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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.

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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 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 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.

Example2: A lake surrounded by rugged orography.

Eastern Lake Geneva.

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Fig8.1.5.8A:  ENS grid points around Lake Geneva.  Only one grid box has less than 50% land and any land locations within that box will be considered as if over water.  The other turquoise shades show the proportion of water cover within the each box and defines the proportional influence of FLake and HTESSEL for any point within the grid box.  For example, a point (T) towards the northeast of the right hand box surrounding grid point Q (coloured turquoise as between 50% and 70% land) even though remote from Lake Geneva will nevertheless experience 50% to 30% influence of the lake. Vevey is marked V on the chart.  Grid boxes are coloured according to the "fraction of land cover" scale on the right.

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Fig8.1.5.8B:  HRES grid points around Lake Geneva.  Much more surface detail is captured by the grid, resulting in a more realistic representation of the influences of land and water within each grid box.  Grid boxes are coloured according to the "fraction of land cover" scale on the right.

In the case shown in the diagram:

For ENS Meteograms:


Vevey (marked V in Fig8.1.5.8) is a town on the eastern shores of Lake Geneva and  is surrounded by three ENS land grid points (PQR) and one ENS lake grid point (S).   The nearest ENS land grid point to location V is grid point Q and this is selected as representative of Vevey, or any other location within the ENS box centred on the ENS grid point (Q)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 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 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 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.



Example2: A lake surrounded by rugged orography.

Eastern Lake Geneva.

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Fig8.1.5.8A:  ENS grid points around Lake Geneva.  Only one grid box has less than 50% land and any land locations within that box will be considered as if over water.  The other turquoise shades show the proportion of water cover within the each box and defines the proportional influence of FLake and HTESSEL for any point within the grid box.  For example, a point (T) towards the northeast of the right hand box surrounding grid point Q (coloured turquoise as between 50% and 70% land) even though remote from Lake Geneva will nevertheless experience 50% to 30% influence of the lake. Vevey is marked V on the chart.  Grid boxes are coloured according to the "fraction of land cover" scale on the right.


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Fig8.1.5.8B:  HRES grid points around Lake Geneva.  Much more surface detail is captured by the grid, resulting in a more realistic representation of the influences of land and water within each grid box.  Grid boxes are coloured according to the "fraction of land cover" scale on the right.

In the case shown in the diagram:

For ENS Meteograms:

Vevey (marked V in Fig8.1.5.8) is a town on the eastern shores of Lake Geneva and  is surrounded by three ENS land grid points (PQR) and one ENS lake grid point (S).   The nearest ENS land grid point to location V is grid point Q and this is selected as representative of Vevey, or any other location within the ENS box centred on the ENS grid point (Q).  The area around grid point (Q) (coloured turquoise) indicates 50-70% land cover with HTESSEL providing energy fluxes and 30-50% water cover with FLake providing energy fluxes. 

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Systematic differences between HRES and ENS can occur in connection with strong gradients along coasts, small islands or in mountainous regions.  Any such discrepancy is usually most clearly apparent during the first few days, when the spread is normally small. Influences of any adjacent sea areas may be over- or under-represented by the ENS and/or HRES meteograms.  

Users should use meteogram output with caution - the data should not be taken as definitive but should be assessed and possibly adjusted.   In particular users should:

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is normally small. Influences of any adjacent sea areas may be over- or under-represented by the ENS and/or HRES meteograms.  

Users should use meteogram output with caution - the data should not be taken as definitive but should be assessed and possibly adjusted.   In particular users should:

  • critically assess forecast values in the light of experience regarding differences between previous forecast values and actual observed observations.
  • assess the effect of the forecast winds (e.g. if the wind blows from land to sea then the influence of a nearby sea point may not be relevant).
  • 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. 
  • consider the representativeness of the meteogram in coastal, island or mountainous regions and take into account consequent differences between HRES and ENS meteograms.
  • consider the impact of the land-sea mask value(s) at the grid point on the forecast parameter (temperature, wind, etc) on the meteogram.

Neither ENS nor HRES should be taken at face value without consideration of the ways each derives temperature values and the effects of local influences.


Amended/Updated 28/04/20 - Example 1 and Final Remarks