BRemen Earth system Model of
Intermediate Complexity

Bremen University, Center for Marine Environmental Sciences, Germany

Gerrit Lohmann ( gerrit.lohmann@dkrz.de)

Martin Butzin

Matthias Prange

Klaus Grosfeld

Gregor Knorr

Vanya Romanova

Silke Schubert

Andre Paul

Lisa Könnecke

  • Technical report: Lohmann, G., M. Butzin, K. Grosfeld, G. Knorr, A. Paul, M. Prange, V. Romanova, S. Schubert, 2003: The Bremen Earth System Model of Intermediate Complexity (BREMIC) designed for long-term climate studies. Model description, climatology, and applications. Technical Report, Bremen University, Bremen, Germany. link

     

     

    Table of contents:

    A) Scope of the model

    B) The Model

    C) Limitations

    D) Performance

    E) Applications

    Selected Applications

    F) References

     

     

     

    A Scope of the model

    An Earth system model of intermediate complexity is developed for the study of climate dynamics on decadal and millennial time-scales. The main task is to identify the driving mechanisms and potential thresholds responsible for climate transitions. Emphasis is placed on the multiple states of the system and the interaction of the dominant pattern of atmospheric variability with the ocean and land surface. In contrast to conventional time-slice experiments, the present approach is not restricted to equilibrium transitions and is capable to utilise all available data for validation. Transient simulations for the past and future climate will examine feedback mechanism in the climate system. Pathways of orbital forcing into climate response will reveal the understanding of climate records. The model explicitely resolves the three-dimensional atmospheric and oceanic dynamics and is therefore conceptual different from statistical dynamical models.

    At time-scales comparable to the glacial-interglacial cycles, the importance of each Earth system component has not been estimated. At this early stage of exploration for the coupled system, it is necessary to be able to carry out a large number of sensitivity experiments. It is expected that, compared to e.g. scenario calculations for the next century, different processes will dominate Earth system interactions at such long time scales. This has to be accounted for a suitable modelling framework in order to allow cooperation between expert groups of different focus. The Earth system model shall have a modular structure with portable Fortran code. The modular structure of the model enables the user to modify model configurations according to the application. New schemes and model components can be included with a minimum of technical expense which is particularly useful for paleoclimatic applications.

     

     

     

    B The Model

    The BREMIC is a combination of different single earth system model components of intermediate to full complexity to a coupled model system approach. Is is based on the three-dimensional Large Scale Geostrophic (LSG) ocean model (Maier-Reimer et al., 1993), including a thermodynamic-dynamic sea ice model. The atmospheric forcing of the ocean model is performed by wind stress patterns, surface air temperature and freshwater fluxes taken from atmospheric general circulation model experiments. Two different model conceptions are used to provide this data. On the one hand the comprehensive atmospheric general circulation model ECHAM are applied in a hybrid coupled model approach, which allows an adjustment of surface temperature and salinity to changes in the ocean circulation, based on an atmospheric energy balance model (Rahmstorf and Willebrand, 1995; Prange et al., 2003). On the other hand a simplified atmospheric circulation model of intermediate complexity (PUMA) is integrated and provides for the corresponding forcing fields. This is especially advantageous for long-term climate studies since PUMA is less consuming in computional time than full AGCM's. The Ocean model can additionally be run using a carbon cycle model (HAMOCC) (Maier-Reimer, 1993), which includes a sediment module. The terrestrial biosphere cycle is represented and modeled with the Lund-Potsdam-Jena (LPJ) model in a diagnostic mode.

     

    Model components

    Atmosphere

    a) The atmospheric circulation model implemented into the BREMIC is the comprehensive AGCM (ECHAM) developed at the Max-Planck Institute for Meteorology (Roeckner et al., 1992). It is used in T42 resolution and simulates the 3-dimensional state of the atmosphere in full complexity. We employ a hybrid modeling approach which allows an adjustment of surface temperature and salinity to changes in the ocean circulation, based on an atmospheric energy balance model with diffusive lateral heat transport (Rahmstorf and Willebrand, 1995; Prange et al., 2003). The applied heat flux parameterization has shown to be a suitable choice, allowing the simulation of observed sea surface temperatures and the maintanance of large-scale temperature anomalies in pertubation experiments. No flux correction is applied for present day and glacial conditions (Prange et al., 2002; Knorr and Lohmann, 2003). A runoff scheme closes the hydrological cycle. The model description and model set-up is given in the appendix of Prange et al. (2003), a detailed description of ECHAM is given in the Technical Report No. 6, DKRZ, 1993 (ECHAM3.ps, 1.5 MB Postscript-file).

    b) Another basis for our Earth system model is the intermediate complexity atmospheric circulation model PUMA. The dynamic core of PUMA (Portable University Model of the Atmosphere), developed at the University of Hamburg (Fraedrich et al., 1998), is based on the Reading multi-layer spectral model proposed by Hoskins and Simmons (1975). It numerically integrates the moist primitive equations conveniently formulated in terms of the vertical component of absolute vorticity, the horizontal divergence, the temperature, the logarithm of the surface pressure and the specific humidity. The equations are solved using the spectral transform method (Orszag, 1970; Eliasen et al., 1970). Physical processes which are not explicitly resolved are parameterized using schemes of intermediate complexity. The surface fluxes of moisture, heat and momentum are based on bulk formulas. The radiation uses a one band approximation for the long wave part and a two band approximation for the short wave part. Large scale precipitation for supersaturated air and a Kuo type convective precipitation scheme (Kuo, 1965; 1974) complete the atmospheric water cycle. Clouds are formed diagnostically based on the relative humidity. The parameterizations for the land surface and the soil include the calculation of temperatures for the surface and the soil, a soil hydrology and a river transport scheme. A snow model following Loth (1995) has been implemented.
    PUMA is designed to be as compatible as possible with the comprehensive GCM ECHAM (Roeckner et al., 1992) and belongs to models of medium complexity (Claussen et al., 2002). For our applications, PUMA is integrated in T-21 spectral resolution, corresponding to Gaussian grid of approximately 5.625° in longitude and 5.625° in latitude. Five equally spaced, terrain following sigma-levels are used in the vertical. Computationally, PUMA requires exceptional less Computer-time than state-of-the-art GCMs at the same resolution and is therefore suitable for long-term climate variability studies.

    Ocean

    The atmospheric model has been coupled to the three-dimensional Large Scale Geostrophic model LSG (Maier-Reimer et al., 1993) designed especially for long-term climate studies (time step of one month) (Ocean Model Description ). This model contains a parameterization for the bottom boundary layer (Beckmann and Döscher, 1997) which drastically improves the density-driven downslope flows (Lohmann, 1998) and is essential for the interpretation of paleoclimatic records (Lohmann and Schulz, 2000). It includes a simple thermodynamic sea ice model, a new advection scheme for temperature and salinity (Farrow and Stevens, 1995; Prange et al., 2003) and parameterization of overflow (Lohmann, 1998). The horizontal resolution is 3.5° on a semi-staggered grid (type 'E') with 11 levels in the vertical. Monthly fields of wind stress, surface air temperature and freshwater flux are taken from atmospheric general circulation model ECHAM3/T42 experiments (Lohmann and Lorenz, 2000).

    Sea ice model

    Thermodynamic sea ice model including a simple momentum balance for advection of sea ice (included in LSG).

    Carbon Cycle

    In the LSG ocean model, the HAMOCC carbon cycle model (Maier-Reimer, 1993) is included. The carbon cycle model including a sediment module HAMOCC.ps (8 MB Postscript-File). First experiments exist for the terrestrial biosphere model LPJ (Lund-Potsdam-Jena) (Sitch et al., 2000), which is forced with the PUMA-LSG climate. The LPJ model is a dynamic global vegetation model combining mechanistic treatments of terrestrial vegetation dynamics, carbon and water cycling.

    Coupling

    The present version of the BREMIC model uses a T21/L5 resolution for the atmosphere and 11 (optionally 22) vertical levels with horizontal resolution of 5 degrees for the ocean. The model contains representations of sub-grid scale fluxes over land, ice, and open sea. The coupled atmosphere-ocean-sea ice model does not require flux adjustments.

    Miscellaneous

    • Langranian tracers are implemented in the atmosphere (Hardenberg, 2000; Bagliani et al., 2000).
    • A sediment model is included in the marine carbon cycle (Heinze et al., 1999).
    • Analysis packages for the model components can be found here .
    • Statistical Analysis packages as PINGOS maintained by MaD. Furthermore, we use the Extra packages origianally developed at the DKRZ.

     

    C Limitations

    Limitation of the current model version is due to the missing feedbacks by cryosphere and vegetation. Further limitations are due to the simplified radiation codes used (chemistry and dust). The coarse resolution and the neglected non-linear terms in the oceanic momentum balance restrict studies to spatial scales of more than a thousand kilometers, the model cannot adequately resolve interannual climate variability in the tropical Pacific.

     

    D Performance

    The required CPU time for the hybrid coupled atmosphere-ocean model is about 24h for 5000 years of model integration on a 2GHz Linux PC. For the version including the tracer routines the years of integration reduces by more than 50%. The ECHAM model in T42 resolution costs about 1 week on the supercomputer in Hamburg for 20-50 years of model integration. PUMA in T21 resolution costs about 1 day for 50 model years.

     

    E Applications

    The model components have been extensively tested in studies of paleoclimate (Winguth et al., 1999; Knorr and Lohmann, 2003, 2004), the hydrological cycle (Lohmann and Lorenz, 2000; Lohmann, 2003, Romanova et al., 2003), interdecadal climate variability (Grosfeld et al., 2003), future climate change scenarios for the next century (Lunkeit et al., 1998), storm track variability (Frisius et al., 1998), and climate sensitivity (Prange et al., 2002, 2003). The model is flexible enough to turn various feedback processes off and on, to study the cause and relationships of the climate components. Simulations and sensitivity studies focus on the following topics:

    • Process of glaciation and deglaciation.
    • Interaction of vegetation, atmospheric dynamics, and the oceanic circulation (e.g. vegetation-snow feedback, vegetation distribution).
    • Diagnostic and prognostic calculations of atmospheric CO2 (including carbon isotopes) on long time scales.
    • Importance of northern versus southern hemispheric forcing and Atlantic-Pacific teleconnections.
    • Dependence of climate variability on the background state.
    • Simulation of the last glacial cycle.

     

    Selected applications:

    THC Hystereses (Prange et al., 2002)

    Deglaciation (Knorr and Lohmann, 2003)

    Ocean Model Description (Prange et al., 2003)

    Meltwater and Mid-depth Warming (Rühlemann et al., 2003)

    Oceanic radiocarbon (Butzin et al., 2003a,b)


     

    F References

    Bagliani, F. Fraedrich, J. Hardenberg, F. Lunkeit, 2000: Lagrangian tracer homogenization and dispersion in a simplified atmospheric GCM. Il Nuovo Cimento , 23C, 433-448.

    Beckmann, A., and R. Döscher, 1997: A method for improved representation of dense water spreading over topography in geopotential-coordinate models. J. Phys. Oceanogr., 27, 581-591.

    Butzin, M., M. Prange, and G. Lohmann, 2003a: Studien zur C-14-Verteilung im glazialen Ozean mit einem globalen Ozeanzirkulationsmodell. Terra Nostra 6, 86-88. (PDF)

    Butzin, M., Prange, M., and G. Lohmann, 2003b: Simulations of oceanic radiocarbon at the Last Glacial Maximum. Paleoceanography (submitted).

    Claussen, M., Mysak, L.A., Weaver, A.J., Crucifix, M., Fichefet, T., Loutre, M.-F., Weber, S.L., Alcamo, J., Alexeev, V.A., Berger, A., Calov, R., Ganopolski, A., Goosse, H., Lohmann, G., Lunkeit, F., Mokhov, I.I., Petoukhov, V., Stone, P., and Wang, Z., 2002: Earth System Models of Intermediate Complexity: Closing the Gap in the Spectrum of Climate System Models. Climate Dynamics 18, 579-586. abstract

    DKRZ, 1993: The ECHAM3 Atmospheric General Circulation Model, Technical Report No. 6.

    Eliasen, E., B. Machenhauer and E. Rasmussen, 1970: On a numerical method for integration of the hydrodynamical equations with a spectral representation of the horizontal fields. Inst. of Theor. Met., 2, Univ. of Copenhagen, 37pp.

    Farrow, D. E., D. P. Stevens, 1995: A new tracer advection scheme for Bryan and Cox type ocean general circulation models. J. Phys. Oceanogr., 25, 1731-1741.

    Fraedrich, K., E. Kirk, and F. Lunkeit, 1998: Portable University Model of the Atmosphere, DKRZ Report 16. PUMA

    Frisius, T, Lunkeit, F., Fraedrich, K., and James, I. N., 1998: Storm-track organization and variability in a simplified atmospheric global circulation model. Q. J. R. Meteorol. Soc., 124, 1019-143.

    Hardenberg, J., K. Fraedrich, F. Lunkeit, A. Provenzale, 2000: Transient chaotic mixing during a baroclinic life cycle. CHAOS, 10, 122-134.

    Grosfeld, K., G. Lohmann, N. Rimbu, F. Lunkeit, and K. Fraedrich, 2003: Predictable response of the atmospheric circulation on North Atlantic multidecadal variability, Journal of Climate, (submitted).

    Heinze, C., E. Maier-Reimer, A. M. E. Winguth, and D. Archer, 1999: A global oceanic sediment model for long-term climate studies. Global Biogeochemical Cycles, 13, 221-250.

    Hoskins, B. J., and A. J. Simmons, 1975: A multi-layer spectral model and the semi-implicit method. Q. J. R. Meteorol. Soc., 101, 1231-1250.

    Knorr, G., and G. Lohmann, 2003: Southern Ocean Origin for Resumption of Atlantic Thermohaline Circulation during Deglaciation. Nature, 424, 532-536. Abstract and Information

    Knorr, G., and Lohmann, G., 2004: The Southern Ocean as Flywheel of the oceanic conveyor belt circulation. PAGES NEWS (to appear).

    Kuo, H. L., 1965: On formation and intensification of tropical cyclones through latent heat release by cumulus convection. J. Atmos. Sci., 22, 40-63.

    Kuo, H. L., 1974: Further studies of the parameterization of the influence of cumulus convection on large-scale flow. J. Atmos. Sci., 31, 1232-1240.

    Lohmann, G., 1998: The Influence of a near-bottom Transport Parameterization on the Sensitivity of the Thermohaline Circulation. J. Phys. Oceanogr., 28, 2095-2103. Abstract

    Lohmann, G., 2003: Atmospheric and oceanic freshwater transport during weak Atlantic overturning circulation. Tellus 55 A, 438-449. Abstract

    Lohmann, G., and Schulz, M., 2000: Reconciling Bølling warmth with peak deglacial meltwater discharge. Paleoceanography, 15 (5), 537-540. Abstract

    Lohmann, G., and Lorenz, S., 2000: On the hydrological cycle under paleoclimatic conditions as derived from AGCM simulations. Journal of Geophysical Research, 105, no. D13, 17,417-436. Abstract

    Lohmann, G., M. Butzin, K. Grosfeld, G. Knorr, A. Paul, M. Prange, V. Romanova, S. Schubert, 2003: The Bremen Earth System Model of Intermediate Complexity (BREMIC) designed for long-term climate studies. Model description, climatology, and applications. Technical Report, Bremen University, Bremen, Germany. link

    Loth, B., 1995: Die Schneedecke als Komponente des Klimasystems und ihre Modellierung. Max-Planck-Institut für Meteorologie. Examensarbeit Nr. 32.

    Lunkeit, F., S. E. Bauer, and K. Fraedrich, 1998: Storm tracks in a warmer climate: Sensitivity studies with a simplified global circulation model. Clim. Dyn., 14, 813-826.

    Maier-Reimer, E., 1993: Geochemical cycles in an ocean general circulation model. Preindustrial Tracer Distributions. Global Biogeochemical Cycles, 7, 645-677.

    Maier-Reimer, E., U. Mikolajewicz, and K. Hasselmann, 1993: Mean circulation of the Hamburg LSG OGCM and its sensitivity to the thermohaline surface forcing. J. Phys. Oceanogr., 23, 731-757.

    Prange, M., V. Romanova, and G. Lohmann, 2002: The glacial thermohaline circulation: stable or unstable? Geophysical Research Letters Vol. 29, No. 21, 2028, doi:10.1029/2002GL015337. Abstract

    Prange, M. , Lohmann, G., and A. Paul, 2003: Influence of vertical mixing on the thermohaline hysteresis: Analyses of an OGCM. J. Phys. Oceanogr., 33 (8), 1707-1721. Abstract

    Rahmstorf, S., J. Willebrand, 1995: The role of temperature feedback in stabilizing the thermohaline circulation. J. Phys. Oceanogr., 25, 787-805.

    Roeckner, E., K. Arpe, L. Bengtsson, S. Brinkop, L. Dümenil, M. Esch, E. Kirk, F. Lunkeit, M. Ponater, B. Rockel, R. Sausen, U. Schlese, S. Schubert, and M. Windelband, 1992: Simulation of present-day climate with the ECHAM model: Impact of model physics and resolution. MPI Report No. 93, ISSN 0937-1060, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 171 pp.

    Romanova, V., M. Prange, and G. Lohmann, 2003: On the stability of the glacial THC and its dependence on the background hydrological cycle. Climate Dynamics (in press).

    Rühlemann, C., Mulitza, S., Lohmann, G., Paul, A., Prange, M., and G. Wefer, 2003a: Abrupt warming of the intermediate-depth Atlantic Ocean in response to thermohaline circulation slowdown during the last deglaciation. PAGES NEWS, Vol. 11, No. 1, April 2003, 17-19. psfile pdf file

    Rühlemann, C., Mulitza, S., Lohmann, G., Paul, A., Prange, M., and G. Wefer, 2003b: Abrupt warming of the intermediate-depth tropical Atlantic caused by thermohaline circulation weakening: evidence from paleoclimate data and model simulations. Paleoceanography (in press).

    Sitch, S., Prentice, I. C., Smith, B., and LPJ consortium members, 2000: A coupled model of vegetation dynamics and the terrestrial carbon cycle. in: S. Sitch, The role of vegetation dynamics in the control of atmospheric CO2 content. Lund, Sweden.

    Winguth, A., D. Archer, E. Maier-Reimer, U. Mikolajewicz, and J.-C. Dupplessy,1999: Sensitivity of the paleonutrient tracer distribution and deep-sea circulation to glacial boundary conditions. Paleoceanogr., 14, 304-323.