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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 (where HTESSEL will be used) and lake/coastal seas (where FLake will be used, for lakes or shallow coastal water), or NEMO alone for sea grid point (where NEMO will be used).

For forecast HRES temperature data, the values are interpolated from those forecast at the three HRES points surrounding the ENS point identified above.

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  • The nearest ENS grid point is selected from among the four ENS points surrounding the selected location.  Within these four grid points:
    • if there is at least one land grid point then the nearest land grid point is chosen (even though a sea grid point may be nearer).  A "land grid point" is one where the   "fraction of land cover"  is greater than 50%.   
    • if there is no land grid point then the nearest ENS grid point is chosen (which will be a sea point).

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Flux information is governed by the "fraction of land coverassigned to the ENS grid point (see Fig8.1.5.6A) .   Thus ENS grid points in rectangles:

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Flux information used by HRES is governed by the "fraction of land coverassigned to the HRES grid points (see Fig8.1.5.6B).   Thus HRES grid points in rectangles that are coloured:

  • green are land points and HTESSEL will supply 90-100% of the flux information.
  • dark green are land points (but with 10-30% water surface) and HTESSEL will supply 70-90% and FLake 10-30% of the flux information.
  • turquoise are land points (but with 30-50% water surface) and HTESSEL will supply 50-70% and FLake 30-50% of the flux information.
  • blue are sea points (i.e. >50% water surface) and NEMO will supply 100% of the flux information.


Users should note note, for flux information: 

  • Coastal waters (less than 50% water cover in a grid box) are treated as lakes (using Flake) rather than as oceans (using NEMO).  
  • Some water surfaces (e.g. The Great Lakes) are classed as lakes rather than sea and FLake is used exclusively.

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Fig8.1.5.6A: 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 sea grid points. Towns mentioned below are Ventnor (V), Newport (N), Freshwater (F) and the city of Portsmouth (P) and locations are marked by a cross.

Execution of the technique outlined above 

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Fig8.1.5.6B: HRES grid points over part of southern England (black dots).  More detail is represented than by the ENS grid, but note two points to the northeast of the island are considered as sea points (one of which is by the city of Portsmouth, marked P).  Grid  Grid boxes are coloured according to the "fraction of land cover" scale on the right. Small  Small open circles denote the locations of certain ENS gridpoints that are discussed in the text.

In the case shown in the diagram for HRES:  

  • An inland location - Newport (location N).  HRES values are interpolated from the three HRES grid points (XYZ) surrounding the ENS grid point. There are two  Two of these HRES grid points are over land (both using 90-100% HTESSEL) and one lies over sea (using 100% FLake).  
  • A coastal location - Ventnor (location V).  Same as Newport.
  • An inland location - Freshwater (location F).  The ENS grid point lies exactly on the line between two points (JK) and HRES values are linearly interpolated.  Both HRES grid points are over land (both using 90-100% HTESSEL).
  • A coastal location - offshore of Ventnor (location O).  HRES values are interpolated from the three HRES grid points (RST) surrounding the ENS grid point.  There are   All three HRES grid points are over sea (all using 100% FLake).
  • A city location - Portsmouth (location P).   HRES values are interpolated from the three HRES grid points (UVW) surrounding the ENS grid point.  There is one HRES grid point over land (using 70-90% HTESSEL and 10-30% FLake) and two over sea (both using 100% FLake).

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  • The same ENS grid point is used for both locations N and V (even though location N is inland and location V is coastal). The interpolated HRES data supplies temperature (and other) data for the ENS meteograms for both locations N and V.  Differences between the inland location N and the coastal location V will not be apparent.  HRES values will normally differ from ENS values as a result of the differing use of energy flux procedures (HTESSEL, FLake, NEMO) at the surrounding HRES grid points..
  • Temperature is adjusted to reflect the differences in height between the altitude of each location and the corresponding HRES and ENS orography.   Despite being on the coast, location V is at greater altitude than location N and will consequently appear cooler.
  • No adjustment is made for the influence of the sea at the coastal location of location V and so the effect of the sea may not be evident on HRES meteograms.  However, one of the HRES grid points is a sea point (Z) and will give some indication of the influence of the sea.   Inspection of meteograms for nearby offshore locations (e.g. location O) may add useful information.
  • The ENS grid point (A) nearest to location F is remote from that location (not even on the island) and land characteristics governing fluxes may be very different.
  • In many cases locations are entirely outside the area defined by the three HRES grid points supplying data. This may seem undesirable, but the methodology adopted does deliver some consistency between the ENS and HRES usage, and indeed alternative approaches are not computationally viable for ECMWF at the current time.

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 Z is helpful in the derivation of temperatures by HRES .  However, if the wind winds were from the north (i.e. wind blowing from land to sea at Ventnor) then the influence of the sea point Z may not be relevant and ENS temperatures may be better.   It is for the user to assess whether a local effect might be relevant (e.g. onset of a sea breeze), or the local prevalence of persistent cloud (e.g.sea fog and low cloud drifting onshore), or the influence of turbulent mixing with stronger winds.

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Fig8.1.5.7: 10-day medium-range meteogram for Ventnor (a coastal location in southern England) from HRES and ENS data time 00UTC 09 May 2017.  During the first three days of the forecast the HRES temperature (blue line) is consistently cooler than the ENS members which are showing very little spread. The  The ENS grid point is inland but the HRES temperature is interpolated from the three HRES grid points nearest to the location of the selected ENS grid point and adjusted for altitude from the HRES orography to the ENS orography.  The diagnosis of discrepancies between HRES and ENS meteograms is complex and it can be difficult to disentangle causes, but users need to be aware of possible reasons in each case. Discrepancy  Discrepancy may possibly be due to altitude-related temperature adjustments, and/or to differences in HTESSEL and FLake tiling at the ENS and HRES grid points.

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