scholarly journals Global ocean biogeochemistry model HAMOCC: Model architecture and performance as component of the MPI-Earth system model in different CMIP5 experimental realizations

2013 ◽  
Vol 5 (2) ◽  
pp. 287-315 ◽  
Author(s):  
Tatiana Ilyina ◽  
Katharina D. Six ◽  
Joachim Segschneider ◽  
Ernst Maier-Reimer ◽  
Hongmei Li ◽  
...  
Climate ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 83
Author(s):  
Hyo-Jong Song ◽  
Jong-Yeon Park

Identifying bottom-up (e.g., physical and biogeochemical) drivers for fish catch is essential for sustainable fishing and successful adaptation to climate change through reliable prediction of future fisheries. Previous studies have suggested the potential linkage of fish catch to bottom-up drivers such as ocean temperature or satellite-retrieved chlorophyll concentration across different global ecosystems. Robust estimation of bottom-up effects on global fisheries is, however, still challenging due to the lack of long-term observations of fisheries-relevant biotic variables on a global scale. Here, by using novel long-term biological and biogeochemical data reconstructed from a recently developed data assimilative Earth system model, we newly identified dominant drivers for fish catch in globally distributed coastal ecosystems. A machine learning analysis with the inclusion of reconstructed zooplankton production and dissolved oxygen concentration into the fish catch predictors provides an extended view of the links between environmental forcing and fish catch. Furthermore, the relative importance of each driver and their thresholds for high and low fish catch are analyzed, providing further insight into mechanistic principles of fish catch in individual coastal ecosystems. The results presented herein suggest the potential predictive use of their relationships and the need for continuous observational effort for global ocean biogeochemistry.


2015 ◽  
Vol 12 (11) ◽  
pp. 3301-3320 ◽  
Author(s):  
K. B. Rodgers ◽  
J. Lin ◽  
T. L. Frölicher

Abstract. Marine ecosystems are increasingly stressed by human-induced changes. Marine ecosystem drivers that contribute to stressing ecosystems – including warming, acidification, deoxygenation and perturbations to biological productivity – can co-occur in space and time, but detecting their trends is complicated by the presence of noise associated with natural variability in the climate system. Here we use large initial-condition ensemble simulations with an Earth system model under a historical/RCP8.5 (representative concentration pathway 8.5) scenario over 1950–2100 to consider emergence characteristics for the four individual and combined drivers. Using a 1-standard-deviation (67% confidence) threshold of signal to noise to define emergence with a 30-year trend window, we show that ocean acidification emerges much earlier than other drivers, namely during the 20th century over most of the global ocean. For biological productivity, the anthropogenic signal does not emerge from the noise over most of the global ocean before the end of the 21st century. The early emergence pattern for sea surface temperature in low latitudes is reversed from that of subsurface oxygen inventories, where emergence occurs earlier in the Southern Ocean. For the combined multiple-driver field, 41% of the global ocean exhibits emergence for the 2005–2014 period, and 63% for the 2075–2084 period. The combined multiple-driver field reveals emergence patterns by the end of this century that are relatively high over much of the Southern Ocean, North Pacific, and Atlantic, but relatively low over the tropics and the South Pacific. For the case of two drivers, the tropics including habitats of coral reefs emerges earliest, with this driven by the joint effects of acidification and warming. It is precisely in the regions with pronounced emergence characteristics where marine ecosystems may be expected to be pushed outside of their comfort zone determined by the degree of natural background variability to which they are adapted. The results underscore the importance of sustained multi-decadal observing systems for monitoring multiple ecosystems drivers.


2020 ◽  
Vol 13 (7) ◽  
pp. 3383-3438 ◽  
Author(s):  
Veronika Eyring ◽  
Lisa Bock ◽  
Axel Lauer ◽  
Mattia Righi ◽  
Manuel Schlund ◽  
...  

Abstract. The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of (1) an easy-to-install, well-documented Python package providing the core functionalities (ESMValCore) that performs common preprocessing operations and (2) a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the second major release of the tool that supports the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). ESMValTool v2.0 includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. ESMValTool v2.0 also successfully reproduces figures from the evaluation and projections chapters of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and incorporates updates from targeted analysis packages, such as the NCAR Climate Variability Diagnostics Package for the evaluation of modes of variability, the Thermodynamic Diagnostic Tool (TheDiaTo) to evaluate the energetics of the climate system, as well as parts of AutoAssess that contains a mix of top–down performance metrics. The tool has been fully integrated into the Earth System Grid Federation (ESGF) infrastructure at the Deutsches Klimarechenzentrum (DKRZ) to provide evaluation results from CMIP6 model simulations shortly after the output is published to the CMIP archive. A result browser has been implemented that enables advanced monitoring of the evaluation results by a broad user community at much faster timescales than what was possible in CMIP5.


2009 ◽  
Vol 34 (1) ◽  
pp. 151-151
Author(s):  
Marisa Montoya ◽  
Alexa Griesel ◽  
Anders Levermann ◽  
Juliette Mignot ◽  
Matthias Hofmann ◽  
...  

2013 ◽  
Vol 6 (2) ◽  
pp. 477-494 ◽  
Author(s):  
K. Matsumoto ◽  
K. Tokos ◽  
A. Huston ◽  
H. Joy-Warren

Abstract. Here we describe the second version of Minnesota Earth System Model for Ocean biogeochemistry (MESMO 2), an earth system model of intermediate complexity, which consists of a dynamical ocean, dynamic-thermodynamic sea ice, and energy moisture balanced atmosphere. The new version has more realistic land ice masks and is driven by seasonal winds. A major aim in version 2 is representing the marine silica cycle mechanistically in order to investigate climate-carbon feedbacks involving diatoms, a critically important class of phytoplankton in terms of carbon export production. This is achieved in part by including iron, on which phytoplankton uptake of silicic acid depends. Also, MESMO 2 is coupled to an existing terrestrial model, which allows for the exchange of carbon, water and energy between land and the atmosphere. The coupled model, called MESMO 2E, is appropriate for more complete earth system simulations. The new version was calibrated, with the goal of preserving reasonable interior ocean ventilation and various biological production rates in the ocean and land, while simulating key features of the marine silica cycle.


2012 ◽  
Vol 5 (3) ◽  
pp. 2999-3033 ◽  
Author(s):  
K. Matsumoto ◽  
K. S. Tokos ◽  
A. Huston ◽  
H. Joy-Warren

Abstract. Here we describe the second version of Minnesota Earth System Model for Ocean biogeochemistry (MESMO 2), an earth system model of intermediate complexity, which consists of a dynamical ocean, dynamic-thermodynamic sea ice, and energy moisture balanced atmosphere. The new version has more realistic land ice masks and is driven by seasonal winds. A major aim in version 2 is representing the marine silica cycle mechanistically in order to investigate climate-carbon feedbacks involving diatoms, a critically important class of phytoplankton in terms of carbon export production. This is achieved in part by including iron, on which phytoplankton uptake of silicic acid depends. Also, MESMO 2 is coupled to an existing terrestrial model, which allows for the exchange of carbon, water, and energy between land and the atmosphere. The coupled model, called MESMO 2E, is appropriate for more complete earth system simulations. The new version was calibrated with the goal of preserving reasonable interior ocean ventilation and various biological production rates in the ocean and land, while simulating key features of the marine silica cycle.


2021 ◽  
Vol 17 (5) ◽  
pp. 2223-2254
Author(s):  
Katherine A. Crichton ◽  
Andy Ridgwell ◽  
Daniel J. Lunt ◽  
Alex Farnsworth ◽  
Paul N. Pearson

Abstract. Since the middle Miocene (15 Ma, million years ago), the Earth's climate has undergone a long-term cooling trend, characterised by a reduction in ocean temperatures of up to 7–8 ∘C. The causes of this cooling are primarily thought to be due to tectonic plate movements driving changes in large-scale ocean circulation patterns, and hence heat redistribution, in conjunction with a drop in atmospheric greenhouse gas forcing (and attendant ice-sheet growth and feedback). In this study, we assess the potential to constrain the evolving patterns of global ocean circulation and cooling over the last 15 Ma by assimilating a variety of marine sediment proxy data in an Earth system model. We do this by first compiling surface and benthic ocean temperature and benthic carbon-13 (δ13C) data in a series of seven time slices spaced at approximately 2.5 Myr intervals. We then pair this with a corresponding series of tectonic and climate boundary condition reconstructions in the cGENIE (“muffin” release) Earth system model, including alternative possibilities for an open vs. closed Central American Seaway (CAS) from 10 Ma onwards. In the cGENIE model, we explore uncertainty in greenhouse gas forcing and the magnitude of North Pacific to North Atlantic salinity flux adjustment required in the model to create an Atlantic Meridional Overturning Circulation (AMOC) of a specific strength, via a series of 12 (one for each tectonic reconstruction) 2D parameter ensembles. Each ensemble member is then tested against the observed global temperature and benthic δ13C patterns. We identify that a relatively high CO2 equivalent forcing of 1120 ppm is required at 15 Ma in cGENIE to reproduce proxy temperature estimates in the model, noting that this CO2 forcing is dependent on the cGENIE model's climate sensitivity and that it incorporates the effects of all greenhouse gases. We find that reproducing the observed long-term cooling trend requires a progressively declining greenhouse gas forcing in the model. In parallel to this, the strength of the AMOC increases with time despite a reduction in the salinity of the surface North Atlantic over the cooling period, attributable to falling intensity of the hydrological cycle and to lowering polar temperatures, both caused by CO2-driven global cooling. We also find that a closed CAS from 10 Ma to present shows better agreement between benthic δ13C patterns and our particular series of model configurations and data. A final outcome of our analysis is a pronounced ca. 1.5 ‰ decline occurring in atmospheric (and ca. 1 ‰ ocean surface) δ13C that could be used to inform future δ13C-based proxy reconstructions.


2021 ◽  
Author(s):  
Stelios Myriokefalitakis ◽  
Elisa Bergas-Massó ◽  
María Gonçalves-Ageitos ◽  
Carlos Pérez García-Pando ◽  
Twan van Noije ◽  
...  

Abstract. Understanding how multiphase processes affect the iron-containing aerosol cycle is key to predict ocean biogeochemistry changes and hence the feedback effects on climate. For this work, the EC-Earth Earth system model in its climate-chemistry configuration is used to simulate the global atmospheric oxalate (OXL), sulfate (SO42−), and iron (Fe) cycles, after incorporating a comprehensive representation of the multiphase chemistry in cloud droplets and aerosol water. The model considers a detailed gas-phase chemistry scheme, all major aerosol components, and the partitioning of gases in aerosol and atmospheric water phases. The dissolution of Fe-containing aerosols accounts kinetically for the solution’s acidity, oxalic acid, and irradiation. Aerosol acidity is explicitly calculated in the model, both for accumulation and coarse modes, accounting for thermodynamic processes involving inorganic and crustal species from sea salt and dust. Simulations for present-day conditions (2000–2014) have been carried out with both EC-Earth and the atmospheric composition component of the model in standalone mode driven by meteorological fields from ECMWF’s ERA-Interim reanalysis. The calculated global budgets are presented and the links between the 1) aqueous-phase processes, 2) aerosol dissolution, and 3) atmospheric composition, are demonstrated and quantified. The model results are supported by comparison to available observations. We obtain an average global OXL net chemical production of 12.61 ± 0.06 Tg yr−1 in EC-Earth, with glyoxal being by far the most important precursor of oxalic acid. In comparison to the ERA-Interim simulation, differences in atmospheric dynamics as well as the simulated weaker oxidizing capacity in EC-Earth result overall in a ~30 % lower OXL source. On the other hand, the more explicit representation of the aqueous-phase chemistry in EC-Earth compared to the previous versions of the model leads to an overall ~20 % higher sulfate production, but still well correlated with atmospheric observations. The total Fe dissolution rate in EC-Earth is calculated at 0.806 ± 0.014 Tg Fe yr−1 and is added to the primary dissolved Fe (DFe) sources from dust and combustion aerosols in the model (0.072 ± 0.001 Tg Fe yr−1). The simulated DFe concentrations show a satisfactory comparison with available observations, indicating an atmospheric burden of ∼0.007 Tg Fe, and overall resulting in an atmospheric deposition flux into the global ocean of 0.376 ± 0.005 Tg Fe yr−1, well within the range reported in the literature. All in all, this work is a first step towards the development of EC-Earth into an Earth System Model with fully interactive bioavailable atmospheric Fe inputs to the marine biogeochemistry component of the model.


2017 ◽  
Author(s):  
Ben A. Ward ◽  
Jamie D. Wilson ◽  
Ros M. Death ◽  
Fanny M. Monteiro ◽  
Andrew Yool ◽  
...  

Abstract. We present an extension to the cGENIE Earth System model that explicitly accounts for the growth and interaction of an arbitrary number of plankton species. The new package (ECOGEM) replaces the implicit, flux-based, parameterisation of the plankton community currently employed, with explicitly resolved plankton populations and ecological dynamics. In ECOGEM, any number of plankton species, with ecophysiological traits (e.g. growth and grazing rates) assigned according to organism size and functional group (e.g. phytoplankton and zooplankton) can be incorporated at run-time. We illustrate the capability of the marine ecology enabled Earth system model (EcoGENIE) by comparing results from one configuration of ECOGEM (with eight generic phytoplankton and zooplankton size classes) to climatological and seasonal observations. We find that the new ecological components of the model show reasonable agreement with both global-scale climatological and local-scale seasonal data. We also compare EcoGENIE results to a the existing biogeochemical incarnation of cGENIE. We find that the resulting global-scale distributions of phosphate, iron, dissolved inorganic carbon, alkalinity and oxygen are similar for both iterations of the model. A slight deterioration in some fields in EcoGENIE (relative to the data) is observed, although we make no attempt to re-tune the overall marine cycling of carbon and nutrients here. The increased capabilities of EcoGENIE in this regard will enable future exploration of the ecological community on much longer timescales than have previously been examined in global ocean ecosystem models and particularly for past climates and global biogeochemical cycles.


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