|Title||The role of satellite data in the forecasting of hurricane Sandy|
|Publication Type||Technical memorandum|
|Secondary Title||ECMWF Technical Memoranda|
|Authors||McNally, A, Bonavita, M, Thépaut, J-N|
The excellent forecasts made by ECMWF predicting the devastating landfall of Hurricane Sandy attracted a great deal of publicity and praise in the immediate aftermath of the event. The almost unprecedented and sudden left hook' of the storm towards the coast of New Jersey was attributed to interactions with the large-scale atmospheric flow. This led to speculation that satellite observations may play an important role in the successful forecasting of this event. To investigate the role of satellite data a number of experiments have been performed at ECMWF where different satellite observations are deliberately withheld and forecasts of the hurricane re-run. In each denial experiment the assimilation system cycles for five days without the withheld observations prior to re-launching the key forecast from 00 UTC on 25 October. All tests are performed at full operational resolution (T1279). Without observations from geostationary satellites the correct landfall of the storm is still reasonably well predicted albeit with a slight timing shift compared to the control forecast. On the other hand without polar-orbiting satellites (which represent 90% of the volume of currently ingested observations) the ECMWF system would have given no useful guidance four to five days ahead that the storm would make landfall on the New Jersey coast. Instead the hurricane is predicted to stay well offshore in the Atlantic and hit the Maine coast 24 hours later. If background errors estimated from the ECMWF Ensemble of Data Assimilations (EDA) are allowed to evolve and adapt to the depleted observing system, then some of the performance loss suffered by withholding polar satellite data can be recovered. The use of the appropriate EDA errors results in a more enhanced use of geostationary satellite observations, which partly compensates for the loss of polar satellite data.