For forecast ENS temperature data, all locations within each grid box surrounding a grid point are considered to have the same values as that forecast at the central grid point. The fluxes of heat, moisture and momentum which in turn determine the surface values of temperature, dewpoint and wind at the grid point are calculated using the proportion of land within the surrounding area (where HTESSEL will be used) and lake/coastal seas (where FLake will be used). For a sea grid point well offshore NEMO is be used to determine the surface fluxes of heat, moisture and momentum.
Energy flux information at each grid point is governed by the "fraction of land cover" assigned to the area surrounding it (see Fig8.1.4.1-1). Thus grid points in rectangles that are coloured:
Users should note, for flux information:
Some water surfaces (e.g. The Great Lakes) are classed as lakes rather than sea and FLake is used exclusively.
Fig8.1.4.1-1: An example over southern England of "fraction of land cover" values showing the proportion of land and water within each 9km x 9km square centred on each grid point. At grid point X the fluxes of heat, moisture and momentum will be determined by 70%-80% by HTESSEL and 20%30% by FLake. At grid point Y the fluxes of heat, moisture and momentum will be determined by 100% by FLake, even though the grid point lies over land.
For land locations:
For sea locations:
The process of selecting which gridpoints ENS that are used on meteograms is illustrated below, using relatively complex but informative examples.
Fig8.1.4-2: 10-day medium-range meteogram for Oslo from HRES/Ensemble Control (blue line) and ENS members (box and whiskers) data time 00UTC 26 June 2023. The map shows a close up of Oslo city. The nearest land grid point to central Oslo is at 59.93N 10.83E which lies some 5km away from and some 141m higher than Oslo city centre. This grid point may well be representative of Haugerud on the fringes of Oslo, but temperatures are reduced to near sea level using 6.5K/km lapse rate.
The Isle of Wight in southern England. The island is approximately 40km long by 25km wide. Coastal areas are strongly influenced by the sea while central parts are not.
Fig8.1.4.1-3: ENS grid points over part of southern England. Rectangles surrounding each grid point are coloured according to the "fraction of land cover" assigned to each grid point and shown by the scale on the right. Within each rectangle all locations are considered to have the same values. The fluxes of heat, moisture and momentum which in turn determine the surface values of temperature, dewpoint and wind at the grid point are calculated using the proportion of land (where HTESSEL will be used) and lake/coastal seas (where FLake will be used for lakes or shallow coastal water), or NEMO alone for grid points over open sea. Towns mentioned below are Ventnor (V), Bembridge (B), Freshwater (F) and the city of Portsmouth (P) and locations are marked by a cross.
Example sites are shown on the diagram:
Users should note:
In the above example, if winds were light and from the East (i.e. wind blowing from sea to land at Ventnor) the influence of the sea point S is helpful in the derivation of temperatures. However, if the winds were from the north (i.e. wind blowing from land to sea at Ventnor) then the influence of the sea point S may not be relevant.
Eastern Lake Geneva. Vevey and Montreux are lakeside towns which are not far apart but have different grid points; one grid point has an altitude near lake level, the other has an altitude associated with the nearby mountains.
Fig8.1.4.1-4: ENS grid points over Lake Geneva. Rectangles surrounding each grid point are coloured according to the "fraction of land cover" assigned to each grid point and shown by the scale on the right. Within each rectangle all locations are considered to have the same values. The fluxes of heat, moisture and momentum which in turn determine the surface values of temperature, dewpoint and wind at the grid point are calculated using the proportion of land (where HTESSEL will be used) and lake (where FLake will be used). Towns mentioned below are Montreux (M) and Vevey (V); locations are marked by a cross.
Example sites are shown on the diagram:
The difference in geographical altitude reflects the hilly nature of land and towns near the lake.
Fig8.1.4.1-5: 10-day medium-range meteogram for Vevey (on the shores of Lake Geneva) from HRES/Ensemble Control (blue line) and ENS members (box and whiskers) data time 00UTC 26 June 2023. The nearest land grid point to Vevey is at 46.50N 6.79E which lies some 5km away from and some 281m higher than Vevey city centre. This grid point may well be representative of the mountains to the northeast of Vevey, but temperatures are reduced to Vevey level using 6.5K/km lapse rate.
Fig8.1.4.1-6: 10-day medium-range meteogram for Montreaux (on the shores of Lake Geneva) from HRES/Ensemble Control (blue line) and ENS members (box and whiskers) data time 00UTC 26 June 2023. The nearest land grid point to Montreaux is at 46.43N 6.92E which is almost coincident with the city. However, the model altitude is some 219m higher than Montreaux city centre. Temperatures are reduced to Montreaux level using 6.5K/km lapse rate.
Because of the complexities of the orography around the location users should note:
Canary Islands
Fig8.1.4.1-7: ENS grid points around the Canary Islands. Rectangles surrounding each grid point are coloured according to the "fraction of land cover" assigned to each grid point and shown by the scale on the right. Within each rectangle all locations are considered to have the same values. The fluxes of heat, moisture and momentum which in turn determine the surface values of temperature, dewpoint and wind at the grid point are calculated using the proportion of land (where HTESSEL will be used) and coastal water (where FLake will be used), or NEMO alone for grid points over open sea. Locations mentioned below are St Cruz de Tenerife and Mount Tiede; locations are marked by a cross.
Example sites are shown on the diagram:
There are wide variations in orography within the islands (the islands are quite mountainous) and the representativeness of a grid point can be uncertain.
Fig8.1.4.1-8: 10-day medium-range meteogram for Santa Cruz de Tenerife from HRES/Ensemble Control (blue line) and ENS members (box and whiskers) data time 00UTC 26 June 2023. The nearest land grid point to Santa Cruz is at 28.51N 16.28W which lies some 5km away from and some 173m higher than Santa Cruz. This grid point may well be representative of the hills to the northeast of Santa Cruz, but temperatures are reduced to Santa Cruz level using 6.5K/km lapse rate.
Fig8.1.4.1-9: 10-day medium-range meteogram for Mount Tiede from HRES/Ensemble Control (blue line) and ENS members (box and whiskers) data time 00UTC 26 June 2023. The nearest land grid point to Mount Tiede is at 28.30N 16.63W which is almost coincident with the mountain peak. However, the model altitude is some 1408m lower than the height of the mountain. Temperatures are corrected to mountain peak level using 6.5K/km lapse rate.
There are wide variations in orography within the islands (the islands are quite mountainous) and the representativeness of a grid point can be uncertain. Local uncertainty in forecast temperatures at altitude can have a large impact of model precipitation especially over mountainous islands and coasts.
Isole Eolie. A set of small volcanic islands near southwest Italy. The islands are roughly 5km x 5km or smaller.
Fig8.1.4.1-10: ENS grid points around southwest Italy. Rectangles surrounding each grid point are coloured according to the "fraction of land cover" assigned to each grid point and shown by the scale on the right. Within each rectangle all locations are considered to have the same values. The fluxes of heat, moisture and momentum which in turn determine the surface values of temperature, dewpoint and wind at the grid point are calculated using the proportion of land (where HTESSEL will be used) and coastal water (where FLake will be used), or NEMO alone for grid points over open sea. Locations mentioned below are marked on the diagram.
The grid points either touch the islands but with less than 50% land cover, or miss the islands completely. All fluxes of heat, moisture and momentum are derived using FLake.
Fig8.1.4.1-11: 10-day medium-range meteogram for the town of Malfa on Malfa Island from HRES/Ensemble Control (blue line) and ENS members (box and whiskers) data time 00UTC 26 June 2023. The ENS grid is scanned for the grid points surrounding the location. None is a land point and nearest sea point is chosen. This point is actually situated on land but the "fraction of land cover" is less than 50% and the surface energy fluxes are determined by FLake. There will be no influence of land energy fluxes. In fact the whole island including the mountains will be treated similarly, no matter how far away from the coast. This grid point may well be representative of the southwest coast of the island. However, local effects may be important on other coasts (e.g. sea breezes). Conditions at inland high ground will not be reliably indicated, particularly for Monte dei Porri which rises to 860m.
Fig8.1.4.1-12: 10-day medium-range meteogram for the town of Stromboli on Stromboli Island from HRES/Ensemble Control (blue line) and ENS members (box and whiskers) data time 00UTC 26 June 2023. The ENS grid is scanned for the grid points surrounding the location. None is a land point and nearest sea point is chosen. There will be no influence of land energy fluxes. In fact the whole island including the mountains will be treated similarly, no matter how far away from the coast. Local effects may be important (e.g. sea breezes). Conditions at inland high ground will not be reliably indicated.
Fig8.1.4.1-13: 10-day medium-range meteogram for the Stromboli volcano on Stromboli Island from HRES/Ensemble Control (blue line) and ENS members (box and whiskers) data time 00UTC 26 June 2023. The ENS grid is scanned for the grid points surrounding the location. None is a land point and nearest sea point is chosen. There will be no influence of land energy fluxes. In fact the whole island including the mountains will be treated similarly, no matter how far away from the coast. Conditions at inland high ground will not be reliably indicated. Note the temperature data at the sea grid point (model height -8m due to the spectral representation of altitude) is amended to that at 422m (the model height at Stromboli volcano) which is itself less than the true geographic height of 926m.
There are wide variations in orography within the islands (the islands are quite mountainous). Grid points are almost exclusively over the sea so land effects will not be taken into account. The representativeness of a grid point can be very uncertain though may be appropriate for coastal parts. Inland parts of small islands will be largely similar to the coasts but nevertheless there is likely to be large local variations in conditions. Local effects can be very important with local sea breezes, nocturnal breezes, shelter, etc. Many small islands are mountainous - Malfa rises to 860m and the active volcano on Stromboli rises to 926m. The effects of volcanic activity are not dealt with by IFS).
It is for the user to make adjustments to meteogram values, particularly temperature.
Modelling the surface orography at an appropriate resolution is crucial to an effective forecast. However, at some level, there always will be smoothing that misses important detail.
Fig8.1.4.1-14: Schematic of the spectral representation of orography. Model orography matches true orography over large parts of the earth but is less exact in rugged mountainous regions. See also Section on Model Orography for further points regarding orography.
Generally model orography matches true orography over large parts of the earth. However, the spectral representation of orography in the IFS can:
The method of assessment and delivery of data for presentation on meteograms has been described in detail to give an understanding of the techniques involved.
IFS uses a spectral representation of orography and so there is some smoothing, particularly in mountainous areas. This means that will have model station heights that are different from the geographic height. For the majority of locations the differences are relatively minor. But there can be a significant difference at locations where there are large variations in geographic heights over a relatively small distance (e.g. deep valleys in rugged terrain, isolated steep islands, or coastal towns adjacent to mountainous regions).
Note: The station height on the meteogram is defined for:
Users should use meteogram output with caution - the data should not be taken as definitive but should be assessed and possibly adjusted. ENS forecast values should not be taken at face value but there should always be consideration of the ways that temperature and other values are derived. The effects of local influences are most important. Disentangling coastal effects from altitude effects can be difficult.
In particular users should:
It is for the user to assess critically the representativeness of the meteogram displayed and to make adjustments in the light of local knowledge and experience.