Advertisement

Climate Dynamics

, Volume 21, Issue 1, pp 27–51 | Cite as

Description and evaluation of the bergen climate model: ARPEGE coupled with MICOM

  • T. FurevikEmail author
  • M. Bentsen
  • H. Drange
  • I. K. T. Kindem
  • N. G. Kvamstø
  • A. Sorteberg
Article

Abstract

A new coupled atmosphere–ocean–sea ice model has been developed, named the Bergen Climate Model (BCM). It consists of the atmospheric model ARPEGE/IFS, together with a global version of the ocean model MICOM including a dynamic–thermodynamic sea ice model. The coupling between the two models uses the OASIS software package. The new model concept is described, and results from a 300-year control integration is evaluated against observational data. In BCM, both the atmosphere and the ocean components use grids which can be irregular and have non-matching coastlines. Much effort has been put into the development of optimal interpolation schemes between the models, in particular the non-trivial problem of flux conservation in the coastal areas. A flux adjustment technique has been applied to the heat and fresh-water fluxes. There is, however, a weak drift in global mean sea-surface temperature (SST) and sea-surface salinity (SSS) of respectively 0.1 °C and 0.02 psu per century. The model gives a realistic simulation of the radiation balance at the top-of-the-atmosphere, and the net surface fluxes of longwave, shortwave, and turbulent heat fluxes are within observed values. Both global and total zonal means of cloud cover and precipitation are fairly close to observations, and errors are mainly related to the strength and positioning of the Hadley cell. The mean sea-level pressure (SLP) is well simulated, and both the mean state and the interannual standard deviation show realistic features. The SST field is several degrees too cold in the equatorial upwelling area in the Pacific, and about 1 °C too warm along the eastern margins of the oceans, and in the polar regions. The deviation from Levitus salinity is typically 0.1 psu – 0.4 psu, with a tendency for positive anomalies in the Northern Hemisphere, and negative in the Southern Hemisphere. The sea-ice distribution is realistic, but with too thin ice in the Arctic Ocean and too small ice coverage in the Southern Ocean. These model deficiencies have a strong influence on the surface air temperatures in these regions. Horizontal oceanic mass transports are in the lower range of those observed. The strength of the meridional overturning in the Atlantic is 18 Sv. An analysis of the large-scale variability in the model climate reveals realistic El Niño – Southern Oscillation (ENSO) and North Atlantic–Arctic Oscillation (NAO/AO) characteristics in the SLP and surface temperatures, including spatial patterns, frequencies, and strength. While the NAO/AO spectrum is white in SLP and red in temperature, the ENSO spectrum shows an energy maximum near 3 years.

Keywords

Outgoing Longwave Radiation Freshwater Flux Hadley Cell NCEP Reanalysis Flux Adjustment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements.

The authors are grateful to Laurent Terray at CERFACS, Toulouse, for the initial set-up of the OASIS coupler in Bergen, to Michel Déqué and David Salas Mélia, Meteo-France, Toulouse, for providing technical assistance and support, and to Lennart Bengtsson, MPI, Hamburg, for a series of useful discussions and thorough guidance during the work. Constructive criticisms and suggestions made by Ronald J. Stouffer, GFDL, Princeton, during the review process, are greatly appreciated. The development of the Bergen Climate Model and the model integrations have received support from the Research Council of Norway through the RegClim project, the "Spissforskningsmidler" (MB), and the Programme for Supercomputing. Additional funding has been received from the Board of Marine Sciences, University of Bergen, and the European Commission funded project PREDICATE (EVK2-CT-1999-00020) (HD). This is contribution A0013 from the Bjerknes Centre for Climate Research.

References

  1. Ardanuy PE, Stowe LL, Gruber A (1991) Shortwave, longwave and net cloud radiative forcing as determined from Nimbus-7 observations. J Geophys Res 96: 18,537–18,549Google Scholar
  2. Barkstrom BR (1984) The Earth Radiation Budget Experiment (ERBE). Bull Am Meteorol Soc 65: 1170–1185CrossRefGoogle Scholar
  3. Barnard S et al. (1997) DYNAMO – Dynamics of North Atlantic models: simulation and assimilation with high resolution models. Tech Rep 294 Inst. Meereskunde, Christian Albrechts Universität, Kiel, GermanyGoogle Scholar
  4. Barthelet P, Terray L, Valcke S (1998) Transient CO2 experiment using the ARPEGE/OPAICE non flux corrected coupled model. Geophys Res Lett 25: 2277–2280Google Scholar
  5. Baumgartner A, Reichel E (1975) The world water balance. R. Oldenbourg, Munich, Germany, pp 179Google Scholar
  6. Beesley JA, Moritz RE (1999) Toward an explanation of the annual cycle of cloudiness over the Arctic Ocean. J Clim 12: 395–415CrossRefGoogle Scholar
  7. Bentsen M, Drange H (2000) Parameterizing surface fluxes in ocean models using the NCEP/NCAR reanalysis data. In: RegClim General Techn Rep 4, pp 149–158. Norwegian Institute for Air Research, Kjeller, NorwayGoogle Scholar
  8. Bentsen M, Evensen G, Drange H, Jenkins AD (1999) Coordinate transformation on a sphere using conformal mapping. Mon Weather Rev 127: 2733–2740CrossRefGoogle Scholar
  9. Bjørgo E, Johannessen OM, Miles MW (1997) Analysis of merged SMMR-SSMI time series of Arctic and Antarctic sea ice parameters 1978–1995. Geophys Res Lett 24: 413–416Google Scholar
  10. Bleck R, Rooth C, Hu D, Smith LT (1992) Salinity-driven thermocline transients in a wind- and thermohaline-forced isopycnic coordinate model of the North Atlantic. J Phys Oceanogr 22: 1486–1505CrossRefGoogle Scholar
  11. Boone A, Masson V, Meyers T, Noilhan J (2000) The influence of the inclusion of soil freezing on simulations by a soil-vegetation-atmosphere transfer scheme. J Appl Meteor 39: 1544–1569CrossRefGoogle Scholar
  12. Bossuet C, Déqué M, Cariolle D (1998) Impact of a simple parameterization of convective gravity-wave drag in a stratosphere-troposphere general circulation model and its sensitivity to vertical resolution. Ann Geophysicae 16: 238–249CrossRefGoogle Scholar
  13. Bougeault P (1985) A simple parameterization of the large-scale effects of deep cumulus convection. MWR 113: 2108–2121CrossRefGoogle Scholar
  14. Bourke RH, McLaren AS (1992) Contour mapping of arctic basin ice draft and roughness parameters. J Geophys Res 97: 17,715–17,728Google Scholar
  15. Cariolle D, Déqué M (1986) Southern hemisphere medium-scale waves and total ozone disturbances in a spectral general circulation model. J Geophys Res 91: 10,825–10,846Google Scholar
  16. Cassou C, Noyret P, Sevault E, Thual O, Terray L, Beaucourt D, Imbard M (1998) Distributed ocean–atmosphere modelling and sensitivity to the coupling flux precision: the CATHODe Project. Mon Weather Rev 126: 1035–1053CrossRefGoogle Scholar
  17. Coiffer J, Ernie Y, Geleyn JF, Clochard J, Hoffman J, Dupont F (1987) The operational hemispheric model at the French Meteorological Service. In: J Meteorol Soc Japan, Special NWP Symposium Vol pp 337–345Google Scholar
  18. Collins M, Tett SFB, Cooper C (2001) The internal climate variability of HadCM3, a version of the Hadley Centre coupled model without flux adjustment. Clim Dyn 17: 61–81CrossRefGoogle Scholar
  19. Courtier P, Freydier C, Geleyn JF, Rabier F, Rochas M (1991) The ARPEGE project at Météo-France. In: Proc ECMWF workshop on numerical methods in atmospheric modelling 2: 193–231. ECMWFGoogle Scholar
  20. Covey CC, AchutaRao KM, Lambert SJ, Taylor KE (2000) Intercomparison of present and future climates simulated by coupled ocean–atmosphere GCMs. PCMDI Report Series 66 Lawrence Livermore National Laboratory, pp 52Google Scholar
  21. da Silva AM, Young CC, Levitus S (1994) Atlas of surface marine data 1994, Volumes 1 and 3. NOAA Atlas NESDIS 6 and 8, US Department of Commerce, Washington, D.C. pp 83Google Scholar
  22. Darnell WL, Staylor WF, Gupta SK, Ritchey NA, Wilber AC (1992) Seasonal variation of surface radiation budget derived from ISCCP-C1 data. J Geophys Res 97: 15,741–15,760Google Scholar
  23. Déqué M, Piedelievre JP (1995) High resolution climate simulation over Europe. Clim Dyn 11: 321–339CrossRefGoogle Scholar
  24. Déqué M, Dreveton C, Braun A, Cariolle D (1994) The ARPEGE/IFS atmosphere model: a contribution to the French community climate modelling. Clim Dyn 10: 249–266CrossRefGoogle Scholar
  25. Déqué M, Marquet P, Jones RG (1998) Simulation of climate change over Europe using a global variable resolution general circulation model. Clim Dyn 14: 173–189CrossRefGoogle Scholar
  26. Dorman CE, Bourke RH (1978) Temperature correction for Tucker's ocean rainfall estimates. Q J R Meteorol Soc 104: 765–773Google Scholar
  27. Douville H, Royer JF, Mahfouf JF (1995) A new snow parameterization for the Météo-France climate model. Part II: validation in a 3D GCM experiment. Clim Dyn 12: 37–52CrossRefGoogle Scholar
  28. Drange H (1999) RegClim ocean modelling at NERSC. In: RegClim General Technical Report 2, pp 93–102. Norwegian Institute for Air Research, Kjeller, NorwayGoogle Scholar
  29. Drange H, Simonsen K (1996) Formulation of Air–Sea Fluxes in the ESOP2 Version of MICOM. Technical Report 125 Nansen Environmental and Remote Sensing Center, Bergen, Norway, pp 23Google Scholar
  30. Fichefet T, Gaspar P (1988) A model study of upper ocean–sea ice interaction. J Phys Oceanogr 18: 181–195CrossRefGoogle Scholar
  31. Flato GM, Boer GJ, Lee WG, McFarlane NA, Ramsden D, Reader MC, Weaver AJ (2000) The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate. Clim Dyn 16: 451–467CrossRefGoogle Scholar
  32. Gal-Chen T, Somerville RCJ (1975) On the use of a coordinate transformation for the solution of the Navier-Stokes equations. J Comput Phys 17: 209–228Google Scholar
  33. Ganopolski A, Rahmstorf S (2001) Rapid changes of glacial climate simulated in an coupled climate model. Nature 409: 153–158Google Scholar
  34. Gaspar P (1988) Modeling the seasonal cycle of the upper ocean. J Phys Oceanogr 18: 161–180CrossRefGoogle Scholar
  35. Geleyn JF (1987) Use of a modified Richardson number for parameterizing the effect of shallow convection. In: J Met Soc Japan, Special NWP Symposium, pp 141–147Google Scholar
  36. Geleyn JF (1988) Interpolation of wind, temperature and humidity values from model levels to the height of measurement. Tellus 40A: 347–351Google Scholar
  37. Geleyn JF, Preuss HJ (1983) A new dataset of satellite derived surface albedo values for operational use at ECMWF. Arch Meterol Geophys Biocl, Ser A 32: 353–359Google Scholar
  38. Gordon C, Cooper C, Senior CA, Banks H, Gregory JM, Johns TC, Mitchell JFB, Wood RA (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16: 147–168CrossRefGoogle Scholar
  39. Gordon HB, O'Farrell SP (1997) Transient climate change in the CSIRO coupled model with dynamic sea ice. Mon Weather Rev 125: 875–907CrossRefGoogle Scholar
  40. Guilyardi E, Madec G (1997) Performance of the OPA/ARPEGE-T21 global ocean–atmosphere coupled model. Clim Dyn 13: 149–165CrossRefGoogle Scholar
  41. Harder M (1996) Dynamik, Rauhigkeit und Alter des Meereises in der Arktis. PhD thesis Alfred-Wegener-Institut für Polar- und Meeresforschung, Bremerhaven, Germany, pp 124Google Scholar
  42. Harrison EF, Minnis P, Barkstrom BR, Ramanathan V, Cess RD, Gibson GG (1990) Seasonal variation of cloud radiative forcing derived from the Earth Radiation Budget Experiment. J Geophys Res 95: 18,687–18,703Google Scholar
  43. Hibler III WD (1979) A dynamic thermodynamic sea ice model. J Phys Oceanogr 9: 815–846CrossRefGoogle Scholar
  44. Hines KM, Bromwich DH, Marshall GJ (2000) Artificial surface pressure trends in the NCEP-NCAR reanalysis over the Southern Ocean and Antarctica. J Clim 13: 3940–3952CrossRefGoogle Scholar
  45. Hortal M (1998) Aspects of the numerics of the ECMWF model. In: Proc Recent developments in numerical methods for atmospheric modelling, ECMWF, pp 127–143Google Scholar
  46. Hortal M, Simmons AJ (1991) Use of reduced Gaussian grids in spectral models. Mon Weather Rev 119: 1057–1074CrossRefGoogle Scholar
  47. Huffman GJ, Adler RF, Rudolf B, Schneider U, Keehn PR (1995) Global precipitation estimates based on a technique for combining satellite-based estimates, rain gauge analysis, and NWP model precipitation information. J Clim 8: 1284–1295CrossRefGoogle Scholar
  48. Hurrel JW (1995) Decadal trends in the North Atlantic Oscillation: regional temperatures and precipitation. Science 269: 676–679Google Scholar
  49. Johannessen OM, Shalina EV, Miles MW (1999) Satellite evidence for an Arctic sea ice cover in transformation. Science 286: 1937–1939CrossRefPubMedGoogle Scholar
  50. Johns TC, Carnell RE, Crossley JF, Gregory JM, Mitchell JFB, Senior CA, Tett SFB, Wood RA (1997) The second Hadley Centre coupled ocean–atmosphere GCM: model description, spinup and validation. Clim Dyn 13: 103–134CrossRefGoogle Scholar
  51. Jones PD (1994) Hemispheric surface air temperature variations: a reanalysis and an update to 1993. J Clim 7: 1784–1802CrossRefGoogle Scholar
  52. Kalnay E et al. (1996) The NCEP/NCAR 40-Year Reanalysis Project. Bull Am Meteor Soc 77: 437–471CrossRefGoogle Scholar
  53. Kaplan A, Kushnir Y, Cane MA, Blumenthal MB (1997) Reduced space optimal analysis for historical datasets: 136 years of Atlantic sea surface temperatures. J Geophys Res 102: 27,835–27,860Google Scholar
  54. Kaplan A, Cane MA, Kushnir Y, Clement AC, Blumenthal MB, Rajagopalan B (1998) Analyses of global sea surface temperature 1856–1991. J Geophys Res 103: 18,567–18,589CrossRefGoogle Scholar
  55. Kaplan A, Kushnir Y, Cane M (2000) Reduced space optimal analysis of historical marine sea level pressure: 1854–1992. J Clim 13: 2987–3002CrossRefGoogle Scholar
  56. Kiehl JT, Trenberth KE (1997) Earth's annual global mean energy budget. Bull Am Meteorol Soc 78: 197–208CrossRefGoogle Scholar
  57. Kiehl JT, Hack JJ, Briegleb BP (1994) The simulated earth radiation budget of the National Center for Atmospheric Research community climate model CCM2 and comparison with the Earth Radiation Budget Experiment (ERBE). J Geophys Res 99: 20,815–20,827Google Scholar
  58. Kraus EB, Turner JS (1967) A one-dimensional model for the seasonal thermocline. II The general theory and its consequences. Tellus 14: 98–105Google Scholar
  59. Lambert SJ, Boer GJ (2001) CMIP1 evaluation and intercomparison of coupled climate models. Clim Dyn 17: 83–106Google Scholar
  60. Levitus S, Boyer TP (1994) World Ocean Atlas 1994 volume 4: temperature. NOAA Atlas NESDIS 4, US Department of Commerce, Washington, D.C, pp 117Google Scholar
  61. Levitus S, Burgett R, Boyer TP (1994) World Ocean Atlas 1994 volume 3: salinity. NOAA Atlas NESDIS 3, US Department of Commerce, Washington, D.C, pp 99Google Scholar
  62. Lott F (1999) Alleviation of stationary biases in a GCM through a mountain drag parameterization scheme and a simple representation of mountain lift forces. Mon Weather Rev 125: 788–801CrossRefGoogle Scholar
  63. Lott F, Miller MJ (1997) A new subgrid-scale orographic drag parameterization: its formulation and testing. Q J R Meteorol Soc 123: 101–127CrossRefGoogle Scholar
  64. Louis JF (1979) A parametric model of vertical eddy fluxes in the atmosphere. Boundary-Layer Meteorol 17: 187–202Google Scholar
  65. Madec G, Imbard M (1996) A global ocean mesh to overcome the North Pole singularity. Clim Dyn 12: 381–388CrossRefGoogle Scholar
  66. Mahfouf JF, Manzi AO, Noilhan J, Giordani H, Déqué M (1995) The land surface scheme ISBA within the Météo-France climate model ARPÉGE. Part I: implementation and preliminary results. J Clim 8: 2039–2057CrossRefGoogle Scholar
  67. Mantoura RFC, Martin JM, Wollast R (eds) (1991) Ocean margin processes in global change vol 9, Physical, chemical and earth sciences research Report. John Wiley Chichester, UK pp 486Google Scholar
  68. Mascart P, Noilhan J, Giordani H (1995) A modified parameterization of flux profile relationships in the surface layer using different roughness length values for heat and momentum. Boundary-Layer Meteorol 72: 331–344Google Scholar
  69. Miller AJ, Lermusiaux PFJ, Poulain PM (1996) A topographic-Rossby mode resonance over the Iceland-Faeroe Ridge. J Phys Oceanogr 26: 2735–2747CrossRefGoogle Scholar
  70. Morcrette JJ (1991) Radiation and cloud radiative properties in the European Centre for Medium Range Forecasts forecasting system. J Geophys Res 95: 9121–9132Google Scholar
  71. Noilhan J, Planton S (1989) A simple parameterization of land surface processes for meteorological models. Mon Weather Rev 117: 536–549CrossRefGoogle Scholar
  72. Oberhuber JM (1988) An atlas based on the 'COADS' data set: the budgets of heat, buoyancy and turbulent kinetic energy at the surface of the global ocean. Tech Rep 15 Max-Planck-Institut für Meteorologie, Hamburg, GermanyGoogle Scholar
  73. Ohmura A, Gilgen H (1993) Re-evaluation of the global energy balance. In: Interactions between the global climate subsystems: the legacy of Hann, vol 75, pp 93–110. American Geophysical UnionGoogle Scholar
  74. Oki T, Sud YC (1998) Design of total run off integrating pathways (TRIP): a global river channel network. Earth interactions vol 2, No. 1, pp 1–37Google Scholar
  75. Palmer TN (2001) A nonlinear dynamical perspective on model error: a proposal for non-local stochastic-dynamic parameterization in weather and climate prediction models. Q J R Meteorol Soc 127: 279–304CrossRefGoogle Scholar
  76. Palmer TN, Räisänen J (2002) Quantifying the risk of extreme seasonal precipitation events in a changing climate. Nature 415: 512–514CrossRefPubMedGoogle Scholar
  77. Paltridge GW, Platt CMR (1976) Radiative processes in meteorology and climatology. Elsevier, Amsterdam, pp 318Google Scholar
  78. Parker DE, Folland CK, Jackson M (1995) Marine surface temperature: observed variations and data requirements. Clim Change 31: 559–600Google Scholar
  79. Parkinson CL, Washington WM (1979) A large-scale numerical model of sea ice. J Geophys Res 84: 311–337Google Scholar
  80. Parkinson CL, Cavalieri DJ, Gloersen P, Zwally HJ, Comiso JC (1999) Arctic sea ice extents, areas, and trends, 1978–1996. J Geophys Res 104: 20,837–20,856CrossRefGoogle Scholar
  81. Payne RE (1972) Albedo of the sea surface. J Atmos Sci 29: 959–970CrossRefGoogle Scholar
  82. Rahmstorf S (1995) Bifurcations of the Atlantic thermohaline circulation in response to changes in the hydrological cycle. Nature 378: 145–149Google Scholar
  83. Rahmstorf S, Ganopolski A (1999) Long-term global warming scenarios computing with an efficient coupled climate model. Clim Change 43: 353–367CrossRefGoogle Scholar
  84. Ramanathan VRD, Subasilar B, Zhang GJ, Contant W, Cess RD, Kiehl JT, Grassl H, Shi L (1995) Warm pool heat budget and shortwave cloud forcing: a missing physics? Science 267: 499–503Google Scholar
  85. Read JF, Pollard RT (1993) Structure and transport of the Antarctic circumpolar current and Agulhas return current at 40°E. J Geophys Res 98: 12,281–12,295Google Scholar
  86. Reynolds RW, Smith TM (1994) Improved global sea surface temperature analysis using optimum interpolation. J Clim 7: 929–948CrossRefGoogle Scholar
  87. Richard JL, Royer JF (1993) A statistical cloud scheme for use in an AGCM. Ann Geophysicae 11: 1093–1115Google Scholar
  88. Rieland M, Raschke E (1999) Diurnal variability of the earth radiation budget: sampling requirements, time integration aspects and error estimates for the Earth Radiation Budget Experiment (ERBE). Theor Appl Climatol 44: 9–24Google Scholar
  89. Roeckner E, Oberhuber JM, Bacher A, Christoph M, Kirchner I (1996) ENSO variability and atmospheric response in a global coupled atmosphere ocean GCM. Clim Dyn 12: 737–754CrossRefGoogle Scholar
  90. Rossow WB, Schiffer RA (1991) ISCCP cloud data products. Bull Am Meteorol Soc 72: 2–20CrossRefGoogle Scholar
  91. Rossow WB, Zhang YC (1995) Calculation of surface and top-of-atmosphere radiative fluxes from physical quantities based on ISCCP datasets: 2. Validation and first results. J Geophys Res 100: 1167–1197Google Scholar
  92. Rothrock DA, Yu Y, Maykut GA (1999) Thinning of the Arctic sea-ice Cover. Geophys Res Lett 26: 3469–3472CrossRefGoogle Scholar
  93. Russel GL, Miller JR, Rind D (1995) A coupled atmosphere–ocean model for transient climate change studies. Atmos–Ocean 33: 683–730Google Scholar
  94. Semtner Jr. AJ (1976) A model for the thermodynamic growth of sea ice in numerical investigations of climate. J Phys Oceanogr 6: 379–389CrossRefGoogle Scholar
  95. Shea DJ (1986) Climatological Atlas: 1950–1979 surface air temperature, precipitation, sea-level pressure, and sea-surface temperature (45°S–90°N). Tech Rep NCAR/TN-269+STR National Center for Atmospheric Research, Boulder, CO, USAGoogle Scholar
  96. Simmons AJ, Burridge DM (1981) An energy and angular momentum conserving vertical finite-difference scheme and hybrid vertical coordinate. Mon Weather Rev 109: 758–768CrossRefGoogle Scholar
  97. Steele M, Morley R, Ermold W (2001) PHC: a global ocean hydrography with a high-quality Arctic Ocean. J Clim 14: 2079–2087CrossRefGoogle Scholar
  98. Stephenson DB, Pavan V (2002) How well do climate models simulate the North Atlantic Oscillation? Clim Dyn. in pressGoogle Scholar
  99. Sun S, Bleck R, Rooth C, Dukowicz J, Chassignet E, Killworth P (1999) Inclusion of Thermobaricity in Isopycnic-Coordinate Ocean Models. J Phys Oceanogr 29: 2719–2729CrossRefGoogle Scholar
  100. Terray L, Thual O (1995) Oasis: le couplage océan–atmosphère. La Météorologie 10: 50–61Google Scholar
  101. Terray L, Thual O, Belamari S, Déqué M, Dandin P, Lévy C, Delecluse P (1995) Climatology and interannual variability simulated by the ARPEGE–OPA model. Clim Dyn 11: 487–505CrossRefGoogle Scholar
  102. Terray L, Valcke S, Piacentini A (1998) OASIS 2.2. User's guide and reference manual. Tech Rep CERFACS, Toulouse, France, pp 77Google Scholar
  103. Tucker GB (1961) Precipitation over the North Atlantic Ocean. Q J R Meteorol Soc 87: 147–158Google Scholar
  104. Wadhams P, Davis NR (2000) Further evidence of ice thinning in the Arctic Ocean. Geophys Res Lett 27: 3973–3976CrossRefGoogle Scholar
  105. Walsh JE, Chapman WL, Shy TL (1996) Recent decrease of sea level pressure in the central Arctic. Notes and Correspondence. J Climate 9: 480–486CrossRefGoogle Scholar
  106. Whitlock CH, Charlock TP, Staylor WF, Pinker RT, Laszlo I, Ohmura A, Gilgen H, Konzelman T, Pasquale RCD, Moats CD, LeCroy SR, Ritchey NA (1995) First global WCRP shortwave surface radiation budget data set. Bull Am Meteorol Soc 76: 905–922CrossRefGoogle Scholar
  107. Woodruff SD, Slutz RJ, Jenne RL, Steurer PM (1987) A comprehensive ocean–atmosphere data set. Bull Am Meteorol Soc 68: 1239–1250CrossRefGoogle Scholar
  108. Xie P, Arkin PA (1997) Global precipitation: A/17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Am Meteorol Soc 78: 2539–2558CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • T. Furevik
    • 1
    • 2
    Email author
  • M. Bentsen
    • 1
    • 3
  • H. Drange
    • 1
    • 2
    • 3
  • I. K. T. Kindem
    • 2
    • 3
  • N. G. Kvamstø
    • 2
  • A. Sorteberg
    • 2
    • 3
  1. 1.Nansen Environmental and Remote Sensing Center, Bergen, Norway
  2. 2.Geophysical Institute, University of Bergen, Allégaten 70, 5007 Bergen, Norway
  3. 3.Bjerknes Centre for Climate Research, Bergen, Norway

Personalised recommendations