Page History

...

• cloud cover (from observations or satellite pictures) with cloud analyses or forecasts.
• cloud structure (from observed and background vertical profiles).

Fig9.2.1-1: The example illustrates how small errors in the extent and thickness of model forecast low cloud and fog can have large impact on forecast 2m temperatures.   Over Spain, 12UTC temperatures approached 12°C in areas where low cloud broke and cleared but remained cold where low cloud and fog persisted (subfreezing in some areas of freezing fog).  The model forecast low cloud to be variable in thickness and rather greater in extent than in reality.

...

The forecast vertical profiles show that the model was fairly good at representing temperature inversions.  However, the model locally missed clouds and fog by a small margins.  Such small errors had a large impact on surface temperatures.  The warm area in central northern Spain associated with high ground above the overnight inversion.

Image AddedImage Added

Fig9.2.1-2: Charts showing distribution of low cloud over Europe at 12UTC 26 Dec 2024.  Also shown are actual and forecast (T+12) vertical profiles for Essen and Muenchen and the errors between the forecast and observed 2m temperatures more generally.  The largest positive errors (reds and yellows, model T2m too high) are where the model has cleared the cloud too quickly and allowed incorrect insolation.   The negative  errors ((blues, model T2m too low) are where the model has maintained the cloud too and hindered insolation.  The cloud distribution is critical and users should anticipate likely deficiencies by monitoring available surface or satellite information. 

Snow cover effects

The analysis and forecast of snow depth, snow compaction, and snow cover are important for forecasting lower-layer and near-surface temperatures and they can have a significant impact on forecast accuracy.  However, the relationship between snow cover and temperature is complex:

...