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Note: HRES and Ensemble Control Forecast are scientifically, structurally and computationally identical.  With effect from Cy49r1, Ensemble Control Forecast output is equivalent to HRES output where shown in the diagrams.   At the time of the diagrams, HRES had resolution of 9km and ensemble members had a resolution of 18km.

2m Dew point and Humidity errors:

2m dew point temperature biases (verified over land) vary geographically, as well as with season and time of day with a daytime dry (low dew point) bias generally.   Large humidity errors can also occur (not always with the same sign as temperature or dew point errors).  Humidity errors often don’t depend strongly on the forecast values and range of temperature. 

Effects contributing to dew point temperature errors

Near surface dew points and humidity are related to a similar variety of processes to those for temperature:

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Some of the above processes in turn depend on land surface characteristics (vegetation, soil type, soil texture, etc.) and processes.  

Cloud Cover effects

Under clear-sky conditions there is generally little error during the day, but a moist bias in the evening.  In cloudy conditions the daytime the bias is dry and is in part related to the representation of turbulent mixing, in particular in cloudy convective cases.  Errors in the prediction of the temperature structure have a strong influence on forecast cloud layer(s) and on humidity forecasts, particularly in the lowest layers (Fig9.2.1.1-1 and Fig9.2.1.1-2).

Turbulent Mixing effects

Errors in near-surface dew point temperatures during winter conditions are very sensitive to the representation of turbulent mixing in stable boundary layers.  Comparison with radiosondes in the lower 200m of the atmosphere suggests underestimation of the temperature gradient and especially the humidity gradient (giving a dry bias).  This is particularly pronounced at lower latitudes.  Full resolution of the details of the temperature structure in the lowest layers of the atmosphere is not possible with current computational resources.

Too much mixing increases the upward diffusion of heat and moisture and hence reduces the temperature and dew point fall at 2m and at the surface.   Errors in wind profiles in the boundary layer, and in wind direction at the surface, are related to the representation of mixing in convective boundary layers, and in particular with the partition of momentum transport between dry and moist updrafts.

Vegetation, Soil moisture and Evaporation effects:

Errors in the representation of evaporation impact forecasts of near-surface humidity.  Leaf area index is a measure of vegetation coverage and determines the degree of evapotranspiration.  Higher values mean more evapotranspiration, and thus greater fluxes of moisture into the atmosphere.

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Evaporation over bare soil is also problematic.  Soil temperature and soil moisture is modelled in IFS but there are not a great deal of directly measured observations available.  However, 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.

Orography effects

IFS model orography smooths out valleys and mountain peaks, especially at lower resolutions.  A forecast 2m dew point 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.

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• more solar energy will be gained on south-facing (N Hem) slopes implying actual temperatures may be higher than forecast.  However upslope movement will increase humidity, possibly to saturation.
• less solar energy will be received on north-facing (N Hem) slopes implying actual temperatures may be lower than forecast, particularly where they are in shadow for much of the time.  Thus high humidity may persist in sheltered valleys.

Lake effects

Lake temperatures can have an effect on forecast of dew point temperatures, particularly in deciding whether the lake is frozen or not.  Proximity of a lake can have an influence on the humidity at a downwind location.

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• NE Scandinavia: mainly Finland, north Sweden.
• Russia: Mainly West of the River Yenisey, also River Lena valley, parts of NE Siberia.
• Canada: Mainly east of the Rockies and particularly: Labrador, Quebec, Ontario, Manitoba, Saskatchewan, Nunavut, Northwest Territories.
• Alaska: Low lying areas.
• Possibly some low lying parts of Southern Argentina.

Low Level Winds and Precipitation effects

Melting of snow, and evaporation of rain or snow, can cause local cooling that will be realised down to surface levels if winds are light or over relatively flat areas.  However, in areas that are not completely flat, any stronger winds will tend to combat this tendency, re-establishing a vertical lapse rate, via adiabatic warming or cooling during descent or ascent over topography, making low lying areas warmer than would have otherwise been the case. 

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Persistent or heavy rainfall can produce waterlogged soil or flooded areas which will increase the 2m dew point and humidity.

Analysis Problems

Occasionally lower tropospheric temperature data has been given low weight during the analysis process.  Usually this relates to problems with assimilating the boundary layer structure in situations with a strong inversion, coupled with the fact that the background is a long way from the truth.  The analysis procedures tend to give lower weight to observations that show major departures from the first guess and, particularly if there is little support from adjacent observations, such data can even be rejected completely.  In consequence, the analysed temperature structure of the boundary layer may only move a small way towards correcting errors in the background.  From a mathematical standpoint it is also (unfortunately!) more difficult to correctly assimilate data near the surface than data higher up (Fig9.2.1-1).

Miscellaneous

• If the predicted humidity is too low then maximum temperatures can be forecast to be too high (e.g. East England and Germany).
• Model 2m dew point and humidity output corresponds to short grass cover (possibly snow-covered), because by meteorological convention observations are ordinarily made over such a surface.  In complex terrain - e.g. forests with clearings - this strategy may not work so well.

Suggested considerations to offset dew point errors

The forecaster should assess the potential for error due to the above factors by:

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