Long description of model 'EURAD-IM'

Table of Contents:

For help concerning the various sections see this page


Basic information [top]

Model name
EURAD-IM

Full model name
EURopean Air pollution Dispersion-Inverse Model extension

Model version and status
Version 4.2

Latest date of revision
03-28-2007

Institutions
Rhenish Institute for Environmental Research at the University of Cologne

Contact person
Hendrik Elbern

Contact address
Rheinisches Institut fuer Umweltforschung
Aachener Str. 201-209
50931 Koeln, Germany

Phone number
+49 (0) 221 400 2258

Fax number
+49 (0) 221 400 2320

E-mail address
he belongs-to eurad dot uni-koeln dot de

URL
www.eurad.uni-koeln.de

Technical support
H. Elbern and Chemical Data Assimilation group of RIU

Level of knowledge needed to operate model
Advanced

Intended field of application [top]

Air pollution modelling (forecasts, episode analysis, trend analysis, reduction szenarios) & Chemical data assimilation studies

Model type and dimension [top]

three-dimensional
chemistry & transport
non-hydrostatic
hemispheric to local
short-term (hours/days) to long-term (years)
forecast and adjoint

Model description summary [top]

The EURAD-IM (EURopean Air pollution Dispersion-Inverse Model) system is designed for both standard `forward` simulations and `backward` adjoint simulations. The former serves as a forecasting tool, while the latter is used for data assimilation, inverse modelling and sensitivity tests.
The EURAD-IM model system serves both scientific system analyses including case studies and reanalyses, and operational forecasts. In both modes the nesting technique is applicable from continental scale to local scale with 1 km resolution.
Data assimilation applications include three and four dimensional variational techniques with the possibility to assimilate remote sensing data of all kinds. The assimilation system, can be run in ensemble mode, to provide skill scores predictions.
Further, with the inverse modelling mode, emission rates can be updated and improved.

Model limitations/approximations [top]

no global implementation
implemented chemistry mechanisms suited for troposphere/lower stratosphere only

Resolution [top]

Temporal resolution
Dynamical time step is grid size dependent (trivial), which is user-defined
Chemical time step depends on the current chemical regime and changing rates within one grid cell
Hourly output (default - but user defined)
Simulated time period: hours to years

Horizontal resolution
Grid size: user-defined (usually in the range 1 to 1000 km)
Domain size: user-defined (usually one town up to hemispheric)

Vertical resolution
User-defined sigma levels
Model top between 100 and 10 hPa

Schemes [top]

Advection & Convection
Bott, monotone Bott (Bott, A., A positive definit advection scheme obtained by nonlinear renormalisation of the advective fluxes, Month. Weath. Rev., 117, 5, 1006-1015, 1989.)
Smolarkiewicz (Smolarkiewicz, P.K., A simple positive definition advection scheme with small implicit diffusion. Month. Weath. Rev., 111, 479-486, 1983.)
Prather (Prather, M.J., Numerical advection by conservation of second order moments. J. Geophys. Res., 91, 6671-6681, 1986.)

Turbulence
Louis-parameterization (Louis, J.-F., A parametric model of verticaleddy fluxes in the atmosphere. Bound.-Layer Meteor., 17, 187-202,1979.)
ABL-scaling (Holtslag, A.A.M. and Nieuwstadt, F.T.M., Scaling the atmospheric boundary layer. Bound.-Layer Meteor., 36, 201-209, 1986.)
Blackadar-mixing (Blackadar, A.K., High resolution models of the planetary boundary layer. In: Pfafflin, J. and E. Ziegler (Eds.): Advances in environmental science and engineering, Gordon and Breach., 1, No. 1, 3-49, 1979.)

Deposition

Dry deposition:
Dry deposition velocities of 15 gas-phase species are calculated using a resistance model which considers the aerodynamic resistance, the quasi-laminar layer resistance, and a land use dependent canopy resistance (Walcek et al., 1986).
The dry deposition of aerosol-phase species is treated size dependent. For each of the three lognormal modes used within the EURAD-IM the process of dry deposition is parameterized using a resistance model (Ackermann et al., 1998). Different gravitational settling velocities are used for each mode.
Ackermann, I.J., H. Hass, M. Memmesheimer, A. Ebel, F.S. Binkowski, and U. Shankar, Atmos. Environ., 32, 2981-2999, 1998.
Walcek, C.J., R.A. Brost, J.S. Chang, and M.L. Wesely, Atmos. Environ., 20, 949-964, 1986.

Wet deposition:

Gas-phase:
Henrys law equilibria for all prognostic species.

Aerosol-phase (Binkowski, 1999):
The accumulation mode particles form cloud condensation nuclei and are 100% absorbed into the cloud water.
The Aitken mode forms interstitual aerosol which is scavenged by cloud droplets.
The wet removal of aerosol is proportional to the wet removal of sulfate.
Binkowski, F.S., Aerosols in Models-3 CMAQ, in: Science algorithms of the EPA Models-3 Community multiscale air quality (CMAQ) modeling system, EPA 600/R-99-030, EPA, 1999.

Chemistry
GAS PHASE:
Several gas-phase chemical mechanisms can be used within the EURAD-IM: 1) RADM2 (Stockwell el al., 1990)
2) RACM (Stockwell et al., 1997)
3) RACM-MIM (Geiger et. al, 2003) - RACM-MIM is an update of the RACM chemistry mechanism which involves a condensed version of the Mainz isoprene mechanism (MIM) for the tropospheric oxidation of isoprene.
4) Euro-RADM (Stockwell and Kley) - The Euro-RADM chemical mechanism was developed to model European atmospheric chemistry. It is based upon the Regional Acid Deposition Model mechanism, version 2 (RADM2).
5) CHEST (Lippert et al., 1996) - CHEST treats the most important chemical processes of the troposphere and lower stratosphere. It contains a condensed version of the RADM2 mechanism.
Geiger, H., I. Barnes, I. Bejan, T. Benter, and M. Spttler, Atmos. Environ., 37, 1503-1519, 2003.
Lippert, E., J. Hendricks, and H. Petry, Proc. of the Int. Colloq.: Impact of Aircraft Emissions upon the Atmosphere, 15.-18. October, Paris, ONERA, 545-550, 1996.
Stockwell, W.R., P. Middleton, and J.S. Chang, J. Geophys. Res., 95, 16343-16367, 1990.
Stockwell, W.R., F. Kirchner, M. Kuhn, and S. Seefeld, J. Geophys. Res., 102, 25847-25879, 1997.

AEROSOLS:
The aerosol dynamics model MADE (Ackermann et al., 1998) is used to provide information on the aerosol size distribution and chemical composition. Fine particles smaller then about 2.5 micrometers are treated by two interacting lognormal modes. The coarse particles form a third mode. The two smaller modes interact with each other through coagulation. Each mode may growth through condensation of gaseous precursurs. The aerosol species treated in the two fine particle modes are secondary anorganic aerosols, primary and elemental carbon, other unspecified material of anthropogenic origin, and anthropogenic and biogenic secondary organic species (Schell et al., 2001).
Two modules are available for the treatment of the equilibrium chemistry in the system H* -- NH4* -- NO3- -- SO4-- - H2O:
1) RPMARES (Binkowski and Shankar, 1995)
2) A High Dimensional Model Representation (HDMR) of an aerosol chemistry module which accurately predicts activity coefficients based on the ion interaction approach (Clegg et al., 1992)

The coarse particles consist of unspecified material of anthropogenic origin, sea salt (Monahan et al., 1986; Martensson, 2003), and mineral dust (Nickovic et al., 2001).

Ackermann, I.J., H. Hass, M. Memmesheimer, A. Ebel, F.S. Binkowski, and U. Shankar, Atmos. Environ., 32, 2981-2999, 1998.
Binkowski, F.S. and. U. Shankar, J. Geophys. Res., 100, 26191-26209, 1995.
Clegg, S.L., K.S. Pitzer, and P. Brimblecombe, J. Phys. Chem., 96, 9470-9479, 1992.
Martensson, E.M., E.D. Nilsson, G. de Leeuw, L.H. Cohen, and H.-C. Hansson, J. Geophys. Res., 108, doi:10.1029/2002JD002263.
Monahan, E.C., D.E. Spiel, and K.L. Davidson, in: Oceanic Whitecaps, E.C. Monahan and G. Mac Niocaill eds., 167-174, D. Reidel, Norwell, Mass., 1986.
Nickovic, S., G. Kallos, A. Papadopoulos, and O. Kakaliagou, J. Geophys. Res., 106, 18113-18129, 2001.
Schell, B., I.J. Ackermann, H. Hass, F.S. Binkowski, and A. Ebel, J. Geophys. Res., 106, 28275-28293, 2001.

Solution technique [top]

Operator splitting technique, centered differences are used for the spatial discretization.

Chemistry: The kinetic preprocessor KPP (Sandu et al., 2003; Sandu and Sander, 2006) is incorporated into the EURAD-IM. Taking a set of chemical reactions and their rate coefficients as input, KPP generates the code for the temporal integration of the kinetic system. Efficiency is obtained by exploiting the sparsity structures of the Jacobian and the Hessian. KPP generates the adjoint model of the chemical system. The Rosenbrock methods Ros-2, Ros-3, Rodas-3, Ros-4 and Rodas-4 can be used as stiff numerical integrators. Ros-2 is the preferred integrator.

Sandu, A., D. N. Daescu, and G.R. Carmichael, Atmos. Environ., 37, 5083-5096, 2003.
Sandu, A. and R. Sander, Atmos. Chem. Phys., 6, 187-195, 2006.

Input [top]

Availability and Validation of Input data
Input data (e.g., j-values, deposition velocities) is taken from research institutes, where the methods and/or models used have proved the international validity and recognition.
For more details please refer directly to the contact person.

Emissions
Emission data are provided by the following institutions/databases:
1) EMEP
2) TNO
3) EDGAR (Emission Database for Global Atmospheric Research, http://www.mnp.nl/edgar)
4) LANUV (Northrine-Westfalia environmental agency)

For a description of EURAD emission model (EEM) see
Memmesheimer, M., J. Tippke, A. Ebel, H. Hass, H. Jakobs, and M. Laube, On the use of EMEP emission inventories for european scale air pollution modelling with the EURAD model, in: Proceedings of the EMEP workshop on photooxidant modelling for long-range transport in relation to abatement strategies, Berlin 1991, pp. 307-321.

Meteorology
All meteorological input data are provided by MM5 Version 3 simulations.

Topography
USGS (U.S. geological survey, www.usgs.gov)

Initial conditions
Three different data sources are available for the initialisation of the EURAD-IM:
1) Climatological profiles; Nested grids can be initialized by linear interpolation of output from a coarser model simulation.
2) Concentration fields from a preceeding model run.
3) Initial values optimized by 3- and 4-d variational data assimilation.

Boundary conditions
Surface: Dry depostion and sedimentation velocities are incorporated into the vertical diffusion equation for the lowest model layer. This boundary condition describes the removal of species by physical encounter with the underlying surface. Gas and aerosol emission fluxes enter the model.
Top: The model top works like a rigid lid.
Lateral Inflow: Prescribed advective flux given by the product of the boundary value and the component of the horizontal velocity perpendicular to the lateral boundary.
Lateral Outflow: Advective flux correction to prevent the reflection of high wavenumber oscillations at the lateral boundary.

Data assimilation options
3d-var
4d-var (+adjoint model)
Reduced Kalman Filter
For method references see available courses or text books (e.g., Daley, R., Atmospheric Data Analysis, Cambridge Univ. Press, 1991).
For information on the implementations see
- Elbern et al., ACP, 7, 3749-3769, 2007. (4d-var)
- http://kups.ub.uni-koeln.de/volltexte/2007/1942/ (4d-var)
- http://db.eurad.uni-koeln.de/promote/docs/dasys_descr.pdf(3d-var)

Output quantities [top]

Meteorological parameters (as MM5 pass-through)
Volume mixing ratios of complete gas phase chemistry mechanism members
Aerosol concentrations

User interface availability [top]

No graphical interface available.

Previous applications [top]

1.
Application type
Urban
Application description
Berlin, 21.7.-30.7.1994, 54-18-6-2 km nesting sequence Memmesheimer, M., H.J. Jakobs, J. Tippke, A.Ebel, G. Piekorz, M. Weber, H. Geiss, S. Jansen, B. Wickert, R. Friedrich, U. Schwarz, G. Smiatek, Simulation of a summer-smog episode in July 1994 on the European and urban scale with special emphasis on the photo-oxidant plume of Berlin. Proceedings of the EUROTRAC-Symposium, 1998, Vol.2, pp. 591-595. Ed.: P.M. Borrell and P. Borrell. WIT Press, 1999.
2.
Application type
Regional
Application description
European scale, 54 km resolution, 01.08.-20.08.1997. 4d-var applications
1) pure initial value optimization
2) pure emission rate optimization
3) joint emission rate/initial value optimization
Elbern, H., Strunk, A., Schmidt, H., Talagrand, O., Emission rate and chemical state estimation by 4-dimensional variational inversion, Atmos. Chem. Phys., 7, 3749-3769, 2007.
www.atmos-chem-phys.net/7/3749/2007
3.
Application type
Episodes
Application description
Different episode simulations using 4d-var data assimilation.
Strunk, A., Tropospheric chemical state estimation by four-dimensional variational data assimilation on nested grids, PhD thesis, Institute for Geophysics and Meteorology, University of Cologne, 2006.
http://kups.ub.uni-koeln.de/volltexte/2007/1942/

Documentation status [top]

Level 1-2: Complete scientific documentation but less complete user`s manuals.

Validation and evaluation [top]

Validation and evaluation has been performed by using available observations offline as well as using sophisticated data assimilation techniques. The current level of evaluation is therefore rather high. Please see the given references for a short overview. For further details refer to the contact person.
Elbern, H., H. Schmidt and A. Ebel, Variational data assimilation for tropospheric chemistry modeling, J. Geophys. Res., 102, (D13), 15,967-15,985, 1997.
Elbern, H. and H. Schmidt, Ozone episode analysis by four-dimensional variational chemistry data assimilation, J. Geophys. Res., D4, (106), 3569-3590, 2001.
Memmesheimer, M., E. Friese, A. Ebel, H. J. Jakobs, H. Feldmann, C. Kessler and G. Piekorz, Long-term simulations of particulate matter in Europe on different scales using sequential nesting of a regional model, Int. J. Environm. and Pollution, 22, (1-2), 108-132, 2004.

Model intercomparison
European scale, 25 km resolution, April - September 1995.
Hass, H., M. van Loon, C. Kessler, R. Stern, J. Matthijsen, F. Sauter, Z. Zlatev, J. Langner, V. Foltescu, M. Schaap, Aerosol Modelling: Results and Intercomparison from European Regional-scale Modelling Systems, A contribution to the EUROTRAC-2 subproject GLOREAM, International Scientific Secretariat (ISS), Munich, Germany, 2003.

Portability and computer requirements [top]

Portability
Implemented on:
Linux PC Cluster
IBM p690 eServer Cluster 1600
Cray T3E

CPU time
100x100x23 grid cells, RACM-MIM chemistry mechanism, 45km horizontal resolution, 24 hours single forward run, 16 processors (4x Intel Core 2 Quad 2400 MHz), Gigabit network: 15 min

Storage
up to 2 GigaByte for 24 hours single forward run

Availability [top]

The model code of the EURAD basic version (without any data assimilation option) is available.

References about model development (up to 5) [top]

  • Hass, H., Description of the EURAD Chemistry-Transport-Model version2 (CTM2), vol 83, Mitteilungen aus dem Institut für Geophysik und Meteorologie der Universität zu Köln, 1991.
  • Ackermann, I.J., H. Hass, M. Memmesheimer, A. Ebel, F.S. Binkowski, and U. Shankar, MADE: Modal Aerosol Dynamics Model for Europe; development and first applications, Atmos. Environ., 32, 2981-2999, 1998.
  • Elbern, H. and H. Schmidt, A four-dimensional variational chemistry data assimilation scheme for Eulerian chemistry transport modeling, J. Geophys. Res., 104, (D15), 18,583-18,598, 1999.
  • Memmesheimer, M., E. Friese, A. Ebel, H. J. Jakobs, H. Feldmann, C. Kessler and G. Piekorz, Long-term simulations of particulate matter in Europe on different scales using sequential nesting of a regional
  • model, Int. J. Environm. and Pollution, 22, (1-2), 108-132, 2004.
  • Elbern, H., Strunk, A., Schmidt, H., Talagrand, O., Emission rate and chemical state estimation by 4-dimensional variational inversion, Atmos. Chem. Phys., 7, 3749-3769, 2007.

Other references [top]

  • Ebel, A., H. Hass, H.J. Jakobs, M. Laube, M. Memmesheimer, A. Oberreuter, H. Geiss and Y.--H. Kuo: Simulation of ozone intrusion caused by a tropopause fold and cut--off low. Atmospheric Environment, 25A, 2131 -- 2144, 1991.
  • Ebel, A., H. Hass, H.J. Jakobs, M. Memmesheimer: Complex chemical transport modelling, its evaluation and application to air pollution episodes. In: Air Pollution, ed. P. Zanetti et al., p. 333--343, Elsevier Sci. Publ., 1993.
  • Elbern, H.: Parallelization and load balancing of a comprehensive atmospheric chemistry transport model. Atmos. Env., Vol. 31, No. 21, 3561--3574, 1997.
  • Ackermann, I. J., Hass, H., Memmesheimer, M., Ebel, A., binkowski, F. B., Shankar,U.: Modal aerosol dynamics model for Europe: development and first applications. Atmos. Environm., 32, 2891- 2999, 1998.
  • Schell, B., Ackermann, I. J., Hass, H., Binkowski, F. S., Ebel, A.: Modelling the formation of secondary organic aerosol within a comprehensive air quality modeling system. J. Geophys. Res., 106, 28275 - 28293, 2002.
  • Hass, H: Description of the EURAD Chemistry-Transport-Model Version 2 (CTM2), Mitteilungen aus dem Institut fuer Geophysik u. Meteorologie der Univer sitaet zu Koeln, 1991 (sold out, xerox copies on request).
  • Ebel, A., H. Elbern, H. Hass, H.J. Jakobs, M. Memmesheimer, H.J. Bock: Meteorological effects on air pollutant variability on regional scales. In: Air Pollution III, eds. A. Ebel, N. Moussiopoulos, Computational Mechanics Publications, Vol. 4, 1-6, 1995.
  • Ebel, A., M. Memmesheimer, H.J. Jakobs: Regional modelling of tropospheric ozone distribution and budgets. In: ``Global Environmental Change; ed. by C. Varotsos, NATO ASI Series, Subseries I, Vol. 53, Springer Verlag, pp. 39--59, 1997.
  • Ebel, A., H. Feldmann, F. Fiedler, H. Hass, H.J. Jakobs, O. Klemm, K. Nester, E. Schaller, A. Schwartz, J. Werhahn: Contributions to the evaluation of chemical transport models within the SANA project. In: Air Pollution III, Computational Mechanics Publications, Vol. 4, 103--110, 1995.
  • Feldmann, H., A. Ebel, H.Hass, M. Memmesheimer, H.J. Jakobs: Analysis of polluted air masses affecting the area of eastern Germany during a SANA episode. In: Air Pollution III, eds. A. Ebel, N. Moussiopoulos, Computational Mechanics Publications, Vol. 4, 95--102, 1995.
  • Hass, H.J.H. Builtjes, D. Simpson, R. Stern: Comparison of model results obtained with several European regional air quality models. Atmos. Environm., 31, 3259--3279, 1997.
  • Hass, H., E. Berge, P. Builtjes, A. Ebel, H.J. Jakobs, M. Memmesheimer, D. Simpson, R. Stern: A Comparison of Long--Range Transport Models applied for a European Summer Episode. In: Proc. of the EUROTRAC Symprosium `94, eds. P.M. Borrell et al., Academic Publishing, SPB, p. 857, 1994.

 

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