Forecasting The Arctic Oscillation

I wonder if the notion of tracking error makes sense for climate models as a way out of the “weather is not climate” problem. It is fair to say that short term variation of weather is too random to predict, and to postulate that science has a better change to predict longer term patterns. However, there needs to be some way to track the longer term prediction without waiting for the next 10-20 years. As it stands today, the climate models are not held responsible for their weather predictions. And that means they are un-falsifiable.
It seems to make sense to track climate models based on their predictions. The tracking errors accumulated over the last 10-15 years should give us a way to determine (statistically speaking) that the models are likely to be wrong over time.
The use of tracking errors to measure performance is not new. We use the same methodology in the financial world to measure historical portfolio performance against benchmark indices.

Steve Goddard (09:27:39) :
We have seen autumn/winter snow cover increasing in recent years. That produces a very different cumulative effect than decreasing snow cover would.
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so much for runaway climate change, eh?

Lief,
Fair enough. When will cycle 24 peak, and what will that peak be?

solrey (09:53:47) :
AGW skeptic Joe Bastardi predicted the negative AO and a cold, snowy winter.
The AGW fearmongers can’t produce accurate forcasts.
The AGW skeptics, on the other hand, do produce accurate forcasts.
Who you gonna trust?
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Be careful. Bastardi always gravitates toward cold and snow. So, he is tends to be correct in a cold winter. I know dozens of long range Mets and none predicted this winter to be cold and snowy FOR THE REASONS that turned it into a cold and snowy winter in the NH. Most selected the Nino as the overriding factor this winter, when in fact we now know severe negative AO’s/NAO’s can trump a strong Nino in large part in the cold dept, and use the sub-tropical jet from the Nino to produce lots of snow. Simplistic explanation for sure, but generally correct for this post. Most Mets are honest enough to admit that they’re still in a learning process regarding weather. The climate guys should admit the same.

lgl (05:54:36) :
Richard Holle (02:17:43) :
“if I pull out the past three patterns of 6558 days, or 240 lunar declinational cycles, and plot them side by side, day by day, they show a resultant pattern that gives a better forecast than any of the models.”
Show us.
My reply;
The link (my name) leads to the set of forecast maps I set up tables of past data for gridding the data from in August – September of 2007. Started to make the daily maps themselves in September of 2007, and produced a set of daily maps from 2008 through 2013, which are still posted to those pages unmodified.
http://www.aerology.com/national.aspx
You may feel free to poke through them free of charge, comparing to the actuals from the past two years for verification or tear me a new one if it comes out that way.
I have made many posts on the principals, in action in this method over the past 10 years, most are still on line and search able by using a Google “Richard Holle aerology” query. There is way too much volume to post here.
I would be glad to answer specific questions about the method, and if you are interested could provide details of the programs, I had contract written to extract the data, grid the data, and make and store the maps onto the site.
I personally have footed the bill for all expenses incurred over the past 25+ years it took me to work out this method. No tax deductions have been applied to my normal income, and no grants or outside funding have been received!

Is yesterday’s weather forecast today’s climate?

anna v (06:18:51) :
Richard Holle (02:17:43) : | Reply w/ Link
My reply: I am only suggesting that we study the effects of the Lunar declinational tides in the atmosphere, because if I pull out the past three patterns of 6558 days, or 240 lunar declinational cycles, and plot them side by side, day by day, they show a resultant pattern that gives a better forecast than any of the models.
With compensation for the changes in the solar cycles, from the past three patterns of high activity, to this one of lower activity I would get the correct amount of cooling, and better representation of the depth, of the cold arctic air invasions that are arriving on time, just larger than before.
Piers Corbyn secret weather method uses the moon and sun as he has explained in several videos, and he seems to be quite successful in long term weather predictions, so you may be right.
On the other hand, when many dynamical inputs enter, and such is the case of earth climate, it is chaos tools that should be used.
anecdotal: in my part of the earth, Greece, the moon phases are traditionally used by sailors and farmers to “predict the weather” as follows: If the wind/clouds/etc change with the moon phase, expect the same weather to the end of the phase. If it does not change then, it will keep the same through the next phase.
My reply;
When Stonehenge was built (at the end of the last Ice age) they studied the solar and lunar declination interactions and found several cycles of import.
As the science of the understanding was reduced to a religion to present to the masses, their response was to look at the light phases, and extract wives tales, and folklore from the phase relationships applied to the time of the year, which are almost close enough to be used as a proxy for the declination angular movement, that requires equipment to measure.
The declinational tides period of 27.32 days is not far from the 28 day light phase period. The patterns generated in the atmosphere, in the form of Rossby waves, have a four fold repeat to the patterns. Where zonal flows dominate in alternating declinational cycles, and more medial flows in the others in between. The shifting of the patterns usually occurs around the time of Maximum North lunar declinational culmination.
Due to the topographical forcing of the terrain in the area you mention, there is sometimes little difference between the cycles, as there will be little difference in the New England area this time from the shift from the past cycle, to the next cycle shifting around the 26th to 27th of January.
It would seem that the story you tell is a valid one. Such is the problem with global verses regional forecasting.

Leif Svalgaard (00:26:32) :
“Dave F (00:18:54) :
anything is even correct in the models.
I don’t believe the current models are correct [too many things are parameterized], but my beef was with the bland assertion that because we cannot predict two weeks ahead, all prediction further out is impossible. If the climate to a large extent is self-regulating [negative feedbacks] then a model may not necessarily ‘go off the rail’ in the far future, but may be kept within bounds by the regulator [whatever it may be].”
This is part of my fundamental problem with GCM, especially to the extent that they are used to formulate climate policy. Who is the “regulator” who will be keeping things “within bounds?” And what are the “bounds?” The farther over time one goes in prediction, one cannot help but parameterize more and more. It is the famous “if present trends continue.” I do not trust the current “regulators,” because it is apparent they have been stacking the deck and doing precisely the parameterizing you deplore because they seek this conclusion. Nor do I believe we will ever be able to reliably predict long term trends in climate to the point where policymakers can trust the results because of the “butterfly effect.” It is that simple, Leif. Sorry, I wish I had your faith that the models in question could be improved to that degree, but we’re dealing with a pretty dicey system here, and your analogies need to be on crutches because they limp pretty badly.

tmtisfree (07:04:28) “[…] the envelope of the possible trajectories is bounded so the system is stable.”
We need more focus on deterministic constraints.