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Temperature  errors (particularly in biases during spring and autumn) are in part related to the representation of vegetation (in terms of cover and seasonality), and evaporation over bare soil.  Heat flux from bare soil is also problematic.   Soil temperature and soil moisture is modelled in IFS but there is not a great deal of directly measured observations available.  However, the impact the impact of heat and moisture fluxes can be a significant contributor to 2m and surface temperature errors, and hence have an impact on humidity.

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IFS model orography smooths out valleys and mountain peaks, especially at lower resolutions.  A forecast 2m temperature may be unrepresentative if it has been calculated for an altitude significantly different from the true one.   A more representative height might be found at one of the nearby grid points.  Any remaining discrepancy can be overcome using Model Output Statistics (MOS) or statistical post-processing (see additional sources of information below).

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Derivation of 2m temperatures

Forecast temperatures on , including for Meteograms, are derived from interpolation between model forecasts of 10m and skin (surface) temperatures:

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Aerosol advected across a region can reduce incoming radiation.  Aerosol Optical Depth (AOD) measures the extinction of a ray of light as it passes through the atmosphere.  This can be due to advection of dust etc.  A very crude rule of thumb is that an anomaly (with respect to climatology) of 1 AOD unit corresponds to a 0.5-1.5 °C day-time temperature decrease under otherwise clear skies.  Cloud cover has a much stronger effect upon surface temperature   and mask any signal from the aerosols.  The radiative impact of the forecast aerosol value is more distinct for shorter lead-times (12 or 24 hours).  At longer lead times, the evolving differences in flow patterns and clouds may become more important for the surface temperature differences than the reduced solar radiation.  Section 2.1.5.7 gives more  More information on aerosols and greenhouse gases is given elsewhere in the guide. 

Fig9.2.1-5: Example of forecast error associated with passage of a zone of associated with saharan dust.

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• Forecast maximum 2m temperatures can be too low particularly during anomalously hot weather.
• If the predicted humidity is too low then maximum temperatures can be forecast to be too high.
• Post-processing (e.g. using a calibrated statistical technique) usually improves 2m temperature forecasts, sometimes substantially.
• Model 2m temperature output corresponds to short grass cover, because by meteorological convention observations are ordinarily made over such a surface.  This strategy may not work so well in:
  • complex terrain - e.g. forests with clearings.
  • over snow areas.  The algorithm which derives 2m temperature uses the model surface temperature while the snow surface is above the earth's surface.  This can be an important consideration where there is deep snow.  See section on snow effects.  

Diurnal Range of temperatures

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Evaporation over bare soil is also problematic.  Soil temperature and soil moisture is modelled in IFS but there is are not a great deal of directly measured observations available.  However, the the impact of heat and moisture fluxes can be a significant contributor to 2m and surface temperature errors, and hence have an impact on humidity.

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Soil moisture and temperature is modelled in four soil levels but there is a considerable lack of real-time observations of soil condition and moisture content.  Nevertheless heat and moisture fluxes have an impact on model surface and 2m temperature and moisture. 

The ensemble mean values of soil moisture slightly overestimate the diurnal cycle of soil temperature:

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