Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM)

Tjiputra, Jerry; Roelandt, C.; Bentsen, Mats; Lawrence, David M.; Lorentzen, Torbjørn; Schwinger, Jörg; Seland, Øyvind; Heinze, Christoph

doi:10.5194/gmd-6-301-2013

Cited by 228 publications

(142 citation statements)

References 95 publications

(136 reference statements)

Supporting

Mentioning

133

Contrasting

Unclassified

Order By: Relevance

“…The HAMburg Ocean Carbon Cycle model (HAMOCC;Maier-Reimer, 1993;Maier-Reimer et al, 2005) has been implemented into MICOM by Assmann et al (2010). The HAMOCC version used in NorESM1-ME is further described by Tjiputra et al (2013) and Schwinger et al (2016). We note that HAMOCC, since it was implemented into MI-COM, has also been further developed by the biogeochemistry group at the Max Planck Institute in Hamburg.…”

Section: The Marine Biogeochemistry Model Micom-hamoccmentioning

confidence: 99%

“…It uses the same sea-ice and land models, but a different ocean component and a different aerosol module embedded in the atmosphere model. Here, we use the model version that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5; Taylor et al, 2012), and that has been described and evaluated in a series of papers Iversen et al, 2013;Tjiputra et al, 2013;Kirkevåg et al, 2013). The only difference between the published model version and the model version employed for this study, is the coupling of prognostic sea-air DMS fluxes calculated by the ocean biogeochemistry component to the atmosphere model (as opposed to the use of prescribed climatological DMS emissions in the CMIP5 model version).…”

Section: Model Description and Experimental Set-upmentioning

confidence: 99%

See 1 more Smart Citation

Amplification of global warming through pH dependence of DMS production simulated with a fully coupled Earth system model

et al. 2017

Self Cite

View full text Add to dashboard Cite

Abstract. We estimate the additional transient surface warming T s caused by a potential reduction of marine dimethyl sulfide (DMS) production due to ocean acidification under the high-emission scenario RCP8.5 until the year 2200. Since we use a fully coupled Earth system model, our results include a range of feedbacks, such as the response of marine DMS production to the additional changes in temperature and sea ice cover. Our results are broadly consistent with the findings of a previous study that employed an offline model set-up. Assuming a medium (strong) sensitivity of DMS production to pH, we find an additional transient global warming of 0.30 K (0.47 K) towards the end of the 22nd century when DMS emissions are reduced by 7.3 Tg S yr −1 or 31 % (11.5 Tg S yr −1 or 48 %). The main mechanism behind the additional warming is a reduction of cloud albedo, but a change in shortwave radiative fluxes under clear-sky conditions due to reduced sulfate aerosol load also contributes significantly. We find an approximately linear relationship between reduction of DMS emissions and changes in top of the atmosphere radiative fluxes as well as changes in surface temperature for the range of DMS emissions considered here. For example, global average T s changes by −0.041 K per 1 Tg S yr −1 change in sea-air DMS fluxes. The additional warming in our model has a pronounced asymmetry between northern and southern high latitudes. It is largest over the Antarctic continent, where the additional temperature increase of 0.56 K (0.89 K) is almost twice the global average. We find that feedbacks are small on the global scale due to opposing regional contributions. The most pronounced feedback is found for the Southern Ocean, where we estimate that the additional climate change enhances sea-air DMS fluxes by about 9 % (15 %), which counteracts the reduction due to ocean acidification.

show abstract

Section: The Marine Biogeochemistry Model Micom-hamoccmentioning

confidence: 99%

Section: Model Description and Experimental Set-upmentioning

confidence: 99%

Amplification of global warming through pH dependence of DMS production simulated with a fully coupled Earth system model

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…DSL variations are related to changes in density of the water columns and changes in the ocean bottom pressure (Gill and Niller 1973). The changes in ocean bottom pressure represent the redistribution of Tjiputra et al (2013) mass by the ocean circulation in response to the atmospheric forcing. This does not include here the changes in the mass of the ocean associated with glacier and ice sheet mass loss or land water storage changes.…”

Section: A Contribution From Dynamic Sea Levelmentioning

confidence: 99%

Evaluating Model Simulations of Twentieth-Century Sea-Level Rise. Part II: Regional Sea-Level Changes

et al. 2017

View full text Add to dashboard Cite

Twentieth-century regional sea level changes are estimated from 12 climate models from phase 5 of the Climate Model Intercomparison Project (CMIP5). The output of the CMIP5 climate model simulations was used to calculate the global and regional sea level changes associated with dynamic sea level, atmospheric loading, glacier mass changes, and ice sheet surface mass balance contributions. The contribution from groundwater depletion, reservoir storage, and dynamic ice sheet mass changes are estimated from observations as they are not simulated by climate models. All contributions are summed, including the glacial isostatic adjustment (GIA) contribution, and compared to observational estimates from 27 tide gauge records over the twentieth century . A general agreement is found between the simulated sea level and tide gauge records in terms of interannual to multidecadal variability over 1900-2015. But climate models tend to systematically underestimate the observed sea level trends, particularly in the first half of the twentieth century. The corrections based on attributable biases between observations and models that have been identified in Part I of this two-part paper result in an improved explanation of the spatial variability in observed sea level trends by climate models. Climate models show that the spatial variability in sea level trends observed by tide gauge records is dominated by the GIA contribution and the steric contribution over 1900-2015. Climate models also show that it is important to include all contributions to sea level changes as they cause significant local deviations; note, for example, the groundwater depletion around India, which is responsible for the low twentieth-century sea level rise in the region.

show abstract

“…The NorESM is a fully coupled climate-biogeochemical model [Tjiputra et al, 2013]. It is the fully coupled version of Model 8 described above.…”

Section: A18 Model 19mentioning

confidence: 99%

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

Lee

Matrai

Friedrichs

et al. 2016

J. Geophys. Res. Oceans

Self Cite

View full text Add to dashboard Cite

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality‐controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan‐Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice‐free versus ice‐influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.

show abstract

Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM)

Cited by 228 publications

References 95 publications

Amplification of global warming through pH dependence of DMS production simulated with a fully coupled Earth system model

Amplification of global warming through pH dependence of DMS production simulated with a fully coupled Earth system model

Evaluating Model Simulations of Twentieth-Century Sea-Level Rise. Part II: Regional Sea-Level Changes

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

Contact Info

Product

Resources

About