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I'm bothered by how the article says "three years ago European models delivered a blow to the U.S. weather apparatus". Better models by Europeans do not make t

I'm bothered by how the article says "three years ago European models delivered a blow to the U.S. weather apparatus". Better models by Europeans do not make the models by Americans any worse. Improved models help everyone.

CWuestefeld 11y ago
That was the first thing I noticed, too. The fact that the Euro computers got Hurricane Sandy right was NOT a bad thing - it helped us. There is no reason to look at this in any way adversarially. I guess it touches a nerve, because of the similar silly comments elsewhere, worrying about how the USA is "losing" if, say, the Chinese economy's size exceeds the size of our own. Other folks doing well doesn't make us worse. When it happens we should be happy: other people are doing well, and we've got an opportunity to learn and improve too!
barney54 11y ago
And even with the new computer the European model is still better at mid range forecasts.
akie 11y ago
I talked to a (very) senior scientist at the World Meteorological Organization not too long ago. He was of the opinion that the U.S. weather models were about 5 to 10 years behind on the European models, and that this was caused by structural underfunding over longer periods of time (i.e. past decades). As I understood it these weather models are basically humongous software programs that are developed in house, but based on publicly available science and fed by data from weather stations. Does your software become better if you run it on a faster computer? It will certainly help, but he instilled on me the impression that the US had a bit more catching up to do than just buying a new supercomputer.
- barney54 11y ago
  He is correct. The European model still outperforms the US (GFS) model: https://twitter.com/RyanMaue/status/700216724067586049 https://twitter.com/RyanMaue/status/700216724067586049
- mturmon 11y ago
  I believe this reflects the community consensus. Perhaps partly money, partly communication/coordination, partly technique. It's embarrassing, and comments nearby saying "we have something to learn" are too complacent. US predictions over CONUS should be at least on par with ECMWF predictions.
mrow84 11y ago
You are correct, and I don't think there is much more of a collaborative than a competitive spirit between the various organisations. However, it is not only the model that is important in weather forecasting, but also the data assimilation system. This is an active area of research with a lot of "art" involved, or, perhaps more realistically, very educated guesswork, about how best to set up and tune any given system. ECMWF have been developing their 4D-VAR system in the atmosphere for quite a long time now, and it is very successful. I think the Americans might be using an ensemble Kalman filter, which has a whole range of tuning issues, so that will probably take them a while to get right. There is an interesting paper that interprets the effects of these two systems that I still don't fully comprehend [0]. The Met Office also uses a 4D-VAR system, but I'm not really clear on the key differences between it an the ECMWF system. Another important topic is coupling ocean and atmosphere models, and how you handle the data assimilation across your coupling - again, this is an active area of research, with lots of subtlety. Of course, the model dynamics and physics are also very important, as is the resolution. This last issue is one of the places where bigger computers have really direct benefits, the other being increasing the size of an ensemble. It's also important to realise that the various systems tend to be better suited to certain things, so whilst the ECMWF system is better in key global metrics, it doesn't (on average) provide better forecasts of all quantities in all situations. [0] http://onlinelibrary.wiley.com/doi/10.1034/j.1600-0870.2001.00118.x/abstract http://onlinelibrary.wiley.com/doi/10.1034/j.1600-0870.2001....

CWuestefeld 11y ago

That was the first thing I noticed, too. The fact that the Euro computers got Hurricane Sandy right was NOT a bad thing - it helped us. There is no reason to look at this in any way adversarially. I guess it touches a nerve, because of the similar silly comments elsewhere, worrying about how the USA is "losing" if, say, the Chinese economy's size exceeds the size of our own. Other folks doing well doesn't make us worse. When it happens we should be happy: other people are doing well, and we've got an opportunity to learn and improve too!

barney54 11y ago

And even with the new computer the European model is still better at mid range forecasts.

akie 11y ago

I talked to a (very) senior scientist at the World Meteorological Organization not too long ago. He was of the opinion that the U.S. weather models were about 5 to 10 years behind on the European models, and that this was caused by structural underfunding over longer periods of time (i.e. past decades). As I understood it these weather models are basically humongous software programs that are developed in house, but based on publicly available science and fed by data from weather stations. Does your software become better if you run it on a faster computer? It will certainly help, but he instilled on me the impression that the US had a bit more catching up to do than just buying a new supercomputer.

barney54 11y ago
He is correct. The European model still outperforms the US (GFS) model: https://twitter.com/RyanMaue/status/700216724067586049 https://twitter.com/RyanMaue/status/700216724067586049
mturmon 11y ago
I believe this reflects the community consensus. Perhaps partly money, partly communication/coordination, partly technique. It's embarrassing, and comments nearby saying "we have something to learn" are too complacent. US predictions over CONUS should be at least on par with ECMWF predictions.

mrow84 11y ago

You are correct, and I don't think there is much more of a collaborative than a competitive spirit between the various organisations. However, it is not only the model that is important in weather forecasting, but also the data assimilation system. This is an active area of research with a lot of "art" involved, or, perhaps more realistically, very educated guesswork, about how best to set up and tune any given system. ECMWF have been developing their 4D-VAR system in the atmosphere for quite a long time now, and it is very successful. I think the Americans might be using an ensemble Kalman filter, which has a whole range of tuning issues, so that will probably take them a while to get right. There is an interesting paper that interprets the effects of these two systems that I still don't fully comprehend [0]. The Met Office also uses a 4D-VAR system, but I'm not really clear on the key differences between it an the ECMWF system. Another important topic is coupling ocean and atmosphere models, and how you handle the data assimilation across your coupling - again, this is an active area of research, with lots of subtlety. Of course, the model dynamics and physics are also very important, as is the resolution. This last issue is one of the places where bigger computers have really direct benefits, the other being increasing the size of an ensemble. It's also important to realise that the various systems tend to be better suited to certain things, so whilst the ECMWF system is better in key global metrics, it doesn't (on average) provide better forecasts of all quantities in all situations. [0] http://onlinelibrary.wiley.com/doi/10.1034/j.1600-0870.2001.00118.x/abstract http://onlinelibrary.wiley.com/doi/10.1034/j.1600-0870.2001....