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  • 1
    In: Ocean modelling online, Amsterdam [u.a.] : Elsevier Science, 1999, 26(2009), 1/2, Seite 1-46, 1463-5011
    In: volume:26
    In: year:2009
    In: number:1/2
    In: pages:1-46
    Description / Table of Contents: Coordinated Ocean-ice Reference Experiments (COREs) are presented as a tool to explore the behaviour of global ocean-ice models under forcing from a common atmospheric dataset. We highlight issues arising when designing coupled global ocean and sea ice experiments, such as difficulties formulating a consistent forcing methodology and experimental protocol. Particular focus is given to the hydrological forcing, the details of which are key to realizing simulations with stable meridional overturning circulations. The atmospheric forcing from [Large, W., Yeager, S., 2004. Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies. NCAR Technical Note: NCAR/TN-460+STR. CGD Division of the National Center for Atmospheric Research] was developed for coupled-ocean and sea ice models. We found it to be suitable for our purposes, even though its evaluation originally focussed more on the ocean than on the sea-ice. Simulations with this atmospheric forcing are presented from seven global ocean-ice models using the CORE-I design (repeating annual cycle of atmospheric forcing for 500 years). These simulations test the hypothesis that global ocean-ice models run under the same atmospheric state produce qualitatively similar simulations. The validity of this hypothesis is shown to depend on the chosen diagnostic. The CORE simulations provide feedback to the fidelity of the atmospheric forcing and model configuration, with identification of biases promoting avenues for forcing dataset and/or model development.
    Type of Medium: Online Resource
    Pages: graph. Darst
    ISSN: 1463-5011
    Language: English
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  • 2
    Publication Date: 2020-02-10
    Description: The Atlantic meridional overturning circulation (AMOC) represents the zonally integrated stream function of meridional volume transport in the Atlantic Basin. The AMOC plays an important role in transporting heat meridionally in the climate system. Observations suggest a heat transport by the AMOC of 1.3 PW at 26°N ‐ a latitude which is close to where the Atlantic northward heat transport is thought to reach its maximum. This shapes the climate of the North Atlantic region as we know it today. In recent years there has been significant progress both in our ability to observe the AMOC in nature and to simulate it in numerical models. Most previous modeling investigations of the AMOC and its impact on climate have relied on models with horizontal resolution that does not resolve ocean mesoscale eddies and the dynamics of the Gulf Stream/North Atlantic Current system. As a result of recent increases in computing power, models are now being run that are able to represent mesoscale ocean dynamics and the circulation features that rely on them. The aim of this review is to describe new insights into the AMOC provided by high‐resolution models. Furthermore, we will describe how high‐resolution model simulations can help resolve outstanding challenges in our understanding of the AMOC.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 3
    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
    Format: application/pdf
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  • 4
    Publication Date: 2022-09-15
    Description: Author Posting. © American Meteorological Society, 2022. 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 52(1),(2022): 75–97, https://doi.org/10.1175/JPO-D-21-0099.1.
    Description: Mesoscale eddies contain the bulk of the ocean’s kinetic energy (KE), but fundamental questions remain on the cross-scale KE transfers linking eddy generation and dissipation. The role of submesoscale flows represents the key point of discussion, with contrasting views of submesoscales as either a source or a sink of mesoscale KE. Here, the first observational assessment of the annual cycle of the KE transfer between mesoscale and submesoscale motions is performed in the upper layers of a typical open-ocean region. Although these diagnostics have marginal statistical significance and should be regarded cautiously, they are physically plausible and can provide a valuable benchmark for model evaluation. The cross-scale KE transfer exhibits two distinct stages, whereby submesoscales energize mesoscales in winter and drain mesoscales in spring. Despite this seasonal reversal, an inverse KE cascade operates throughout the year across much of the mesoscale range. Our results are not incompatible with recent modeling investigations that place the headwaters of the inverse KE cascade at the submesoscale, and that rationalize the seasonality of mesoscale KE as an inverse cascade-mediated response to the generation of submesoscales in winter. However, our findings may challenge those investigations by suggesting that, in spring, a downscale KE transfer could dampen the inverse KE cascade. An exploratory appraisal of the dynamics governing mesoscale–submesoscale KE exchanges suggests that the upscale KE transfer in winter is underpinned by mixed layer baroclinic instabilities, and that the downscale KE transfer in spring is associated with frontogenesis. Current submesoscale-permitting ocean models may substantially understate this downscale KE transfer, due to the models’ muted representation of frontogenesis.
    Description: The OSMOSIS experiment was funded by the U.K. Natural Environment Research Council (NERC) through Grants NE/1019999/1 and NE/101993X/1. ACNG acknowledges the support of the Royal Society and the Wolfson Foundation, and XY that of a China Scholarship Council PhD studentship.
    Keywords: Ageostrophic circulations ; Dynamics ; Eddies ; Energy transport ; Frontogenesis/frontolysis ; Instability ; Mesoscale processes ; Nonlinear dynamics ; Ocean circulation ; Ocean dynamics ; Small scale processes ; Turbulence
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
    Publication Date: 2022-07-20
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Light, C., Arbic, B., Martin, P., Brodeau, L., Farrar, J., Griffies, S., Kirtman, B., Laurindo, L., Menemenlis, D., Molod, A., Nelson, A., Nyadjro, E., O’Rourke, A., Shriver, J., Siqueira, L., Small, R., & Strobach, E. Effects of grid spacing on high-frequency precipitation variance in coupled high-resolution global ocean–atmosphere models. Climate Dynamics, (2022): 1–27, https://doi.org/10.1007/s00382-022-06257-6.
    Description: High-frequency precipitation variance is calculated in 12 different free-running (non-data-assimilative) coupled high resolution atmosphere–ocean model simulations, an assimilative coupled atmosphere–ocean weather forecast model, and an assimilative reanalysis. The results are compared with results from satellite estimates of precipitation and rain gauge observations. An analysis of irregular sub-daily fluctuations, which was applied by Covey et al. (Geophys Res Lett 45:12514–12522, 2018. https://doi.org/10.1029/2018GL078926) to satellite products and low-resolution climate models, is applied here to rain gauges and higher-resolution models. In contrast to lower-resolution climate simulations, which Covey et al. (2018) found to be lacking with respect to variance in irregular sub-daily fluctuations, the highest-resolution simulations examined here display an irregular sub-daily fluctuation variance that lies closer to that found in satellite products. Most of the simulations used here cannot be analyzed via the Covey et al. (2018) technique, because they do not output precipitation at sub-daily intervals. Thus the remainder of the paper focuses on frequency power spectral density of precipitation and on cumulative distribution functions over time scales (2–100 days) that are still relatively “high-frequency” in the context of climate modeling. Refined atmospheric or oceanic model grid spacing is generally found to increase high-frequency precipitation variance in simulations, approaching the values derived from observations. Mesoscale-eddy-rich ocean simulations significantly increase precipitation variance only when the atmosphere grid spacing is sufficiently fine (〈 0.5°). Despite the improvements noted above, all of the simulations examined here suffer from the “drizzle effect”, in which precipitation is not temporally intermittent to the extent found in observations.
    Description: Support for CXL’s effort on this project was provided by a Research Experiences for Undergraduates (REU) supplement for National Science Foundation (NSF) grant OCE-1851164 to BKA, which also provided partial support for PEM. In addition, BKA acknowledges NSF grant OCE-1351837, which provided partial support for AKO, Office of Naval Research grant N00014-19-1-2712 and NASA grants NNX17AH55G, which also provided partial support for ADN, and 80NSSC20K1135. JTF’s participation, and the SPURS-II buoy data, were funded by NASA grants 80NSSC18K1494 and NNX15AG20G.
    Keywords: Precipitation ; High-frequency precipitation ; Numerical modeling ; High-resolution models ; Coupled ocean-atmosphere models
    Repository Name: Woods Hole Open Access Server
    Type: Article
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