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  • 1
    Publication Date: 2021-02-08
    Description: We present a new surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA-55), referred to here as JRA55-do. The JRA55-do dataset aims to replace the CORE interannual forcing version 2 (hereafter called the CORE dataset), which is currently used in the framework of the Coordinated Ocean-ice Reference Experiments (COREs) and the Ocean Model Intercomparison Project (OMIP). A major improvement in JRA55-do is the refined horizontal grid spacing (∼ 55 km) and temporal interval (3 hr). The data production method for JRA55-do essentially follows that of the CORE dataset, whereby the surface fields from an atmospheric reanalysis are adjusted relative to reference datasets. To improve the adjustment method, we use high-quality products derived from satellites and from several other atmospheric reanalysis projects, as well as feedback on the CORE dataset from the ocean modelling community. Notably, the surface air temperature and specific humidity are adjusted using multi-reanalysis ensemble means. In JRA55-do, the downwelling radiative fluxes and precipitation, which are affected by an ambiguous cloud parameterisation employed in the atmospheric model used for the reanalysis, are based on the reanalysis products. This approach represents a notable change from the CORE dataset, which imported independent observational products. Consequently, the JRA55-do dataset is more self-contained than the CORE dataset, and thus can be continually updated in near real-time. The JRA55-do dataset extends from 1958 to the present, with updates expected at least annually. This paper details the adjustments to the original JRA-55 fields, the scientific rationale for these adjustments, and the evaluation of JRA55-do. The adjustments successfully corrected the biases in the original JRA-55 fields. The globally averaged features are similar between the JRA55-do and CORE datasets, implying that JRA55-do can suitably replace the CORE dataset for use in driving global ocean–sea-ice models.
    Type: Article , PeerReviewed
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  • 2
    Publication Date: 2019-09-23
    Description: We characterise the representation of the Southern Ocean water mass structure and sea ice within a suite of 15 global ocean-ice models run with the Coordinated Ocean-ice Reference Experiment Phase II (CORE-II) protocol. The main focus is the representation of the present (1988-2007) mode and intermediate waters, thus framing an analysis of winter and summer mixed layer depths; temperature, salinity, and potential vorticity structure; and temporal variability of sea ice distributions. We also consider the interannual variability over the same 20 year period. Comparisons are made between models as well as to observation-based analyses where available. The CORE-II models exhibit several biases relative to Southern Ocean observations, including an underestimation of the model mean mixed layer depths of mode and intermediate water masses in March (associated with greater ocean surface heat gain), and an overestimation in September (associated with greater high latitude ocean heat loss and a more northward winter sea-ice extent). In addition, the models have cold and fresh/warm and salty water column biases centred near 50 degrees S. Over the 1933-2007 period, the CORE-II models consistently simulate spatially variable trends in sea-ice concentration, surface freshwater fluxes, mixed layer depths, and 200-700 in ocean heat content. In particular, sea-ice coverage around most of the Antarctic continental shelf is reduced, leading to a cooling and freshening of the near surface waters. The shoaling of the mixed layer is associated with increased surface buoyancy gain, except in the Pacific where sea ice is also influential. The models are in disagreement, despite the common CORE-II atmospheric state, in their spatial pattern of the 20-year trends in the mixed layer depth and sea-ice
    Type: Article , PeerReviewed
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  • 3
    Publication Date: 2019-02-01
    Description: The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs. OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations
    Type: Article , PeerReviewed
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  • 4
    Publication Date: 2022-01-31
    Description: We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.
    Type: Article , PeerReviewed
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  • 5
    Publication Date: 2022-01-31
    Description: The climate of the last two millennia was characterised by decadal to multi‐centennial variations which were recorded in terrestrial records and had important societal impacts. The cause of these climatic events is still under debate but changes in the North Atlantic circulation have often been proposed to play an important role. In this review we compile available high‐resolution paleoceanographic datasets from the northern North Atlantic and Nordic Seas. The records are grouped into regions related to modern ocean conditions and their variability is discussed. We additionally discuss our current knowledge from modelling studies, with a specific focus on the dynamical changes that are not well inferred from the proxy records. An illustration is provided through the analysis of two climate model ensembles and an individual simulation of the last millennium. This review thereby provides an up‐to‐date paleo‐perspective on the North Atlantic multidecadal to multi‐centennial ocean variability across the last two millennia.
    Type: Article , PeerReviewed
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  • 6
    Publication Date: 2023-02-08
    Description: We present a new framework for global ocean- sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean-sea-ice models (JRA55-do).We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean-ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean-sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80% of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP- 2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP- 2. For example, the sea surface temperatures of the OMIP- 2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating processlevel responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean-sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.
    Type: Article , PeerReviewed
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  • 7
    Publication Date: 2020-10-05
    Description: This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 8
    Publication Date: 2020-10-19
    Description: We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
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  • 9
    Publication Date: 2022-05-25
    Description: Author Posting. © American Meteorological Society, 2007. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 37 (2007): 1918-1938, doi:10.1175/jpo3089.1.
    Description: The interannual variability in upper-ocean (0–400 m) temperature and governing mechanisms for the period 1968–97 are quantified from a global ocean hindcast simulation driven by atmospheric reanalysis and satellite data products. The unconstrained simulation exhibits considerable skill in replicating the observed interannual variability in vertically integrated heat content estimated from hydrographic data and monthly satellite sea surface temperature and sea surface height data. Globally, the most significant interannual variability modes arise from El Niño–Southern Oscillation and the Indian Ocean zonal mode, with substantial extension beyond the Tropics into the midlatitudes. In the well-stratified Tropics and subtropics, net annual heat storage variability is driven predominately by the convergence of the advective heat transport, mostly reflecting velocity anomalies times the mean temperature field. Vertical velocity variability is caused by remote wind forcing, and subsurface temperature anomalies are governed mostly by isopycnal displacements (heave). The dynamics at mid- to high latitudes are qualitatively different and vary regionally. Interannual temperature variability is more coherent with depth because of deep winter mixing and variations in western boundary currents and the Antarctic Circumpolar Current that span the upper thermocline. Net annual heat storage variability is forced by a mixture of local air–sea heat fluxes and the convergence of the advective heat transport, the latter resulting from both velocity and temperature anomalies. Also, density-compensated temperature changes on isopycnal surfaces (spice) are quantitatively significant.
    Description: This work was supported in part from NOAA Office of Global Programs ACCP Grant NA86GP0290, NSF Grant OCE96-33681, and the WHOI Ocean and Climate Change Institute.
    Keywords: Temperature ; Interannual variability ; Advection ; Heating ; Air–sea interaction
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 10
    Publication Date: 2022-05-25
    Description: Author Posting. © American Meteorological Society, 2012. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 25 (2012): 5153–5172, doi:10.1175/JCLI-D-11-00463.1.
    Description: Atlantic meridional overturning circulation (AMOC) variability is documented in the Community Climate System Model, version 4 (CCSM4) preindustrial control simulation that uses nominal 1° horizontal resolution in all its components. AMOC shows a broad spectrum of low-frequency variability covering the 50–200-yr range, contrasting sharply with the multidecadal variability seen in the T85 × 1 resolution CCSM3 present-day control simulation. Furthermore, the amplitude of variability is much reduced in CCSM4 compared to that of CCSM3. Similarities as well as differences in AMOC variability mechanisms between CCSM3 and CCSM4 are discussed. As in CCSM3, the CCSM4 AMOC variability is primarily driven by the positive density anomalies at the Labrador Sea (LS) deep-water formation site, peaking 2 yr prior to an AMOC maximum. All processes, including parameterized mesoscale and submesoscale eddies, play a role in the creation of salinity anomalies that dominate these density anomalies. High Nordic Sea densities do not necessarily lead to increased overflow transports because the overflow physics is governed by source and interior region density differences. Increased overflow transports do not lead to a higher AMOC either but instead appear to be a precursor to lower AMOC transports through enhanced stratification in LS. This has important implications for decadal prediction studies. The North Atlantic Oscillation (NAO) is significantly correlated with the positive boundary layer depth and density anomalies prior to an AMOC maximum. This suggests a role for NAO through setting the surface flux anomalies in LS and affecting the subpolar gyre circulation strength.
    Description: The CCSM project is supported by NSF and the Office of Science (BER) of the U.S. Department of Energy. SGY and YOK were supported by the NOAA Climate Program Office under Climate Variability and Predictability Program Grants NA09OAR4310163 and NA10OAR4310202, respectively.
    Description: 2013-02-01
    Keywords: Meridional overturning circulation ; Coupled models ; Ocean models ; Oceanic variability
    Repository Name: Woods Hole Open Access Server
    Type: Article
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