Fig. 1: Distribution of surface classes at model grid resolution
(5 km). A Mesoscale Atmospheric Model Combining Meteorology, Chemistry, Biology, and Heterogeneity
D. Hinneburg, N. Mölders
(Wiss. Mitt. Inst. f. Meteor. Univ. Leipzig u. Inst. f. Troposphärenforschung e.V. Leipzig, Bd. 12, 44-58, 1999)
Abstract
A mesoscale non-hydrostatic atmospheric model was extended by including both a chemical transport module (CTM) for the chemical triade NO, NO2, and O3, and an explicit surface-subgrid module (ESSM) for a subscale resolution of the topographical surface.
CTM: The simulated time-dependent concentration fields result from the following processes involved: anthropogenic emission at different heights, biogenic emission, dry deposition on the receptive surface, chemical reactions, turbulent diffusion, and passive transport according to the model dynamics. The calculations in the lowest model layer, usually treated as a constant-flux layer, are now performed on a vertical subgrid that was inserted to better resolve the often observed high concentration gradients within the surface layer.
ESSM: Moreover, an equidistant horizontal-subgrid is introduced for finer resolving the topography. The surface fluxes of momentum, sensible and latent heat, long-wave radiation, soil heat flux and wetness as well as the surface-energy balance are calculated in the usual approximations, however, employing the individual surface and soil properties of the subgrid cells. The averaged subgrid quantities serve as boundary values required for the model-grid calculations. Within the CTM the ESSM method leads to an intersection of the horizontal ESSM subgrid and the vertical CTM subgrid.
Preliminary results representing an interim realization state of the ESSM demonstrate partially strong changes of the dry deposition rates caused by subgrid-resolved surface properties.
Zusammenfassung
Ein mesoskaliges nicht-hydrostatisches Atmosphärenmodell ist um ein Chemie-Transport-Modul (CTM) zur Berücksichtigung der Triaden-Komponenten NO, NO2 und O3 sowie um ein Verfahren zur verfeinerten Auflösung der topographischen Unterlage (explicit surface-subgrid modul ESSM) erweitert worden.
CTM: Die simulierten zeitabhängigen Konzentrationsfelder sind das Resultat folgender modellierter Prozesse: Anthropogene Emission in verschiedenen Höhenschichten, biogene Emission, trockene Deposition (Rezeption), die speziellen chemischen Umwandlungen, turbulente Diffusion und passiver Transport. Da der Schwerpunkt der Prozesse und die höchsten Konzentrationsgradienten innerhalb der bodennahen ersten Modellschicht vorliegen, werden die Berechnungen in dieser Schicht auf einem verfeinerten vertikalen Untergitter durchgeführt.
ESSM: Unabhängig von den Eigenheiten des CTM wird für alle untergrundbezogenen meteorologischen Größen ein regelmäßiges horizontales Untergitter zwecks Berücksichtigung des subskalig aufgelösten topographischen Untergrundes eingeführt. Auf diesem Untergitter werden in den bisherigen Näherungen alle Oberflächenflüsse für Impuls, fühlbare und latente Wärme, langwellige Strahlung, der Bodenwärmefluß, die Bodenfeuchte sowie die Energiebilanz am Boden berechnet. Die über die Untergitterzellen gemittelten Werte dienen den weiteren Berechnungen im normalen Modellgitter als die erforderlichen Randwerte. Innerhalb des CTM führt die ESSM-Methode zu einer Überlagerung des vertikalen CTM-Untergitters mit dem horizontalen Untergitter des ESSM.
Erste Simulationsergebnisse, die dem derzeitigen Stand in der Realisierung des ESSM entsprechen, erbringen teilweise stark veränderte Depositionsraten infolge der Berücksichtigung der horizontal feiner aufgelösten Topographie.
1. Introduction
The gap between the spatial resolution of model results desired on the one side, and the limited capacities of customary computers on the other side, is permanently open for each modeller, especially in chemistry transport modelling. However, there are questions which by all means require some special effort to force up the effective model resolution. One member of this group is represented by the emission-deposition-chemistry simulations, which are the subject just of this paper.
The processes mentioned are entangled in the turbulent and immanent peculiarities of the local surface type. Indeed, the biogenic and also the anthropogenic emissions of trace gases arise from the narrow surface layer, and the dry deposition is decisively controlled by the foliage receptivity. Consequently, the horizontal variation of the relevant processes and quantities follows the real surface heterogeneity. Even in the vertical direction the fluxes of the trace gases do not agree with the constant-flux approach due to the sources and sinks by emissions and chemical reactions (e.g., Kramm, 1989; Spindler et al., 1996).
To meet the requirements for a higher grid resolution, several techniques have been utilized by different authors. Model nesting as the most expensive procedure employs the fine grid of the innermost model of a hierarchy of interacting models with increasing mesh size and extent of the respective model areas (e.g., Bigalke, 1992; Jacobs et al., 1995). The nesting method in general establishes an excess of grid points at sites, where it would be dispensable. Multi-scale modelling represents a second method, which also uses a grid hierarchy, however, in the form of a monolithic model (e.g., Kumar and Russel, 1996). Here, the possible splitting of processes onto the different grids proves to be advantageous.
A much more efficient, but rather radical way is to confine a subgrid to the lowest model layer and to apply it exclusively to the vertical fluxes. The method (Seth et al., 1994; Mölders et al., 1996) which is persued in detail in chapter 2, presumes at the first calculation height minimal deviation (a) from horizontal homogeneity between the subgrid cells and (b) from the vertical local equilibrium in the subgrid cells. Thus, the local vertical fluxes of the subgrid cells should form an averaged flux for the grid cell just at that height (middle of the lowest model layer). The main advantage of this economical method originates from the very high resolution of the complete model surface and from the sparse resolution in higher regions.
The model basis for the present work is given by the mesoscale non-hydrostatic atmospheric model GESIMA (Kapitza and Eppel, 1992; Eppel et al., 1995). This model (see chapter 2.1) was extended by a proper chemical transport module (chapter 2.2) and by the explicit surface-subgrid method (chapter 2.3). In the chemical transport module, an intersection between the immanent vertical subgrid and the explicit horizontal subgrid occurs for the calculation of the trace gas concentrations and fluxes (chapter 2.4). The actual degree of the partial realization of this intersection, nevertheless, allowed the accomplishment of simulations with and without inclusion of subgrid treatment. The comparison of the results gives signs of striking subscale-effects as to the deposition rates spatially averaged on the subgrid scale. Moreover, in future, the intended consequent realization of the grid intersection will enable an explicit spatial disaggregation of the deposition results on the subgrid resolution.
The underlying model region has an extension of 100 km x 70 km and is located with its north boundary line between the southeastern suburbs of Berlin and the town Frankfurt/Oder. Figures 1 and 2 show the distribution of land use classes with resolutions of 5 km x 5 km (grid) and 1 km x 1 km (subgrid), respectively. The data serve as direct input for the simulations on the corresponding scale. It is obvious from the fine-structures of Fig. 2, that subgrid treatment would achieve higher validity than standard-grid simulation.
2. Model Description
2.1. Basic Model
The mesoscale non-hydrostatic atmospheric model GESIMA (Kapitza and Eppel, 1992; Eppel et al., 1995) has been applied to a lot of meteorological problems preferably on scales of 5 km to 1 km mesh size (e.g., Mengelkamp, 1991; Rudolph and Gayer, 1995; Mölders and Raabe, 1996; Hinneburg and Tetzlaff, 1996; Hinneburg et al., 1997). In case of a model region of 250 km x 250 km, for instance, the model grid can not account for a resolution much finer than 5 km. Thus, the model formally calls for an extension yielding a finer resolution of the surface without changing the overall grid spacing. In the following, only those model features are to be shortly described that are relevant for the subject in question and that remain unchanged during the actual modifications.
In the near-surface layer (first model layer), the vertical fluxes of momentum, sensible and latent heat and of several passive admixtures (e.g., cloud particles) are regarded in the constant-flux approach by referencing to the corresponding quantities calculated at the middle of the layer (belonging to the internal boundary layer). The sensible heat within the soil is simulated semi-implicitly by solving the diffusion equation similarly to the turbulent atmospheric diffusion (see Eppel et al., 1995), whereas soil wetness is calculated by applying the force-restore method with regard to the evaporative conductivity of the vegetation-canopy layer. Radiation transfer is accounted for by the two-stream approximation. The soil surface temperature is determined by balancing the specified energy fluxes.
The land use characteristics and the respective surface parameters as well as the terrain elevations and slopes are assumed to be homogeneous within a grid cell. Horizontal processes such as advection and turbulent diffusion are applied to the atmospheric quantities beginning from (the middle of) the first model layer. A terrain-following coordinate system with a non-equidistant vertical grid is used to discretize the variables involved in the anelastic dynamic and passive transport equations.
The application of the atmospheric model requires a pre-run of the 1-dimensional model version in order to provide the mean (and initial) vertical profiles of the meteorological quantities. The pre-run is carried out for fixed, completely homogeneous surface conditions met as the regional average or at the inflow side.
2.2. Chemical Transport Module (CTM)
The chemical transport module (preliminary studies by Haenel, 1997) inserted in the atmospheric model dynamics considers the concentrations and fluxes of the trace gases NO, NO2, and O3 and the corresponding reactions within this triade (Kramm et al., 1996). As argued in chapter 1, an additional vertical subgrid (not to confuse with the horizontal explicit surface-subgrid method of chapter 2.3) beneath the first calculation (reference) height of the common model grid was implied. The concentration values at this reference level belong to both the grid and the subgrid (see point e).
The numerical calculations on the vertical subgrid replace the assumption of a constant flux usually made in the surface layer of mesoscale atmospheric models (see chapter 1). The individual chemical and atmospheric processes taken into account are described in the following:
a) Anthropogenic emission:
Actual input data of anthropogenic emission of NO and NO2 for the model region and date of interest are available as plain sources (1 km2) from Wickert et al. (1997). Depending on the source intensity q its value is partitioned here a posteriory to three types of emittents:
q < 0.02 t km-2 h-1 : emissions from traffic
q < 0.10 t km-2 h-1 : emissions from traffic and heating (households, normal industry)
q > 0.10 t km-2 h-1 : emissions from traffic, heating, and power stationsThe emission types are vertically located at and distributed over different (optionable) model layers to get the resultant emission density rates, which enter into the simulations as volume sources. The values are equally splitted between NO and NO2.
b) Biogenic emission:
The biogenic NO emission flux, Fb, is modelled in dependence on the type of vegetation and the surface temperature Ts (Williams et al., 1987; see parameters therein):
Fb(NO) = f0 exp(f1 Ts-f2) (1)
No biogenic emissions of NO2 and O3 are assumed. The so-called compensation values (boundary condition at the surface) of the gaseous concentrations are settled by the biogenic flux (see point e).
c) Dry deposition:
The dry deposition is modelled in accordance to the frequently used flux-resistance concept (e.g., Ganzeveld and Lelieveld, 1995). Consequently, the deposition flux, Fd (negative defined downward), is the ratio of the local concentration c at the lowest calculation height and the total resistance R over the concerning distance of mass transfer:
Fd = - c(z1sub) / R (2)
Due to the additional vertical subgrid in the first model layer, the concentration value refers to the lowest subgrid height, z1sub, which is chosen as to lie deep within the molecular-turbulent sublayer. With this in mind and the approximations applied (see, however, Kramm et al., 1995), the integral reciproke atmospheric diffusivity over the remaining distance down to the receptor surface is neglected here. Therefore, the total resistance for dry deposition from the first subgrid level consists only of the canopy resistance for the recepting surface.
The big-leaf concept (e.g., Erisman et al., 1994) leads to an expression for the bulk resistance of the (vegetation) receptor surface, which is composed of the bulk cuticular, stomatal, and soil resistance:
R-1 = Rcut-1 + Rstom-1 + Rsoil-1, (3)
where Rcut = 104 sm-1 and Rsoil = 103 sm-1. The stomatal resistance Rstom is taken as the reciprocal of the evaporative conductivity which is calculated in the basic surface routine of the model and depends on vegetation type, solar radiation, temperature, humidity, and soil wetness.
d) Ozone formation and destruction:
The photodissociation of NO2 by sunlight leads to the formation of ozone:
NO2 + hv + O2 => NO + O3 (4)
The process forms a sink for the NO2 concentration and a source for the NO and O3 concentrations. The reaction constant is proportional to the short-wave radiation intensity (see references in Kramm et al., 1996). The destruction of ozone in the presence of NO is caused by a reverse oxidation process:
NO + O3 => NO2 + O2 , (5)
where the reaction constant depends on air temperature and density (see references in Kramm et al., 1996).
The net changes of the concentrations due to the reactions are accounted for in the subgrid as well as in the grid calculations.
e) Turbulent vertical diffusion:
The turbulent vertical diffusion is calculated semi-implicitly both in the vertical subgrid and in the grid by applying proper diffusion coefficients and concentration gradients (see Haenel, 1997; Eppel et al., 1995). The upper boundary for the subgrid-diffusion calculation and the lower boundary for the grid-diffusion calculation are matched so as to strongly couple both systems (see below).
The lower boundary condition for the concentration in the calculations on the subgrid (compensation value, c(0)) is determined by the biogenic emission rate following the flux-resistance concept (compare points b and c):
c(0) = Fb R (6)
At a balanced situation between the concurrent fluxes of biogenic emission and dry deposition through a given surface, the net flux
Fd + Fb = - [c(z1sub)-c(0)] / R (7)
would vanish and also the gradient between the first (lowest) concentration value, c(z1sub), and the compensation value, c(0), as it should be. Obviously, biogenic emission immediately leads to positive compensation (boundary) values c(0), however, deposition is existing even when the reference concentration would be smaller than c(0) and the effective flux would be directed upwards.
The upper boundary for the subgrid-diffusion calculation is fixed by the concentration value c(z1) at the first grid-reference level, which is identical with the upper end-point of the vertical subgrid (grid-to-subgrid coupling).
The lower boundary for the grid-diffusion calculation represents the reverse coupling between the grid systems (subgrid-to-grid coupling) carried out every time step. The flux calculated and located at the highest subgrid level beneath the first reference level serves as the boundary condition and removes the surface flux of the customary constant-flux approach (see chapter 2.1).
The upper boundary for the grid-diffusion (at the model top) underlies the usual optional rules (vanishing flux, or constant flux, etc.).
f) Passive transport and horizontal turbulent diffusion:
The passive transport (horizontal and vertical advection) and the horizontal component of the turbulent diffusion are involved only in the normal grid simulations, effecting only indirectly the subgrid calculations through the upper boundary condition. Within the vertical subgrid range (i.e., at the half of the first model layer) these processes are assumed to be strongly dominated by the local properties of the surface (local equilibrium) and thus can be neglected.
2.3. Explicit Surface-Subgrid Method (ESSM)
The explicit surface-subgrid method originally introduced by Seth et al. (1994), has already been applied to the atmospheric model GESIMA in a study by Mölders et al. (1996). In the present paper, an elaborated version of this method (Mölders, 1998) was adapted to the actual model version in a very similar fashion and with special regard to the processes involved here (see chapter 2.2).
The method employs the standard model physics of the surface processes, however, on a horizontal subgrid, which is embedded into the standard model grid. All surface parameters, boundary conditions and other relevant properties concerning the surface and the soil, are referred to the subdivided topography. The submodel substitutes the existing surface-flux relations by calculating all fluxes and relevant quantities on the individual subcells. Especially, the energy balances for the determination of the surface temperatures are solved on the fine grid. The corresponding subgrid-resolved variables are stored for each time step.
The conditions of the parameterizations of the surface fluxes as utilized in the standard model should be valid also for the smaller subgrid-cell extent. Homogeneity of the surface properties and dominance of the vertical over the horizontal fluxes as well as horizontal independence of the subgrid cells are assumed. Nevertheless, the explicit subgrid method does not only insert a subgrid for the surface and for the soil layers, but also permits subcell-discrimination of the reference values on the first vertical calculation (grid)level (Mölders, 1998), i.e., for the whole model surface layer (see below).
In the present model, the lowest reference values of air temperature and humidity are heterogenized within each grid cell with respect to the subgrid values of the surface temperature and soil wetness, respectively (see Seth et al., 1994; Mölders, 1998). The reference values of the other meteorological quantities for the surface flux calculations remain unchanged as mean grid values (e.g., wind speed, particle concentrations). In this manner, the coupling between the grid and the subgrid variables is performed down-directed. The reverse bound is sustained by means of subgrid-averaged fluxes acting as the surface fluxes for the atmospheric simulations in the standard grid resolution. This mutual exchange of reference values and fluxes is performed at each time step of the simulations.
The explicit surface-subgrid procedure described above can be reduced in some qualitative details to meet the method of the rather similar mosaic approach (e.g., Mölders and Raabe, 1996) developed by Avissar and Pielke (1989). The method is distinguished by splitting the grid cells according to surface-classifying instead of spatial aspects. The effective differences of the formalisms were investigated by Mölders et al. (1996). Another (simpler) method of including subscale heterogeneity is achieved by surface-parameter averaging which, however, represents a more crude techniques (see Tetzlaff and Mölders, 1997).
All the methods mentioned above are realized as optional variants in the model presented. Moreover, the application of the customary dominance principle onto a high-resolved surface topography to obtain grid-resolved surface classes is also accounted for in the model options. In dependence on the special subgrid or non-subgrid treatment desired, the input topography has to be provided at the corresponding resolution. In contrast to the land use types, the orographic elevations of the subgrid cells are of no significance in the context under consideration.
2.4. CTM-ESSM Intersection
On the one side the chemical transport module (CTM) performs the near-surface simulations for the gaseous components on a vertical subgrid (compare chapter 2.2). The explicit surface-subgrid method (ESSM), on the other side, treats all quantities including the chemical ones with respect to their horizontal subscale distribution within the same range. Thus, an intersection of both the vertical and the horizontal subgrid systems is required for the simulation of trace gas concentrations and fluxes.
The conditions of validity as well as the evidence of the results of the interacting procedures take no incompatible features and pretensions. Consequently, the surface-layer part of the chemical transport module is qualified to be embedded as a whole in the explicit surface-subgrid procedure. The vertical 1-dimensional simulations in this sublayer are to be performed in each subgrid cell considering the processes described in subsections a - e of chapter 2.2, followed by averaging the corresponding fluxes for the boundary conditions of the standard-grid atmospheric simulation. The ESSM method inevitably entails, that the emissions and concentrations, though separately treated about the vertical surface-layer subgrid within each horizontal-subgrid cell, have to adjust to form a mean value on the first reference level of the common model grid (compare the beginning of chapter 2.2).
The increase of the number of variables and calculations does not only concern the 3-dimensional concentration fields of the chemical species considered, but also the 3-dimensional fields of the anthropogenic emission density rates and the 2-dimensional flux fields of the biogenic emissions and the dry deposition. Nevertheless, the combined subdivision into all directions is restricted to the undermost model layer and, in contrast to other subgrid methods, the remaining model layers stay unaffected.
The recent model status represents an interim realization of the explicit surface-subgrid method concerning the chemical transport module. Up to now, only the biogenic emission (point b of chapter 2.2) and the transport resistances for the process of dry deposition (point c) have been expressed in the subgrid resolution. All other processes and all concentration values are not yet included in the (horizontal) subgrid treatment. However, the simulations performed are able to show the mean impact of the subscale structures transmitted by all dynamic, thermal, radiative, and trace-gas recipient properties of the surface on the mean grid-values of dry deposition.
3. Results
3.1. Meteorological and Emission Conditions
The NOx emission and deposition conditions are investigated for the 27th July 1994. The anthropogenic emission input data taken from Wickert et al. (1997) are available for every hour with a local resolution of 1 km2. Due to the preliminary restrictions made in the actual model version (see chapter 2.4), these emission rates are spatially averaged to fit the model grid which was chosen as the 5 km x 5 km grid system (Fig.1). The anthropogenic emission density rates averaged over their vertical extent (compare point a in chapter 2.2) are shown in Fig. 3 for the indicated disposal time of the deposition results (chapter 3.2).
It is obvious that the main contributions to the anthropogenic emissions (Fig. 3) originate from industrial point sources, urban traffic and heating, and motorways. At present, the model is not able to realize a finer resolution of the anthropogenic emission data and concentration values, however, the dynamic and thermal fluxes at the surface as well as the dry deposition and biogenic emission are explicitly calculated on the 1km-subgrid topography as shown in Fig. 2. The biogenic emission rates, which are not included in Fig. 3, are computed analytically in dependence on the surface properties (see point b in chapter 2.2).
The meteorological parameters needed to initialize the simulations were chosen in accordance to a situation with cloud-less high, small wind speed from north-east and moderate soil wetness. The 3-dimensional 24h-simulations were started at midnight. The background concentration profiles of all gaseous compounds are assumed to be negligible. Thus, during the simulations, the local emissions, the meteorological dynamics, and the local deposition conditions determine the dry deposition rates at the grid points.
3.2. Dry Deposition
The distribution of the dry NOx deposition rates on the 5km-grid is shown in Fig. 4 for 1400 local time. The results include the subscale effects in the way described above (chapters 2.4 and 3.1). Because of the minor importance of advective transport in the case discussed, high deposition rates appear at sites that are characterized coincidently by strong emissions (Fig. 3) and low deposition resistances (see vegetation areas in Fig. 2). Vegetation (especially, grassland and agriculture) exhibits high values of evaporative conductivity and, as a consequence, low deposition resistances for recepting the gaseous species. The varying subscale presence of these surface classes in the individual model grid cells should therefore give the general pattern for the distribution of the deposition rates.
To demonstrate that the role of subgrid (vegetation) structures is decisive for the amount of dry deposition, a relative heterogeneity measure dhet is defined for each grid cell (see also in this issue: Mölders and Tetzlaff, 1999). This measure quantifies the effective difference between the deposition rates calculated with (ESSM) and without (dominance principle) subgrid. The definition starts from equation (2) under the assumption of a homogeneous concentration distribution in the grid cells:
dhet = ( {Rsub-1}- R-1 ) / Rmin-1 , -1 < dhet < 1 (8)
In this formula, the first term (in braces) of the difference is the average of the reciprocal subgrid-cell resistances in a grid cell, the second term is the reciprocal resistance of the grid-cell resistance determined by the dominance principle, and the scaling quantity Rmin stands for the minimum resistance occuring in the set of surface classes. Considering the functional dependence on the surface classes under the special conditions of optimal dry deposition, the resistances in equation (8) can be reduced to the stomatal resistances, which approximately results in a linear dependence of the reciprocal resistances on the individual surface parameters of the maximum evaporative conductivity g (compare equation (3) and context). The quantity g varies from 0 for bare soil to 0.04 ms-1 for low vegetation (Eppel et al., 1995). The heterogeneity measure can now be expressed as
dhet = ( {gsub} - g ) / gmax , (9)
where the positive/negative maximum value appears, when large subscale areas of vegetation/ bare soil are completely ignored by the dominance principle used in standard-grid modelling for the surface characterization (the braces mean subgrid averaging).
The pattern of the heterogeneity quantity dhet is shown in Fig. 5 (using gmax = 0.01 ms-1 and cutting the values dhet > 1). The frame of zero values apparent in the outer region is a consequence of the subgrid homogeneity forced in the inner and outer boundary region. Indeed, a very similar pattern of distribution is found for the differences between the deposition rates simulated with and without explicit subgrid treatment (Fig. 6). The general agreement of the positive and negative zones in Figures 5 and 6 is a striking argument for the obliging adoption of subgrid methods by deposition models. The limited intensity scale of the differences illustrated in Fig. 6 is cutting some values, however, in some grid cells the analysed differences due to subscale surface structures amount up to 100 % of the deposition rates.
The time-integrated (24 h) and area-averaged (whole model region) deposition of NOx derived from the simulation results is shown in Table 1 for the various versions of subgrid treatment (see chapter 2.3):
Table 1: Total mean of the dry NOx deposition rates for the model region integrated over one day.
Method NO deposition(kg/km2d) NO2 deposition(kg/km2d)
Dominance principle 1.15 1.12
Parameter averaging 1.23 1.19
Mosaic approach 1.12 1.01
Explicit subgrid 1.04 1.03
Apart from the direct impact on the calculated deposition fluxes, the different methods have also indirect influence via the dynamic and thermal quantities. Thus, the total deposition values partially compensate the non-linear local deviations caused by these methods. Nevertheless, compared to the non-subgrid treatment (dominance principle) the explicit surface-subgrid method leads to total changes of the daily NOx deposition by about 10 %, whereas the other methods realize smaller effects. The proper calculation of deposition fluxes prevents the model from accumulating the flux deviations and, hence, from artificially charging/discharging the atmosphere by the gaseous compounds during the simulations. It should be mentioned in this context that the recent preliminary subgrid simulations assume full homogeneity of the gaseous concentrations within each grid cell and that the complete realization of the methods is still outstanding.
4. Conclusions
1.) The explicit surface-subgrid method in connection with the vertical fine-resolution of the surface layer inserted in the chemical transport module proves to be effective and much less expensive than the methods of model nesting or multi-scale modelling.
2.) The subgrid techniques, though here utilized on a rather preliminary level, leads to locally appreciable changes in the dry deposition rates depending on the subscale distribution of vegetation.
3.) It has to be expected that the described methods when realized completely in the chemical transport module may not only produce further changes on the mean deposition, but also will provide subscale-resolved results.
Acknowledgement
We would like to express our thanks to the BMBF for the financial support of the project ‘Development of modules for modelling of dry deposition in complex terrain with heterogeneous characteristics of the surface’ under the contract TFS LT2 D.2 within the framework of the National Troposphere Programme. The authors wish also to thank the group of R. Friedrich, IER Stuttgart, for providing the preliminary emission data, and A. Smiatek, IFU Garmisch-Partenkirchen, for providing the land use data.
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Authors’ Address:
D. Hinneburg, N. Mölders
LIM - Institut für Meteorologie, Universität Leipzig
Stephanstr. 3
D-04103 Leipzig
Fig. 1: Distribution of surface classes at model grid resolution
(5 km).
Fig. 2: Distribution of surface classes at subgrid resolution
(1 km).
Fig. 3: Anthropogenic NOx emission density rates
at 1400 LT.
Fig. 4: Dry NOx deposition rates at 1400 LT including
explicit subgrid effects.
Fig. 5: Heterogeneity measure of subscale vegetation according
to the definition by equation (9).
Fig.
6: Difference of NOx deposition rates at 1400 LT calculated
with and without subgrid contributions.