Forecasting climate?
The average value of a meteorological element over 30 years is defined as a climatological normal. Source: NOAA/NWS
It’s been done:
From the University of California – Los Angeles
Can scientists look at next year’s climate?
Is it possible to make valid climate predictions that go beyond weeks, months, even a year? UCLA atmospheric scientists report they have now made long-term climate forecasts that are among the best ever — predicting climate up to 16 months in advance, nearly twice the length of time previously achieved by climate scientists.
Forecasts of climate are much more general than short-term weather forecasts; they do not predict precise temperatures in specific cities, but they still may have major implications for agriculture, industry and the economy, said Michael Ghil, a distinguished professor of climate dynamics in the UCLA Department of Atmospheric and Oceanic Sciences and senior author of the research.
The study is currently available online in the journal Proceedings of the National Academy of Sciences (PNAS) and will be published in an upcoming print edition of the journal.
“Certain climate features might be predictable, although not in such detail as the temperature and whether it will rain in Los Angeles on such a day two years from now,” said Ghil, who is also a member of UCLA’s Institute of Geophysics and Planetary Physics. “These are averages over larger areas and longer time spans.”
Long-term climate forecasts could help predict El Niño events more than a year in advance. El Niño is a climate pattern characterized by the warming of equatorial surface waters, which dramatically disrupts weather patterns over much of the globe and strikes as often as every second year, as seldom as every seventh year or somewhere in between.
A major issue addressed by Ghil and his colleagues in the PNAS research is the difficulty of separating natural climate variability from human-induced climate change and how to take natural variability into account when making climate models.
For the study, Ghil and his UCLA colleagues Michael Chekroun and Dmitri Kondrashov of the department of atmospheric and oceanic sciences analyzed sea-surface temperatures globally. To improve their forecasts, they devised a new algorithm based on novel insights about the mathematics of how short-term weather interacts with long-term climate. Weather covers a period of days, while climate covers months and longer.
As is customary in this field, Ghil and his colleagues used five decades of climate data and test predictions retrospectively. For example, they used climate data from 1950 to 1970 to make “forecasts” for January 1971, February 1971 and beyond and see how accurate the predictions were. They reported achieving higher accuracy in their predictions 16 months out than other scientists achieved in half that time.
The research was federally funded by the U.S. Department of Energy and the National Science Foundation.
Extreme climate, extreme events
Ghil also led a separate, three-year European Commission–funded project called “Extreme Events: Causes and Consequences” involving 17 institutions in nine countries. In a recent paper on extreme events, published this summer in the journal Nonlinear Processes in Geophysics, Ghil and colleagues addressed not only extreme weather and climate but extreme events such as earthquakes and other natural catastrophes, and even extreme economic events. Their study included an analysis of the macro-economic impact of extreme events.
“It turns out, surprisingly, that it is worse when catastrophes occur during an economic expansion, and better during a recession,” Ghil said. “If your roof blows off in a hurricane, it’s easier to get somebody to fix your roof when many people are out of work and wages are depressed. This finding is consistent with, and helps explain, reports of the World Bank on the impact of natural catastrophes.”
Ghil spoke this past July about a mathematical theory of climate sensitivity at the International Congress on Industrial and Applied Mathematics, in Vancouver, a quadrennial event that showcases the most important contributions to the field over the preceding four years.
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amazing stuff…..the term climate addresses the PAST weather, it is simply the average of the weather over the previous 30 years…..climate is NOT in any way a predictor of the future, IF the earth had a very stable climate then indeed it could be a very good idea of what is coming, BUT in our chaotic system of constant CHANGE the climate says NOTHING about the future weather tomorrow, next week, next month or 10 years from now.
I haven’t read the comments but just wanted to say that I love the photo at the top of the post. I am so glad that WUWT has immortalised this image – now as previously – in the minds of so many people worldwide.
You have the young guy holding the wheel making a mysterious inverted ‘V’ sign on the desk while looking serious, the older guy touching his own thigh with one hand while the other hand tries to restrain or remove it. The guy with the arms folded looking quite pissed off and the amiable looking guy who looks like somebody you’d be happy to meet at a nice barbeque!
I think it’s a classic image.
Truly it is said: “a picture paints a thousand words”. In this case about state of climate ‘science’.
The forecasts on my pages have been posted there for 44 months now and there are still 28 months of forecast to go. It is a compilation of three analog periods of the harmonic oscillation of the inner planets orbital periods and the Moons orbital parameters that repeat every 6558 days.
http://research.aerology.com/aerology-analog-weather-forecasting-method/
The original raw data was pulled and averaged together (in December of 2007) to see if there were any patterns that repeated, does better than the NWS 5 day forecast on average, with detailed maps for daily Highs, Lows, Precipitation with range to expect, Snow fall and Snow on ground.
It has been drier in Texas than the past patterns show, but they still shows a drouth, and since the solar minimum, the Gulf states have been dryer than usual (from the past patterns). The fronts still arrive on time just no rain, did a good job on the Tornadoes this last spring.
Major revisions are under way to upgrade the detail of the maps, and add Canada, Alaska, and Australia. With the completion of outside forecast verification testing I will be able to give you accuracy numbers relative to Clim stats, NWS, and other service providers. All funds have come out of my own pocket. Ideas from around the net can be found in the research Blog format on the current state of the knowledge of the “Natural Variability”. Who’s doing what, and when they discovered it, can be followed in the original blog articles I copied comments from.
I see now how they get the temperature forcasts …
They spin this wheel, and whatever temperature is at the apex is the IPCC forecasted temperture due to AGW … Brilliantly simple.
“They reported achieving higher accuracy in their predictions 16 months out than other scientists achieved in half that time.”
After much practice, they can now fire an arrow with higher accuracy than anyone before, though they still can’t hit the target…
At least that’s how it sounds to me.
The propaganda war is ugly, but the eco-freaks are starting to sound like a broken record.
Anyways, Dr. Qamar from India had this to say on more proof of global warming:
Here is the link
If anyone is interested in seeing me bash this to shreds. you know where to go.
Anybody got $50? I’ll sell you a model that is guaranteed to “forecast” the weather near you for 1971 & 1972. Or for just another $10 you can have the premium model which will give you 1981 & 1982 as well. You can readily check for yourself how incredibly accurate this model is in predicting backwards and anything that good must work in the other direction. No? Ask me about my generous discounts for bulk user licences.
If you can’t extend the science, then truncate the definition. That’s about all they’ve done and the latter is far easier than the former.
Two of the authors, Kondrashov and Ghil, run one of the ENSO forecasting models – UCLA TCD.
It doesn’t look to be that accurate going back into the Archives (from March predictions, missed the 2007 La Nina, accurate on the double-dip 2008 La Nina, missed the 2009 El Nino, missed the 2010 La Nina), but some of the more recent predictions are closer.
http://iri.columbia.edu/climate/ENSO/currentinfo/modelviews/ensofcst_UCLA.gif
If thirty years is the norm then we dont need a lot of statistical obfuscation to predict the future -just continue the trend.Lets do a little calculation from the SST data for the simple minded using the Hadley Center SST’s
1981 SST .027
2011 thru July 0.284
Thirty year increase = 0.257
90 years brings us to 2101
Increase to 2101 = 3x 0.257 = 0.771
We can live with that. With higher CO2 and a slightly warmer wetter world and fewer droughts agricultural productivity should jump nicely. Cancel the end of civilisation
Well I believe; I’ve seen the light; Halelujah !
I mean if climate science can now postdict an extra 700,000 years of Greenland “ice core climate data” previous to the mere 100,000 years of Greenland “ice core climate data” for which we actually have real H2O brand ice cores, using a mathematical formula prestidigitation; then preguessing the next 16months of “climate weather” must be duck soup.
If you are lucky enough to have a paper copy of that now defunct NOAA global pole to pole CO2 abundance record for about a dozen years or so, then you aare aware, that the north polar annual CO2 peak to peak cycle, is 18 ppm; about 7 months going up, and 5 months coming back down; and that 18 ppm range is three times the mere 6 ppm amplitude at Mauna Loa.
In contrast, the south polar CO2 cycle is about 1 ppm p-p tops; well actually -1ppm p-p since it is 6 months out of phase with the north pole.
So with such a gross pole to pole assymetry in CO2 abundance; who in their right mind, would believe that Antarctic ice cores, can be used to predict what non-existent Greenland ice cores would show; but for the slight inconvenience of their non-existence.
So yeah, I believe with my whole being, that they already know the next 16 months of climate weather.
How many of them would it take to change a light bulb?
Easy!
It takes ALL OF THEM!
One of them has to apply for a grant to study the problem of how to change a light bulb, one of them has to administer the grant, while another one has to apply for a grant to study light bulbs themselves, and someone has to administer that grant … …
ad infinitum ad nauseum … … …
Most of us have had doubts about long term climate forecasting, but to have actual scientists claim that 16 months is “nearly twice the length of time previously achieved by climate scientists” is quite amazing!
“The method has two steps: (i) select noise samples—or “snippets”—from the past noise,
which have forced the system during short-time intervals that resemble the LFV phase just preceding the currently observed state; and (ii) use these snippets to drive the system from the current state into the future.”
I just started looking at this and maybe it’s just me but doesn’t the above suggest that who is doing the selecting and which “snippets” are selected provide a fairly obvious window for bias to enter into the system?
“A major issue addressed by Ghil and his colleagues in the PNAS research is the difficulty of separating natural climate variability from human-induced climate change and how to take natural variability into account when making climate models.”
If “human-induced climate change” is such a big factor, why separate it from natural climate variability? Won’t it negatively effect any predictions? I mean, if “human-induced climate change” exacerbates droughts, snowfall, rainfall and so on, how can any model that doesn’t take this into account be accurate? Or am I missing something?
Lets hope they are as good as the MET Office UK at seasonal to long term prediction. Last time I checked the MET stopped issuing them to the public as they were wrong 5 years in a row. “Barbeque Summers” and “snow being a rare and exciting event” They still issue their wildly innacurate forecasts to the government but then when did politicians care about getting things right or even in the ball park?
At the risk of being hanged…
May I please drop the documentations from Dr. Theodor Landscheidt into discussion, who made El Nino/La Nina predictions with a high prediction quality up to 7 years?
This documantation was written in 1998.
Please notice the predictions in Chapter 11, that were completely correct.
http://www.john-daly.com/sun-enso/sun-enso.htm
So predictions are obviously possible, but on other methods than the above.
Again, “It’s the sun, stupid”.
I think most people were reacting to the news article, and not to the research paper per se. However, Bill Illis is right that this work contains some difficult mathematics–it is beyond a first course in differential equations because, among other things, we never present stochastic driving in such a course, and usually not in vector form. Moreover, one needs some statistics, and probably beyond introductory statistics, in order to be comfortable with such things as PDFs, stochasticity, and so forth. Finally, one does not encounter Lyapunov exponents short of graduate school, nor spectral components, nor low-frequency variability unless one has had a lot of education, or is educated in specific areas. None of this is as elementary as you suggest–I know I’ve taught a lot of this material. Maybe at Cal Tech things are different. I think the paper is difficult to read and comprehend without a lot of effort, and without looking at the papers in the bibliography.
I notice the pic uses a Wheel ranging all the way from a +3.5° C anomaly to >7°. The mindset of the proponents/perpetrators is thereby immediately revealed.
It would be interesting to rate the accuracy of this AGW biased forecast against other long range forecasts such as Farmers Almanack, Piers Corbyn and others. The only other AGW biased forecast was from the UK Met Office which was so abysmal it had to be stopped as it was so embarrasing to AGW supporters.
I think that 3 month forecasts would be better as it is soon enough for a quick check on accuracy. Six months from now there should be sufficient feedback to see if their claims are at all credible.
PS. They may need to start adding negative numbers to their wheel!
They’ve taken the picture link down so you’ll need to re-host it yourself
>>
JCG says:
September 12, 2011 at 9:13 am
<<
Sometimes individuals are so anxious to demonstrate their limited knowledge and to belittle others (such as Bill Illis) that their attempts are obviously naive.
One has to be careful when reading science papers, because the authors may be redefining various standard notations. For example, your comment:
>>
Note: I was amused in the paper to see dx/dt referred to (in the vector sense as bold) as X(dot). Classic!
<<
is really silly. If you read the” supporting information,” shortly after discussing two predator-prey models, they redefine dt as:
dt = (a + x₁)d[tau]; (where [tau] represents the lower case Greek letter tau.)
The authors further define x dot as the derivative of x with respect to [tau]. They aren’t really using Newton’s dot notation (at least, not in the supporting section).
Earlier in the section they mention “convolution product.” I doubt that convolution algebra, the Convolution Theorem, and Fourier and Laplace transforms are taught in elementary calculus.
I agree with Kevin Kilty. You’re not going to understand this paper with a cursory reading. It may take several days to several weeks, investigation of the references, and running of models to really get a handle on the paper.
Jim
As always the test of the model is in the accuracy of the predictions it makes, not whether the maths is a bit difficult. It would be great to have an accurate long range weather forecast, so I look forward to seeing how it all turns out.
Goldie says:
September 12, 2011 at 6:16 pm
And the benefit of this approach is that you shan’t wait long!
Jim Masterson says:
September 12, 2011 at 6:09 pm
I agree with Kevin Kilty. You’re not going to understand this paper with a cursory reading. It may take several days to several weeks, investigation of the references, and running of models to really get a handle on the paper.
Jim
In the present world we are inundated with stories about one or another of the key commodities necessary for human well being which are at or approaching Peak. Various fossil fuels, food crops, potable water are but a few of those factors I’ve seen suggested to be on the path to inadequacy. All these discussions never even mention the commodity that is and always has been the scarcest and least sustainable. At the point where we each emerge in the delivery room we are all at Peak Life. We will never have more potential lifetime available to us than we do at that moment.
I make this point in this context, because you’ve suggested, and I would agree quite rightly, that a thorough dissection of this opus would require from several days to several weeks to accomplish. My admittedly rather superficial scan of this paper suggests to me that, even if I should be able to get back up to speed on mathematics that I knew reasonably well 40 years ago but which I have had almost no occasion to utilize in the intervening decades, In the end I’d still be left with the same question I have after my brief scan i.e. is something that is merely worthless a significantly large enough advance on something that is completely worthless to make it worth the investment of my rapidly dwindling lifetime to make the assessment. The authors may be correct in asserting their method’s superiority, but judging from the graphics included neither method is likely to be the kind of thing I will have much confidence in and, as I’ve said , Life’s too short.