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Why Did the ECMWF Forecast Joaquin So Well?

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This blog from Bob Henson might be of interest.

 

 

The post-mortems have begun on how well Hurricane Joaquin was predicted, and one of the key themes is why the flagship global model of the European Centre for Medium-Range Weather Forecasts (ECMWF) beat NOAA’s Global Forecast System (GFS) to the punch in forecasting that Joaquin would remain well offshore. On Wednesday, September 30, less than six days from a potential landfall, the ECMWF operational model was consistently keeping Joaquin offshore, even as the GFS and nearly all other models were bringing the hurricane into the U.S. East Coast. From late Wednesday into Thursday, the GFS and other models began to shift toward an offshore track for Joaquin, as the hurricane itself was still diving southwestward into the Bahamas. By Friday, there was virtually unanimous model agreement on the offshore track that proved accurate.

 

http://www.wunderground.com/blog/JeffMasters/comment.html?entrynum=3148

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That's an interesting article; never realised these differences in data assimilation existed.

 

One current weakness in the GFS relative to the ECMWF, noted in the New York Times article, is its technique for data assimilation (bringing as many observations as possible into the starting point of a model run). ECMWF employs a four-dimensional data assimilation technique, while the GFS uses a 3D technique. The fourth dimension is time: the 4D system allows data from satellites and other sensors to be woven into a model run over multiple time steps, rather than being injected into the model at a single time step. In this and several other ways, including the ability to draw on a wider range of observations, the ECMWF data assimilation appears to give it the edge. A 4D data assimilation system is now being developed for the GFS, perhaps to be incorporated within the next year.

 

Run data sources for the ECM.

 

http://old.ecmwf.int/products/forecasts/d/overview/monitoring/coverage/dcover!AMVs-Infrared!00!pop!od!mixed!w_coverage!latest!obs/

 

Mind bogglingly extensive!

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That's an interesting article; never realised these differences in data assimilation existed.

 

One current weakness in the GFS relative to the ECMWF, noted in the New York Times article, is its technique for data assimilation (bringing as many observations as possible into the starting point of a model run). ECMWF employs a four-dimensional data assimilation technique, while the GFS uses a 3D technique. The fourth dimension is time: the 4D system allows data from satellites and other sensors to be woven into a model run over multiple time steps, rather than being injected into the model at a single time step. In this and several other ways, including the ability to draw on a wider range of observations, the ECMWF data assimilation appears to give it the edge. A 4D data assimilation system is now being developed for the GFS, perhaps to be incorporated within the next year.

 

Run data sources for the ECM.

 

http://old.ecmwf.int/products/forecasts/d/overview/monitoring/coverage/dcover!AMVs-Infrared!00!pop!od!mixed!w_coverage!latest!obs/

 

Mind bogglingly extensive!

 

Just a 'bit' different to the days when surface observations on land and sea were, along with 6 hourly radio sonde data, the only data available at each main synoptic hour. Those were the days!

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I don't like change John lol

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I have always hold the ECM of high esteem last winter it did falter but as did the other models. It is the superior model out there, I assume this is due to the greater wealth of data available.

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It is generally held in weather circles that the GFS is struggling at the moment for a variety of reasons. A key reason is that the US has invested heavily in supercomputing hardware but has neglected software development. At the same time NOAA's National Weather Service is very distributed with multiple separate organisations e.g. NCEP and its many centres. Focussing on hardware, a complex bureaucracy and (if you look at their website) not really talking about software is meaning the GFS is really struggling. It's definitely a number of years (perhaps 10?) behind the UM (Met Office) or IFS (ECMWF). I always think that the competition and collaboration between these two latter organisations keeps them on their toes :) â€‹!

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Looking at the latest scores UKMO is now in 2nd place for day 6 forecast. A big improvement. Doesn't look like GFS's latest upgrade has kept the pace with ECM and UKMO

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