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• its age (the model facilitates slow, natural compression),
• melting (small amounts of snow on the ground tend to take too long to melt, even if the temperature of the overlying air is well above 0°C).
• interception (of rain)
• addition of new snow.

However, at present, there is no mechanism to deal with density variations in the vertical within the snowpack.  This has an impact on energy fluxes which in turn has potential to adversely affect the forecasts of 2m temperature.   For example, when new low density snow falls onto old dense snow, the atmosphere may be "re-insulated" from a ground heat source, allowing 2m temperatures to drop lower in reality than in the model.  In practice this particular problem will be exaggerated by temperature sensors ending up closer to the snow surface when snow has fallen (assuming they are not elevated manually).

Currently snow is modelled by a multi-layer snow scheme allowing more realistic heat transfer. 

The albedo is related to the extent (and age) of snow cover and snow characteristics in analysed and forecast fields have an effect on the radiation that could be absorbed.  This has a corresponding impact on forecasts of 2m and surface temperatures.    Better assessment of the albedo when the multi-layer snow scheme is introduced will allow faster response to changes in the radiative forcing.

Forecast temperatures can be in error by:

• as much as 10°C too warm (very occasionally even worse) where there is:
  
  • snow cover under anticyclonic conditions and light winds,
  • strong radiation under clear skies leading to a strengthening night-time surface inversion.

(Both the above scenarios are difficult to forecast, but Finland, Scandinavia and large areas of northern Europe are particularly prone to forecast temperatures being too warm).

The albedo is related to the extent (and age) of snow cover and snow characteristics in analysed and forecast fields have an effect on the radiation that could be absorbed.  This has a corresponding impact on forecasts of 2m and surface temperatures.    Better assessment of the albedo when the multi-layer snow scheme is introduced will allow faster response to changes in the radiative forcing.

Forecast temperatures can be in error by:

• as much as 10°C too warm (very occasionally even worse) where there is:
  
  • snow cover under anticyclonic conditions and light winds,
  • strong radiation under clear skies leading to a strengthening night-time surface inversion.

(Both the above scenarios are difficult to forecast, but Finland, Scandinavia and large areas of northern Europe are particularly prone to forecast temperatures being too warm).

• as much as 5°C or 10°C too low where there is:
  • spurious snow cover (i.e.
  as much as 5°C or 10°C too low where there is:
  • spurious snow cover (i.e. snow that should have melted).  

(This effect is particularly evident where the model retains a snow depth >10cm, the level at which the ground is assumed to be completely covered).

Currently snow is modelled by a multi-layer snow scheme allowing more realistic heat transfer.

(Note: Previous to June 2023, only a single layer snow model was available.  There was no mechanism to deal with density variations in the vertical within the snowpack.  This had an impact on energy fluxes which in turn had potential to adversely affect the forecasts of 2m temperature.   For example, when new low density snow falls onto old dense snow, the atmosphere might be "re-insulated" from a ground heat source, allowing 2m temperatures to drop lower in reality than in the model.  In practice this particular problem will be exaggerated by temperature sensors ending up closer to the snow surface when snow has fallen (assuming they are not elevated manually)).

Fig9.2.1.3: The snow depth in the vicinity of Murmansk is shown as a shade of green (5-10cm).   A snow depth of 10cm (actual snow depth, not water equivalent ) is the threshold for the IFS to assume the entire grid box fully snow covered (snow cover fraction = 1 ).  Thus a difference around this threshold value can change the tile partitioning and thus snow coverage may not be uniform or continuous over the grid box.  The snow-free tiles would have less insulation from the soil underneath so maintaining the average skin temperature to higher temperature compared to a fully snow-covered grid box.  This can potentially impact the 2-metre temperature computation.

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