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Large, William
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Large, William
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Large, W G
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- PublicationOpen AccessNorth Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states(2014-01)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;Danabasoglu, G.; NCAR, Boulder, CO USA ;Yeager, S. G.; NCAR, Boulder, CO USA ;Bailey, D.; NCAR, Boulder, CO USA ;Behrens, E.; GEOMAR, Helmholtz Ctr Ocean Res, Kiel, Germany ;Bentsen, M.; Uni Res Ltd, Uni Climate, Bergen, Norway ;Bi, D.; CSIRO, Ctr Australian Weather & Climate Res, Melbourne, Australia ;Biastoch, A.; GEOMAR, Helmholtz Ctr Ocean Res, Kiel, Germany ;Boening, C.; GEOMAR, Helmholtz Ctr Ocean Res, Kiel, Germany ;Bozec, A.; Florida State Univ, COAPS, Tallahassee, FL 32306 USA ;Canuto, V. M.; NASA, Goddard Inst Space Studies, New York, NY 10025 USA ;Cassou, C.; CERFACS, Toulouse, France ;Chassignet, E.; Florida State Univ, COAPS, Tallahassee, FL 32306 USA ;Coward, A. C.; NOCS, Southampton, Hants, England ;Danilov, S.; Alfred Wegener Inst Polar & Marine Res AWI, Bremerhaven, Germany ;Diansky, N.; Russian Acad Sci, Inst Numer Math, Moscow, Russia ;Drange, H.; Univ Bergen, Bergen, Norway ;Farneti, R.; Abdus Salaam Int Ctr Theoret Phys, Trieste, Italy ;Fernandez, E.; CERFACS, Toulouse, France ;Fogli, P. G.; Ctr Euro Mediterraneo Cambiamenti Climatici CMCC, Bologna, Italy ;Forget, G.; MIT, Cambridge, MA 02139 USA ;Fujii, Y.; Japan Meteorol Agcy, MRI, Tsukuba, Ibaraki, Japan ;Griffies, S. M.; NOAA, GFDL, Princeton, NJ USA ;Gusev, A.; Russian Acad Sci, Inst Numer Math, Moscow, Russia ;Heimbach, P.; MIT, Cambridge, MA 02139 USA ;Howard, A.; CUNY Medgar Evers Coll, Brooklyn, NY 11225 USA ;Jung, T.; Alfred Wegener Inst Polar & Marine Res AWI, Bremerhaven, Germany ;Kelley, M.; NOAA, GFDL, Princeton, NJ USA ;Large, W. G.; NCAR, Boulder, CO USA ;Leboissetier, A.; NASA, Goddard Inst Space Studies, New York, NY 10025 USA ;Lu, J.; Florida State Univ, COAPS, Tallahassee, FL 32306 USA ;Madec, G.; CNRS IRD UPMC, IPSL LOCEAN, Paris, France ;Marsland, S. J.; CSIRO, Ctr Australian Weather & Climate Res, Melbourne, Australia CSIRO, Bur Meteorol, Melbourne, Australia ;Masina, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia ;Navarra, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia ;Nurser, A. J. G.; NOCS, Southampton, Hants, England ;Pirani, A.; Natl Oceanog Ctr, Int CLIVAR Project Off, Southampton, Hants, England ;Salas y Melia, D.; CNRM, Toulouse, France ;Samuels, B. L.; NOAA, GFDL, Princeton, NJ USA ;Scheinert, M.; GEOMAR, Helmholtz Ctr Ocean Res, Kiel, Germany ;Sidorenko, D.; Alfred Wegener Inst Polar & Marine Res AWI, Bremerhaven, German ;Treguier, A.; IUEM, CNRS Ifremer IRD UBO, UMR 6523, Lab Phys Oceans, Plouzane, France ;Tsujino, H.; Japan Meteorol Agcy, MRI, Tsukuba, Ibaraki, Japan ;Uotila, P.; CSIRO, Ctr Australian Weather & Climate Res, Melbourne, Australia ;Valcke, S.; CERFACS, Toulouse, France ;Voldoire, A.; CNRM, Toulouse, France ;Wangi, Q.; Alfred Wegener Inst Polar & Marine Res AWI, Bremerhaven, Germany; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; Simulation characteristics from eighteen global ocean–sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60- 1 Please note that this is an author-produced PDF of an article accepted for publication following peer review. The definitive publisher-authenticated version is available on the publisher Web site year period from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summarized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contributors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertical and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics considered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort.480 271 - PublicationRestrictedOn the corrections of ERA-40 surface flux products consistent with the Mediterranean heat and water budgets and the connection between basin surface total heat flux and NAO(2010-06-25)
; ; ; ;Pettenuzzo, D.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia ;Large, W. G.; National Center for Atmospheric Research, Boulder, Colorado, USA ;Pinardi, N.; Corso di Scienze Ambientali, Bologna University, Bologna, Italy; ; This is a study of heat fluxes and heat budget of the Mediterranean Sea using the European Centre for Medium␣Range Weather Forecasts (ECMWF) 45 year reanalysis data set ERA␣40. The simple use of the ERA␣40 surface flux components fails to close the budget and, in particular, the shortwave radiation flux is found to be underestimated with respect to observed data by about 10%. The heat flux terms are recomputed and corrected in order to close the heat and freshwater budgets of the Mediterranean basin over the period 1958 to 2001, thus producing a corrected ERA␣40 surface flux data set. Various satellite and in situ observational data are used to construct spatially varying corrections to the ERA␣40 products needed to compute the air␣sea fluxes. The corrected interannual and climatological net surface heat and freshwater fluxes are ␣7 W/m2 and ␣0.64 m/yr, respectively, which are regarded as satisfactorily closing the Mediterranean heat and water budgets. It is also argued that there is an important contribution from large heat losses associated with a few severe winters over the Mediterranean Sea. This is shown to be related to wind regime anomalies, which strongly affect the latent heat of evaporation that is mainly responsible for the interannual modulation of the total heat flux. Furthermore, the surface total heat flux anomaly time series is compared with the North Atlantic Oscillation (NAO) index, and the result is a positive correlation with ocean warming for positive NAO index periods and ocean cooling associated with negative index periods.124 19 - PublicationRestrictedJRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do)(2018)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ;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.117 2