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The diagnostics aim to represent cloud-to-ground plus intra-cloud lightning strikes.  Note that many ground-based lightning sensing systems are much more adept at identifying cloud-to-ground strikes.

Fig81Fig8.1.13.A-1(left): ecCharts display of lightning flash density (average strikes/100km²/h average during the previous 6h) from HRES.

Fig81Fig8.1.13.B-1(centre): ecCharts display of probability of lightning flash density (here >2 strikes/100km²/h average during the previous 6h).

Fig81Fig8.1.13.C-1(right): ecCharts display of probability of lightning flash density (here >0.1 strikes/100km²/h average during the previous 6h).

In the example in Fig81Fig8.1.13.A-1, values for Bordeaux (location shown by the pin) are given in the probe display at the top where less than 1 strike per hour average during the last 6 hours is forecast within the surrounding 100km² by HRES.  However, ENS gives probabilities for the same period of 45% for more than 2 strikes per hour average, and 80% for more than 0.1 strikes per hour average, during the same period.

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• are displayed as units per 100km² (i.e. per 10km x 10km square, or ~0.1^ox0.1^o) surrounding the relevant grid point.  So HRES does not indicate lightning strikes precisely at a given location. Recall also that HRES gridboxes measure about 9km by 9km, so greater detail than in raw model output is not possible.  Note also that strikes more than 10km away may be visible (or audible) to an observer.
• verify better when considered over larger areas and/or over longer time scales.
• often show peak activity about an hour earlier than observed.
• often show activity decaying away too early in the afternoon while in reality thunderstorms continue through the afternoon and often linger well into the night.
• often show lightning activity to be too intense, particularly during periods of higher activity.
• when considered over several years, tend to underestimate activity when compared with a 10 year climatology of satellite data, particularly over central Africa but also over parts of eastern Europe and central Asia.  Conversely, it is possible there is too much activity forecast over parts of the tropical Pacific.
• can exhibit systematic errors in the European area during the autumn in particular; at times there will be much more activity over the Mediterranean (sea area) than predicted (this may relate to the assumptions about graupel distributions over land and sea).

The six figures below (Fig81Fig8.1.13.B to Fig81-2 to Fig8.1.13.G-7) relate to the above bullet points.

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The probability of lightning activity is a good indicator of the risk of lightning strikes at a given location.  Selection of the threshold for lightning strike density allows the user to assess the risk at a location or within an area.  Selecting a low threshold (e.g. 0.1 strikes/100km²/h during the previous 3h) gives an indication of whether any lightning activity can be expected at all.   For many customers this is the aspect that is of primary interest.

Fig81Fig8.1.13.B-2: Mean correlation, for lightning flash density over Europe in summer 2015, between IFS short range forecasts and ground based observations, as a function of averaging spatial resolution (x-axis), and for different averaging periods (different lines).  Model forecasts of lightning activity should not be considered as being precise in time and space but rather as indicators of activity within a region, with there being greater confidence for larger areas over longer time scales.  Note lightning flash density is displayed on ecCharts as units per 100km² (equates to spatial resolution ~ 0.1^o).

Fig81Fig8.1.13.C-3: Mean normalised diurnal cycle of lightning activity from IFS short-range forecasts (black line) against three ground-based observation networks of lightning sensors (coloured) over Europe in summer 2015.  Model forecasts of lightning activity decay away too early in the afternoon while in reality thunderstorms continue through the afternoon and often linger well into the night.

Fig81Fig8.1.13.D-4: a)Observed mean lightning flash densities over 6hr, b)Probability (>30%) of lightning flash density exceeding 0.5 flashes 100km^-2 hr^-1 derived from ENS.

The charts illustrate that on the broad scale the forecasts capture the areas at risk, but the location of the activity is rather imprecise.

Fig81Fig8.1.13.E:-5 Time series of daily mean lightning flash densities from IFS short-range forecasts (blue) and from ground-based observation network of lightning sensors (red) over Europe during summer 2015.  The IFS forecast lightning activity tends to be too intense, particularly during periods of higher activity.

Fig81Fig8.1.13.F-6: Annual mean lightning flash densities from a) satellite climatology and b)10 year-long IFS model runs.  IFS  tends to underestimate activity, more particularly over central Africa but also evident over parts of eastern Europe and central Asia.  Conversely, it is possible there is too much activity forecast over parts of the tropical Pacific.

Fig81Fig8.1.13.G-7: Seasonal mean lightning flash density for months SON from 15 years of observations (left) and from 10 year-long 80km IFS simulations (right).  The scale is in flashes/km²/year.  Agreement for other seasons (not shown) is much better.

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