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Fig2.1.4.4-3: Schematic representation of the multi-layer snow scheme for permanent snow (e.g. Greenland, Antarctica) and for glaciers. Snow depth is defined as ≥10m. Any additional snow accumulation is added into the fifth snow layer in order to preserve the characteristics and thermal flux qualities of thinner layers at the top of the snowpack.
| rsnow | Conductive resistance between exposed snow and atmosphere | |||
|---|---|---|---|---|
| rforest | Conductive resistance between forest snow and atmosphere | |||
| KS | Downward short wave radiation | Ti | Temperature of snow layer i | |
| LS | Downward long wave radiation | ρi | Density of snow layer i | |
| HS | Sensible heat flux | Si | Mass of frozen water in snow layer i | |
| ES | Latent heat flux | Wi | Mass of liquid water in snow layer i | |
| RS | Net (precipitation and evaporation) water flux at the surface | di | depth of I-layer in the snowpack | |
| aS | Albedo of exposed snow | Ki | Short wave radiation between snow layers I and I+1 | |
| aF | Albedo of forest snow | Gi | Conductive heat flux between snow layers I and I+1 | |
| Ri | Liquid water flux between snow layers I and I+1 | |||
| TSO | Temperature of uppermost soil layer | GB | Conductive heat flux at snow-soil surface | |
| WSO | Liquid water of uppermost soil layer | KB | Short wave radiation at snow-soil surface | |
| dSO | Depth of uppermost soil layer | RB | Liquid water flux at snow-soil surface | |
| rsoil | Conductive resistance between snow and soil |
Table2.1.4.4-1: List of symbols for parameters shown in Fig2.1.4.4-1, Fig2.1.4.4-2, Fig2.1.4.4-3.
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The snow depth in the model changes when fresh snow falls or when snow on the ground melts, evaporates or is compressed. The response in dry periods at different altitudes is shown in Fig2.1.4.4-8.
Fresh Fresh snowfall is added to the top layer, with a new snow density depending on air temperature and wind speed. Both convective and dynamic snowfall is considered to be homogenous over the grid box. Melted snow is removed from the top layer. The snow mass is then redistributed across the different layers but relatively shallow layers of snow are maintained at the top and at the base so that the atmosphere/snow and soil/snow heat fluxes can be best modelled.
Liquid water from rainfall onto snow or melting percolates downwards and can refreeze on a different level, releasing latent heat. If snow already exists on the ground then freezing rain and ice pellets are accounted for as rainfall that has frozen.
Snow depth water equivalent is the sum of frozen and liquid water within the snowpack. Snow density considers meltwater refreezing, so the density will vary but the snow water equivalent should not change.
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- Total snow cover is assumed where snow depth is diagnosed as >10cm. Only snow or forest snow "tiles" are used by HTESSEL.
- Partial snow cover is assumed where snow depth is diagnosed as <10cm. A snow water equivalent of 6cm is considered to be associated with 60% snow cover (Fig2.1.4.4-6). Other "tiles" which describe the location are used by HTESSEL in addition to the snow or forest snow "tiles".
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Snow is not intercepted by a tree canopy and will accumulate on the ground
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. Snow does not accumulate on sea ice or lake ice.
The albedo of snow in forested areas is given by a look-up table depending on (high) vegetation type (Table 2.1.4.4-1). The albedo of exposed snow decays with time between 0.85 for fresh white snow to 0.5 for . It is reset to 0.85 after large snowfall events.
Table2.1.4.4-1:Mean values of Northern Hemisphere five-year (2000-2004) broad band surface albedo (in the presence of snow) aggregated by high vegetation type.
Data assimilation for snow on the ground
Snow cover, snow Snow cover, snow depth and snow compaction affect all IFS atmospheric forecast models. It is important the IFS monitors actual values and updates the background fields accordingly. Any discrepancy will cause errors in the forecast as several physical properties of snow influence:
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Snowfields are initialized every day at 00UTC from continuous offline data.
Snow data assimilation at ECMWF relies on:
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Incorrect analyses and forecasts of snow are possible:
- in data sparse areas and the representativeness of observations.
- after a prolonged period without observations.
- at altitudes above 1500m.
- near glaciers. Glaciers are considered as very deep snow rather than ice - this can cause nearby correct observations to be rejected.
- at some high-latitude grid points in the model it is common for snow depth to be extremely high and may not be assimilated.
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