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Once official reports signify the existence of a tropical cyclone, it is automatically tracked.  The tracking algorithm uses HRES CONTROL-10 output and is based on using the extrapolation of past movement and the mid-tropospheric steering flow to obtain a first-guess position 6 hours into the future.  The actual forecast position is then determined by searching for mean sea level pressure (MSLP) and 850hPa vorticity extremes around the first-guess position.  In some circumstances the thickness maximum, the central MSLP, surface winds, and the orography are also considered in the evaluation.  This process repeats at 6 hour intervals through the forecast until either the tropical cyclone dies or the end of day10 is reached.

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Strike probability is defined as the proportion of members that predict that the tropical cyclone will pass within a 120km radius of a given location at any time during the next five days.  In other words, the time dimension is integrated over the forecast range (see Fig8.1.10.1.2B).  This allows for a quick assessment of high-risk areas, regardless of the exact timing.  A 40% probability at a specific location means that approximately 40% of ENS ensemble members place that particular tropical cyclone centre within a 120km radius of that location at some point during the coming 10 days.  If a tropical cyclone is forecast to loop back on itself, and so pass close to the same location two or more times, as happens occasionally, the probability shown on the plot will be the highest probability encountered in any given 6h time interval during the forecast period.

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Lagrangian meteograms are a convenient way of evaluating the forecast for a specific tropical cyclone.  They contain time series of the central pressure and of the 10m wind speed maximum predicted within a 7ºx7º lat-long box centred on the cyclone and following its motion in each forecast member.   The "box and whisker" symbols are similar to those used on the Ensemble Meteograms.  However, unlike the standard meteograms, the number of ENS ensemble members represented by the boxes and whiskers varies, and can be assessed by reference to the strike probability chart or individual forecast trajectories chart.

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Examples of forecast tropical cyclone products

On web site

The ENS ensemble Forecast Tropical Storm Products for tropical cyclone 07S over the western Indian Ocean in the spring of 2017 are used as an example below. 

ECMWF ENS ensemble forecast with data time 00UTC 08 March 2017.  Time series (Fig8.1.10.1.2C) are plotted for the ENS ensemble mean (black dotted) and HRES CONTROL-10 (black solid); this convention is is also used on the map track plot (Fig8.10.1.2B).  On the individual trajectories plot in Fig8.10.1.2A the Control CONTROL-10 track is shown instead of the ENS ensemble mean.

Fig8.1.10.1.2A(Left):  Individual ENS ensemble forecast trajectories of the centre of tropical cyclone 07S.

Fig8.1.10.1.2B(Centre):  Strike probability chart. Colours show the proportion of members that predict that the centre of Tropical Cyclone 07S will pass within a 120km radius at any time during the next five days.  ENS Ensemble mean (dotted line) and HRES CONTROL-10 (solid line).

Fig8.1.10.1.2C(Right):  Top: ENS Ensemble probabilities (not including HRESCONTROL-10) for the intensity of this tropical cyclone to fall into each of the 5 tropical cyclone intensity categories shown at 6hr intervals to 10 days.  Centre and Bottom:  Lagrangian meteograms of distribution the full ENS ensemble (in box and whisker format), the ENS ensemble mean (dotted line) and HRES CONTROL-10 (solid line) for the maximum 10m mean wind speed (kts) associated with tropical cyclone 07S, and MSLP (hPa) at the Tropical Cyclone 07S pressure centre.  Note the categories used on the top panel are derived on the basis of the variable shown on the middle panel.

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Fig8.1.10.1.3A: Web chart of tropical cyclone activity (Including genesis) showing tropical storm strike probability. The web chart is clickable (shown by an arrow icon in top left corner) and a click at any location gives meteograms, plumes, wavegrams or a sequence of EFIs and CDFs for 2m temperature, rainfall and 24hr maximum wind gust.  Forecast for 00UTC 10 January 2018, T+72 ENS ensemble data time 00UTC 8 January 2018.   

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Fig8.1.10.1.3C: Sample CDFs (at the point indicated by the arrow) for the same ENS ensemble forecast as shown in Fig8.1.10.1.3A.  Note the high EFI for 24hr maximum 10m wind gust, which can be very useful, though the user needs to be aware of the innate difficulties of representing the absolute values of winds around tropical cyclones.

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Tropical cyclone activity charts for named or pre-existing tropical cyclones are also available on ecChardsecCharts.  The information can be combined with other significant weather parameters (e.g. 10m winds, significant wave heaightheight, etc).

Fig8.1.10.1.4: ecChart showing the ENS ensemble member tracks of TC03S up to 1 February 2017 (T+72)  and the associated probabilities of significant wave height >4m based on ENS ensemble members (probability given by colour in the scale below the chart).  TC tracks from the ENS ensemble forecast sequence are shown as thin lines (fading for older times) and HRES  CONTROL-10  forecast sequence as the black line.    Data time of forecast, 12UTC 29 January 2017.

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Fig8.1.10.1.5A(Right): Locations of TC Ferdinand from HRES CONTROL-10 forecast DT 00UTC 23 Feb 2020 (solid line on chart).  At 12UTC 29 Feb 2020 the algorithm incorrectly identifies the location of Ferdinand at the location of TC Esther and subsequently follows the movement and developments of TC Esther.  The sudden change in the HRES forecast values of central pressure (much lower) and 10m wind (much higher) are shown on the respective graphs - these correspond to TC Esther.  On this occasion the forecast values of ENS mean and ENS ensemble mean and ensemble probabilities do not suffer from the same problem.

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