Coordinated Ocean-ice Reference Experiments (COREs)

Griffies, Stephen M.; Biastoch, Arne; Böning, Claus W.; Bryan, Frank O.; Danabasoglu, Gökhan; Chassignet, Eric P.; England, Matthew H.; Gerdes, Rüdiger; Haak, Helmuth; Hallberg, Robert; Hazeleger, Wilco; Jungclaus, Johann; Large, William G.; Madec, Gurvan; Pirani, Anna; Samuels, Bonita L.; Scheinert, Markus; Gupta, Alex Sen; Severijns, Camiel; Simmons, Harper L.; Tréguier, Anne‐Marie; Winton, M.; Yeager, Stephen; Yin, Jingxue

doi:10.1016/j.ocemod.2008.08.007

Cited by 633 publications

(678 citation statements)

References 112 publications

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“…The model includes three phytoplankton groups (small, large, and diazotrophs) and uses the variable chlorophyll:C formulation of Geider et al, [1997] to estimate NPP. Results contributed to this study were conducted with the Modular Ocean Model (MOM) version 4p1 [Griffies, 2012] with sea ice dynamics as described in Winton coupled atmosphere dynamics [Griffies et al, 2009]. Complete details of the simulation and model validation can be found in Stock et al [2014a].…”

Section: A5 Modelmentioning

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

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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.

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Section: A5 Modelmentioning

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

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“…[10] Ocean model input is from the Large and Yeager [2004] bulk-forcing data sets, as part of the forcing for Common Ocean-Ice Reference Experiments (CORE) [Griffies et al, 2008]. The atmospheric state combines reanalysis with satellite data, and surface fluxes are allowed to respond to evolving model sea surface temperature [Large and Yeager, 2004].…”

Section: Experimental Designmentioning

confidence: 99%

“…The atmospheric state combines reanalysis with satellite data, and surface fluxes are allowed to respond to evolving model sea surface temperature [Large and Yeager, 2004]. Precipitation fields are prescribed, and we apply weak salinity restoring to inhibit model drift [Griffies et al, 2008]. We combined TC wind footprints derived from QuikScat with a 7 year interval of the interannual input winds.…”

Section: Experimental Designmentioning

confidence: 99%

Modeled sensitivity of upper thermocline properties to tropical cyclone winds and possible feedbacks on the Hadley circulation

Sriver

Huber

2010

Geophysical Research Letters

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[1] The sensitivity of upper thermocline properties, and global climate, to tropical cyclone (TC) winds is examined using global ocean and atmosphere general circulation models. We combine seven years of global, satellite-based TC wind records with a standard surface wind input data set derived from reanalysis, and we apply idealized factors to TC winds in order to model the ocean's equilibrium response to increases in TC intensities. We find TC-induced vertical ocean mixing impacts upper thermocline properties, such as temperature and mixed layer depth, and the effects are amplified for increasing intensities. The model's ocean heat transport is also affected, but only when TC winds are increased substantially compared to present-day values. Atmospheric model simulations show altered ocean temperature can lead to changes in the mean Hadley circulation. Results suggest increased TC activity may affect global climate by altering the ocean's thermal structure, which could be important for large scale oceanatmosphere feedbacks. Citation: Sriver, R. L., and M. Huber

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“…Additionally, some of the models used different reanalysis or reanalysis-derived products for their surface boundary conditions. Three of the models have used NCEP-1 reanalysis fluxes [Kalnay et al, 1996], one has used NCEP-2 reanalysis fluxes [Kalnay et al, 1996], and one model has used fluxes from the Coordinated Ocean-Ice Reference Experiment (CORE) project [Large and Yeager, 2004;Griffies et al, 2009].…”

Section: Appendix A: Description Of Modelsmentioning

confidence: 99%

“…This model was forced with the NCEP derived CORE fields over 1959-2004[Large and Yeager, 2004Griffies et al, 2009]. Surface salinity was restored to observations with a 60 day timescale for the upper 10 m layer.…”

Section: A5 Mom4-topaz (The ''Gfdl'' Simulation)mentioning

confidence: 99%

Using altimetry to help explain patchy changes in hydrographic carbon measurements

et al. 2009

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[1] Here we use observations and ocean models to identify mechanisms driving large seasonal to interannual variations in dissolved inorganic carbon (DIC) and dissolved oxygen (O 2 ) in the upper ocean. We begin with observations linking variations in upper ocean DIC and O 2 inventories with changes in the physical state of the ocean. Models are subsequently used to address the extent to which the relationships derived from short-timescale (6 months to 2 years) repeat measurements are representative of variations over larger spatial and temporal scales. The main new result is that convergence and divergence (column stretching) attributed to baroclinic Rossby waves can make a first-order contribution to DIC and O 2 variability in the upper ocean. This results in a close correspondence between natural variations in DIC and O 2 column inventory variations and sea surface height (SSH) variations over much of the ocean. Oceanic Rossby wave activity is an intrinsic part of the natural variability in the climate system and is elevated even in the absence of significant interannual variability in climate mode indices. The close correspondence between SSH and both DIC and O 2 column inventories for many regions suggests that SSH changes (inferred from satellite altimetry) may prove useful in reducing uncertainty in separating natural and anthropogenic DIC signals (using measurements from Climate Variability and Predictability's CO 2 /Repeat Hydrography program).

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Coordinated Ocean-ice Reference Experiments (COREs)

Cited by 633 publications

References 112 publications

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

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

Modeled sensitivity of upper thermocline properties to tropical cyclone winds and possible feedbacks on the Hadley circulation

Using altimetry to help explain patchy changes in hydrographic carbon measurements

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