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

被引:0
|
作者
T. Furevik
M. Bentsen
H. Drange
I. K. T. Kindem
N. G. Kvamstø
A. Sorteberg
机构
[1] Nansen Environmental and Remote Sensing Center,
[2] Bergen,undefined
[3] Norway,undefined
[4] Geophysical Institute,undefined
[5] University of Bergen,undefined
[6] Allégaten 70,undefined
[7] 5007 Bergen,undefined
[8] Norway,undefined
[9] Bjerknes Centre for Climate Research,undefined
[10] Bergen,undefined
[11] Norway,undefined
来源
Climate Dynamics | 2003年 / 21卷
关键词
Outgoing Longwave Radiation; Freshwater Flux; Hadley Cell; NCEP Reanalysis; Flux Adjustment;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:27 / 51
页数:24
相关论文
共 50 条
  • [21] Performance of the OPA/ARPEGE-T21 global ocean-atmosphere coupled model
    E. Guilyardi
    G. Madec
    Climate Dynamics, 1997, 13 : 149 - 165
  • [22] Mechanisms of tropical Pacific interannual-to-decadal variability in the ARPEGE/ORCA global coupled model
    Carole Cibot
    Eric Maisonnave
    Laurent Terray
    Boris Dewitte
    Climate Dynamics, 2005, 24 : 823 - 842
  • [23] Mechanisms of tropical Pacific interannual-to-decadal variability in the ARPEGE/ORCA global coupled model
    Cibot, C
    Maisonnave, E
    Terray, L
    Dewitte, B
    CLIMATE DYNAMICS, 2005, 24 (7-8) : 823 - 842
  • [24] Performance of the OPA/ARPEGE-T21 global ocean-atmosphere coupled model
    Guilyardi, E
    Madec, G
    CLIMATE DYNAMICS, 1997, 13 (02) : 149 - 165
  • [25] Coupling of a Regional Climate Model with a Crop Development Model and Evaluation of the Coupled Model across China
    Jing Zou
    Zhenghui Xie
    Chesheng Zhan
    Feng Chen
    Peihua Qin
    Tong Hu
    Jinbo Xie
    Advances in Atmospheric Sciences, 2019, 36 : 527 - 540
  • [26] Coupling of a Regional Climate Model with a Crop Development Model and Evaluation of the Coupled Model across China
    Jing ZOU
    Zhenghui XIE
    Chesheng ZHAN
    Feng CHEN
    Peihua QIN
    Tong HU
    Jinbo XIE
    AdvancesinAtmosphericSciences, 2019, 36 (05) : 527 - 540
  • [27] Coupling of a Regional Climate Model with a Crop Development Model and Evaluation of the Coupled Model across China
    Zou, Jing
    Xie, Zhenghui
    Zhan, Chesheng
    Chen, Feng
    Qin, Peihua
    Hu, Tong
    Xie, Jinbo
    ADVANCES IN ATMOSPHERIC SCIENCES, 2019, 36 (05) : 527 - 540
  • [28] Transient CO2 experiment using the ARPEGE/OPAICE non flux corrected coupled model
    Barthelet, P
    Terray, L
    Valcke, S
    GEOPHYSICAL RESEARCH LETTERS, 1998, 25 (13) : 2277 - 2280
  • [29] The CNRM-CM5.1 global climate model: description and basic evaluation
    Voldoire, A.
    Sanchez-Gomez, E.
    Salas y Melia, D.
    Decharme, B.
    Cassou, C.
    Senesi, S.
    Valcke, S.
    Beau, I.
    Alias, A.
    Chevallier, M.
    Deque, M.
    Deshayes, J.
    Douville, H.
    Fernandez, E.
    Madec, G.
    Maisonnave, E.
    Moine, M-P.
    Planton, S.
    Saint-Martin, D.
    Szopa, S.
    Tyteca, S.
    Alkama, R.
    Belamari, S.
    Braun, A.
    Coquart, L.
    Chauvin, F.
    CLIMATE DYNAMICS, 2013, 40 (9-10) : 2091 - 2121
  • [30] The CNRM-CM5.1 global climate model: description and basic evaluation
    A. Voldoire
    E. Sanchez-Gomez
    D. Salas y Mélia
    B. Decharme
    C. Cassou
    S. Sénési
    S. Valcke
    I. Beau
    A. Alias
    M. Chevallier
    M. Déqué
    J. Deshayes
    H. Douville
    E. Fernandez
    G. Madec
    E. Maisonnave
    M.-P. Moine
    S. Planton
    D. Saint-Martin
    S. Szopa
    S. Tyteca
    R. Alkama
    S. Belamari
    A. Braun
    L. Coquart
    F. Chauvin
    Climate Dynamics, 2013, 40 : 2091 - 2121