Recently the Chief of the met office went on UK TV to say:
“OUR SHORT TERM FORECASTS ARE AMONG THE BEST IN THE WORLD.” (see video here)
Yesterday, the UK Met Office had to make a rare mea culpa, saying they had botched their own recent snow forecast, it is useful to point out that they aren’t the only one with egg on their faces.
In early October, the Arctic Oscillation (AO) took an unexpected dip into deeply negative territory, which led to the sixth snowiest October on record in the Northern Hemisphere and the snowiest on record in the US. If you look at the 14 day forecast at the bottom of the graph below, you can see that the dip caught NOAA forecasters off guard.
Source: NOAA Arctic Oscillation Forecast
According to Rutgers University Snow Lab, October, 2009 was the snowiest on record in the US.
| Contiguous United States | ||||
| Month | Rank | Area | Departure | Mean |
| 12-2009 | 1/44 | 4161 | 1292 | 2869 |
| 11-2009 | 39/44 | 585 | -512 | 1097 |
| 10-2009 | 1/42 | 538 | 385 | 153 |
| 9-2009 | 5/41 | 21 | 13 | 8 |
| 8-2009 | 12-41/41 | 0 | -5 | 5 |
| 7-2009 | 24-40/40 | 0 | -17 | 17 |
| 6-2009 | 32-42/42 | 0 | -64 | 64 |
| 5-2009 | 37/43 | 34 | -151 | 185 |
| 4-2009 | 17/43 | 859 | 106 | 753 |
| 3-2009 | 23/43 | 1964 | -18 | 1983 |
| 2-2009 | 17/43 | 3172 | 110 | 3062 |
| 1-2009 | 15/43 | 3696 | 185 | 3511 |
Source: Rutgers University Snow Lab
The director of NCAR captured the moment perfectly in this East Anglia Email – dated October 12.
From: Kevin Trenberth <trenbert@xxxxxxxxx.xxx>To: Michael Mann <mann@xxxxxxxxx.xxx>
Subject: Re: BBC U-turn on climate
Date: Mon, 12 Oct 2009 08:57:37 -0600
Cc: Stephen H Schneider <shs@xxxxxxxxx.xxx>, Myles Allen <allen@xxxxxxxxx.xxx>, peter stott <peter.stott@xxxxxxxxx.xxx>, “Philip D. Jones” <p.jones@xxxxxxxxx.xxx>, Benjamin Santer <santer1@xxxxxxxxx.xxx>, Tom Wigley <wigley@xxxxxxxxx.xxx>, Thomas R Karl <Thomas.R.Karl@xxxxxxxxx.xxx>, Gavin Schmidt <gschmidt@xxxxxxxxx.xxx>, James Hansen <jhansen@xxxxxxxxx.xxx>, Michael Oppenheimer <omichael@xxxxxxxxx.xxx>
Hi all
Well I have my own article on where the heck is global warming? We are asking that here in Boulder where we have broken records the past two days for the coldest days on record. We had 4 inches of snow. The high the last 2 days was below 30F and the normal is 69F, and it smashed the previous records for these days by 10F. The low was about 18F and also a record low, well below the previous record low. This is January weather (see the Rockies baseball playoff game was canceled on saturday and then played last night in below freezing weather).
Trenberth, K. E., 2009: An imperative for climate change planning: tracking Earth’s global
energy. Current Opinion in Environmental Sustainability, 1, 19-27,
doi:10.1016/j.cosust.2009.06.001. [1][PDF] (A PDF of the published version can be obtained
from the author.)
The fact is that we can’t account for the lack of warming at the moment and it is a
travesty that we can’t.
http://www.eastangliaemails.com/emails.php?eid=1048&filename=1255352257.txt
Once again, this begs the question – if the GCMs can’t forecast the AO two weeks in advance, how can they possible forecast snow and cold 70 years in advance? University of Colorado professor Mark Williams used climate models in 2008 to come up with a remarkable prediction (below) in a year when Aspen broke their snowfall record.
Study: Climate change may force skiers uphill
From the From the Associated Press
Tuesday, December 16, 2008
DENVER — A study of two Rocky Mountain ski resorts says climate change will mean shorter seasons and less snow on lower slopes.
The study by two Colorado researchers says Aspen Mountain in Colorado and Park City in Utah will see dramatic changes even with a reduction in carbon emissions, which fuel climate change.
University of Colorado-Boulder geography professor Mark Williams said Monday that the resorts should be in fairly good shape the next 25 years, but after that there will be less snowpack — or no snow at all — at the base areas, and the season will be shorter because snow will accumulate later and melt earlier.
If carbon emissions increase, the average temperature at Park City will be 10.4 degrees warmer by 2100, and there likely will be no snowpack, according to the study. Skiing at Aspen, with an average temperature 8.6 degrees higher than now, will be marginal.
Since the first of October, Colorado is averaging two to eight degrees below normal, as is most of the US:
Source : NOAA High Plains Regional Climate Center
In December 2009, Colorado averaged three to fifteen degrees below normal, once again correlating with a strongly negative Arctic Oscillation
Source : NOAA High Plains Regional Climate Center
Climate models are iterative through time, which means once they go off in the weeds they can not recover. If AO trends can not be forecast more than a few days in advance, it would seem problematic to make any sort of meaningful long-term climate projections using GCMs.
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anna v, multivariate phase-relations of a variety of terrestrial variables show nonrandom patterns. There are scales & locations at which oscillations appear hard-bounded. My sense is that due to monitoring network limitations we have (manageable) aliasing issues in our records and that we additionally should consider the possibility that some data which appear quantitative are only ordinal (as suggested by Tsonis+ and many others before & since). There are classes of chaotic functions that conditionally allow for hard-bounded, patterned bouncing – for example the simple logistic equation. However, starting out from the assumption that everything is chaos invites more abstract computer-model fiddling that will tell us nothing about patterns awaiting discovery (via phase-conditioned analysis) in the existing empirical record. We have to invest the patience necessary to avoid misguided assumptions. Getting the assumptions wrong is the most costly error we can make.
Leif Svalgaard (12:56:37) :
It is likely that the current models cannot be improved, but when [if?] we learn about what causes the longer cycles that are evident, then incorporating those might lead to improved forecasting. The ‘butterfly effect’ has its limitations. In its purest form it refers to the effects of non-linearities [and calculational instability – e.g. round-off errors], but those are still limited by the energy available. The butterfly effect will not cause the Earth to emit, say, twice as much energy as it receives. So there are built-in brakes on the system.
This is a far more nuanced answer than Leif gave earlier and I agree with what he says here. A better understanding of the causes of the bounding conditions will lead to better simulation of the mid term possibilities, regardless of the fact we can’t pin down the smaler scale complexities.
However, until we understand the processes which lead to the Earth heading to one or the other attractor in it’s current bipolar shifts between ice age and interglacial quasi-stabilities, we will have to guess and hope about the longer term. I think the climate is both analogue and ‘twitchy’ within the bipolar state and not susceptible to logic gates.
There’s plenty we can and should learn about it though.
Leif Svalgaard (00:26:32) :
An interesting point I had never thought of. Could be that the climate sensitivity is not a constant the way a GCM would treat it. Change in the climate may change the sensitivity figure.
tallbloke (14:10:04) :
This is a far more nuanced answer than Leif gave earlier and I agree with what he says here
Really the same answer, but elaboration usually helps [not for all people though – if they don’t like what they hear]
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.
Steve, could you please supply me with the reference(s) that show an increasing trend in au/wi snow cover? Click on my name and use the Contact applet. This matter is of importance to forestry, especially regarding forest fires. Some are claiming the exact opposite; I need ammo for the debate. Thank you.
“Dave F (14:20:17) :
Leif Svalgaard (00:26:32) :
An interesting point I had never thought of. Could be that the climate sensitivity is not a constant the way a GCM would treat it. Change in the climate may change the sensitivity figure.”
I think Leif was referring not to the climate sensitivity being possibly variable, but more to things like parameterized instead of computed cloud cover.
Leif Svalgaard (00:26:32) :
An interesting point I had never thought of. Could be that the climate sensitivity is not a constant the way a GCM would treat it. Change in the climate may change the sensitivity figure.
Climate responses may be non-linear. Who’d have thought. 🙂
Good to see some recognition of LIMITS in this thread. The following was an unparameterized exercise in detecting shared boundaries (i.e. envelope):
http://www.sfu.ca/~plv/-LOD_aa_Pr._r.._LNC.png
Shifts in dominance amongst bounding factors present a formidable challenge – i.e. the envelope for one era may not be the right envelope for another era.
DirkH (14:45:23) :
I think Leif was referring not to the climate sensitivity being possibly variable, but more to things like parameterized instead of computed cloud cover.
Certainly the latter, but would not exclude the former, actually.
Stormy weather for the Met Office:
“BUFFETED by complaints about its inaccurate weather forecasts, the Met Office now faces being dumped by the BBC after almost 90 years.
The Met Office contract with the BBC expires in April and the broadcaster has begun talks with Metra, the national forecaster for New Zealand, as a possible alternative. ”
http://entertainment.timesonline.co.uk/tol/arts_and_entertainment/tv_and_radio/article6991064.ece
Leif Svalgaard (14:26:25) :
tallbloke (14:10:04) :
This is a far more nuanced answer than Leif gave earlier and I agree with what he says here
Really the same answer, but elaboration usually helps [not for all people though – if they don’t like what they hear]
If it’s the same answer at least it’s qualified with an if and a maybe the second time around. I’ll settle for that.
I’ve learned to bypass the invitations to verbal combat Leif puts in square brackets. 🙂
Steve Goddard (09:27:39) said “We have seen autumn/winter snow cover increasing in recent years. That produces a very different cumulative effect than decreasing snow cover would.”
The snow cover has very little cumulative effect. To prove that and to prove that initial conditions don’t matter in climate models, simply cover Central America in 6 inches of snow and run the model. In real life, and in the model if it is accurate, the change in albedo from the snow cover would last an hour or two and resultant weather effects (including global averages) for a day or two. The change in biosphere (plants killed off by the cold) would probably last a month or two will little effect on the climate. Initial conditions don’t matter and snow doesn’t matter all that much.
My other comment on model resolution is that it isn’t sufficient to model mesoscale weather and won’t be for a decade or two. That means that convection and clouds are essentially parameterized and as Sean and WSBriggs point out, which means the assumptions going in dictate the model results. The assumptions can come from higher resolution submodels or real world measurements, but those are difficult to integrate into the coarse model since those details are not independent of the larger scale model phenomena.
Paul Vaughan (15:08:07) :
Shifts in dominance amongst bounding factors present a formidable challenge – i.e. the envelope for one era may not be the right envelope for another era.
What is shows is just the spectacular breakdown of a correlation. The usual reason for this was that the correlation was spurious to begin with. So, so much for that one. On the junk heap it goes 🙂 joining the hundreds already there.
tallbloke (15:35:23) :
I’ve learned to bypass the invitations to verbal combat Leif puts in square brackets.
Why would you even contemplate that in the first place, unless you felt that it was applicable to you, which I don’t think it is [I could be wrong] (another set of square brackets to bypass)
Leif Svalgaard (15:24:03) :
El Nino approaches. Don’t know if you’ve had the unmistakable pleasure of experiencing one in the Golden State, so stay put, watch the show, and stay the hell away from moving water.
Eric,
A few hours of snow cover in Central America has little effect on the earth’s radiation budget. On the other hand, North America, Europe and Asia covered with snow for months – has a huge effect.
anna v (06:18:51)
I am intrigued, “chaos tools” and “deterministic chaos”. Can we tool and determine chaos or is weather best described as ‘something indeterminate going on within boundaries?’.
The human race seems to be going through a period of extreme sensitivity to weather, we certainly know more about it than 100yrs ago in terms of placing a number to a factor but lack the skill to project weather into climate and, except for those in the IPCC, does it really matter?.
Can chaos be defined or is it indeterminate? and just another way of saying “I don’t know” (within boundaries) ?
I am smiling as I write this, this thread is armchair philosophy at its best.
Mike D,
The increase in October-January snow cover in the NH was discussed last week on WUWT.
http://wattsupwiththat.com/2010/01/10/second-snowiest-december-on-record-in-the-northern-hemisphere/#more-15089
Regarding climate modelling – I had an online article published last year that goes someway in explaining the problems inherent in this approch, found here: http://www.onlineopinion.com.au/view.asp?article=9069&page=0
Anna V
“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.”
I live in rural south-eastern Australia and our longest termed farming resident (since deceased) used to say the exact same thing. Interesting that those people who live by the weather are usually the best observers of it – makes me think Richard Holle is on to something, too.
[I could be wrong] (another set of square brackets to bypass)
Heh. If we keep this up, you’ll run out of bracket styles eventually. 🙂
tallbloke (17:02:14) :
[I could be wrong] (another set of square brackets to bypass)
Heh. If we keep this up, you’ll run out of bracket styles eventually. 🙂
It was actually a serious question. Was I wrong?
Modeled long term forecasting ability is logically failed due to it’s desire not to predict climate but extreme weather events, and more of them, based on a CO2 increase. However, there are far stronger drivers of extreme weather events that swamp CO2 affects on weather, such as the recent AO dive. It will be these parameters that cause the models to fail.
Climate is a steady state entity unless your address changes. It does not need long-term or short term forecasting. The climate in NE Oregon will remain the same without any need to change the description of what it will be like tomorrow or in 200 years. It is the meanderings and trends of weather that are the hard part, both in terms of short range, and long range predictions. Therefore, if short term extremes are missed, most assuredly, long term extremes will be missed. Why? They arise from one and the same chaotic process. Short term weather prediction is the same as long term weather prediction. Be good at it on the one hand, you will be good at it on the other hand. Otherwise you will suck at both. End of argument.
Richard Holle (23:54:22) and savethesharks (23:38:46)
This ‘crazy-ass’ thunderstorm followed a meandering path from the border with NSW, up the Canungra valley, over Tamborine Mt to the Gold Coast then back inland to a western Brisbane suburb called The Gap. I know these areas well, I have two daughters in its path. It is a supercell that merged with other cells and dumped its energy in the form of wind, rain and hail in a ferocious ‘microburst’.
I witnessed one from my position in Canberra, form over the city and cause a lot of roof damage to the Australian National University, mostly from hail blocking gutters. It was like a giant white, solitary cup-cake in its formation.
For those unfamiliar with microbursts, this is interesting ………
http://www.bom.gov.au/weather/qld/cyclone/thunderstorms/16Nov2008/qldth20081116.shtml
Forecasting
So the science is settled, has been for a few years now.
The global temps will go up.
GCM’s can’t predict extreme weather.
What’s the point of keeping these GCM’s running?
If they can’t “predict” what is their purpose now? To adjust projected temps by a few tenths of a degree here or there? What’s the point?
Obviously it’s time to retire these GCM’s
Any flaws in this logic?
Pamela Gray (17:58:34) :
Modeled long term forecasting ability is logically failed due to it’s desire not to predict climate but extreme weather events, and more of them, based on a CO2 increase. However, there are far stronger drivers of extreme weather events that swamp CO2 affects on weather, such as the recent AO dive. It will be these parameters that cause the models to fail.
My reply;
The lunar declinational tides at the time of culmination maximum North or South in the short term 27.32 day periods give rise to most of the severe weather in the whole period. As the inertia of the tidal air mass following the moon’s transit across the equator, rushes in to the mid-latitudes, at culmination as the moon hangs there for two days.
This generates the large cyclones, that continue on with their inertia as the moon slides back toward the equator. With the (NH) wrap around effect, polar air comes from the west, and they sweep up toward the North East, creating the shear that brings the tornadoes in spring and summer.
The operational “dry line” being the cold old polar front being sucked in from behind.
The other times when there are surges in medial flows, seem to be caused by effects of synod conjunctions, of the outer planets that seem to have the same type of effects, as seen in the satellite image sequences.
Knowing that correlation is not causation, I have been trying to put my finger on the causes of this obvious effect. It happens about four times a year, in sync with the outer planet synod conjunctions and is scaled to their relative size / closeness. I have been trying to find some magnetic or solar wind carried signal to relate the causation to.
The timing is clear, the mechanism is hidden, and the strength of effect is calculable, and should be programmable into models, that could use these ideas as a base, to ground the butterflies to the flowers.
Re: Leif Svalgaard (15:44:25)
You might read up on Ben Chao’s ideas about NAO.