Status:Ongoing analysis Material from: Linus, Matthieu, ...
1. Impact
On 14 December, TC Chido has severely hit the French island of Mayotte in the northern part of the Mozambique Channel, in the Indian Ocean, before making landfall in Mozambique. Mayotte is a French Department, home to 320,000 residents.
This is an unprecedented event, surpassing the “reference” set by Cyclone Kamisy in April 1984: comparisons have been drawn to TC as far back as February 1934. Damages on the territory have been huge.
Analysis by Meteo France (in French): https://meteofrance.com/actualites-et-dossiers/actualites/le-cyclone-chido-frappe-mayotte
2. Description of the event
3. Predictability
3.1 Data assimilation
3.2 HRES
3.3 ENS
The plots below show the tropical cyclone track for TC Chido for the operational ECMWF forecasts from 14 December 00UTC (first plot) to 5 December 00UTC (last plot). The symbols shows the position on 14 December 12UTC (hourglass for BestTrack). HRES (blue), ENS CF (blue), ENS PF (grey) and BestTrack (black). AIFS is included in green.
The plots below show the same as above but with DestinE4.4 in purple.
The plots below show the tropical cyclone track for TC Chido for some ML forecasts from 14 December 00UTC (first plot) to 6 December 00UTC (last plot). AIFS (cyan), FourCastNet (yellow), Pangu-Weather (red), GraphCast (green), Aurora (purple) and BestTrack (black). ENS CF is included in blue.
The plots below show the tropical cyclone intensity (central pressure - top, maximum wind -bottom) for TC Chido for the operational ECMWF forecasts from 14 December 00UTC (first plot) to 5 December 00UTC (last plot). ENS CF (blue), ENS PF (grey) and BestTrack (black). AIFS is included in green.
The plots below show the same as above but with DestinE4.4 in purple.
The plots below show the tropical cyclone intensity (central pressure - top, maximum wind -bottom) for TC Chido for some machine learning forecasts from 14 December 00UTC (first plot) to 6 December 00UTC (last plot).
3.4 Monthly forecasts
3.5 Comparison with other centres
4. Experience from general performance/other cases
5. Good and bad aspects of the forecasts for the event