum zones, global nitrogen fluxes, and the oceanic nitrogen inventory.
W. Koeve, H. Wagner, P. Kähler, and A. Oschlies
Geosci. Model Dev., 8, 2079–2094, https://doi.org/10.5194/gmd-8-2079-2015, https://doi.org/10.5194/gmd-8-2079-2015, 2015
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The natural abundance of 14C in CO2 dissolved in seawater is often used to evaluate circulation and age in the ocean and in ocean models. We study limitations of using natural 14C to determine the time elapsed since water had contact with the atmosphere. We find that, globally, bulk 14C age is dominated by two equally important components, (1) the time component of circulation and (2) the “preformed 14C-age”. Considering preformed 14C-age is critical for an assessment of circulation in models.
L. Nickelsen, D. P. Keller, and A. Oschlies
Geosci. Model Dev., 8, 1357–1381, https://doi.org/10.5194/gmd-8-1357-2015, https://doi.org/10.5194/gmd-8-1357-2015, 2015
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In this paper we find that including the marine cycle of the phytoplankton nutrient iron in a global climate model improves the agreement between observed and simulated nutrient concentrations in the ocean and that a better description of the source of iron from the sediment to the ocean is more important than that of iron-containing dust deposition. Finally, we find that the response of the iron cycle to climate warming affects the phytoplankton growth and nutrient cycles.
B. Su, M. Pahlow, H. Wagner, and A. Oschlies
Biogeosciences, 12, 1113–1130, https://doi.org/10.5194/bg-12-1113-2015, https://doi.org/10.5194/bg-12-1113-2015, 2015
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A box model of the eastern tropical South Pacific oxygen minimum zone suggests that anaerobic water-column remineralization rates have to be slower than aerobic remineralization in order to explain the relatively high values of observed nitrate concentrations. Lateral oxygen supply sufficient to oxidize about one-fifth of the export production is required to prevent an anoxic deep ocean. Under these circumstances, the region can be a net source of fixed nitrogen to the surrounding ocean.
W. Koeve, O. Duteil, A. Oschlies, P. Kähler, and J. Segschneider
Geosci. Model Dev., 7, 2393–2408, https://doi.org/10.5194/gmd-7-2393-2014, https://doi.org/10.5194/gmd-7-2393-2014, 2014
A. E. F. Prowe, M. Pahlow, S. Dutkiewicz, and A. Oschlies
Biogeosciences, 11, 3397–3407, https://doi.org/10.5194/bg-11-3397-2014, https://doi.org/10.5194/bg-11-3397-2014, 2014
I. Kriest and A. Oschlies
Biogeosciences, 10, 8401–8422, https://doi.org/10.5194/bg-10-8401-2013, https://doi.org/10.5194/bg-10-8401-2013, 2013
O. Duteil, W. Koeve, A. Oschlies, D. Bianchi, E. Galbraith, I. Kriest, and R. Matear
Biogeosciences, 10, 7723–7738, https://doi.org/10.5194/bg-10-7723-2013, https://doi.org/10.5194/bg-10-7723-2013, 2013
C. J. Somes, A. Oschlies, and A. Schmittner
Biogeosciences, 10, 5889–5910, https://doi.org/10.5194/bg-10-5889-2013, https://doi.org/10.5194/bg-10-5889-2013, 2013
V. Cocco, F. Joos, M. Steinacher, T. L. Frölicher, L. Bopp, J. Dunne, M. Gehlen, C. Heinze, J. Orr, A. Oschlies, B. Schneider, J. Segschneider, and J. Tjiputra
Biogeosciences, 10, 1849–1868, https://doi.org/10.5194/bg-10-1849-2013, https://doi.org/10.5194/bg-10-1849-2013, 2013
A. Landolfi, H. Dietze, W. Koeve, and A. Oschlies
Biogeosciences, 10, 1351–1363, https://doi.org/10.5194/bg-10-1351-2013, https://doi.org/10.5194/bg-10-1351-2013, 2013
M. El Jarbi, J. Rückelt, T. Slawig, and A. Oschlies
Biogeosciences, 10, 1169–1182, https://doi.org/10.5194/bg-10-1169-2013, https://doi.org/10.5194/bg-10-1169-2013, 2013
L. M. Zamora, A. Oschlies, H. W. Bange, K. B. Huebert, J. D. Craig, A. Kock, and C. R. Löscher
Biogeosciences, 9, 5007–5022, https://doi.org/10.5194/bg-9-5007-2012, https://doi.org/10.5194/bg-9-5007-2012, 2012
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A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
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Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
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TorchClim v1.0: a deep-learning plugin for climate model physics
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GOSI9: UK Global Ocean and Sea Ice configurations
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Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Deifilia Aurora To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
EGUsphere, https://doi.org/10.5194/egusphere-2024-1714, https://doi.org/10.5194/egusphere-2024-1714, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers three-dimensional atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20–30%. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases accessibility of training and working with the model.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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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 show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Maria Rosa Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-73, https://doi.org/10.5194/gmd-2024-73, 2024
Revised manuscript accepted for GMD
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Observational data and modelling capabilities are expanding in recent years, but there are still barriers preventing these two data sources to be used in synergy. Proper comparison requires generating, storing and handling a large amount of data. This manuscript describes the first step in the development of a new set of software tools, the ‘VISION toolkit’, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
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We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-97, https://doi.org/10.5194/gmd-2024-97, 2024
Revised manuscript accepted for GMD
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Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-70, https://doi.org/10.5194/gmd-2024-70, 2024
Revised manuscript accepted for GMD
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Hurricanes may worsen the water quality in the lower Mississippi River Basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate-nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in LMRB during Hurricane Ida in 2021, but less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni G. Seijo-Ellis, Donata Giglio, Gustavo M. Marques, and Frank O. Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1378, https://doi.org/10.5194/egusphere-2024-1378, 2024
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A CESM/MOM6 regional configuration of the Caribbean Sea was developed as a response to the rising need of high-resolution models for climate impact studies. The configuration is validated for the period of 2000–2020 and improves significant errors in a low resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon river are well captured and the mean flows across the multiple passages in the Caribbean Sea agree with observations.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Catherine Guiavarc'h, Dave Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene T. Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
EGUsphere, https://doi.org/10.5194/egusphere-2024-805, https://doi.org/10.5194/egusphere-2024-805, 2024
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GOSI9 is the new UK’s hierarchy of global ocean and sea ice models. Developed as part of a collaboration between several UK research institutes it will be used for various applications such as weather forecast and climate prediction. The models, based on NEMO, are available at three resolutions 1°, ¼° and 1/12°. GOSI9 improves upon previous version by reducing global temperature and salinity biases and enhancing the representation of the Arctic sea ice and of the Antarctic Circumpolar Current.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Cited articles
Ågren, G. I.: The C : N : P stoichiometry of autotrophs – theory and
observations, Ecol. Lett., 7, 185–191,
https://doi.org/10.1111/j.1461-0248.2004.00567.x, 2004. a
Anderson, L. A. and Sarmiento, J. L.: Redfield ratios of remineralization
determined by nutrient data analysis, Global Biogeochem. Cycles, 8, 65–80,
https://doi.org/10.1029/93GB03318, 1994. a
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020. a
Arteaga, L., Pahlow, M., and Oschlies, A.: Global patterns of phytoplankton
nutrient and light colimitation inferred from an optimality-based model,
Global Biogeochem. Cycles, 28, 648–661, https://doi.org/10.1002/2013GB004668, 2014. a
Arteaga, L., Pahlow, M., and Oschlies, A.: Modelled Chl:C ratio and derived
estimates of phytoplankton carbon biomass and its contribution to total
particulate organic carbon in the global surface ocean, Global Biogeochem.
Cycles, 30, 1791–1810, https://doi.org/10.1002/2016GB005458, 2016. a, b
Behrenfeld, M. J. and Falkowski, P. G.: Photosynthetic rates derived from
satellite-based chlorophyll concentration, Limnol. Oceanogr., 42, 1–20,
https://doi.org/10.4319/lo.1997.42.1.0001, 1997. a
Bopp, L., Resplandy, L., Orr, J. C., Doney, S. C., Dunne, J. P., Gehlen, M., Halloran, P., Heinze, C., Ilyina, T., Séférian, R., Tjiputra, J., and Vichi, M.: Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models, Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, 2013. a
Carr, M.-E., Friedrichs, M. A., Schmeltz, M., Noguchi Aita, M., Antoine, D., Arrigo, K. R., Asanuma, I., Aumont, O., Barber, R., Behrenfeld, M., Bidigare, R., Buitenhuis, E. T., Campbell, J., Ciotti, A., Dierssen, H., Dowell, M., Dunne, J., Esaias, W., Gentili, B., Gregg, W., Groom, S., Hoepffner, N., Ishizaka, J., Kameda, T., Le Quéré, C., Lohrenz, S., Marra, J., Mélin, F., Moore, K., Morel, A., Reddy, T. E., Ryan, J., Scardi, M., Smyth, T., Turpie, K., Tilstone, G., Waters, K., and Yamanaka, Y.: A
comparison of global estimates of marine primary production from ocean color,
Deep-Sea Res. Pt. II, 53, 741–770, https://doi.org/10.1016/j.dsr2.2006.01.028, 2006. a
Chen, B. and Smith, S. L.: Optimality-based approach for computationally
efficient modeling of phytoplankton growth, chlorophyll-to-carbon, and
nitrogen-to-carbon ratios, Ecol. Model., 385, 197–212,
https://doi.org/10.1016/j.ecolmodel.2018.08.001, 2018. a
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System Model Version 2 (CESM2), J. Adv.
Model. Earth Syst., 12, e2019MS001916, https://doi.org/10.1029/2019ms001916, 2020. a
Deutsch, C., Sarmiento, J. L., Sigman, D. M., Gruber, N., and Dunne, J. P.:
Spatial coupling of nitrogen inputs and losses in the ocean, Nature, 445,
163–167, https://doi.org/10.1038/nature05392, 2007. a
DeVries, T. and Weber, T.: The export and fate of organic matter in the ocean:
New constraints from combining satellite and oceanographic tracer
observations, Global Biogeochem. Cycles, 31, 535–555,
https://doi.org/10.1002/2016GB005551, 2017. a
DeVries, T., Deutsch, C., Primeau, F., Chang, B., and Devol, A.: Global rates
of water-column denitrification derived from nitrogen gas measurements,
Nature Geosci., 5, 547–550, https://doi.org/10.1038/ngeo1515, 2012. a
Ducklow, H. W. and Doney, S. C.: What Is the Metabolic State of the
Oligotrophic Ocean? A Debate, Annu. Rev. Mar. Sci., 5, 525–533,
https://doi.org/10.1146/annurev-marine-121211-172331, 2013. a
Dunne, J. P., Armstrong, R. A., Gnanadesikan, A., and Sarmiento, J. L.:
Empirical and mechanistic models for the particle export ratio, Global
Biogeochem. Cycles, 19, GB4026, https://doi.org/10.1029/2004GB002390, 2005. 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
Eby, M., Zickfeld, K., Montenegro, A., Archer, D., Meissner, K. J., and Weaver,
A. J.: Lifetime of Anthropogenic Climate Change: Millennial Time Scales of
Potential CO2 and Surface Temperature Perturbations, J. Climate, 22,
2501–2511, https://doi.org/10.1175/2008JCLI2554.1, 2009. a, b
Eby, M., Weaver, A. J., Alexander, K., Zickfeld, K., Abe-Ouchi, A., Cimatoribus, A. A., Crespin, E., Drijfhout, S. S., Edwards, N. R., Eliseev, A. V., Feulner, G., Fichefet, T., Forest, C. E., Goosse, H., Holden, P. B., Joos, F., Kawamiya, M., Kicklighter, D., Kienert, H., Matsumoto, K., Mokhov, I. I., Monier, E., Olsen, S. M., Pedersen, J. O. P., Perrette, M., Philippon-Berthier, G., Ridgwell, A., Schlosser, A., Schneider von Deimling, T., Shaffer, G., Smith, R. S., Spahni, R., Sokolov, A. P., Steinacher, M., Tachiiri, K., Tokos, K., Yoshimori, M., Zeng, N., and Zhao, F.: Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity, Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, 2013. a
Fernández-Castro, B., Pahlow, M., Mouriño-Carballido, B.,
Marañón, E., and Oschlies, A.: Optimality-based Trichodesmium
Diazotrophy in the North Atlantic Subtropical Gyre, J. Plankton Res., 38,
946–963, https://doi.org/10.1093/plankt/fbw047, 2016. a, b, c, d
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Mishonov, A. V.,
Baranova, O. K., Zweng, M. M., Reagan, J. R., and Johnson, D. R.: Dissolved
Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation, in: World Ocean
Atlas 2013, edited by: Levitus, S., vol. 3, NOAA Atlas NESDIS 75, available at:
http://www.nodc.noaa.gov/OC5/indprod.html (last access: 1 August 2018), 2013a. a, b
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Mishonov, A. V.,
Baranova, O. K., Zweng, M. M., Reagan, J. R., and Johnson, D. R.: Dissolved
Inorganic Nutrients (phosphate, nitrate, silicate), in: World Ocean Atlas
2013, edited by: Levitus, S., vol. 4, NOAA Atlas NESDIS 76, available at:
http://www.nodc.noaa.gov/OC5/indprod.html (last access: 1 August 2018), 2013b. a, b
Getzlaff, J. and Dietze, H.: Effects of increased isopycnal diffusivity
mimicking the unresolved equatorial intermediate current system in an earth
system climate model, Geophys. Res. Lett., 40, 2166–2170,
https://doi.org/10.1002/grl.50419, 2013. a, b
Gismervik, I.: Numerical and functional responses of choreo- and oligotrich
planktonic ciliates, Aquat. Microb. Ecol., 40, 163–173,
https://doi.org/10.3354/ame040163, 2005. a
Gruber, N.: The dynamics of the marine nitrogen cycle and its influence on
atmospheric CO2 variations, in: The Ocean Carbon Cycle and Climate,
edited by: Follows, M. and Oguz, T., pp. 97–148, Kluwer, Dordrecht, 2004. a
Gruber, N. and Sarmiento, J. L.: Global Patterns of marine nitrogen fixation
and denitrification, Global Biogeochem. Cycles, 11, 235–266,
https://doi.org/10.1029/97GB00077, 1997. a
Holling, C. S. and Buckingham, S.: A behavioral model of predator-prey
functional responses, Behav. Sci., 21, 183–195, https://doi.org/10.1002/bs.3830210305,
1976. a
Houlton, B. Z., Wang, Y.-P., Vitousek, P. M., and Field, C. B.: A unifying
framework for dinitrogen fixation in the terrestrial biosphere, Nature, 454,
327–330, https://doi.org/10.1038/nature07028, 2008. a, b, c, d
Hu, C., Lee, Z., and Franz, B.: Chlorophyll a algorithms for oligotrophic
oceans: A novel approach based on three-band reflectance difference, J.
Geophys. Res.-Oceans, 117, C01011, https://doi.org/10.1029/2011jc007395, 2012. a, b
Hülse, D., Arndt, S., Wilson, J. D., Munhoven, G., and Ridgwell, A.:
Understanding the causes and consequences of past marine carbon cycling
variability through models, Earth Sci. Rev., 171, 349–382,
https://doi.org/10.1016/j.earscirev.2017.06.004, 2017. a
Keller, D. P., Lenton, A., Scott, V., Vaughan, N. E., Bauer, N., Ji, D., Jones, C. D., Kravitz, B., Muri, H., and Zickfeld, K.: The Carbon Dioxide Removal Model Intercomparison Project (CDRMIP): rationale and experimental protocol for CMIP6, Geosci. Model Dev., 11, 1133–1160, https://doi.org/10.5194/gmd-11-1133-2018, 2018. a
Key, R., Olsen, A., van Heuven, S., Lauvset, S. K., Velo, A., Lin, X.,
Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S.,
Steinfeldt, R., Jeansson, E., Ishi, M., Perez, F. F., and Suzuki, T.: Global
Ocean Data Analysis Project, Version 2 (GLODAPv2), ORNL/CDIAC-162, NDP-P093,
Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US
Department of Energy, https://doi.org/10.3334/CDIAC/OTG.NDP093_GLODAPv2, 2015. a, b
Kiørboe, T., Møhlenberg, F., and Hamburger, K.: Bioenergetics of the
planktonic copepod Acartia tonsa: relation between feeding, egg
production and respiration, and composition of specific dynamic action, Mar.
Ecol. Prog. Ser., 26, 85–97, https://doi.org/10.3354/meps026085, 1985. a
Klausmeier, C. A., Litchman, E., Daufresne, T., and Levin, S. A.: Phytoplankton
stoichiometry, Ecol. Res., 23, 479–485, https://doi.org/10.1007/s11284-008-0470-8,
2008. a
Kriest, I.: Calibration of a simple and a complex model of global marine biogeochemistry, Biogeosciences, 14, 4965–4984, https://doi.org/10.5194/bg-14-4965-2017, 2017. a, b
Kriest, I. and Oschlies, A.: MOPS-1.0: towards a model for the regulation of the global oceanic nitrogen budget by marine biogeochemical processes, Geosci. Model Dev., 8, 2929–2957, https://doi.org/10.5194/gmd-8-2929-2015, 2015. a
Krishna, S., Pahlow, M., and Schartau, M.: Comparison of two carbon-nitrogen
regulatory models calibrated with mesocosm data, Ecol. Model., 411, 108711,
https://doi.org/10.1016/j.ecolmodel.2019.05.016, 2019. a
Kvale, K. F., Khatiwala, S., Dietze, H., Kriest, I., and Oschlies, A.: Evaluation of the transport matrix method for simulation of ocean biogeochemical tracers, Geosci. Model Dev., 10, 2425–2445, https://doi.org/10.5194/gmd-10-2425-2017, 2017. a, b
Kwiatkowski, L., Aumont, O., Bopp, L., and Ciais, P.: The Impact of Variable
Phytoplankton Stoichiometry on Projections of Primary Production, Food
Quality, and Carbon Uptake in the Global Ocean, Global Biogeochem. Cycles,
32, 516–528, https://doi.org/10.1002/2017gb005799, 2018. a
Landolfi, A., Dietze, H., Koeve, W., and Oschlies, A.: Overlooked runaway feedback in the marine nitrogen cycle: the vicious cycle, Biogeosciences, 10, 1351–1363, https://doi.org/10.5194/bg-10-1351-2013, 2013. a
Landolfi, A., Kaehler, P., Koeve, W., and Oschlies, A.: Global Marine N2
Fixation Estimates: From Observations to Models, Front. Microbiol., 9, 2112,
https://doi.org/10.3389/fmicb.2018.02112, 2018. a
Laufkötter, C., Vogt, M., Gruber, N., Aita-Noguchi, M., Aumont, O., Bopp, L., Buitenhuis, E., Doney, S. C., Dunne, J., Hashioka, T., Hauck, J., Hirata, T., John, J., Le Quéré, C., Lima, I. D., Nakano, H., Seferian, R., Totterdell, I., Vichi, M., and Völker, C.: Drivers and uncertainties of future global marine primary production in marine ecosystem models, Biogeosciences, 12, 6955–6984, https://doi.org/10.5194/bg-12-6955-2015, 2015. a
Lauvset, S. K., Key, R. M., Olsen, A., van Heuven, S., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Perez, F. F., Suzuki, T., and Watelet, S.: A new global interior ocean mapped climatology: the 1∘ × 1∘ GLODAP version 2, Earth Syst. Sci. Data, 8, 325–340, https://doi.org/10.5194/essd-8-325-2016, 2016. a, b
Laws, E. A., Falkowski, P. G., Walker O. Smith, J., Ducklow, H., and McCarthy,
J. J.: Temperature effects on export production in the open ocean, Global
Biogeochem. Cycles, 14, 1231–1246, https://doi.org/10.1029/1999GB001229, 2000. a
Lessard, E. J. and Murrell, M. C.: Microzooplankton herbivory and phytoplankton
growth in the northwestern Sargasso Sea, Aquat. Microb. Ecol., 16,
173–188, https://doi.org/10.3354/ame016173, 1998. a
Letscher, R. T. and Moore, J. K.: Preferential remineralization of dissolved
organic phosphorus and non-Redfield DOM dynamics in the global ocean:
Impacts on marine productivity, nitrogen fixation, and carbon export, Global
Biogeochem. Cycles, 29, 2014GB004904, https://doi.org/10.1002/2014GB004904, 2015. a
Löptien, U. and Dietze, H.: Effects of parameter indeterminacy in pelagic
biogeochemical modules of Earth System Models on projections into a warming
future: the scale of the problem, Global Biogeochem. Cycles, 31, 1155–1172,
https://doi.org/10.1002/2017GB005690, 2017. a
Löscher, C. R., Mohr, W., Bange, H. W., and Canfield, D. E.: No nitrogen fixation in the Bay of Bengal?, Biogeosciences, 17, 851–864, https://doi.org/10.5194/bg-17-851-2020, 2020. a
Luo, Y.-W., Doney, S. C., Anderson, L. A., Benavides, M., Berman-Frank, I., Bode, A., Bonnet, S., Boström, K. H., Böttjer, D., Capone, D. G., Carpenter, E. J., Chen, Y. L., Church, M. J., Dore, J. E., Falcón, L. I., Fernández, A., Foster, R. A., Furuya, K., Gómez, F., Gundersen, K., Hynes, A. M., Karl, D. M., Kitajima, S., Langlois, R. J., LaRoche, J., Letelier, R. M., Marañón, E., McGillicuddy Jr., D. J., Moisander, P. H., Moore, C. M., Mouriño-Carballido, B., Mulholland, M. R., Needoba, J. A., Orcutt, K. M., Poulton, A. J., Rahav, E., Raimbault, P., Rees, A. P., Riemann, L., Shiozaki, T., Subramaniam, A., Tyrrell, T., Turk-Kubo, K. A., Varela, M., Villareal, T. A., Webb, E. A., White, A. E., Wu, J., and Zehr, J. P.: Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates, Earth Syst. Sci. Data, 4, 47–73, https://doi.org/10.5194/essd-4-47-2012, 2012. a, b, c, d, e, f
Martiny, A. C., Vrugt, J. A., and Lomas, M. W.: Concentrations and ratios of
particulate organic carbon, nitrogen, and phosphorus in the global ocean,
Sci. Data, 1, 140048, https://doi.org/10.1038/sdata.2014.48, 2014. a, b, c
Matrai, P. A. and Keller, M. D.: Total organic sulfur and
dimethylsulfoniopropionate in marine phytoplankton: intracellular variations,
Mar. Biol., 119, 61–68, https://doi.org/10.1007/BF00350107, 1994. a
Millero, F. J., Fiol, S., Campbell, D. M., and Parilla, G.: Carbon dioxide,
hydrographic, and chemical data obtained during the R/V Hespérides
cruise in the Atlantic Ocean (WOCE section A5, July 14–August
15, 1992), Carbon Dioxide Information Analysis Center, Oak Ridge National
Laboratory, U.S. Department of Energy, https://doi.org/10.3334/CDIAC/otg.ndp074, 2000. a, b
Mills, M. M., Brown, Z. W., Lowry, K. E., van Dijken, G. L., Becker, S., Pal,
S., Benitez-Nelson, C. R., Downer, M. M., Strong, A. L., Swift, J. H.,
Pickart, R. S., and Arrigo, K. R.: Impacts of low phytoplankton
Monteiro, F. M. and Follows, M. J.: On nitrogen fixation and preferential
remineralization of phosphorus, Geophys. Res. Lett., 39, L06607,
https://doi.org/10.1029/2012GL050897, 2012. a
Monteiro, F. M., Dutkiewicz, S., and Follows, M. J.: Biogeographical controls
on the marine nitrogen fixers, Global Biogeochem. Cycles, 25, GB2003,
https://doi.org/10.1029/2010GB003902, 2011. a
Mulholland, M. R., Bernhardt, P. W., Widner, B. N., Selden, C. R., Chappell,
P. D., Clayton, S., Mannino, A., and Hyde, K.: High Rates of N2 Fixation
in Temperate, Western North Atlantic Coastal Waters Expand the Realm of
Marine Diazotrophy, Global Biogeochem. Cycles, 33, 826–840,
https://doi.org/10.1029/2018gb006130, 2019. a, b
Niemeyer, D., Kemena, T. P., Meissner, K. J., and Oschlies, A.: A model study of warming-induced phosphorus–oxygen feedbacks in open-ocean oxygen minimum zones on millennial timescales, Earth Syst. Dynam., 8, 357–367, https://doi.org/10.5194/esd-8-357-2017, 2017. a, b
Norberg, J.: Biodiversity and ecosystem functioning: A complex adaptive systems
approach, Limnol. Oceanogr., 49, 1269–1277,
https://doi.org/10.4319/lo.2004.49.4_part_2.1269, 2004. a
O'Malley, R.: Ocean Productivity,
available at: http://www.science.oregonstate.edu/ocean.productivity/index.php (last access: 20 June 2019),
2017. a
Oschlies, A., Koeve, W., and Garçon, V.: An Eddy-Permitting Coupled
Physical-Biological Model of the North Atlantic 2. Ecosystem Dynamics and
Comparison With Satellite and JGOFS Local Studies Data, Global Biogeochem.
Cycles, 14, 499–523, 2000. a
Oschlies, A., Duteil, O., Getzlaff, J., Koeve, W., Landolfi, A., and Schmidtko,
S.: Patterns of deoxygenation: sensitivity to natural and anthropogenic
drivers, Phil. Trans. R. Soc. Lond. A, 375, 20160325,
https://doi.org/10.1098/rsta.2016.0325, 2017. a, b
Pahlow, M.: Linking chlorophyll-nutrient dynamics to the Redfield N:C ratio
with a model of optimal phytoplankton growth, Mar. Ecol. Prog. Ser., 287,
33–43, https://doi.org/10.3354/meps287033, 2005. a, b, c
Pahlow, M.: UVic-updates-opem: Optimality-based Plankton Ecosystem Model (OPEM v1.0) for the UVic-ESCM, OceanRep, https://doi.org/10.3289/SW_1_2020, 2020. a
Park, J.-Y., Stock, C. A., Dunne, J. P., Yang, X., and Rosati, A.: Seasonal to
multiannual marine ecosystem prediction with a global Earth system model,
Science, 365, 284–288, https://doi.org/10.1126/science.aav6634, 2019. a, b
Prowe, A. E. F., Visser, A. W., Andersen, K. H., Chiba, S., and Kiørboe, T.:
Biogeography of zooplankton feeding strategy, Limnol. Oceanogr., 64,
661–678, https://doi.org/10.1002/lno.11067, 2018. a
Smith, S. L., Yamanaka, Y., Pahlow, M., and Oschlies, A.: Optimal uptake
kinetics: physiological acclimation explains the pattern of nitrate uptake by
phytoplankton in the ocean, Mar. Ecol. Prog. Ser., 384, 1–12,
https://doi.org/10.3354/meps08022, 2009. a, b, c
Smith, S. L., Pahlow, M., Merico, A., and Wirtz, K. W.: Optimality-based
modeling of planktonic organisms, Limnol. Oceanogr., 56, 2080–2094,
https://doi.org/10.4319/lo.2011.56.6.2080, 2011. a
Smith, S. L., Pahlow, M., Merico, A., Acevedo-Trejos, E., Sasai, Y., Yoshikawa,
C., Sasaoka, K., Fujiki, T., Matsumoto, K., and Honda, M. C.: Flexible
phytoplankton functional type (FlexPFT) model: size-scaling of traits and
optimal growth, J. Plankton Res., 38, 977–992, https://doi.org/10.1093/plankt/fbv038,
2016. a
Strom, S. L.: Growth and grazing rates of the herbivorous dinoflagellate
Gymnodinium sp. from the open subarctic Pacific Ocean, Mar. Ecol.
Prog. Ser., 78, 103–113, https://doi.org/10.3354/meps078103, 1991. a
Strom, S. L., Miller, C. B., and Frost, B. W.: What sets the lower limit to
phytoplankton stocks in high-nitrate, low-chlorophyll regions of the open
ocean?, Mar. Ecol. Prog. Ser., 193, 19–31, https://doi.org/10.3354/meps193019, 2000. a
Su, B., Pahlow, M., and Prowe, F.: The role of microzooplankton trophic
interactions in modelling a suite of mesocosm ecosystems, Ecol. Model., 368,
169–179, https://doi.org/10.1016/j.ecolmodel.2017.11.013, 2018. a, b
Talmy, D., Blackford, J., Hardman-Mountford, N. J., Polimene, L., Follows, M. J., and Geider, R. J.: Flexible C:N ratio enhances metabolism of large phytoplankton when resource supply is intermittent, Biogeosciences, 11, 4881–4895, https://doi.org/10.5194/bg-11-4881-2014, 2014. a
Talmy, D., Martiny, A. C., Hill, C., Hickman, A. E., and Follows, M. J.:
Microzooplankton regulation of surface ocean POC:PON ratios, Global
Biogeochem. Cycles, 30, 311–332, https://doi.org/10.1002/2015GB005273, 2016. a
Taucher, J. and Oschlies, A.: Can we predict the direction of marine primary
production change under global warming?, Geophys. Res. Lett., 38, L02603,
https://doi.org/10.1029/2010GL045934, 2011. a, b
Vichi, M., Pinardi, N., and Masina, S.: A generalized model of pelagic
biogeochemistry.for the global ocean ecosystem. Part I: Theory, J. Mar.
Syst., 64, 89–109, https://doi.org/10.1016/j.jmarsys.2006.03.006, 2007. a
Wang, W.-L., Moore, J. K., Martiny, A. C., and Primeau, F. W.: Convergent
estimates of marine nitrogen fixation, Nature, 566, 205–211,
https://doi.org/10.1038/s41586-019-0911-2, 2019. a, b
Weaver, A., Eby, M., Wiebe, E., Bitz, C., Duffy, P., Ewen, T., Fanning, A.,
Holland, M., MacFadyen, A., Matthews, H., Meissner, K., Saenko, O.,
Schmittner, A., Wang, H., and Yoshimori, M.: The UVic Earth System Climate
Model: Model description, climatology, and applications to past, present and
future climates, Atmos.-Ocean, 39, 361–428,
https://doi.org/10.1080/07055900.2001.9649686, 2001. a, b, c
Short summary
The stoichiometry of marine biotic processes is important for the regulation of atmospheric CO2 and hence the global climate. We replace a simplistic, fixed-stoichiometry plankton module in an Earth system model with an optimal-regulation model with variable stoichiometry. Our model compares better to the observed carbon transfer from the surface to depth and surface nutrient distributions. This work could aid our ability to describe and project the role of marine ecosystems in the Earth system.
The stoichiometry of marine biotic processes is important for the regulation of atmospheric CO2...
