An ERA40-based atmospheric forcing for global ocean circulation models |
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| Authors: | Laurent Brodeau Bernard Barnier Anne-Marie Treguier Thierry Penduff Sergei Gulev |
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| Institution: | 1. LEGI, UMR 5519 CNRS-UJF-INPG, BP 53, 38041 Grenoble, France;2. LPO, UMR 6523 CNRS-IFREMER-IRD-UBO, IFREMER, BP 70, 29280 Plouzané, France;3. P.P. SIO – RAS, 36 Nakhimovsky Ave., 117218 Moscow, Russian Federation;4. Department of Oceanography, The Florida State University, Tallahassee, Florida;1. Groupe d’études de l’Atmosphère Météorologique, Centre National de Recherches Météorologiques (GAME-CNRM, CNRS UMR3589/Météo-France), Toulouse, France;2. Ecole Nationale Supérieure de Techniques Avancées (ENSTA), ParisTech, Unité de Mécanique (UME), Palaiseau, France;3. Centre de Météorologie Marine (CMM, Météo-France), Brest, France;4. Mediterranean Institute of Oceanography (MIO, Aix-Marseille University/CNRS UMR7294/IRD UMR235/Université du Sud Toulon-Var), Marseille, France;1. NOAA Geophysical Fluid Dynamics Laboratory, Princeton, USA;2. Department of Geosciences, University of Arizona, Tucson, USA;3. Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, USA;4. National Center for Atmospheric Research, Boulder, USA;5. GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany;6. Uni Climate, Uni Research Ltd., Bergen, Norway;7. Centre for Australian Weather and Climate Research, a partnership between CSIRO and the Bureau of Meteorology, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Melbourne, Australia;8. Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University, Tallahassee, FL, USA;9. Alfred Wegener Institute (AWI) for Polar and Marine Research, Bremerhaven, Germany;10. Antarctic Climate and Ecosystems Cooperative Research Centre, University of Tasmania, Hobart, Australia;11. University of Bergen, Bergen, Norway;12. International Centre for Theoretical Physics (ICTP), Trieste, Italy;13. Centre Européen de Recherche et de Formation Avancéen Calcul Scientifique (CERFACS), URA 1875, CNRS/INSU, Toulouse, France;14. New York University, New York 10012, USA;15. National Oceanography Centre Southampton (NOCS), Southampton, UK;p. Centre National de Recherches Météorologiques (CNRM-GAME), Toulouse, France;q. McGill University, Montreal, Canada;r. Laboratoire de Physique des Oceans, UMR 6523, CNRS-Ifremer-IRD-UBO, Plouzane, France;s. Meteorological Research Institute (MRI), Japan Meteorological Agency, Tsukuba, Japan;t. Centre for Australian Weather and Climate Research, a partnership between CSIRO and the Bureau of Meteorology, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Hobart, Australia;1. Institute of Marine and Coastal Sciences, Rutgers University, 71 Dudley Road, New Brunswick, NJ 08901, USA;2. Institute of Marine Biosciences, National Research Council, 1411 Oxford Street, Halifax, Canada NS B3H 3Z1;3. Alfred Wegener Institute for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany;1. Center for Satellite Applications and Research, National Oceanic and Atmospheric Administration, College Park, MD, United States;2. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States;3. Division of Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, NC, United States |
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| Abstract: | We develop, calibrate and test a dataset intended to drive global ocean hindcasts simulations of the last five decades. This dataset provides surface meteorological variables needed to estimate air-sea fluxes and is built from 6-hourly surface atmospheric state variables of ERA40. We first compare the raw fields of ERA40 to the CORE.v1 dataset of Large and Yeager (2004), used here as a reference, and discuss our choice to use daily radiative fluxes and monthly precipitation products extracted from satellite data rather than their ERA40 counterparts. Both datasets lead to excessively high global imbalances of heat and freshwater fluxes when tested with a prescribed climatological sea surface temperature. After identifying unrealistic time discontinuities (induced by changes in the nature of assimilated observations) and obvious global and regional biases in ERA40 fields (by comparison to high quality observations), we propose a set of corrections. Tropical surface air humidity is decreased from 1979 onward, representation of Arctic surface air temperature is improved using recent observations and the wind is globally increased. These corrections lead to a significant decrease of the excessive positive global imbalance of heat. Radiation and precipitation fields are then submitted to a small adjustment (in zonal mean) that yields a near-zero global imbalance of heat and freshwater. A set of 47-year-long simulations is carried out with the coarse-resolution (2° × 2°) version of the NEMO OGCM to assess the sensitivity of the model to the proposed corrections. Model results show that each of the proposed correction contributes to improve the representation of central features of the global ocean circulation. |
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