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  • 1
    Publication Date: 2020-12-02
    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.
    Description: Published
    Description: 79-139
    Description: 4A. Oceanografia e clima
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    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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  • 3
    Publication Date: 2022-05-26
    Description: Author Posting. © American Meteorological Society, 2017. 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 30 (2017): 4965-4981, doi:10.1175/JCLI-D-16-0228.1.
    Description: To improve the understanding of storm tracks and western boundary current (WBC) interactions, surface storm tracks in 12 CMIP5 models are examined against ERA-Interim. All models capture an equatorward displacement toward the WBCs in the locations of the surface storm tracks’ maxima relative to those at 850 hPa. An estimated storm-track metric is developed to analyze the location of the surface storm track. It shows that the equatorward shift is influenced by both the lower-tropospheric instability and the baroclinicity. Basin-scale spatial correlations between models and ERA-Interim for the storm tracks, near-surface stability, SST gradient, and baroclinicity are calculated to test the ability of the GCMs’ match reanalysis. An intermodel comparison of the spatial correlations suggests that differences (relative to ERA-Interim) in the position of the storm track aloft have the strongest influence on differences in the surface storm-track position. However, in the North Atlantic, biases in the surface storm track north of the Gulf Stream are related to biases in the SST. An analysis of the strength of the storm tracks shows that most models generate a weaker storm track at the surface than 850 hPa, consistent with observations, although some outliers are found. A linear relationship exists among the models between storm-track amplitudes at 500 and 850 hPa, but not between 850 hPa and the surface. In total, the work reveals a dual role in forcing the surface storm track from aloft and from the ocean surface in CMIP5 models, with the atmosphere having the larger relative influence.
    Description: JFB was partially supported by the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections program (Grant NA15OAR4310094). Y-OK was supported by NSF Division of Atmospheric and Geospace Science Climate and Large-scale Dynamics Program (AGS-1355339), NASA Physical Oceanography Program (NNX13AM59G), and DOE Office of Biological and Environmental Research Regional and Global Climate Modeling Program (DE-SC0014433). RJS was supported by DOE Office of Biological and Environmental Research (DE-SC0006743) and NSF Directorate for Geosciences Division of Ocean Sciences (1419584),
    Description: 2017-10-03
    Keywords: Atmosphere-ocean interaction ; Storm tracks
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
    Publication Date: 2022-05-26
    Description: Author Posting. © American Meteorological Society, 2017. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 97 (2016): 2305-2327, doi:10.1175/BAMS-D-15-00274.1.
    Description: Well-known problems trouble coupled general circulation models of the eastern Atlantic and Pacific Ocean basins. Model climates are significantly more symmetric about the equator than is observed. Model sea surface temperatures are biased warm south and southeast of the equator, and the atmosphere is too rainy within a band south of the equator. Near-coastal eastern equatorial SSTs are too warm, producing a zonal SST gradient in the Atlantic opposite in sign to that observed. The U.S. Climate Variability and Predictability Program (CLIVAR) Eastern Tropical Ocean Synthesis Working Group (WG) has pursued an updated assessment of coupled model SST biases, focusing on the surface energy balance components, on regional error sources from clouds, deep convection, winds, and ocean eddies; on the sensitivity to model resolution; and on remote impacts. Motivated by the assessment, the WG makes the following recommendations: 1) encourage identification of the specific parameterizations contributing to the biases in individual models, as these can be model dependent; 2) restrict multimodel intercomparisons to specific processes; 3) encourage development of high-resolution coupled models with a concurrent emphasis on parameterization development of finer-scale ocean and atmosphere features, including low clouds; 4) encourage further availability of all surface flux components from buoys, for longer continuous time periods, in persistently cloudy regions; and 5) focus on the eastern basin coastal oceanic upwelling regions, where further opportunities for observational–modeling synergism exist.
    Description: PZ, BK, and RM acknowledge support from NOAA Grant NA14OAR4310278, and PZ acknowledges support from NSF AGS-1233874. BM acknowledges support from the Regional and Global Climate Modeling Program of the U.S. Department of Energy’s Office of Science, Cooperative Agreement DE-FC02-97ER62402. PC acknowledges support from U.S. NSF Grants OCE-1334707 and AGS-1462127, and NOAA Grant NA11OAR4310154. PC also acknowledges support from China’s National Basic Research Priorities Programme (2013CB956204) and the Natural Science Foundation of China (41222037 and 41221063). TF acknowledges support from NSF Grant OCE-0745508 and NASA Grant NNX14AM71G. PB acknowledges support from the BMBF SACUS (03G0837A) project. TT and PB acknowledge support from the European Union Seventh Framework Programme (FP7 20072013) under Grant Agreement 603521 for the PREFACE Project. ES and ZW acknowledge support from NSF AGS-1338427, NOAA NA14OAR4310160, and NASA NNX14AM19G; and ES is grateful for further support from the National Monsoon Mission, Ministry of Earth Sciences, India.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
    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
    Format: text
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  • 6
    Publication Date: 2019-09-23
    Description: Current climate models systematically underestimate the strength of oceanic fronts associated with strong western boundary currents, such as the Kuroshio and Gulf Stream Extensions, and have difficulty simulating their positions at the mid-latitude ocean’s western boundaries1. Even with an enhanced grid resolution to resolve ocean mesoscale eddies—energetic circulations with horizontal scales of about a hundred kilometres that strongly interact with the fronts and currents—the bias problem can still persist2; to improve climate models we need a better understanding of the dynamics governing these oceanic frontal regimes. Yet prevailing theories about the western boundary fronts are based on ocean internal dynamics without taking into consideration the intense air–sea feedbacks in these oceanic frontal regions. Here, by focusing on the Kuroshio Extension Jet east of Japan as the direct continuation of the Kuroshio, we show that feedback between ocean mesoscale eddies and the atmosphere (OME-A) is fundamental to the dynamics and control of these energetic currents. Suppressing OME-A feedback in eddy-resolving coupled climate model simulations results in a 20–40 per cent weakening in the Kuroshio Extension Jet. This is because OME-A feedback dominates eddy potential energy destruction, which dissipates more than 70 per cent of the eddy potential energy extracted from the Kuroshio Extension Jet. The absence of OME-A feedback inevitably leads to a reduction in eddy potential energy production in order to balance the energy budget, which results in a weakened mean current. The finding has important implications for improving climate models’ representation of major oceanic fronts, which are essential components in the simulation and prediction of extratropical storms and other extreme events3, 4, 5, 6, as well as in the projection of the effect on these events of climate change.
    Type: Article , PeerReviewed
    Format: text
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  • 7
    Publication Date: 2019-02-01
    Description: Well-known problems trouble coupled general circulation models of the eastern Atlantic and Pacific Ocean basins. Model climates are significantly more symmetric about the equator than is observed. Model sea surface temperatures are biased warm south and southeast of the equator, and the atmosphere is too rainy within a band south of the equator. Near-coastal eastern equatorial SSTs are too warm, producing a zonal SST gradient in the Atlantic opposite in sign to that observed. The U.S. Climate Variability and Predictability Program (CLIVAR) Eastern Tropical Ocean Synthesis Working Group (WG) has pursued an updated assessment of coupled model SST biases, focusing on the surface energy balance components, on regional error sources from clouds, deep convection, winds, and ocean eddies; on the sensitivity to model resolution; and on remote impacts. Motivated by the assessment, the WG makes the following recommendations: 1) encourage identification of the specific parameterizations contributing to the biases in individual models, as these can be model dependent; 2) restrict multimodel intercomparisons to specific processes; 3) encourage development of high-resolution coupled models with a concurrent emphasis on parameterization development of finer-scale ocean and atmosphere features, including low clouds; 4) encourage further availability of all surface flux components from buoys, for longer continuous time periods, in persistently cloudy regions; and 5) focus on the eastern basin coastal oceanic upwelling regions, where further opportunities for observational–modeling synergism exist.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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  • 8
    Publication Date: 2024-02-07
    Description: Two decades of high-resolution satellite observations and climate modeling studies have indicated strong ocean–atmosphere coupled feedback mediated by ocean mesoscale processes, including semipermanent and meandrous SST fronts, mesoscale eddies, and filaments. The air–sea exchanges in latent heat, sensible heat, momentum, and carbon dioxide associated with this so-called mesoscale air–sea interaction are robust near the major western boundary currents, Southern Ocean fronts, and equatorial and coastal upwelling zones, but they are also ubiquitous over the global oceans wherever ocean mesoscale processes are active. Current theories, informed by rapidly advancing observational and modeling capabilities, have established the importance of mesoscale and frontal-scale air–sea interaction processes for understanding large-scale ocean circulation, biogeochemistry, and weather and climate variability. However, numerous challenges remain to accurately diagnose, observe, and simulate mesoscale air–sea interaction to quantify its impacts on large-scale processes. This article provides a comprehensive review of key aspects pertinent to mesoscale air–sea interaction, synthesizes current understanding with remaining gaps and uncertainties, and provides recommendations on theoretical, observational, and modeling strategies for future air–sea interaction research.
    Type: Article , PeerReviewed
    Format: text
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