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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

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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 (Fig9.2.1-51).

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.

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