ECMWF is augmenting the tropical cyclone (TC) track products that it makes available for dissemination in BUFR format. They We now include the tracks of tropical cyclones that develop (i.e. undergo genesis) during the forecast integrations (the 'Genesis category'), as a supplement to the tracks that we had already been providing provide for existing tropical cyclones that exist in the analysis, i.e. where there is an official observation TC report for the analysis at the initial time of the forecast time (the 'Pre-existing category'). These The track products are provided for both high-resolution (HRES) and ensemble (ENS) forecast systems for the period T+0 to T+240h.
forecasts out to 10 days ahead.
ECMWF's TC track products contain the following variables: time, position (latitude/longitude in degrees), central pressure (hPa), intensity (i.e. maximum 10m wind speed in m/s in a 750 x 750km box centred on the TC location) and position of that 10m wind speed maximum (latitude/longitude). These are now provided for every tropical cyclone identified and tracked in every ENS forecast, and in HRES.
This change means that users will see (in general) more TCs in the ECMWF BUFR products. Users can distinguish the new 'genesis' TCs by using the storm identifier in the BUFR product as explained below.
This change will be introduced on Tuesday 10 November 2015.
Naming convention for the 'Genesis category' of tropical cyclones
...
P - South Pacific
For example, the "Storm Identifier" 71W represents the 2nd new TC feature identified in the North West Pacific basin (W) in forecasts from a particular ENS member or HRES. In general there is no guarantee that '71W' (for example) in one ENS or HRES run is 'the same' feature as '71W' in another ENS or HRES run from the same data time, though for lower numbers they are a bit more likely, perhaps, to be 'the same'. Strictly speaking however one can never say that a certain newly developing cyclone in one member is the same as a certain newly developing cyclone in another member. One could in principle approximate this type of association using a cluster technique though we do not do that. Similarly any apparent association between a cyclone in a certain member from a certain data time and another cyclone in that same member from a later data time that has the same ID will be purely coincidental. This is because we do not attempt to cluster across different data times either.