# Section 2.1.4.1 Modelling land surfaces - HTESSEL

## Land surfaces

Within each grid box there are several different types of ground surface, each covering a proportion of the area surrounding a grid point (Fig2.1.4.1-1 and Fig2.1.4.1-2).  The ground types are described by a set of "tiles" for:

• bare soil.
• low vegetation (e.g. grass).
• high vegetation (e.g. trees).
• intercepted water at surface and foliage covered by water (e.g. rainfall intercepted by leaves).
• shaded snow or forest snow (e.g. snowy woodland, snow under high vegetation).
• exposed snow (snow on bare ground or low vegetation).
• lakes and coastal waters.

Up to six different "tiles" (ground types) may be used within a land grid box, each proportional to its coverage.  Each "tile" has its own properties, describing the heat, water and momentum exchanges with the atmosphere.   Each vegetation type for the 'tile' is assigned a height and is also characterised by a number of other (fixed) parameters.   These are used in calculating the surface fluxes, and hence a skin (surface) temperature, for each of the different “tiles .   Particular attention is paid to evaporation, as near-surface temperature and humidity are very closely related to this process.

The total energy fluxes for the whole grid box are derived from the proportional contributions of each "tile".  These depend on the type and relative area of low and high vegetation and the presence of snow and intercepted water.  If no snow or intercepted water, the fractional tile coverage of both high and low vegetation are defined by an offline dataset and the residual fraction is considered bare ground.

However, the areal extent of each land surface tile type can vary in a rapid, interactive way during the model run, as rain falls then evaporates, or snow accumulates then melts, etc.  The characteristics of the soil may also change (e.g. infiltration or runoff of rain, temperature structure of soil etc).  The slope and aspect of orography within each grid box (e.g. south-facing, steepness) is not taken into account and HTESSEL may consequently under- or over-estimate solar heating and runoff.

### Considerations

• The average ground type within a grid box is not necessarily representative of an individual location.  Land surface characteristics can be very variable within a grid box.  Users and forecasters should take into account the peculiarities of a location when interpreting model output.
• Currently there is no representation of an urban or city surface where extensive concrete and buildings are likely to have very different characteristics from tiles shown above, and possibly also provide a source of heat (the heat island effect) and even moisture (from air-conditioning units).
• The slope and aspect of orography within each grid box (e.g. south-facing, steepness) is not taken into account and HTESSEL may consequently under- or over-estimate solar heating and runoff.

 Vegetation type Assignedvegetationheight Assignedvegetationcoverage Vegetation type Assignedvegetationheight Assignedvegetationcoverage Evergreen needle leaf trees H 0.90 Bogs and marshes L 0.60 Deciduous needle leaf trees H 0.90 Water and land mixtures L 0.60 Evergreen broad leaf trees H 0.90 Deciduous broad leaf trees H 0.90 Tundra L 0.50 Mixed forest / woodland H 0.90 Semi-desert L 0.10 Interrupted forest H 0.90 Desert – – Irrigated crops L 0.90 Crops, mixed farming L 0.90 Short grass L 0.85 Tall grass L 0.70 Ice caps and glaciers – – Evergreen shrubs L 0.50 Inland  water – – Deciduous shrubs L 0.50 Ocean – –

Table 2.1.4.1-1: Assignment of height characteristic and vegetation coverage for each type of vegetation or surface.  In cases of snow, vegetation assigned as high (H) can have snow cover beneath; vegetation assigned as low (L) are considered as snow covered.  See "Modelling snow" section.  The assigned vegetation coverage gives information to the soil model regarding transpiration and root depth.  See "Modelling soil" section.   Albedo values are associated with the Leaf Area Index.

Fig2.1.4.1-1: An example of the variability of land surface within an approximate grid box illustrating the difficulty in assigning representative HTESSEL "tiles" for the whole grid square area.  The red lines show the extent of a very approximate 9km x 9km schematic HRES and ENS grid square.   The flag locates the grid point.  There is a large variation in ground surface type and the proportional contribution to the heat, moisture and momentum fluxes are difficult to assess.  For this grid box, high vegetation 'tile' covers about 5%, low vegetation 'tile' covers about 70%, estuary (lake) 'tile' covers about 20%, and the remaining area about 5% is considered a bare ground 'tile'.  There is no 'tile' for urban areas so these are considered as bare ground.  An ENS meteogram is interpolated from the four grid points surrounding a given station within the box.  See Section on Selection of grid points for Meteograms for details.

Fig2.1.4.1-2: An example of the variability of land surface within an approximate grid box illustrating the difficulty in assigning a representative HTESSEL "tiles" for the whole grid square area.  The red lines show the extent of a very approximate 9km x 9km schematic HRES and ENS grid square.  The flag locates the grid point.  There is some variation in ground surface type but it is predominantly covered by evergreen needle leaf trees.  The proportional contribution to the heat, moisture and momentum fluxes are rather simpler to assess.  In winter snow the appropriate tile would be forest snow.  Runoff would be rapid over Rocky Mountain sides, much slower over low-lying river valleys   For this grid box, high vegetation 'tile' covers about 75%, low vegetation 'tile' covers about 5%, lake 'tile' covers about 5%, and the remaining area about 15% is considered a bare ground 'tile'.  This consists of 5% rock area but 10% urban area which is also considered as bare ground.  An  ENS meteogram is interpolated from the four grid points surrounding a given station within the box.  See Section on Selection of grid points for Meteograms for details.

### Additional sources of information

(Note: In older material there may be references to issues that have subsequently been addressed)