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Trom

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  1. Well GFS 18Z showing a couple of days of South Easterlies which keeps the snow risk this weekend. Then the Atlantic breaks through and giving us a westerly regime. By T72 high pressure is edging in leaving us in a southwesterly regime and hence mild but dry especially to the south of the country. Temperatures up to low/mid-teens for most of England by T90. By T117 were again in a more westerly regime as the high pressure ebbs east. We then seem to alternate between westerlies and south westerlies. Scotland flirts with a short-lived North Westerly by T138 bringing temperatures there down and the rest of the UK is in a North Westerly by T156 which will, therefore, bring a dip in temperatures to lower single digits but nothing that will bring snow away from mountainous areas in the north-west. By T183 it's back to south westerlies. Doesn't look inspiring.
  2. I've got to agree. Looking at it the surface temperatures look too high on Monday for most areas (seems to be around 5c). At the moment to me, it really looks like elevation is needed, even in the North. Snow chances do look to increase as the week progresses but with the flows direction, it all still remains highly marginal away from high ground. As for the south I really can't see anything other than sleet next week. I do hope I'm wrong and those 850's dip a little further to get the right side of marginal for more widespread areas.
  3. Whilst it's relatively quiet on here it's interesting that from a behavioural aspect that the December of 2010 has certainly skewed perceptions that late November can be cold and early December are particularly snowy months but March 2013 has not skewed perceptions that March is particularly wintery. Of course January and February are the historically most wintery for the UK. I wonder if psychologically it's because November and December are the start of winter whilst March is the end (obviously not meteorological seasons before some one calls me out). Anyway letting past events impact on future unconditional probabilities aka the gamblers fallacy is a repeating feature of the models thread come winter time and has been for many a year. So it looks Atlantic driven for the next week, albeit a relatively benign Westerly pattern. Unsettled would be the definition especially the further West you are. Then it's wait and see wether the SSW can shake things up in terms of a last cold shot.
  4. This is exactly the conclusion I formed some time ago. There's no doubt that they have an effect but the correlations between all these measures or at least current understanding of them seems to be limited. I very much admire Tamara et al who are willing to share there knowledge as our understanding of the interplays between them develops. They are often the target of some posters when things don't go to plan but I think we need to accept that our understanding and hence usefulness of these measures In terms of forecasting rather than hind-casting will improve over time. pioneering is how I see this area right now and I have great respect to those who are willing to share their musings publicly.
  5. With regards to verification stats are they for the global output or more geo specific. The only reason I ask is that if they are for the model output as a whole I'd imagine the UK with its complicated global position would have lower correlations. Is this a fair comment to make? Edit: Sorry ignore I see this has been answered later in the thread.
  6. Is the GFS the most progressive post it's update? It was the first to hold the Atlantic back.
  7. Poor old GFS getting a bashing. Don't forget it was the first model that attempted to hold back the Atlantic when Meto and ECM were being far more progressive. Noticeable as the GFS has the reputation (deserved or not) for being the most likely to default to zonal. Does it still have this post upgrade? It certainly has a tendency to sniff something out then underplay it relative to ECM before moving towards the Euro output. I read somewhere that it's slightly inferior stats were due to the initialisation data and that it had some years ago been run with ECM initialisation data which improved it's verification stats. Also thank you to those that have championed more volatility information being posted with mean charts. I notice quite a few posts of means along with ensemble charts which personally I've found to improve my ability to interpret those mean charts without having to delve around to find volatility. I'm guessing if the trends continue this place will be a lot busier and all the behavioural dissonances will rear their heads. Anyway so much more positive than a few days back.
  8. "But as shown in this draft paper Seasonal forecasting of the polar stratosphere and its coupling with the troposphere (Seviour et al - with Scaife again) the Northern hemisphere zonal wind forecast made in November for Dec-Feb has a correlation of only 0.16 with the ERA-Interim reanalysis - https://github.com/wseviour/glosea5-paper/blob/master/paper.md" 0.16 wow that's almost random.
  9. This goes back to the point I've made a few times on here, that mean without some kind of dispersion measure is an odd way to describe a data set. I know of no other field of study other than this website that mentions one without the other. It's just bizarre to describe distributions without a volatility measure. But of course if runs tightly cluster around a mean it tells us that there is a trend. By their very definition mean charts wont be able to sniff out a model change (as the positive and negative deviations will cancel out to some extent), but when the standard deviation of ensembles increases it tells you that there is greater uncertainty and hence the mean becomes less significant relative to volatility as the important measure. Of course when the standard deviation of runs is low relative to the mean then it becomes useful. I'm not having a go at any individual posters but really think that if you are going to post a mean then you need to post the ensembles so give it some kind of context, so that forum users can glean whether they are looking a significant trend or just a sign of uncertainty - both useful to know when interpreting the models. Observing frequencies of particular outcomes can also be useful to determine implied probabilities in the forecast data so get looking for clusters.
  10. Wow I found that really cool. We went from mildish and hammering rain to sleet and snow blizzard in about 10 minutes and to see the dew points plummet like that isn't an every day occurrence. In fact I can't remember a snow to rain event quite as extreme as that in my lifetime. I agree I've seen deeper snow but it's still 2 inches when I was wondering if I'd see a flake. You are not that far from me. Always a funny thing with snow though small differences can lead to different precipitation rates. Must of been in the sweet spot for this one. Having said that my family is living in the garden in a caravan whilst our house is refurbished and the up coming weather is going to be tough for us. Can't deal with ice days when your water supply is a relatively poorly insulated hose!
  11. Thank you - you don't see that very often in these Isles. I guessed it had to look a bit like this from the charts but wow that really is a dead Atlantic stream. Like someone flipped a switch. Not really any energy heading North or South from the US let alone West.
  12. Would anyone happen to have a chart of the jet stream for roughly the same time. Sorry I don't have access right now.
  13. Excellent post - the obsession with mean runs (which I haven't noticed in prior years) in FI seems very odd to me. As an Economist looking at data distributions and describing them by mean without a dispersion measure seems pointless. Even with a dispersion measure you would still want to see skew. From my perspective all these charts give you is a very broad brush trend of all the ensembles. When you look at the dispersion patterns in FI they are so vast. Median would be a better measure given how most people use them. There are dispersion measures using standard deviation which give a good idea of how well the op is supported relative to ensemble mean. Nick F posted one back on page 168. I'd like to see much more of this data being posted on the model thread. The charts he posted showed exactly where the models had the greatest variability in the northern hemisphere. We have a lot of data produce by the models but this measure goes under reported on the forum. Essentially it's telling us where the models are solid and where they are uncertain. Nick F if you could post more (or let me know where they can be found) that would be great.
  14. The map below shows the current distribution of Buzzards in the UK. Are you expecting an easterly to shift them west across the country? Sorry for the tease
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