Articles | Volume 10, issue 6
Geosci. Model Dev., 10, 2425–2445, 2017
https://doi.org/10.5194/gmd-10-2425-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: The Transport Matrix Method (TMM) for ocean biogeochemical...
Geosci. Model Dev., 10, 2425–2445, 2017
https://doi.org/10.5194/gmd-10-2425-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
29 Jun 2017
Model evaluation paper
| 29 Jun 2017
Evaluation of the transport matrix method for simulation of ocean biogeochemical tracers
Karin F. Kvale et al.
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Karin Kvale, David P. Keller, Wolfgang Koeve, Katrin J. Meissner, Christopher J. Somes, Wanxuan Yao, and Andreas Oschlies
Geosci. Model Dev., 14, 7255–7285, https://doi.org/10.5194/gmd-14-7255-2021, https://doi.org/10.5194/gmd-14-7255-2021, 2021
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We present a new model of biological marine silicate cycling for the University of Victoria Earth System Climate Model (UVic ESCM). This new model adds diatoms, which are a key aspect of the biological carbon pump, to an existing ecosystem model. Our modifications change how the model responds to warming, with net primary production declining more strongly than in previous versions. Diatoms in particular are simulated to decline with climate warming due to their high nutrient requirements.
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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Constants of global biogeochemical ocean models are often tuned
by handto match observations of nutrients or oxygen. We investigate the effect of this tuning by optimising six constants of a global biogeochemical model, simulated in five different offline circulations. Optimal values for three constants adjust to distinct features of the circulation applied and can afterwards be swapped among the circulations, without losing too much of the model's fit to observed quantities.
Karin F. Kvale, Katherine E. Turner, Angela Landolfi, and Katrin J. Meissner
Biogeosciences, 16, 1019–1034, https://doi.org/10.5194/bg-16-1019-2019, https://doi.org/10.5194/bg-16-1019-2019, 2019
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Drivers motivating the evolution of calcifying phytoplankton are poorly understood. We explore differences in global ocean chemistry with and without calcifiers during rapid climate changes. We find the presence of phytoplankton calcifiers stabilizes the volume of low oxygen regions and consequently stabilizes the concentration of nitrate, which is an important nutrient required for photosynthesis. By stabilizing nitrate concentrations, calcifiers improve their growth conditions.
Karin F. Kvale and Katrin J. Meissner
Biogeosciences, 14, 4767–4780, https://doi.org/10.5194/bg-14-4767-2017, https://doi.org/10.5194/bg-14-4767-2017, 2017
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Climate models containing ocean biogeochemistry contain a lot of poorly constrained parameters, which makes model tuning difficult. For more than 20 years modellers have generally assumed phytoplankton light attenuation parameter value choice has an insignificant affect on model ocean primary production; thus, it is often overlooked for tuning. We show that an empirical range of light attenuation parameter values can affect primary production, with increasing sensitivity under climate change.
K. F. Kvale, K. J. Meissner, D. P. Keller, M. Eby, and A. Schmittner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-1709-2014, https://doi.org/10.5194/gmdd-7-1709-2014, 2014
Revised manuscript not accepted
Sophy Oliver, Coralia Cartis, Iris Kriest, Simon F. B Tett, and Samar Khatiwala
Geosci. Model Dev., 15, 3537–3554, https://doi.org/10.5194/gmd-15-3537-2022, https://doi.org/10.5194/gmd-15-3537-2022, 2022
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Global ocean biogeochemical models are used within Earth system models which are used to predict future climate change. However, these are very computationally expensive to run and therefore are rarely routinely improved or calibrated to real oceanic observations. Here we apply a new, fast optimisation algorithm to one such model and show that it can calibrate the model much faster than previously managed, therefore encouraging further ocean biogeochemical model improvements.
Tianfei Xue, Ivy Frenger, A. E. Friederike Prowe, Yonss Saranga José, and Andreas Oschlies
Biogeosciences, 19, 455–475, https://doi.org/10.5194/bg-19-455-2022, https://doi.org/10.5194/bg-19-455-2022, 2022
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The Peruvian system supports 10 % of the world's fishing yield. In the Peruvian system, wind and earth’s rotation bring cold, nutrient-rich water to the surface and allow phytoplankton to grow. But observations show that it grows worse at high upwelling. Using a model, we find that high upwelling happens when air mixes the water the most. Then phytoplankton is diluted and grows slowly due to low light and cool upwelled water. This study helps to estimate how it might change in a warming climate.
Jiajun Wu, David P. Keller, and Andreas Oschlies
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-104, https://doi.org/10.5194/esd-2021-104, 2022
Preprint under review for ESD
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In this study we investigate an ocean-based carbon dioxide removal method: macroalgae open-ocean mariculture and sinking (MOS), which aims to cultivate seaweeds in the open ocean surface and sink matured biomass quickly to the deep seafloor. Our results suggest that MOS has a considerable potential as an ocean-based CDR method. However, MOS has inherent side effects on marine ecosystems and biogeochemistry, which will require a careful evaluation beyond this first idealized modeling study.
Chia-Te Chien, Jonathan V. Durgadoo, Dana Ehlert, Ivy Frenger, David P. Keller, Wolfgang Koeve, Iris Kriest, Angela Landolfi, Lavinia Patara, Sebastian Wahl, and Andreas Oschlies
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-361, https://doi.org/10.5194/gmd-2021-361, 2022
Preprint under review for GMD
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We present the implementation and evaluation of a marine biogeochemical model, Model of Oceanic Pelagic Stoichiometry (MOPS) in the Flexible Ocean and Climate Infrastructure (FOCI) climate model. FOCI-MOPS enables the simulation of marine biological processes, the marine carbon, nitrogen and oxygen cycles, air-sea gas exchange of CO2 and O2. As shown by our evaluation, FOCI-MOPS overall shows an adequate performance that makes it an appropriate tool for Earth climate system simulations.
Karin Kvale, David P. Keller, Wolfgang Koeve, Katrin J. Meissner, Christopher J. Somes, Wanxuan Yao, and Andreas Oschlies
Geosci. Model Dev., 14, 7255–7285, https://doi.org/10.5194/gmd-14-7255-2021, https://doi.org/10.5194/gmd-14-7255-2021, 2021
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We present a new model of biological marine silicate cycling for the University of Victoria Earth System Climate Model (UVic ESCM). This new model adds diatoms, which are a key aspect of the biological carbon pump, to an existing ecosystem model. Our modifications change how the model responds to warming, with net primary production declining more strongly than in previous versions. Diatoms in particular are simulated to decline with climate warming due to their high nutrient requirements.
Maria-Theresia Verwega, Christopher J. Somes, Markus Schartau, Robyn Elizabeth Tuerena, Anne Lorrain, Andreas Oschlies, and Thomas Slawig
Earth Syst. Sci. Data, 13, 4861–4880, https://doi.org/10.5194/essd-13-4861-2021, https://doi.org/10.5194/essd-13-4861-2021, 2021
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This work describes a ready-to-use collection of particulate organic carbon stable isotope ratio data sets. It covers the 1960s–2010s and all main oceans, providing meta-information and gridded data. The best coverage exists in Atlantic, Indian and Southern Ocean surface waters during the 1990s. It indicates no major difference between methods and shows decreasing values towards high latitudes, with the lowest in the Southern Ocean, and a long-term decline in all regions but the Southern Ocean.
Miriam Tivig, David P. Keller, and Andreas Oschlies
Biogeosciences, 18, 5327–5350, https://doi.org/10.5194/bg-18-5327-2021, https://doi.org/10.5194/bg-18-5327-2021, 2021
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Nitrogen is one of the most important elements for life in the ocean. A major source is the riverine discharge of dissolved nitrogen. While global models often omit rivers as a nutrient source, we included nitrogen from rivers in our Earth system model and found that additional nitrogen affected marine biology not only locally but also in regions far off the coast. Depending on regional conditions, primary production was enhanced or even decreased due to internal feedbacks in the nitrogen cycle.
Henrike Schmidt, Julia Getzlaff, Ulrike Löptien, and Andreas Oschlies
Ocean Sci., 17, 1303–1320, https://doi.org/10.5194/os-17-1303-2021, https://doi.org/10.5194/os-17-1303-2021, 2021
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Oxygen-poor regions in the open ocean restrict marine habitats. Global climate simulations show large uncertainties regarding the prediction of these areas. We analyse the representation of the simulated oxygen minimum zones in the Arabian Sea using 10 climate models. We give an overview of the main deficiencies that cause the model–data misfit in oxygen concentrations. This detailed process analysis shall foster future model improvements regarding the oxygen minimum zone in the Arabian Sea.
Heiner Dietze and Ulrike Löptien
Biogeosciences, 18, 4243–4264, https://doi.org/10.5194/bg-18-4243-2021, https://doi.org/10.5194/bg-18-4243-2021, 2021
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In recent years fish-kill events caused by oxygen deficit have been reported in Eckernförde Bight (Baltic Sea). This study sets out to understand the processes causing respective oxygen deficits by combining high-resolution coupled ocean circulation biogeochemical modeling, monitoring data, and artificial intelligence.
Jaard Hauschildt, Soeren Thomsen, Vincent Echevin, Andreas Oschlies, Yonss Saranga José, Gerd Krahmann, Laura A. Bristow, and Gaute Lavik
Biogeosciences, 18, 3605–3629, https://doi.org/10.5194/bg-18-3605-2021, https://doi.org/10.5194/bg-18-3605-2021, 2021
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In this paper we quantify the subduction of upwelled nitrate due to physical processes on the order of several kilometers in the coastal upwelling off Peru and its effect on primary production. We also compare the prepresentation of these processes in a high-resolution simulation (~2.5 km) with a more coarsely resolved simulation (~12 km). To do this, we combine high-resolution shipboard observations of physical and biogeochemical parameters with a complex biogeochemical model configuration.
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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In this study we use a regional biogeochemical model of the eastern tropical South Pacific Ocean to implicitly simulate the effect that fluctuations in populations of small pelagic fish, such as anchovy and sardine, may have on the biogeochemistry of the northern Humboldt Current System. To do so, we vary the zooplankton mortality in the model, under the assumption that these fishes eat zooplankton. We also evaluate the model for the first time against mesozooplankton observations.
Chia-Te Chien, Markus Pahlow, Markus Schartau, and Andreas Oschlies
Geosci. Model Dev., 13, 4691–4712, https://doi.org/10.5194/gmd-13-4691-2020, https://doi.org/10.5194/gmd-13-4691-2020, 2020
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We demonstrate sensitivities of tracers to parameters of a new optimality-based plankton–ecosystem model (OPEM) in the UVic-ESCM. We find that changes in phytoplankton subsistence nitrogen quota strongly impact the nitrogen inventory, nitrogen fixation, and elemental stoichiometry of ordinary phytoplankton and diazotrophs. We introduce a new likelihood-based metric for model calibration, and it shows the capability of constraining globally averaged oxygen, nitrate, and DIC concentrations.
Markus Pahlow, Chia-Te Chien, Lionel A. Arteaga, and Andreas Oschlies
Geosci. Model Dev., 13, 4663–4690, https://doi.org/10.5194/gmd-13-4663-2020, https://doi.org/10.5194/gmd-13-4663-2020, 2020
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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.
Nadine Mengis, David P. Keller, Andrew H. MacDougall, Michael Eby, Nesha Wright, Katrin J. Meissner, Andreas Oschlies, Andreas Schmittner, Alexander J. MacIsaac, H. Damon Matthews, and Kirsten Zickfeld
Geosci. Model Dev., 13, 4183–4204, https://doi.org/10.5194/gmd-13-4183-2020, https://doi.org/10.5194/gmd-13-4183-2020, 2020
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In this paper, we evaluate the newest version of the University of Victoria Earth System Climate Model (UVic ESCM 2.10). Combining recent model developments as a joint effort, this version is to be used in the next phase of model intercomparison and climate change studies. The UVic ESCM 2.10 is capable of reproducing changes in historical temperature and carbon fluxes well. Additionally, the model is able to reproduce the three-dimensional distribution of many ocean tracers.
Sabine Mathesius, Julia Getzlaff, Heiner Dietze, Andreas Oschlies, and Markus Schartau
Earth Syst. Sci. Data, 12, 1775–1787, https://doi.org/10.5194/essd-12-1775-2020, https://doi.org/10.5194/essd-12-1775-2020, 2020
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Controlled manipulation of environmental conditions within large enclosures in the ocean, pelagic mesocosms, has become a standard method to explore responses of marine plankton communities to anthropogenic change. Among the challenges of interpreting mesocosm data is the often uncertain role of vertical mixing. This study introduces a mesocosm mixing model that is able to estimate vertical diffusivities and thus provides a tool for future mesocosm data analyses that account for mixing.
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
Short summary
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Constants of global biogeochemical ocean models are often tuned
by handto match observations of nutrients or oxygen. We investigate the effect of this tuning by optimising six constants of a global biogeochemical model, simulated in five different offline circulations. Optimal values for three constants adjust to distinct features of the circulation applied and can afterwards be swapped among the circulations, without losing too much of the model's fit to observed quantities.
Fabian Reith, Wolfgang Koeve, David P. Keller, Julia Getzlaff, and Andreas Oschlies
Earth Syst. Dynam., 10, 711–727, https://doi.org/10.5194/esd-10-711-2019, https://doi.org/10.5194/esd-10-711-2019, 2019
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This modeling study is the first one to look at the suitability and collateral effects of direct CO2 injection into the deep ocean as a means to bridge the gap between CO2 emissions and climate impacts of an intermediate CO2 emission scenario and a temperature target on a millennium timescale, such as the 1.5 °C climate target of the Paris Agreement.
Tronje P. Kemena, Angela Landolfi, Andreas Oschlies, Klaus Wallmann, and Andrew W. Dale
Earth Syst. Dynam., 10, 539–553, https://doi.org/10.5194/esd-10-539-2019, https://doi.org/10.5194/esd-10-539-2019, 2019
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Oceanic deoxygenation is driven by climate change in several areas of the global ocean. Measurements indicate that ocean volumes with very low oxygen levels expand, with consequences for marine organisms and fishery. We found climate-change-driven phosphorus (P) input in the ocean is hereby an important driver for deoxygenation on longer timescales with effects in the next millennia.
Daniela Niemeyer, Iris Kriest, and Andreas Oschlies
Biogeosciences, 16, 3095–3111, https://doi.org/10.5194/bg-16-3095-2019, https://doi.org/10.5194/bg-16-3095-2019, 2019
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Recent studies suggest spatial variations of the marine particle flux length scale. Using a global biogeochemical ocean model, we investigate whether changes in particle size and size-dependent sinking can explain this variation. We address uncertainties by varying aggregate properties and circulation. Both aspects have an impact on the representation of nutrients, oxygen and oxygen minimum zones. The formation and sinking of large aggregates in productive areas lead to deeper flux penetration.
Ulrike Löptien and Heiner Dietze
Biogeosciences, 16, 1865–1881, https://doi.org/10.5194/bg-16-1865-2019, https://doi.org/10.5194/bg-16-1865-2019, 2019
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Anthropogenic greenhouse gas emissions trigger complex climate feedbacks. Output form Earth system models provides a basis for related political decision-making. One challenge is to arrive at reliable model parameter estimates for the ocean biogeochemistry module. We illustrate pitfalls through which flaws in the ocean module are masked by wrongly tuning the biogeochemistry and discuss ensuing uncertainties in climate projections.
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.
Karin F. Kvale, Katherine E. Turner, Angela Landolfi, and Katrin J. Meissner
Biogeosciences, 16, 1019–1034, https://doi.org/10.5194/bg-16-1019-2019, https://doi.org/10.5194/bg-16-1019-2019, 2019
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Drivers motivating the evolution of calcifying phytoplankton are poorly understood. We explore differences in global ocean chemistry with and without calcifiers during rapid climate changes. We find the presence of phytoplankton calcifiers stabilizes the volume of low oxygen regions and consequently stabilizes the concentration of nitrate, which is an important nutrient required for photosynthesis. By stabilizing nitrate concentrations, calcifiers improve their growth conditions.
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.
Iris Kriest
Biogeosciences, 14, 4965–4984, https://doi.org/10.5194/bg-14-4965-2017, https://doi.org/10.5194/bg-14-4965-2017, 2017
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Early biogeochemical ocean models were of a simple structure, with few biogeochemical components. I here investigate whether additional biological complexity improves the fit with respect to observed global climatologies of annual mean nutrients and oxygen. After optimisation against these tracers a simple model fits observations almost as well as a more complex one, also with respect to independent estimates of global biogeochemical fluxes.
Karin F. Kvale and Katrin J. Meissner
Biogeosciences, 14, 4767–4780, https://doi.org/10.5194/bg-14-4767-2017, https://doi.org/10.5194/bg-14-4767-2017, 2017
Short summary
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Climate models containing ocean biogeochemistry contain a lot of poorly constrained parameters, which makes model tuning difficult. For more than 20 years modellers have generally assumed phytoplankton light attenuation parameter value choice has an insignificant affect on model ocean primary production; thus, it is often overlooked for tuning. We show that an empirical range of light attenuation parameter values can affect primary production, with increasing sensitivity under climate change.
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
Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, https://doi.org/10.5194/gmd-10-2169-2017, 2017
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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.
Heiner Dietze, Julia Getzlaff, and Ulrike Löptien
Biogeosciences, 14, 1561–1576, https://doi.org/10.5194/bg-14-1561-2017, https://doi.org/10.5194/bg-14-1561-2017, 2017
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The Southern Ocean is a sink for anthropogenic carbon. Projections of how this sink will evolve in an ever-warming climate are based on coupled ocean-circulation–biogeochemical models. This study compares uncertainties of simulated oceanic carbon uptake associated to physical (eddy) parameterizations with those associated wtih (unconstrained) supply of bioavailable iron supply to the surface ocean.
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.
Heiner Dietze and Ulrike Löptien
Ocean Sci., 12, 977–986, https://doi.org/10.5194/os-12-977-2016, https://doi.org/10.5194/os-12-977-2016, 2016
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Winds blowing over the ocean drive ocean currents. The oceanic response to winds is, in turn, influenced by ocean currents. Theoretical considerations suggest that the latter effect is especially pronounced in the Baltic Sea. The study presented here puts theses theoretical considerations in a high-resolution ocean circulation model of the Baltic Sea to the test.
Jörg Schwinger, Nadine Goris, Jerry F. Tjiputra, Iris Kriest, Mats Bentsen, Ingo Bethke, Mehmet Ilicak, Karen M. Assmann, and Christoph Heinze
Geosci. Model Dev., 9, 2589–2622, https://doi.org/10.5194/gmd-9-2589-2016, https://doi.org/10.5194/gmd-9-2589-2016, 2016
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We present an evaluation of the ocean carbon cycle stand-alone configuration of the Norwegian Earth System Model. A re-tuning of the ecosystem parameterisation improves surface tracer fields between versions 1 and 1.2 of the model. Focus is placed on the evaluation of newly implemented parameterisations of the biological carbon pump (i.e. the sinking of particular organic carbon). We find that the model previously underestimated the carbon transport into the deep ocean below 2000 m depth.
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.
U. Löptien and H. Dietze
Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, https://doi.org/10.5194/os-11-573-2015, 2015
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Marine biogeochemical ocean models are embedded into earth system models - which are, to an increasing degree, applied to project the fate of our warming world. These biogeochemical models generally depend on poorly constrained model parameters. In this study we investigate the the demands on observations for an objective estimation of such parameters. A major result is that even modest noise (10%) inherent to observations can hinder the assignment of reasonable parameters.
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.
U. Löptien and H. Dietze
Earth Syst. Sci. Data, 6, 367–374, https://doi.org/10.5194/essd-6-367-2014, https://doi.org/10.5194/essd-6-367-2014, 2014
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
H. Dietze, U. Löptien, and K. Getzlaff
Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, https://doi.org/10.5194/gmd-7-1713-2014, 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
K. F. Kvale, K. J. Meissner, D. P. Keller, M. Eby, and A. Schmittner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-1709-2014, https://doi.org/10.5194/gmdd-7-1709-2014, 2014
Revised manuscript not accepted
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
S. Khatiwala, T. Tanhua, S. Mikaloff Fletcher, M. Gerber, S. C. Doney, H. D. Graven, N. Gruber, G. A. McKinley, A. Murata, A. F. Ríos, and C. L. Sabine
Biogeosciences, 10, 2169–2191, https://doi.org/10.5194/bg-10-2169-2013, https://doi.org/10.5194/bg-10-2169-2013, 2013
R. Wanninkhof, G. -H. Park, T. Takahashi, C. Sweeney, R. Feely, Y. Nojiri, N. Gruber, S. C. Doney, G. A. McKinley, A. Lenton, C. Le Quéré, C. Heinze, J. Schwinger, H. Graven, and S. Khatiwala
Biogeosciences, 10, 1983–2000, https://doi.org/10.5194/bg-10-1983-2013, https://doi.org/10.5194/bg-10-1983-2013, 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
Related subject area
Climate and Earth system modeling
A derivative-free optimisation method for global ocean biogeochemical models
Empirical values and assumptions in the convection schemes of numerical models
Precipitation over southern Africa: is there consensus among global climate models (GCMs), regional climate models (RCMs) and observational data?
On the impact of dropsondes on the ECMWF Integrated Forecasting System model (CY47R1) analysis of convection during the OTREC (Organization of Tropical East Pacific Convection) field campaign
Assessment of the sea surface temperature diurnal cycle in CNRM-CM6-1 based on its 1D coupled configuration
CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)
An evaluation of the E3SMv1 Arctic ocean and sea-ice regionally refined model
Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset
The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
Evaluation of a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) scheme for aerosol activation in global models using multiple aircraft data over both continental and marine environments
Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1
Landslide Susceptibility Assessment Tools v1.0.0b – Project Manager Suite: a new modular toolkit for landslide susceptibility assessment
Added value of EURO-CORDEX high-resolution downscaling over the Iberian Peninsula revisited – Part 1: Precipitation
Added value of EURO-CORDEX high-resolution downscaling over the Iberian Peninsula revisited – Part 2: Max and min temperature
Constraining a land cover map with satellite-based aboveground biomass estimates over Africa
Analysing the PMIP4-CMIP6 collection: a workflow and tool (pmip_p2fvar_analyzer v1)
Impacts of a revised surface roughness parameterization in the Community Land Model 5.1
Novel coupled permafrost–forest model (LAVESI–CryoGrid v1.0) revealing the interplay between permafrost, vegetation, and climate across eastern Siberia
The effects of ocean surface waves on global intraseasonal prediction: case studies with a coupled CFSv2.0–WW3 system
Earth system model parameter adjustment using a Green's functions approach
Effects of forcing differences and initial conditions on inter-model agreement in the VolMIP volc-pinatubo-full experiment
From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: coupling of MAGICC (v7.5.1) and MESMER (v0.8.3)
Global simulation of dissolved 231Pa and 230Th in the ocean and the sedimentary 231Pa∕230Th ratios with the ocean general circulation model COCO ver4.0
The linear feedback precipitation model (LFPM 1.0) – a simple and efficient model for orographic precipitation in the context of landform evolution modeling
Building a machine learning surrogate model for wildfire activities within a global Earth system model
Variability and extremes: statistical validation of the Alfred Wegener Institute Earth System Model (AWI-ESM)
Extreme events representation in CMCC-CM2 standard and high-resolution general circulation models
TopoCLIM: rapid topography-based downscaling of regional climate model output in complex terrain v1.1
CARDAMOM-FluxVal version 1.0: a FLUXNET-based validation system for CARDAMOM carbon and water flux estimates
Supporting hierarchical soil biogeochemical modeling: version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2)
Using neural network ensembles to separate ocean biogeochemical and physical drivers of phytoplankton biogeography in Earth system models
GAN–argcPredNet v1.0: a generative adversarial model for radar echo extrapolation based on convolutional recurrent units
A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes
An automatic lake-model application using near-real-time data forcing: development of an operational forecast workflow (COASTLINES) for Lake Erie
ShellChron 0.4.0: a new tool for constructing chronologies in accretionary carbonate archives from stable oxygen isotope profiles
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PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5
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Assessment of the Finite-VolumE Sea ice–Ocean Model (FESOM2.0) – Part 2: Partial bottom cells, embedded sea ice and vertical mixing library CVMix
Evaluation and optimisation of the I/O scalability for the next generation of Earth system models: IFS CY43R3 and XIOS 2.0 integration as a case study
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Sophy Oliver, Coralia Cartis, Iris Kriest, Simon F. B Tett, and Samar Khatiwala
Geosci. Model Dev., 15, 3537–3554, https://doi.org/10.5194/gmd-15-3537-2022, https://doi.org/10.5194/gmd-15-3537-2022, 2022
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Global ocean biogeochemical models are used within Earth system models which are used to predict future climate change. However, these are very computationally expensive to run and therefore are rarely routinely improved or calibrated to real oceanic observations. Here we apply a new, fast optimisation algorithm to one such model and show that it can calibrate the model much faster than previously managed, therefore encouraging further ocean biogeochemical model improvements.
Anahí Villalba-Pradas and Francisco J. Tapiador
Geosci. Model Dev., 15, 3447–3518, https://doi.org/10.5194/gmd-15-3447-2022, https://doi.org/10.5194/gmd-15-3447-2022, 2022
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The paper provides a comprehensive review of the empirical values and assumptions used in the convection schemes of numerical models. The focus is on the values and assumptions used in the activation of convection (trigger), the transport and microphysics (commonly referred to as the cloud model), and the intensity of convection (closure). Such information can assist satellite missions focused on elucidating convective processes and the evaluation of model output uncertainties.
Maria Chara Karypidou, Eleni Katragkou, and Stefan Pieter Sobolowski
Geosci. Model Dev., 15, 3387–3404, https://doi.org/10.5194/gmd-15-3387-2022, https://doi.org/10.5194/gmd-15-3387-2022, 2022
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The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Reliable climatic information is therefore necessary for the optimal adaptation of local communities. In this work we show that regional climate models are reliable tools for the simulation of precipitation over southern Africa. However, there is still a great need for the expansion and maintenance of observational data.
Stipo Sentić, Peter Bechtold, Željka Fuchs-Stone, Mark Rodwell, and David J. Raymond
Geosci. Model Dev., 15, 3371–3385, https://doi.org/10.5194/gmd-15-3371-2022, https://doi.org/10.5194/gmd-15-3371-2022, 2022
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The Organization of Tropical East Pacific Convection (OTREC) field campaign focuses on studying convection in the eastern Pacific and Caribbean. Observations obtained from dropsondes have been assimilated into the ECMWF model and compared to a model run in which sondes have not been assimilated. The model performs well in both simulations, but the assimilation of sondes helps to reduce the departure for pre-tropical-storm conditions. Variables important to studying convection are also studied.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
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A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Hui Wan, Kai Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, Shixuan Zhang, and Ross Dixon
Geosci. Model Dev., 15, 3205–3231, https://doi.org/10.5194/gmd-15-3205-2022, https://doi.org/10.5194/gmd-15-3205-2022, 2022
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This paper describes a tool embedded in a global climate model for sampling atmospheric conditions and monitoring physical processes as a numerical simulation is being carried out. The tool facilitates process-level model evaluation by allowing the users to select a wide range of quantities and processes to monitor at run time without having to do tedious ad hoc coding.
Milena Veneziani, Wieslaw Maslowski, Younjoo J. Lee, Gennaro D'Angelo, Robert Osinski, Mark R. Petersen, Wilbert Weijer, Anthony P. Craig, John D. Wolfe, Darin Comeau, and Adrian K. Turner
Geosci. Model Dev., 15, 3133–3160, https://doi.org/10.5194/gmd-15-3133-2022, https://doi.org/10.5194/gmd-15-3133-2022, 2022
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We present an Earth system model (ESM) simulation, E3SM-Arctic-OSI, with a refined grid to better resolve the Arctic ocean and sea-ice system and low spatial resolution elsewhere. The configuration satisfactorily represents many aspects of the Arctic system and its interactions with the sub-Arctic, while keeping computational costs at a fraction of those necessary for global high-resolution ESMs. E3SM-Arctic can thus be an efficient tool to study Arctic processes on climate-relevant timescales.
Hamidreza Omidvar, Ting Sun, Sue Grimmond, Dave Bilesbach, Andrew Black, Jiquan Chen, Zexia Duan, Zhiqiu Gao, Hiroki Iwata, and Joseph P. McFadden
Geosci. Model Dev., 15, 3041–3078, https://doi.org/10.5194/gmd-15-3041-2022, https://doi.org/10.5194/gmd-15-3041-2022, 2022
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This paper extends the applicability of the SUEWS to extensive pervious areas outside cities. We derived various parameters such as leaf area index, albedo, roughness parameters and surface conductance for non-urban areas. The relation between LAI and albedo is also explored. The methods and parameters discussed can be used for both online and offline simulations. Using appropriate parameters related to non-urban areas is essential for assessing urban–rural differences.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
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The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Hengqi Wang, Yiran Peng, Knut von Salzen, Yan Yang, Wei Zhou, and Delong Zhao
Geosci. Model Dev., 15, 2949–2971, https://doi.org/10.5194/gmd-15-2949-2022, https://doi.org/10.5194/gmd-15-2949-2022, 2022
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The aerosol activation scheme is an important part of the general circulation model, but evaluations using observed data are mostly regional. This research introduced a numerically efficient aerosol activation scheme and evaluated it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The decent performance indicates that the scheme is suitable for simulations of cloud droplet number concentrations over wide conditions.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Jewgenij Torizin, Nick Schüßler, and Michael Fuchs
Geosci. Model Dev., 15, 2791–2812, https://doi.org/10.5194/gmd-15-2791-2022, https://doi.org/10.5194/gmd-15-2791-2022, 2022
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With LSAT PM we introduce an open-source, stand-alone, easy-to-use application that supports scientific principles of openness, knowledge integrity, and replicability. Doing so, we want to share our experience in the implementation of heuristic and data-driven landslide susceptibility assessment methods such as analytic hierarchy process, weights of evidence, logistic regression, and artificial neural networks. A test dataset is available.
João António Martins Careto, Pedro Miguel Matos Soares, Rita Margarida Cardoso, Sixto Herrera, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 2635–2652, https://doi.org/10.5194/gmd-15-2635-2022, https://doi.org/10.5194/gmd-15-2635-2022, 2022
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This work focuses on the added value of high-resolution models relative to their forcing simulations, with a recent observational gridded dataset as a reference, covering the entire Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional climate models encouraged this study. For precipitation, most models reveal added value. The gains are even more evident for precipitation extremes, particularly at a more local scale.
João António Martins Careto, Pedro Miguel Matos Soares, Rita Margarida Cardoso, Sixto Herrera, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 2653–2671, https://doi.org/10.5194/gmd-15-2653-2022, https://doi.org/10.5194/gmd-15-2653-2022, 2022
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This work focuses on the added value of high-resolution models relative to their forcing simulations, with an observational gridded dataset as a reference covering the Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional models encouraged this study. For the max and min temperature, although most models reveal added value, some display losses. At more local scales, coastal sites display important gains, contrasting with the interior.
Guillaume Marie, B. Sebastiaan Luyssaert, Cecile Dardel, Thuy Le Toan, Alexandre Bouvet, Stéphane Mermoz, Ludovic Villard, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 15, 2599–2617, https://doi.org/10.5194/gmd-15-2599-2022, https://doi.org/10.5194/gmd-15-2599-2022, 2022
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Most Earth system models make use of vegetation maps to initialize a simulation at global scale. Satellite-based biomass map estimates for Africa were used to estimate cover fractions for the 15 land cover classes. This study successfully demonstrates that satellite-based biomass maps can be used to better constrain vegetation maps. Applying this approach at the global scale would increase confidence in assessments of present-day biomass stocks.
Anni Zhao, Chris M. Brierley, Zhiyi Jiang, Rachel Eyles, Damián Oyarzún, and Jose Gomez-Dans
Geosci. Model Dev., 15, 2475–2488, https://doi.org/10.5194/gmd-15-2475-2022, https://doi.org/10.5194/gmd-15-2475-2022, 2022
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We describe the way that our group have chosen to perform our recent analyses of the Palaeoclimate Modelling Intercomparison Project ensemble simulations. We document the approach used to obtain and curate the simulations, process those outputs via the Climate Variability Diagnostics Package, and then continue through to compute ensemble-wide statistics and create figures. We also provide interim data from all steps, the codes used and the ability for users to perform their own analyses.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Stefan Kruse, Simone M. Stuenzi, Julia Boike, Moritz Langer, Josias Gloy, and Ulrike Herzschuh
Geosci. Model Dev., 15, 2395–2422, https://doi.org/10.5194/gmd-15-2395-2022, https://doi.org/10.5194/gmd-15-2395-2022, 2022
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We coupled established models for boreal forest (LAVESI) and permafrost dynamics (CryoGrid) in Siberia to investigate interactions of the diverse vegetation layer with permafrost soils. Our tests showed improved active layer depth estimations and newly included species growth according to their species-specific limits. We conclude that the new model system can be applied to simulate boreal forest dynamics and transitions under global warming and disturbances, expanding our knowledge.
Ruizi Shi, Fanghua Xu, Li Liu, Zheng Fan, Hao Yu, Hong Li, Xiang Li, and Yunfei Zhang
Geosci. Model Dev., 15, 2345–2363, https://doi.org/10.5194/gmd-15-2345-2022, https://doi.org/10.5194/gmd-15-2345-2022, 2022
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To better understand the effects of surface waves on global intraseasonal prediction, we incorporated the WW3 model into CFSv2.0. Processes of Langmuir mixing, Stokes–Coriolis force with entrainment, air–sea fluxes modified by Stokes drift, and momentum roughness length were considered. Results from two groups of 56 d experiments show that overestimated sea surface temperature, 2 m air temperature, 10 m wind, wave height, and underestimated mixed layer from the original CFSv2.0 are improved.
Ehud Strobach, Andrea Molod, Donifan Barahona, Atanas Trayanov, Dimitris Menemenlis, and Gael Forget
Geosci. Model Dev., 15, 2309–2324, https://doi.org/10.5194/gmd-15-2309-2022, https://doi.org/10.5194/gmd-15-2309-2022, 2022
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The Green's functions methodology offers a systematic, easy-to-implement, computationally cheap, scalable, and extendable method to tune uncertain parameters in models accounting for the dependent response of the model to a change in various parameters. Herein, we successfully show for the first time that long-term errors in earth system models can be considerably reduced using Green's functions methodology. The method can be easily applied to any model containing uncertain parameters.
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
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This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
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We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Yusuke Sasaki, Hidetaka Kobayashi, and Akira Oka
Geosci. Model Dev., 15, 2013–2033, https://doi.org/10.5194/gmd-15-2013-2022, https://doi.org/10.5194/gmd-15-2013-2022, 2022
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For realistically simulating the recently observed distributions of dissolved 230Th and 231Pa in the ocean, we highlight the importance of the removal process of 231Pa and 230Th at the seafloor (bottom scavenging) and the dependence of scavenging efficiency on particle concentration. We show that consideration of these two processes can well reproduce not only the oceanic distribution of 231Pa and 230Th but also the sedimentary 231Pa/230Th ratios.
Stefan Hergarten and Jörg Robl
Geosci. Model Dev., 15, 2063–2084, https://doi.org/10.5194/gmd-15-2063-2022, https://doi.org/10.5194/gmd-15-2063-2022, 2022
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The influence of climate on landform evolution has attracted great interest over the past decades. This paper presents a simple model for simulating the influence of topography on precipitation and the decrease in precipitation over large continental areas. The approach can be included in numerical models of large-scale landform evolution and causes only a moderate increase in the numerical complexity. It opens a door to investigating feedbacks between climate and landform evolution.
Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
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Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
Justus Contzen, Thorsten Dickhaus, and Gerrit Lohmann
Geosci. Model Dev., 15, 1803–1820, https://doi.org/10.5194/gmd-15-1803-2022, https://doi.org/10.5194/gmd-15-1803-2022, 2022
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Climate models are of paramount importance to predict future climate changes. Since many severe consequences of climate change are due to extreme events, the accurate behaviour of models in terms of extremes needs to be validated thoroughly. We present a method for model validation in terms of climate extremes and an algorithm to detect regions in which extremes tend to occur at the same time. These methods are applied to data from different climate models and to observational data.
Enrico Scoccimarro, Daniele Peano, Silvio Gualdi, Alessio Bellucci, Tomas Lovato, Pier Giuseppe Fogli, and Antonio Navarra
Geosci. Model Dev., 15, 1841–1854, https://doi.org/10.5194/gmd-15-1841-2022, https://doi.org/10.5194/gmd-15-1841-2022, 2022
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This study evaluated the ability of the CMCC-CM2 climate model participating to the last CMIP6 effort, in representing extreme events of precipitation and temperature at the daily and 6-hourly frequencies. The 1/4° resolution version of the atmospheric model provides better results than the version at 1° resolution for temperature extremes, at both time frequencies. For precipitation extremes, especially at the daily time frequency, the higher resolution does not improve model results.
Joel Fiddes, Kristoffer Aalstad, and Michael Lehning
Geosci. Model Dev., 15, 1753–1768, https://doi.org/10.5194/gmd-15-1753-2022, https://doi.org/10.5194/gmd-15-1753-2022, 2022
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This study describes and evaluates a new downscaling scheme that addresses the need for hillslope-scale atmospheric forcing time series for modelling the local impact of regional climate change on the land surface in mountain areas. The method has a global scope and is able to generate all model forcing variables required for hydrological and land surface modelling. This is important, as impact models require high-resolution forcings such as those generated here to produce meaningful results.
Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
Geosci. Model Dev., 15, 1789–1802, https://doi.org/10.5194/gmd-15-1789-2022, https://doi.org/10.5194/gmd-15-1789-2022, 2022
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Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Jinyun Tang, William J. Riley, and Qing Zhu
Geosci. Model Dev., 15, 1619–1632, https://doi.org/10.5194/gmd-15-1619-2022, https://doi.org/10.5194/gmd-15-1619-2022, 2022
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We here describe version 2 of BeTR, a reactive transport model created to help ease the development of biogeochemical capability in Earth system models that are used for quantifying ecosystem–climate feedbacks. We then coupled BeTR-v2 to the Energy Exascale Earth System Model to quantify how different numerical couplings of plants and soils affect simulated ecosystem biogeochemistry. We found that different couplings lead to significant uncertainty that is not correctable by tuning parameters.
Christopher Holder, Anand Gnanadesikan, and Marie Aude-Pradal
Geosci. Model Dev., 15, 1595–1617, https://doi.org/10.5194/gmd-15-1595-2022, https://doi.org/10.5194/gmd-15-1595-2022, 2022
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It can be challenging to understand why Earth system models (ESMs) produce specific results because one can arrive at the same result simply by changing the values of the parameters. In our paper, we demonstrate that it is possible to use machine learning to figure out how and why particular components of an ESM (such as biology or ocean circulations) affect the output. This work could be applied to observations to improve the accuracy of the formulations used in ESMs.
Kun Zheng, Yan Liu, Jinbiao Zhang, Cong Luo, Siyu Tang, Huihua Ruan, Qiya Tan, Yunlei Yi, and Xiutao Ran
Geosci. Model Dev., 15, 1467–1475, https://doi.org/10.5194/gmd-15-1467-2022, https://doi.org/10.5194/gmd-15-1467-2022, 2022
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In extrapolation methods, there is a phenomenon that causes the extrapolated image to be blurred and unrealistic. The paper proposes the GAN–argcPredNet v1.0 network model, which aims to solve this problem through GAN's ability to strengthen the characteristics of multi-modal data modeling. GAN–argcPredNet v1.0 has achieved excellent results. Our model can reduce the prediction loss in a small-scale space so that the prediction results have more detailed features.
Swen Brands
Geosci. Model Dev., 15, 1375–1411, https://doi.org/10.5194/gmd-15-1375-2022, https://doi.org/10.5194/gmd-15-1375-2022, 2022
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The present study evaluates the last two global climate model generations in terms of their capability to reproduce recurrent regional atmospheric circulation patterns in the Northern Hemisphere mid-to-high latitudes under present climate conditions. These patterns are linked with many environmental variables on the local scale and thus provide an overarching concept for model verification. The results are expected to be of interest for model developers and regional climate scientists.
Shuqi Lin, Leon Boegman, Shiliang Shan, and Ryan Mulligan
Geosci. Model Dev., 15, 1331–1353, https://doi.org/10.5194/gmd-15-1331-2022, https://doi.org/10.5194/gmd-15-1331-2022, 2022
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An operational hydrodynamics forecast system, COASTLINES, using the Windows Task Scheduler, Python, and MATLAB scripts, to automate application of a 3-D model (AEM3D) in Lake Erie was developed. The system predicted storm-surge and up-/downwelling events that are important for flood water and drinking water/fishery management. This example of the successful development of an operational forecast system can be adapted to simulate aquatic systems as required for management and public safety.
Niels J. de Winter
Geosci. Model Dev., 15, 1247–1267, https://doi.org/10.5194/gmd-15-1247-2022, https://doi.org/10.5194/gmd-15-1247-2022, 2022
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ShellChron is a tool for determining the relative age of samples in carbonate (climate) archives based on the seasonal variability in temperature and salinity or precipitation recorded in stable oxygen isotope measurements. The model allows dating of fossil archives within a year, which is important for climate reconstructions on the sub-seasonal to decadal scale. In this paper, I introduce ShellChron and test it on a range of real and virtual datasets to demonstrate its use.
Fanglou Liao, Xiao Hua Wang, and Zhiqiang Liu
Geosci. Model Dev., 15, 1129–1153, https://doi.org/10.5194/gmd-15-1129-2022, https://doi.org/10.5194/gmd-15-1129-2022, 2022
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The ocean heat content (OHC) estimated using two eddying hindcast simulations, OFES1 and OFES2, was compared from 1960 to 2016, with observation-based results as a reference. Marked differences were found, especially in the Atlantic Ocean. These were related to the differences in the net surface heating, heat advection, and vertical heat diffusion. These documented differences may help the community better understand and use these quasi-global high-resolution datasets for their own purposes.
Kai-Yuan Cheng, Lucas M. Harris, and Yong Qiang Sun
Geosci. Model Dev., 15, 1097–1105, https://doi.org/10.5194/gmd-15-1097-2022, https://doi.org/10.5194/gmd-15-1097-2022, 2022
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This paper presents the implementation of container technology for the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), a unified atmospheric model that can be used as a global, a global–nest, and a regional model for weather-to-seasonal prediction. Container technology makes SHiELD cross-platform and easy to use, which opens opportunities for collaborative research and development. The performance and scalability of the containerized SHiELD are evaluated and discussed.
Junichi Tsutsui
Geosci. Model Dev., 15, 951–970, https://doi.org/10.5194/gmd-15-951-2022, https://doi.org/10.5194/gmd-15-951-2022, 2022
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A new simple climate model, MCE, was developed. It can emulate the basic behavior of comprehensive climate models in a minimal way with sufficient accuracy, providing a reasonable way to assess climate change mitigation scenarios in terms of consistency with long-term temperature goals. The model's simple structure is suitable for building probability distributions of key model parameters such that they reflect uncertainty ranges of multiple climate projections and observed warming trends.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Geosci. Model Dev., 15, 883–900, https://doi.org/10.5194/gmd-15-883-2022, https://doi.org/10.5194/gmd-15-883-2022, 2022
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The Vegetation Optimality Model (VOM) is a coupled water–vegetation model that predicts vegetation properties rather than determines them based on observations. A range of updates to previous applications of the VOM has been made for increased generality and improved comparability with conventional models. This showed that there is a large effect on the simulated water and carbon fluxes caused by the assumption of deep groundwater tables and updated soil profiles in the model.
Thomas S. Ball, Naomi E. Vaughan, Thomas W. Powell, Andrew Lovett, and Timothy M. Lenton
Geosci. Model Dev., 15, 929–949, https://doi.org/10.5194/gmd-15-929-2022, https://doi.org/10.5194/gmd-15-929-2022, 2022
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C-LLAMA is a simple model of the global food system operating at a country level from 2013 to 2050. The model begins with projections of diet composition and populations for each country, producing a demand for each food commodity and finally an agricultural land use in each country. The model can be used to explore the sensitivity of agricultural land use to various drivers within the food system at country, regional, and continental spatial aggregations.
Israel Silber, Robert C. Jackson, Ann M. Fridlind, Andrew S. Ackerman, Scott Collis, Johannes Verlinde, and Jiachen Ding
Geosci. Model Dev., 15, 901–927, https://doi.org/10.5194/gmd-15-901-2022, https://doi.org/10.5194/gmd-15-901-2022, 2022
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The Earth Model Column Collaboratory (EMC2) is an open-source ground-based (and air- or space-borne) lidar and radar simulator and subcolumn generator designed for large-scale models, in particular climate models, applicable also for high-resolution models. EMC2 emulates measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. We demonstrate the use of EMC2 to compare AWARE measurements with the NASA GISS ModelE3 and LES.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
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The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
Tommi Bergman, Risto Makkonen, Roland Schrödner, Erik Swietlicki, Vaughan T. J. Phillips, Philippe Le Sager, and Twan van Noije
Geosci. Model Dev., 15, 683–713, https://doi.org/10.5194/gmd-15-683-2022, https://doi.org/10.5194/gmd-15-683-2022, 2022
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We describe in this paper the implementation of a process-based secondary organic aerosol and new particle formation scheme within the chemistry transport model TM5-MP version 1.2. The performance of the model simulations for the year 2010 is evaluated against in situ observations, ground-based remote sensing and satellite retrievals. Overall, the simulated aerosol fields are improved, although in some areas the model shows a decline in performance.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
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We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
Katherine V. Calvin, Abigail Snyder, Xin Zhao, and Marshall Wise
Geosci. Model Dev., 15, 429–447, https://doi.org/10.5194/gmd-15-429-2022, https://doi.org/10.5194/gmd-15-429-2022, 2022
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Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. We identify parameter combinations that best replicate historical land use in the United States.
Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, https://doi.org/10.5194/gmd-15-335-2022, 2022
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Structured-mesh ocean models are still the most mature in terms of functionality due to their long development history. However, unstructured-mesh ocean models have acquired new features and caught up in their functionality. This paper continues the work by Scholz et al. (2019) of documenting the features available in FESOM2.0. It focuses on the following two aspects: (i) partial bottom cells and embedded sea ice and (ii) dealing with mixing parameterisations enabled by using the CVMix package.
Xavier Yepes-Arbós, Gijs van den Oord, Mario C. Acosta, and Glenn D. Carver
Geosci. Model Dev., 15, 379–394, https://doi.org/10.5194/gmd-15-379-2022, https://doi.org/10.5194/gmd-15-379-2022, 2022
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Climate prediction models produce a large volume of simulated data that sometimes might not be efficiently managed. In this paper we present an approach to address this issue by reducing the computing time and storage space. As a case study, we analyse the output writing process of the ECMWF atmospheric model called IFS, and we integrate into it a data writing tool called XIOS. The results suggest that the integration between the two components achieves an adequate computational performance.
Lukas Strebel, Heye R. Bogena, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 15, 395–411, https://doi.org/10.5194/gmd-15-395-2022, https://doi.org/10.5194/gmd-15-395-2022, 2022
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We present the technical coupling between a land surface model (CLM5) and the Parallel Data Assimilation Framework (PDAF). This coupling enables measurement data to update simulated model states and parameters in a statistically optimal way. We demonstrate the viability of the model framework using an application in a forested catchment where the inclusion of soil water measurements significantly improved the simulation quality.
Anna Vaughan, Will Tebbutt, J. Scott Hosking, and Richard E. Turner
Geosci. Model Dev., 15, 251–268, https://doi.org/10.5194/gmd-15-251-2022, https://doi.org/10.5194/gmd-15-251-2022, 2022
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We develop a new method for climate downscaling, i.e. transforming low-resolution climate model output to high-resolution projections, using a deep-learning model known as a convolutional conditional neural process. This model is shown to outperform an ensemble of baseline methods for downscaling daily maximum temperature and precipitation and provides a powerful new downscaling framework for climate impact studies.
Eduardo Moreno-Chamarro, Louis-Philippe Caron, Saskia Loosveldt Tomas, Javier Vegas-Regidor, Oliver Gutjahr, Marie-Pierre Moine, Dian Putrasahan, Christopher D. Roberts, Malcolm J. Roberts, Retish Senan, Laurent Terray, Etienne Tourigny, and Pier Luigi Vidale
Geosci. Model Dev., 15, 269–289, https://doi.org/10.5194/gmd-15-269-2022, https://doi.org/10.5194/gmd-15-269-2022, 2022
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Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in their ability to reproduce present and future climate changes. Model realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. We here show that increasing resolution of up to ~ 25 km can help reduce model biases but not remove them entirely.
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Short summary
Computer models of ocean biology and chemistry are becoming increasingly complex, and thus more expensive, to run. One solution is to approximate the behaviour of the ocean physics and store that information outside of the model. That
offlineinformation can then be used to calculate a steady-state solution from the model's biology and chemistry, without waiting for a traditional
onlineintegration to complete. We show this offline method reproduces online results and is 100 times faster.
Computer models of ocean biology and chemistry are becoming increasingly complex, and thus more...
