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  1. Isn't the 18z runs of both GFS and the new GFS(parallel) after +200, the pattern that OPI predicts for the winter?
  2. Is this something similar to the OPI pattern? The one that predicts for the winter i mean. Perhaps we start to see the precursors of winter's circulation pattern?
  3. More importantly, if someone's gut feeling proves to be correct over someone else's scientific work, it is still the scientific work that has won and deserves the credit. :-)
  4. I think yesterday, it wasn't saying tomorrow. It said soon, next week or something like that. Anyway just be patient. Tomorrow we will have the prediction.
  5. Hmm.... http://www.accuweather.com/en/weather-news/europe-winter-2014-2015-forecast-snow-cold/36777733 Fewer Storms for Ireland, United Kingdom and FranceAnother aspect of the upcoming winter season is that large and widespread damaging wind events are expected to be less common than last winter, which featured several noteworthy storms that caused damage from the British Isles into northern Europe. While occasional shots of cold air will send temperatures tumbling across Ireland, the United Kingdom and France early in the winter, a persistent southerly flow caused by storms tra
  6. What is median? (I actually know what it is, but i can't understand its usefulness here and perhaps you mean something different)
  7. I don't think this is the main reason. Actually i'm not speaking specifically about any post here, but only speaking generally, but the main reason for mocking words about any such try like OPI for example, is that people don't understand how science works. OPI may be a complete bust(hopefully it isn't). But it opens new roads of research. And anyway it's a scientific try based on the scientific method that may or may not work after all, so it's a respectful one. The problem is and always was that, ignorant about science people, ONLY SEE THE END RESULT. They could care less about the sci
  8. From what i understand from the paper, they have selected this area as they've found a strong correlation of the winter's geopotential heights there, with October's OPI. Here is the google translation of what it says in the paper(that was written in Italian): Google translation: Just about to central-western, it was possible validate, even in numerically, the predictive power of OPI, referring to the parameter of the fault geopotential average calculated on the winter quarter. The latter, for each year was calculated again using the maps available for download from the archives NCEP re
  9. Of course, but this is just for the useless in-between results we get every day(which are just for the fun of it). The actual final OPI value in November 1st, will be based on input of real values of the atmosphere for the 31 days of October, so nothing unscientific is going on at this aspect.
  10. As i've said it's from NCEP's(of NOAA) reanalysis project. Here are the complete temperature statistics for the 50° N to 55° N , 5° W to 0°E (Greenwich meridian), area**: **The area: Monthly average 850 hPa temperatures in degrees Celcius of the above area: Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec1948 -1.703 -2.286 2.857 0.303 2.981 4.046 6.110 5.970 6.456 3.316 4.646 1.2001949 -0.064 -0.148 -1.788 2.247 1.679 6.478 7.831 7.794 7.674 4.519 -0.097
  11. And combined them in such a way?? I don't really understand what you are saying. Here is what i've done: The OPI team tried to create an index(OPI) that would correlate well with winter AO(another index). I took these OPI values(ALL of them, i haven't selected them with any special criteria) for the Octobers and have tried to see if they correlate with the temperatures(in 850 hPa) of a specific part of the earth(your area, UK). I have not picked special data, i have not selected anything, i have taken all years that OPI has been calculated(from 1976 till 2013) and calculated the co
  12. What? Why not? Well temperature is not simple either. It's a combination of billions of measurements of the kinetic energy of billions and billions molecules. OPI is a specific value, temperature is a specific value and that's what matters when we do correlation tests. The validity of the results and the hidden variables behind is another issue.
  13. I have made a simple calculation about the correlation between October's OPI and the average temperature of following winter in the 850 hPa level for a big portion of UK. (I provide the values i used in the end of this post) So i took the October's OPI value and the following winter's average temperatures in degrees Celcius in the 850 hPa level for december+january+february, for the area that is defined by 5° W to 0° E and 50° N to 55° N (that contains most of England and Wales) and have calculated Pearson's r correlation coefficient and Kendall's tau. The values of temperatures have bee
  14. This is not necessarily a mistake. If the procedure is done correctly and you succeed in a high correlation of your prediciton then nothing is wrong of course and you have done a good job. But of course the question is always if you haven't ovedone it with your model and your number of inputs is larger compared to the observation and the phenomenon you want to explain. I think you(English dudes) call it overfitting or something right? And the ultimate and perhaps only test is of course the FUTURE. If your model can explain the next new "values",- in our case the next AO-, with similar corr
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