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It consists of a chain of models which may be grouped into two main sub-systems:
- the Local Scale Pre-Processor for Atmospheric Dispersion: LSPAD,
- the Risø Meso-scale Puff dispersion model: RIMPUFF.
LSPAD reads on-line meteorological data or numerical weather prediction data for "now-cast" or "fore-cast" simulations, interpolates/extrapolates this data onto the points of the calculation grid covering the area of interest, and calculates the fields of derived parameters needed by RIMPUFF.
RIMPUFF reads the source data and the data fields of LSPAD, and performs the calculations of dispersion, deposition, and, for radioactive isotopes, gamma-doses. It handles a high number of different materials released simultaneously (e.g. different radioactive isotopes). In case of radioactive isotopes the decay chains are accounted for.
The Local Scale Model Chain is presently implemented in two real-time online decision support systems for nuclear emergencies: the European system RODOS [8] [12], and the Danish system Argos-NT [5].
On-line meteorological input data
Real-time application of the model chain requires an on-line connection to real-time measurements of local meteorological quantities (wind speed and direction, temperature, temperature gradient, and rain intensity), or to up to date numerical weather prediction (NWP) data. With the latter a dispersion forecast can be made. Data must be available for at least one met-tower or one NWP-point in the vicinity of the release point (on-site). For application of the system on distances beyond the local (10-20) km scale, on-line meteorological measurements from within the regional (100 km) scale or a larger number of NWP points can be used. Concerning numerical weather prediction data, LSMC is set up to operate on data extracted from the Danish Meteorological Institutes high resolution limited area model DMI-HIRLAM [13].
The Local Scale Pre-Processor for Atmospheric Dispersion (LSPAD)
In addition to the standard meteorological parameters like wind and temperature, also dispersion controlling scaling parameters such as stability category, mixing height, and friction velocity and Monin-Obukhov length, are needed by the dispersion program RIMPUFF.
LSPAD provides these data, by interpolation and extrapolation of the "raw" meteorological data to the calculation grid followed by the calculation of the derived parameters at every grid point. The wind speed "interpolation" is made using the departments LINCOM flow model suite, which provides a much more consistent and surface reflecting flow field than any interpolation scheme can do. The stability parameter determination is based on models from the literature.
Linearized wind flow model family: LINCOM
Detailed modelling of the wind and turbulence fields on the local scale is important for prediction of the trajectory-directions and the time of arrival of radioactive clouds traversing hilly terrain and heterogeneous surfaces (e.g. over land-water-land interfaces).
LINCOM is a fast diagnostic flow model, which is based on the solution of the continuity and a set of linearized momentum equations, using a first order spectral turbulent diffusion closure. The wind and turbulence fields are modelled under influence of: 1) the local topography (hills), 2) the surface aerodynamic roughness (z0), and 3) the vertical thermal stratification of the atmosphere (to be implemented in LSMC).
The linearized LINCOM-concept for neutral stratified, pressure-gradient driven winds over hilly terrain was first conceived in [17]. In the LINCOM-T version, LINCOM is extended in concept to include effects of thermally driven flows such as valley breeze and nocturnal drainage flows [10], and in the LINCOM-z0 version it has been extended to model the effects of local changes in the surface aerodynamic roughness [1][2]. In addition to changes in the mean wind introduced by the variation in the surface roughness, the "z0" version also models the local turbulence levels, i.e. the surface shear stress field (U*), over the local scale grid.
Figure 1: Northern Zealand - Denmark on a 0.5 km * 0.5 km grid. left: Roughness distribution (z0); mid: LINCOM-z0 mean wind field (U); right: LINCOM-z0 generated turbulence wind field (U*).
Linearization of the momentum equations is possible and reasonable due to the fact, that LINCOM solves for velocity perturbations caused by the mentioned factors of influence, perturbations to an otherwise even flow over a flat terrain with even roughness. The final flow solution is the sum of this even "background flow" and the perturbations.
Pasquill-Gifford, similarity and mixing height
The stability parameters are calculated at every grid point from the velocity determined for that point combined with the temperature gradient found at the "nearest" measurement station or numerical weather prediction point. Due to the large discrepancies between temperature gradients over land and over water, a land grid point looks for the nearest land based met-station or NWP point, and a water grid point for nearest water based information.
The Pasquill-Gifford stability category is determined in accordance with IAEA Safety Series, 1982 [6], the friction velocity and Monin-Obukhov length are calculated following the model of van Ulden and Holtslag, 1985 [18], and the mixing height is taken as the maximum of the mechanical mixing height according to the model of Nieuwstadt, 1980 [11], and either the convective mixing height from the model of Batchvarova and Gryning, 1991 [3], or that of the HIRLAM NPW data where it by Sørensen et al. 1996 [14], is determined from a critical bulk Richardson number.
The puff dispersion model RIMPUFF
The local scale puff diffusion model RIMPUFF [15] provides a detailed real-time simulation of the atmospheric dispersion phenomenon and accounts for local changes in meteorological conditions in both time and space. It is based on Lagrangian tracking of a number of evolving puffs, a puff being an instantaneously released fixed amount of isotopes, the concentration profile of which is approximated with a Gaussian profile. RIMPUFF is provided with puff-splitting features such as "pentafurcation" (horizontal split of a puff into five minor puffs) and "trifurcation" (vertical split of a puff into three minor puffs) for improved modelling of dispersion over complex terrain involving channelling, slope winds, and effects of an inversion layer. RIMPUFF also includes a gamma dose integration module [16].
The puff advection and growth calculation uses typically time steps of the order of 10 seconds and is based on the local wind and turbulence fields provided by LSPAD once every meteorological time step, typically every 10 minutes.
All diffusion and deposition parameterization in RIMPUFF is formula-based. For the horizontal and vertical dispersion parameters sy and sz (horizontal and vertical standard deviations for the corresponding Gaussian profiles) it includes three parameterization schemes:
- Karlsruhe-Jülich height and distance from source dependent 1-hour averaged plume sigma's.
- Risø instantaneous (no averaging) instant puff-diffusion sigma's.
- Similarity-theory based plume-sigma's - averaging time 10 minutes to 1 hour.
Deposition of airborne material is also modeled with RIMPUFF using the source depletion model. The dry deposition model accounts for different deposition of different chemical forms of the dispersed material, e.g. iodine vapor (elementary iodide) and iodine aerosols. Deposition velocities can further be specified to depend on land use. Figure 2 shows a RIMPUFF calculated footprint of deposited radioactivity from a 137Cs plume traversing Northern Zealand. During the plume passage, the deposition rate varies depending on the local surface characteristics (land, water, forest, urban, etc.) [4].
Figure 2: Footprint of a depositing 137Cs plume over Northern Zealand as calculated by RIMPUFF. The deposition rates vary locally according to land use
The atmospheric turbulent transport velocity can under certain conditions limit the effective dry deposition velocities for aerosol particulate [7]. RIMPUFF also takes this turbulence-limited deposition velocity into account.
A new feature called "shear rise" has been introduced in RIMPUFF based on experience obtained during operational tests of the system. As the vertical size sz of the puff (standard deviation of Gaussian profile) at some distance downwind from the source has grown to a value larger than the initial release height, the "shear rise" feature causes the mean puff height to increase with the puff size. As the wind speed and direction at the puff centre determines its path, the shear rise option provides one method to account for the effect of vertical wind shear.
For cases of strong vertical directional wind shear, a more particle look-alike modeling of dispersion can be achieved in RIMPUFF by vertically splitting the puffs into three minor puffs at different heights. This method is called "Trifurcation". It is triggered by a wind shear larger than a precept level. The trifurcation obeys the following requirements:
- The amount of each isotope remains unchanged.
- The concentration of the isotopes at the centre position of the original puff remains unchanged.
- In a vertical plane and taken about the centre position of the original puff, the second moment of the concentration distribution remains unchanged.
- The sizes of the three new puffs all equal one-half the size of the original puff.
The main idea behind introducing trifurcation is that once a puff is trifurcated, the two new satellite puffs can set off in individual directions following the wind at their different centre heights. Information about the vertical directional wind shear is contained in the LSPAD calculated wind fields, which are determined at two or more heights.
An example of the effect of vertical directional shear on dispersion footprint is shown in Fig.3. The consequence for emergency response strategy may be dramatic!
Figure 3: Plume dispersion during strong vertical wind direction shear, with (solid) and without (dotted) the combined shear rise and trifurcation feature.
Rimpuff can be used for calculation of doses. These calculations could either be simple inhalation doses (time integrated concentrations) or radiation doses (gamma doses from puffs and from deposited radioactivity). The gamma doses from puffs are calculated using the finite cloud model [16].
References
[1] Astrup P., N.O. Jensen and T. Mikkelsen (1996): Surface Roughness Model for LINCOM. Risø report Risø-R-900(EN), ISBN 87-550-2187-5, ISSN 0106-2840; 30 pp. Available on request from: Information Service Department, Risø National Laboratory, e-mail: risoe@risoe.dk
[2] Astrup P., N.O. Jensen and T. Mikkelsen (1997): A fast model for mean and turbulent winds characteristics over terrain with mixed surface roughness. Radiat. Prot. Dosim. (1997) Vol. 73 p. 257-260
[3] Batchvarova E. and S.-E. Gryning (1991): Applied Model for the Growth of the Daytime Mixed Layer. Boundary-Layer Meteorology. Vol 56, pp. 261--274.
[4] Hasager, C.B. and S. Thykier-Nielsen, (1999): IRS-1C LISS III Land Cover Maps used in Real-time Pollution Deposition Modelling. Remote Sensing of Environment. To be published.
[5] Hoe S., H. Müller, and S. Thykier-Nielsen (2000): Integration of dispersion and radio ecological modelling in ARGOS NT. To appear in: Proceedings of IRPA 10, Tenth International Congress of the International Radiation Protection Association, Hiroshima, Japan, May 14 - 19, 2000.
6] International Atomic Energy Agency (1982): Safety series. No.57.
[7] Jensen, N.O. and P. Hummelshøj (1995): Derivation of canopy resistance for water vapour fluxes over a spruce forest, using a new technique for the viscous sublayer resistance. Agricultural and Forest Meteorology, Vol 73, pp 339-352.
[8] Kelly, G.N., J. Ehrhardt and V.M. Shershakov (1996): Decision support for off-site emergency preparedness in Europe. Radiation Protection Dosimetry. Vol 64, No. 1/2, pp 129-141. RODOS(GEN)-RP(96)03.
[9] Mikkelsen, T., S. Thykier-Nielsen, P. Astrup, and J.M. Santabarbara (1998): RIMPUFF: A prediction model for airborne spread of pathogenic diseases among animals. In: Houe, H. (ed.): Luftbåren smitteoverførsel. CEPROS seminar, Foulum (DK), 23 Oct 1998. Center for Produktions- og Sundhedsstyring i Husdyrbruget, Foulum. CEPROS-rapport nr. 1, 1998, 8 p.
[10] Moreno, J., A.M. Sempreviva, T. Mikkelsen, G. Lai and R. Kamada (1994). A spectral diagnostic model for wind flow simulation: extension to thermal forcing. In proceedings of the: Second International Conference on Air Pollution, 27-29 September 1994, Barcelona, Spain. Eds. J.M. Baldasano, C.A. Brebbia, H. Power and P. Zanetti, Computational Mechanics Publications, Southhamton, U.K., Vol II, pp 51-58.
[11] Nieuwstadt, F.T.M. (1981): The Steady-State Height and Resistance Laws of the Nocturnal Boundary Layer: Theory compared with Cabauw Observations. Boundary-Layer Meteorology. Vol 20, pp. 3-17.
[12] Rodos: www.rodos.fzk.de
[13] Sass, B.H. (1994): The DMI Operational HIRLAM Forecasting System, Version 2.3. Danish Meteorological Institute. DMI Techical Report 94-8.
[14] Sørensen J.H., A. Rasmussen and H. Svensmark (1996): Forecast of Atmospheric Boundary-Layer Height Utilised for ETEX Real-Time Dispersion Modelling. Physics and Chemistry of the Earth. Vol 21, pp. 435--439.
[15] Thykier-Nielsen S., S. Deme and T. Mikkelsen (1998): Description of Atmospheric Dispersion Model RIMPUFF; RODOS(WG2)-TN(98)2.
[16] Thykier-Nielsen, S., S. Deme, and E. Láng (1995). Calculation method for gamma-dose rates from Gaussian puffs. Risø-R-775-(EN).
[17] Troen, I. and de Baas, A.F. (1986): A spectral diagnostic model for wind flow simulation in complex terrain. In: Proceedings of the European Wind Energy Association Conference & Exhibition, pp.37-41, Rome, 1986.
[18] van Ulden, A.P. and A.A.M. Holtslag (1985): Estimation of Atmospheric Boundary Layer Parameters for Diffusion Applications. Journal of Climate and Applied Meteorology. Vol 24, pp. 1196-1207 |