Model/Experiment Documentation for AMIP-II

University of Illinois at Urbana-Champaign: Model UIUC 24-L ST-GCM 1998

Contact Information

Modeling Group

Climate Research Group, University of Illinois at Urbana-Champaign (CRG/UIUC)

AMIP Representative(s)

• Dr. Michael Schlesinger, Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, 105 South Gregory Avenue, Urbana, Illinois 61801; Phone: +1-217-333-2192; Fax: +1-217-244-4393; e-mail: schlesin@atmos.uiuc.edu; World Wide Web URL: http://crga.atmos.uiuc.edu/.
  

• Fanglin Yang, Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, 105 South Gregory Avenue, Urbana, Illinois 61801; Phone: +1-217-333-7948; Fax: +1-217-244-4393; e-mail: fanglin@atmos.uiuc.edu; World Wide Web URL: http://crga.atmos.uiuc.edu/~fanglin/.
  

End of Contact Information

New Information for AMIP II

Experimental Implementation

Simulation Period

• Start time (AMIP II specification: 00Z 1 January 1979).
• Stop time (AMIP II specification: 00Z 1 March 1996).

Earth Orbital Parameters

Values of

• Obliquity (AMIP II specification: 23.441 degrees).
• Eccentricity (AMIP II specification: 0.016715).
• Longitude of perihelion (AMIP II specification: 102.7 degrees).

Calendar

Calendar used for model integration.

• 365 day/year calendar without leap years

Radiative Boundary Conditions

• Solar constant (AMIP II specification: 1365 W/m**2).
• Solar cycles present (seasonal and diurnal cycles).
• Carbon dioxide concentration (AMIP II specification: 348 ppm).
• Ozone concentration:
  Use monthly climatology of zonal-averaged ozone [Wang et al., 1995] as vertical profile and TOMS monthly climatology of total ozone as latitute-longitude distribution. Column total ozone equas to TOMS total ozone.
• Concentrations of other greenhouse gases:
  1650 ppbv for methane,
  306 ppbv for nitrous oxide;
  CFC11=214.5 ppbv
  CFC12=371.1 ppbv
  CFC22=200.0 ppbv
• Aerosol concentration(s):
  Longner and Rodhe [1991]'s natural sulfate aerosol as background monthly climatology.

Ocean Surface Boundary Conditions

• AMIP II specification: Use of AMIP II sea surface temperature and sea ice boundary conditions derived by Taylor et al. (see Web document at http://www-pcmdi.llnl.gov/amip/AMIP2EXPDSN/BCS/amip2bcs.html) from observational data of Fiorino (see Web document at http://www-pcmdi.llnl.gov/amip/AMIP2EXPDSN/BCS_OBS/amip2_bcs.htm).
• Spatial interpolation procedure for use of these boundary conditions in the model (As recommended: obtain from PCMDI).
• Temporal interpolation procedure for use of these boundary conditions in the model
  Daily distributions are obtained by linear interpolation of monthly means in adjacent three months.

Orography/Land-Sea Mask

• obtained from the 1 x 1-degree data of Gates and Nelson [1975]; area-averaged over each 4 x 5-degree model grid square.
• Global-average value of model orography: 207.79m (recommended: 237.33 m).
• Relevant references.
  Gates, W.L., and A.B. Nelson [1975]: A new (revised) tabulation of the Scripps topography on a one-degree grid. Part 1: Terrain heights. Tech. Report R-1276-1-ARPA, The Rand Corporation, Santa Monica, CA, 132 pp.

Atmospheric Mass

• Global-average value of model surface pressure: 986.1 hPa.
  (recommended: observed value of 982.4 hPa or a deviation from this of 1 hPa per 8 m deviation of orography from the observed average of 237.33 m)

Spinup/Initialization

• Procedure for spin-up of the model to quasi-equilibrium at the nominal starting time of 00Z 1 January 1979:
  first, run the model for 15 years with AMIP-II climatological sea-surface temperature and sea ice distributions; then run the model for one year with superficial SST and sea ice of 1978 obtained from PCMDI.
• Initialization (at 00Z 1 January 1979) procedure for the model's:
  variables saved from the spin-up run were used
• Relevant references
  Fanglin Yang, Michael E. Schlesinger and E. Rozanov, 1999:Description and Performance of the UIUC 24-Layer Stratosphere/Troposphere General Circulation Model. ( submitted to JGR).
  

Computer/Operating System

• Computer and number of processors utilized: DEC/Alpha, one 550 MHz CPU
• Operating system: Unix

Computational Performance

Number of minutes of computation time per simulated day: 12
 

Model Output Description

Calculation of Standard Output Variables

• Method for calculation of percentage time that a pressure surface is below ground (As recommended: procedure of Boer, 1995 Mon. Wea. Rev., 114, 885-902).

• Method for calculation of monthly mean tendencies at 17 WMO standard pressure levels:
• • Temperature tendency due to total diabatic heating.
  • Temperature tendencies due to short-wave and long-wave radiation.
  • Temperature tendency due to moist convection.
  • Temperature tendency due to dry convection.
  • Temperature tendency due to large-scale/stratiform precipitation.
  • Total moisture tendency due to diabatic processes.
• All calculated once per hour on model sigma layers and interpolated to the 17 WMO standard pressure levels. At the end of each month, monthly means are derived.

• Method for calculation of cloud properties:
• • cloud water/ice: prognostic, see Oh [1989].
  • extinction coefficient (cloud optical thickness/layer depth): see Yang et al. [1999].
  • cloud emittance: see Yang et al. [1999].

• Method for calculation of surface variables
• • 10 m winds: extrapolated using winds at the lowest two model layers [Oh, 1989].
  • 2m specific humidity: taking as the average at the lowest model layer.
  • 2m temperature: extrapolated downward using the air temperature at the lowest model layer.

• Method for calculation of mean sea-level pressure
  Trenberth et al.'s method (NCAR/TN-369+STR, NCAR TECHNICAL NOTE, DECEMBER, 1993)
• (recommended: ECMWF algorithm--code to be provided by PCMDI).

• Method for calculation of clear-sky radiation and cloud radiative forcing
  See also Radiation and Yang et al. [1999].

• Method for calculation of potential vorticity: not supplied.

• Method for calculation of planetary boundary layer height:
  The lowest 3 model layers (surface to about 900 hPa) are treated as bounday layer and the geopotentail height of the 21th layer calculated along the model integration is saved as planetary boundary layer height.
  

Sampling Procedures

• Sampling procedure for calculation of monthly means of standard output variables (e.g., accumulation over every model time step vs accumulation of 6-hourly averages). Recommendations: See the AMIP II Guidelines: Appendix A Table Notes (at Web address http://www-pcmdi.llnl.gov/amip/NEWS/amipnl8.html#Appendix-A) for variable-dependent sampling procedures.
  Performed as recommended.

Interpolation Procedures

• Algorithm for interpolation of standard output variables to 17 WMO pressure surfaces
  monthly averages computed in model coordinates weighted by time varying mass on the 17 WMO pressure surfaces).
• Algorithm for treatment of variables on pressure surfaces below ground (if applicable).
  Trenberth et al.'s method (NCAR/TN-369+STR, NCAR TECHNICAL NOTE, DECEMBER, 1993)

Output Data Structure/Format/Compression

• Structure/format of output data
  AMIP II specification: LATS structure in NetCDF format.
• Original and compressed word length of data (in bits per word) and description of compression algorithm:
  4 bits per word. Individual files were compressed using "gzip", then a group of data were put together using "tar".

Model Characteristics

AMIP II Model Designation

CRG/UIUC, 24-L ST-GCM (4x5L24) 1998

Model Lineage

• The 24-layer stratospheric-tropospheric general circulation model (24-L ST-GCM) was developed based on the UIUC 7-layer tropospheric [Oh, 1989] and 11-layer tropospheric/lower-stratospheric AGCMs [Wang and Schlesinger, 1999], which are decendents of the OSU/UIUC 2-layer AGCM [Gates et al., 1971; Ghan et al., 1982]. The 7-layer AGCM, with its top at 200 hPa, differs from the 2-layer AGCM mainly in its vertical resolution and the treatment of radiation, clouds, precipitation and the planetary boundary layer [Oh, 1989]. The 11-layer AGCM, with its top at 50 hPa, possesses the same dynamic and physical features as the 7-layer AGCM, but is significantly improved in simulating the present climate, especially the tropical intraseasonal oscillation [Wang and Schlesinger, 1999]. The 24-layer ST-GCM has its top at 1mb. New parameterizations have been developed for the transfer of both thermal infrared radiation and solar radiation. The interaction between clouds and radiation has also been modified. The radiative effects of aerosols in both the troposphere and stratosphere have been included. A parameterization scheme for orographically excited subgrid-scale gravity-wave drag has been included in the model [Yang et al., 1999].
•  

Designation of most similar model documented for AMIP I
UIUC MLAM-AMIP (4x5L7) 1993

End of New Information for AMIP II

Differences From Most Similar AMIP I Model

Note, for each of the following model properties, only differences from the most similar AMIP I model need be described--you may omit mention of properties that are the same. Please cite references (including information on author(s), year, title, journal name/report series number, volume number, and page numbers) wherever these are relevant to describing a particular model difference. For guidance, consult the current AMIP I model summary documentation at World Wide Web address  http://www-pcmdi.llnl.gov/modeldoc/amip/01toc.html

As a temporary version serving ourself, I included all infomation below.

Model Documentation

Bibliography of key documents describing model characteristics.

Fanglin Yang, Michael E. Schlesinger and E. Rozanov, 1999:Description and Performance of the UIUC 24-Layer Stratosphere/Troposphere General Circulation Model. ( submitted to JGR).

Oh, J.-H., 1989: Physically-based general circulation model parameterization of clouds and their radiative interaction. Ph. D. dissertation, Department of Atmospheric Sciences, Oregon State University, Corvallis, OR, 315 pp.

Numerical/Computational Properties

Horizontal Representation

• Formulation of horizontal variation of model variables (e.g., second-order finite differences on a C grid, spectral basis functions with transformation to Gaussian grid, etc.).
• Variable-dependent differences in formulation, if present (e.g., spectral dynamical variables vs semi-Lagrangian grid-point water vapor and chemistry).

Horizontal Resolution

• Finite differences on a B-grid (cf. Arakawa and Lamb 1977), conserving total atmospheric mass, energy, and potential enstrophy.

Vertical Domain

• Model top in units of hPa: 1 hPa
• Pressure of lowest atmospheric level (in hPa) when surface pressure is 1000 hPa: 990hPa

Vertical Representation

• Vertical coordinates: sigma
• Vertical differencing: Finite-difference
• Relevant references: Oh [1989]

Vertical Resolution

• Total number of vertical levels: 24
• Number of levels below 800 hPa and above 200 hPa for a surface pressure of 1000 hPa: 5; 12

Time Integration Scheme(s)

• For integration of dynamics each hour, the first step by the Matsuno scheme is followed by a sequence of leapfrog steps, each of length 6 minutes. The diabatic terms (including full radiation calculations), dissipative terms, and the vertical flux convergence of the specific humidity are recalculated hourly.

Smoothing/Filling

• Orography is area-averaged on the model grid (see Orography). A longitudinal smoothing of the zonal pressure gradient and the zonal and meridional mass flux is performed at latitudes polewards of 38 degrees (cf. Ghan et al. 1982). It is unnecessary to fill spurious negative values of atmospheric moisture, since these are not generated by the numerical schemes.

Dynamical/Physical Properties

Equations of State

• Primitive-equations dynamics are expressed in terms of u and v winds, temperature, surface pressure, and specific humidity. Cloud water is also a prognostic variable (see Cloud Formation).

Diffusion

• Horizontal diffusion is not modeled.
• Representation of vertical diffusion above the surface layer:
  Vertical diffusion of momentum, sensible heat, and moisture operates in the troposphere below 200 hPa. The diffusion depends on the vertical wind shear, but not on stability (cf. Oh 1989 and Oh and Schlesinger 1991a).

Gravity Wave Drag

• Description of gravity wave drag parameterization: Palmer et. al [1986]'s GWD parameterization.

Chemistry

• Enumeration of radiatively active gases: CO2, ozone, water vapor, CH4, N2O, CFC-11, CFC-12, HCFC-22, O2, and sulfate aerosol.
• Description of main properties: see also Radiative Boundary Conditions

Radiation

• Treatment of clear-sky shortwave radiation:
  There are 11 solar bands: 0.175 - 0.225; 0.225-0.280; 0.245 - 0.260; 0.280 - 0.295; 0.295 - 0.310; 0.310 - 0.320; 0.320 - 0.400; 0.400 - 0.700; 0.700 - 1.22; 1.22 - 2.27; 2.27 - 10.0 (micron). cf [Chou,1990; 1992] and Chou and Lee [1996].
• Treatment of clear-sky longwave radiation:
  There are 9 longwave bands: 0-340; 340-540; 540-800; 800-980; 980-1100; 1100-1215; 1215-1380; 1380-1900; 1900-3000 (cm-1). cf Chou and Suarez [1994].
• Treatment of interactions with clouds:
  Longwave Radiation: The effects of clouds on terrestrial radiation are included in the parameterization by introducing a mean flux transmittance which is the product of the gaseous transmittances and a cloud-related coefficient [Chou and Suarez, 1994]. This coefficient is calculated for each GCM layer and conveys information about cloudiness, cloud optical thickness, and cloud overlapping. Clouds are grouped into three categories - high clouds above the 16th -layer of the model, middle clouds between the 16th and 19th -layers, and low clouds below the 19th -layer . Clouds within each category are assumed to be maximally overlapped, while the different cloud categories are assumed to be randomly overlapped. The cloud transmission function for a given layer depends on the cloud liquid and/or ice water path and cloud emissivities, with the latter prescribed following Stephens [1978] for liquid-water clouds and Starr and Cox [1985] and Griffith et al. [1980] for ice clouds.
  Shortwave Radiation: Cloud grouping and overlapping are treated in the same way as in the longwave-radiative transfer parameterization. The shortwave radiative properties of liquid-water clouds [Slingo, 1989] depend on liquid-water path and the equivalent radius of the drop-size distribution, the latter determined by the in-cloud liquid-water content and cloud-droplet number concentration (CDNC). The CDNC is empirically related to the sulfate aerosol mass concentration [Boucher and Lohmann, 1995]. Shortwave radiative properties of ice clouds are also functions of the ice-water path and ice crystal effective size, assumed to be 70 µm. For mixed-phase clouds, the optical depth is the summation of water-cloud optical depth and ice-cloud optical depth, the single-scattering albedo is optical-depth weighted, and the asymmetry factor is optical-depth and single-scattering-albedo weighted. The delta-Eddington method is first used to calculate transmittance and reflectance of each layer [King and Harshvardhan, 1986], and then the two-stream adding method following equations (3)-(5) of Chou [1992] is applied to compute the upward and downward fluxes in both the clear and cloudy atmosphere. cf Yang et. al [1998].

Convection

• Penetrative convection is simulated by a modified Arakawa-Schubert (1974)scheme. The scheme predicts mass fluxes from mutually interacting cumulus subensembles which have different entrainment rates and levels of neutral buoyancy (depending on the properties of the large-scale environment) that define the tops of the clouds and their associated convective updrafts. In turn, the predicted convective mass fluxes feed back on the large-scale fields of temperature (through latent heating and compensating subsidence), moisture (through precipitation and detrainment), and momentum (through cumulus friction). The effects on convective cloud buoyancy of phase changes from water to ice, and the drying and cooling effects of convective-scale downdrafts on the environment are not explicitly included.
• The cloud-base mass flux for each cumulus sub-ensemble is determined following Arakawa (1969) such that the convective instability for each subensemble is removed with an e-folding time of one hour (cf. Oh 1989).
• The model also simulates middle-level convection, defined by convective instability between any two adjacent layers, with the instability also being removed with an e-folding time of one hour. In addition, if the lapse rate becomes dry-convectively unstable anywhere within the model atmosphere, enthalpy is redistributed vertically in an energy-conserving manner.

Cloud Formation

• The cloud parameterization is formulated separately for stratiform and cumuloform clouds, as described by Oh (1989) and Oh and Schlesinger (1991b). For both cloud types, the liquid/ice water is computed prognostically, and the fractional cloud coverage of each grid box semiprognostically. The stratiform cloud fraction varies as the square root of the relative humidity. The cumuloform cloud fraction is determined as a function of the relative humidity and the convective mass flux (see Convection).
• Cloud in the PBL (see Planetary Boundary Layer) is diagnostically computed on the basis of a cloud-topped mixed layer model (cf. Lilly 1968and Guinn and Schubert 1989).

Precipitation

• Precipitation forms via the simulated microphysical processes (autoconversion from cloud liquid/ice water) in the prognostic cloud scheme (cf. Oh 1989 and Oh and Schlesinger 1991b ). The large-scale precipitation rate is an exponential function of the liquid water mixing ratio and the cloud water content. The difference of these quantities multiplied by the cumulus mass flux yields the convective precipitation rate (see Convection).
• The rate of evaporation of falling large-scale precipitation is proportional to the product of the rainfall rate, the relative humidity deficit from saturation, and the cloud-free fraction of the grid box. Evaporation of convective precipitation is proportional to the product of the relative humidity deficit and the cloud water content.

Planetary Boundary Layer

• The top of the PBL is taken to be the height of the lowest three atmospheric layers (total thickness about 150 hPa for a surface pressure of 1000 hPa). PBL cloud is diagnostically computed on the basis of a cloud-topped mixed layer model. See also Cloud Formation, Diffusion, Surface Characteristics and Surface Fluxes .

Sea Ice

The prescription of the model's sea ice extent and concentration should be described in the experimental implementation of Ocean Surface Boundary Conditions (see above). Here, provide relevant references and describe the method of determining:

• AMIP-II monthly sea ice extents are prescribed. The surface temperature of the ice is determined prognostically from the surface energy balance (see Surface Fluxes) including heat conduction from the ocean below. The conduction flux is a function of the prescribed heat conductivity and ice thickness (monthly means varying with location), and of the difference between the surface temperature and that of the ocean (a fixed 271.5 K). When snow accumulates on sea ice, this conduction flux can contribute to snowmelt. Cf. Ghan et al. (1982) for further details.

Snow Cover

• Precipitation falls as snow if the surface air temperature is < 0 degrees C. Snow mass is determined from a prognostic budget equation that includes the rates of accumulation, melting, and sublimation. Over land, the rate of snowmelt is computed from the difference between the downward heat fluxes at the surface and the upward heat fluxes that would occur for a ground temperature equal to the melting temperature of snow (0 degrees C); snowmelt contributes to soil moisture (see Land Surface Processes). Accumulation and melting of snow may also occur on sea ice (see Sea Ice). The surface sublimation rate is equated to the evaporative flux from snow (see Surface Fluxes) unless sublimation removes all the local snow mass in less than 1 hour; in that case the sublimation rate is set equal to the snow-mass removal rate. Snow cover also alters the surface albedo (see Surface Characteristics). Cf. Ghan et al. (1982) for further details.

Surface Characteristics

• 7 surface types (1) evergreen wood and forest; (2) mixed and deciduous wood, and forest; (3) grassland; (4) cropland; (5) shrub and semi-desert; (6) desert; and (7) tundra, mountain, arctic flora [Vinnikov and Yeserkepova, 1991].
• Surface roughness is specified as in Hansen et al. (1983) . Over land, the roughness length is a fit to the data of Fiedler and Panofsky (1972)deviation of the orography. The maximum of this value as a function of the standard and that of the roughness of the local vegetation (including a "zero plane displacement" value for tall vegetation types--cf. Monteith 1973land. Over sea ice, the roughness is a constant 4.3) determines the roughness length over x 10^-4 m after Doronin (1969)length is a function of the surface wind speed . Over ocean, the roughness following Garratt (1977).
• Snow-free surface albedo is updated monthly by interpolation using values for January, April, July, and October specified from data of Matthews (1983) . The albedo of snow-covered surfaces is determined as a linear weighted (by snow depth) interpolation of snow-free and snow-covered values. The albedo of snow is a function of its temperature (cf. Manabe et al. 1991); it also depends on solar zenith angle (cf. Briegleb and Ramanathan 1982 ), but not on spectral interval.
• Longwave emissivity is specified to be unity (blackbody emission) for all surfaces.

Surface Fluxes

For distinguished surface types (see above):

• Treatment of surface radiative fluxes.
• The turbulent surface fluxes of momentum, sensible heat, and moisture are parameterized as bulk formulae that include surface atmospheric values of winds, as well as differences between skin values of temperatures and specific humidities and their surface atmospheric values. Following Oh and Schlesinger (1990) [32], the surface wind is taken as a fraction (0.7 over water and 0.8 over land and ice) of the winds extrapolated from the lowest two model layers. The surface atmospheric values of temperatures and humidities are taken to be the same as those at the lowest atmospheric level .The aerodynamic drag and transfer coefficients depend on vertical stability (bulk Richardson number) and surface roughness length (see Surface Characteristics), with the same transfer coefficient used for the fluxes of sensible heat and moisture. In addition, the surface moisture flux depends on an evapotranspiration efficiency beta that is taken as unity over snow, ice and water; over land, beta is a function of the fractional soil moisture (see Land Surface Processes).

Land Surface Processes

• Following Priestly (1959) and Bhumralkar (1975), the average ground temperature over the diurnal skin depth is computed from a prognostic budget equation whose source/sink terms include the net surface radiative flux and the sensible and latent heat fluxes (see Surface Fluxes); the thermal conductivity, volumetric heat capacity, and bulk heat capacity of snow, ice, and land are also taken into account. If the predicted ground temperature for land ice is > 0 degrees C, the ice is implicitly assumed to melt, since the model does not include a budget equation for land ice. See also Snow Cover.
• Soil wetness is expressed as the ratio of soil moisture content to a field capacity that is specified as a function of soil texture and surface cover after data of Vinnikov and Yeserkepova (1991). Soil wetness is determined from a prognostic budget equation that includes the rates of precipitation, snowmelt, surface evaporation, and runoff. The evapotranspiration efficiency beta over land (see Surface Fluxes) is assigned a value that is the lesser of 1.33 times the soil wetness fraction or unity. The runoff rate is a nonlinear function of the soil wetness and the combined rates of precipitation and snowmelt. If the predicted soil wetness fraction exceeds unity, the excess moisture is taken as additional runoff.

  
  
  

Last update 20 April 1999. For questions or comments, contact Fanglin Yang

CRG/UIUC