PMIP Documentation of ECHAM3
Model Max-Planck-Institut fuer Meteorologie: Model MPI ECHAM3 (T42 L19) 1994
Dr. habil. Bjoern Grieger, formerly at the University of Bremen,
now at the Max-Planck-Institute for Aeronomy, Max-Planck-Str. 2,
D-37191 Katlenburg-Lindau, Germany, Phone: +49 5556 979 466, Fax:
+49 2561 9595 6137, e-mail: email@example.com
Stephan Lorenz, University of Bremen, Fachbereich 5, Postfach 330440, 28334 Bremen, Germany; Phone: +49 40 41173 175; Fax: +49 40 41173; e-mail: firstname.lastname@example.org
Dr. Ulrike Wyputta, formerly at the University of Bremen, e-mail: email@example.com
WWW URL: http://www.palmod.uni-bremen.de/palmod.html
Number of days in each month: 30 30 30 30 30 30 30 30 30 30 30 30
Deutsches Klimarechenzentrum (DKRZ) Modellbetreuungsgruppe, 1992: The ECHAM3 atmospheric general circulation model. DKRZ Tech. Report No. 6, ISSN 0940-9237, Deutsches Klimarechenzentrum, Hamburg, Germany, 184 pp.
Roeckner, E., K. Arpe, L. Bengtsson, S. Brinkop, L. Duemenil, M. Esch, E. Kirk, F. Lunkeit, M. Ponater, B. Rockel, R. Sausen, U. Schlese, S. Schubert, and M. Windelband, 1992: Simulation of the present-day climate with the ECHAM model: Impact of model physics and resolution. MPI Report No. 93, ISSN 0937-1060, Max-Planck-Institut fuer Meteorologie, Hamburg, Germany, 171 pp.
Lorenz, S., B. Grieger, P. Helbig and K. Herterich 1996: Investigating
the sensitivity of the Atmospheric General Circulation Model ECHAM 3 to
paleoclimatic boundary conditions, Geologische Rundschau 85, 513-524
latitude-longitude. dim_longitude*dim_latitude: 128*64
0.0, 0.0, 0.0003389933, 0.0033571866, 0.0130700434, 0.0340771467, 0.0706498323, 0.1259166826, 0.2011954093, 0.2955196487, 0.4054091989, 0.5249322235, 0.6461079479, 0.7596983769, 0.8564375573, 0.9287469142, 0.9729851852, 0.9922814815, 1.0.
For a surface pressure of 1000 hPa, five levels are below 800 hPa and
seven levels are above 200 hPa. The two lowest layers are pure sigma layers
and the top two layers are at constant pressures.
Vertical diffusion operates above the planetary boundary layer (PBL)
only in conditions of static instability. In the PBL, vertical diffusion
of momentum, heat, cloud water, and moisture is proportional to the vertical
gradient of the appropriate field. The vertically variable diffusion coefficient
depends on stability (expressed as a bulk Richardson number) and the vertical
shear of the u-wind, following standard mixing-length theory. See also
Planetary Boundary Layer and Surface Fluxes.
Shortwave equations are expressed in terms of optical depth, single-scattering albedo, diffuse and direct backscattering parameters, and diffusivity factor; longwave equations (with scattering effects neglected) are expressed in terms of the Planck function, optical depth, and diffusivity factor. Absorbers determining shortwave and longwave optical depths include ozone, carbon dioxide, and water vapor (with continuum absorption included). Optical depths for diffuse shortwave and longwave absorption are calculated using coefficients derived from "exact" reference models. Effects of pressure broadening on longwave absorption are also treated.
In the shortwave, optical depths for Rayleigh scattering are determined from the molecular cross section for each gas, and those for absorption and Mie scattering by ocean, desert, and urban aerosols are from data of Shettle and Fenn (1975) . Single scattering albedo is derived from the optical depths for diffuse shortwave scattering/absorption. At a given vertical level, the total optical depth for direct shortwave radiation (which is dependent on solar zenith angle) is obtained from linear superposition of optical depths for scattering/absorption by gases and aerosols summed over all the levels above.
The shortwave optical depth for clouds is parameterized after the method
of Stephens (1978) , and the single-scattering albedo and backscattering
parameter follow Kerschgens et al. (1978) . Longwave emissivity is an exponential
function of geometrical cloud thickness, prognostic cloud water content,
and a mass absorption coefficient, following Stephens (1978). For purposes
of the radiation calculations, clouds in contiguous vertical layers are
treated as fully overlapped, and as randomly overlapped otherwise. Cf.
DKRZ (1992) for further details. See also Cloud Formation.
Cloud droplets grow by condensation if the grid-mean relative humidity exceeds this threshold relative humidity or if the relative humidity in the c fraction of the grid box exceeds 100 percent. The condensation rate depends on the moisture convergence into the grid box, with a fraction c of the convergence producing more cloud, and the fraction (1 - c) increasing the relative humidity of the cloud-free part of the grid box.
The cloud water in the cloud-free fraction (1 - c) that increases (decreases)
as a result of advective/diffusive transports into the grid cell or through
numerical effects (e.g., spectral truncation) is assumed to evaporate (condense)
instantaneously; explicit filling of negative cloud water values is therefore
unnecessary (see Smoothing/Filling). Convective cloud water is not advected
(rather, there is instantaneous precipitation and/or evaporation to the
environment--see Precipitation). Cf. DKRZ (1992) for further details. See
also Radiation for treatment of cloud-radiative interactions.
For stratiform mixed-phase precipitation formation (i.e., in a temperature
range from 0 to -40 degrees C), the ice and liquid phases are treated independently.
Growth of cloud droplets (see Cloud Formation) to precipitating raindrops
occurs by autoconversion, following the exponential relationship of Sundqvist
(1978) , and by collisions with larger drops, following the parameterization
of Smith (1990) . Partitioning of cloud liquid vs ice is according to the
temperature-dependent relation of Matveev (1984) , and the loss of ice
crystals by sedimentation follows Heymsfield (1977) . Evaporation of stratiform
precipitation in a layer below cloud is proportional to the saturation
deficit, but cannot exceed the precipitation flux at the layer top. Stratiform
snow forms if the cloud layer temperature snow forms if the cloud layer
temperature is <0 degrees C. Falling convective and stratiform snow
melts if the temperature of a layer is >2 degrees C. Cf. DKRZ (1992) for
further details. See also Snow Cover.
For 6 fix: SSTs and sea-ice prescribed at their present day value, as in the control run.
For 21 fix: SSTs and sea-ice: a global reconstruction of the surface
conditions was supplied by the CLIMAP project (1981). It includes the sea
ice distribution and SSTs for February and August. The annual cycle of
SSTs was approximated by a sine function, taking the values for February
and August like extrema.
For 21fix run, sea ice edge of CLIMAP data is used for February and
August. The area covered by the glacial ice sheets is also taken from CLIMAP,
but the the thickness of the ice sheets is altered according to Tushingham
and Peltier (1991), which implies a thickness reduction of Laurentide ice
sheet by about one third compared with the CLIMAP thickness and a corresponding
increase of the thickness of the other ice sheets.
The surface roughness is calculated in differnet ways over land and over sea, where the land/sea distribution is taken from a US navy data set. The surface roughness length is prescribed as a uniform 1 x 10-3 meter over sea ice; it is computed prognostically over open ocean from the surface wind stress by the method of Charnock (1955) , but is constrained to be a minimum of 1.5 x 10-5 m. Over sea ice, the roughness length is assumed to be constant. Over land, the roughness length is a function of the orography, where the vegetation is taken from Wilson and Henderson-Sellers (1985). (see Orography) There exist 3 types of vegetation: forest, no vegetation and land ice.
The annual-mean surface albedo is obtained from satellite data of Geleyn and Preuss (1983) . Over land, this background albedo is altered by snow cover as a linear function of the ratio of the water-equivalent snow depth to a critical value (0.01 m). Albedos of snow (range 0.30 to 0.80), sea ice (range 0.50 to 0.75), and continental ice (range 0.6 to 0.8) vary as a function of surface temperature and forested area, as given by Robock (1980) and Kukla and Robinson (1980) . The albedo of ocean is a constant 0.065 for diffuse radiation, while that for the direct beam depends on solar zenith angle, but never exceeds 0.15.
Longwave emissivity is prescribed as 0.996 for all surfaces. Cf. DKRZ
1992 for further details.
Surface turbulent eddy fluxes of momentum, dry static energy (sensible heat), cloud water, and moisture are simulated as stability-dependent bulk formulae, following Monin-Obukhov similarity theory. The required near-surface values of wind, temperature, cloud water, and humidity are taken to be those at the lowest atmospheric level (sigma = 0.996). (At the surface, cloud water is assumed to be zero.) Surface drag and transfer coefficients in the bulk formulae are functions of stability and roughness length (see Surface Characteristics), following Louis (1979) and Louis et al. (1981) , but with modifications by Miller et al. (1992) for calm conditions over the oceans. The stability criterion is the moist bulk Richardson number, which includes the impact of cloud processes on buoyancy (cf. Brinkop 1992) .
The surface moisture flux depends on the surface specific humidity;
over ocean, snow, ice, and wet vegetation fractions of each grid box, this
is taken as the saturated humidity at the surface temperature and pressure
(i.e., potential evaporation is assumed). Over the bare soil fraction,
the surface specific humidity is the product of relative humidity (that
is a function of soil moisture--see Land Surface Processes) and the saturated
specific humidity. For a dry vegetation canopy, the potential evaporation
is reduced by an evapotranspiration efficiency factor beta that is the
inverse sum of aerodynamic resistance and stomatal resistance; the latter
depends on radiation stress, canopy moisture, and soil moisture stress
in the stress in the vegetation root zone (cf. Sellers et al. 1986 , Blondin
1989 , and Blondin and Boettger 1987 ).
Snow pack temperature is also computed from the soil heat equation using heat diffusivity/capacity for ice in regions of permanent continental ice, and for bare soil where water-equivalent snow depth is <0.025 m. For snow of greater depth, the temperature of the middle of the snow pack is solved from an auxiliary heat conduction equation (cf. Bauer et al. 1985 ). The temperature at the upper surface is determined by extrapolation, but it is constrained not to exceed the snowmelt temperature of 0 degrees C.
There are separate prognostic moisture budgets for snow, vegetation canopy, and soil reservoirs. Snow cover is augmented by snowfall and is depleted by sublimation and melting (see Snow Cover). Snow melts (augmenting soil moisture) if the temperatures of the snow pack and of the uppermost soil layer exceed 0 degrees C. The canopy intercepts precipitation and snow (proportional to the vegetated fraction of a grid box), which is then subject to immediate evaporation or melting.
Soil moisture is represented as a single-layer "bucket" model (cf. Manabe 1969 ) with field capacity 0.20 m that is modified to account for vegetative and orographic effects. Direct evaporation of soil moisture from bare soil and from the wet vegetation canopy, as well as evapotranspiration via root uptake, are modeled (see Surface Fluxes). Surface runoff includes effects of subgrid-scale variations of field capacity related to the orographic variance (see Orography); in addition, wherever the soil is frozen, moisture contributes to surface runoff instead of soil moisture. Deep runoff due to drainage processes also occurs independently of infiltration if the soil moisture is between 5 and 9 percent of field capacity (slow drainage), or is larger than 90 percent of field capacity (fast drainage). Cf. Duemenil and Todini (1992) for further details.