For a specific location, the appropriate grid point data for meteograms or vertical profiles are selected in different ways. This can lead to inconsistencies in forecast surface temperatures.
Where the selected ensemble point is:
More details are given in the sections: Land-sea mask, Modelling land surfaces, Modelling coastal waters, Modelling lake and coastal waters, Modelling ocean surfaces, Selection of grid points for meteograms, Selection of grid points for vertical profiles.
Some influences of the adjacent sea areas or mountains may be over- or under-represented by the ensemble meteograms. This can significantly affect the forecast parameter on the meteogram (temperature, wind, etc). Users should assess differences in meteograms and vertical profiles for coastal, island or mountainous regions. In particular consider:
The differences in forecast temperature can be magnified at some coastal locations where sea and land energy fluxes are very different (e.g. Gulf of Bothnia, Arabian Gulf) or where there is complex coastal or mountainous geography. Even a marked contrast in land characteristics can have an effect.
Also the derivation of forecast 2m temperatures at each grid point depends in part on the modelling of the structure of the lowest layers below 10m (L137). This can be influenced by the stability or instability over the differing surfaces. In Fig9.9.4 below:
Other influences regarding forecast 2m temperatures also have an impact.
Fig9.9.1: Selection of grid points for meteograms. Consider the four ensemble grid points that surround a location of interest. If there is at least one land grid point within these four, then the nearest land point will be chosen regardless of distance. This means that meteograms at some coastal locations may not reflect the effects of the nearby sea. If only sea points are available then the nearest sea grid point will be chosen, even if the location lies over land, and may not reflect the effects of the land. Dots represent grid spacing of 9km. The colour scale represents the proportion of heat, moisture and momentum for each grid point derived by HTESSEL and Flake at 9km resolution.
Fig9.9.2: Selection of grid points for vertical profiles. Consider the four ensemble grid points that surround the location of interest. The nearest grid point will be chosen regardless of being land or sea grid point. This means that vertical profiles at some coastal locations may not reflect the effects of the nearby sea or may not reflect the effects of the land. Crosses represent grid spacing 0f 18km. The colour scale represents the proportion of heat, moisture and momentum for each grid point derived by HTESSEL and Flake at 9km resolution.
Fig9.9.3: Comparing the selection of grid points for meteograms and vertical profiles at various locations derived from Figs 9.9.1 and 9.9.2 above. There can be significant differences in near surface temperatures and can have consequences regarding destabilisation. Diurnal temperature ranges shown on meteograms might be greater than shown on vertical profiles or may not be captured at all where a sea grid point lies over land.
Dots represent grid spacing of 9km. The colour scale represents the proportion of heat, moisture and momentum for each grid point derived by HTESSEL and Flake at 9km resolution.
Fig9.9.4: An example of differing forecast 2m temperatures given by meteogram and vertical profile using the processes outlined above. Consider Bournemouth (XBH):
The chart is a section of the charts above and the data is for T+36 VT 12UTC 25 Aug 2025 DT 00UTC 24 Aug 2025. The wind arrows are only shown to indicate the location of grid points at 9km resolution although some advection of boundary layer air is forecast moving from sea to land. The land/sea distribution governs the proportion of energy flux from land or sea at each grid point (coloured as above).
(FUG Associated with Cy49r1)