North Atlantic climate far more predictable following major scientific breakthrough

CMCC FOUNDATION – EURO-MEDITERRANEAN CENTER ON CLIMATE CHANGE

A team of scientists, led by UK Met Office, has achieved a scientific breakthrough allowing the longer-term prediction of North Atlantic pressure patterns, the key driving force behind winter weather in Europe and eastern North America. CMCC scientists Panos AthanasiadisAlessio BellucciDario Nicolì and Paolo Ruggieri from CSP – Climate Simulation and Prediction Division were also involved in this study.

Published in Nature, the study analysed six decades of climate model data and suggests decadal variations in North Atlantic atmospheric pressure patterns (known as the North Atlantic Oscillation) are highly predictable, enabling advanced warning of whether winters in the coming decade are likely to be stormy, warm and wet or calm, cold and dry.

However, the study revealed that this predictable signal is much smaller than it should be in current climate models. Hence 100 times more ensemble members are required to extract it, and additional steps are needed to balance the effects of winds and greenhouse gases. The team showed that, by taking these deficiencies into account, skillful predictions of extreme European winter decades are possible.

Lead author Dr Doug Smith, who heads decadal climate prediction research and development at the Met Office Hadley Centre, said: “The message from this study is double-edged: climate is much more predictable than we previously thought, but there is a clear need to improve how models simulate regional changes.”

Advance warning of severe winter weather is imperative to those who make risk-based decisions over longer timescales.For example, better forecasts can help the Environment Agency plan water management and flood defences, insurance companies plan for the changing risks, the energy sector to mitigate against potential blackouts and surges, and airports plan for potential disruption.

Improving model simulations will enhance the countries’ response, resilience and security against the effects of extreme weather and climate change – influencing future policy decisions to protect people’s lives, property and infrastructure.

###

Read more:
The paper on Nature:
Smith, D.M., Scaife, A.A., Eade, R. et al. North Atlantic climate far more predictable than models implyNature 583, 796-800 (2020). https://doi.org/10.1038/s41586-020-2525-0

Source: based on Met Office press release

From EurekAlert!

111 thoughts on “North Atlantic climate far more predictable following major scientific breakthrough

  1. The Brits have an unfair advantage. They are the only country with Weather. Everybody else just had a climate.

    So they have a long tradition of examining it…..

  2. data and suggests decadal variations in North Atlantic atmospheric pressure patterns (known as the North Atlantic Oscillation) are highly predictable

    Sorry, no. Since the NAO is a Jet Stream/atmospheric pressure oscillation, it varies by the week, not the decade. Now, the oceanic temperature variations AMO (Atlantic Multidecedal Oscillation) is, by definition, a decadal variation, but not the NAO & jet stream.

    https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/month_nao_index.shtml

      • Krishna , I have been harbouring a suspicion of double peaking of the AMO from looking at various meteorological signals relevant to the N Atlantic . Your chart seems to confirm this . Dare you speculate on a mechanism ? We appear to be on the declining shoulder of the second peak of the latest positive phase of AMO . In the last century that indicated NH cooling .
        I keep hoping that someone will post here, or at , say , dropbox, a definitive article on AMO. I don’t quite trust the Wiki article although I did learn that it was M E Mann who named it , although not the first to suspect its presence as a major climate influence.

    • The paper is paywalled, but the lead author, Doug Smith, has been working on NAO predictability, on a seasonal scale, since 2014. His claim is that the predictability is there, in the data, with relatively high SNR, but current ensemble models just lack the skill to find it, backing this up with data which shows “promising” correlation to seasonal trends.

      So this 2020 paper is apparently the culmination of this research.

      Here is his 2014 paper, which lays out the basis of this idea:
      https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/qj.2479

      “Seasonal to decadal prediction of the winter North Atlantic Oscillation: emerging capability and future prospects”, Doug M. Smith, et al.,
      https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/qj.2479 [pdf, 2014]

      • So, like the missing heat hiding deep in the oceans, the truth of the climate’s predictability is hiding deep in the data, & climate models are not good enough to find it. Send more money.

        • ” the truth of the climate’s predictability is hiding deep in the data,”

          Actually, the truth of a prediction is plain to see, but we have to wait until the predicted time to see it. We do not even need to know the details of how the predictions were made. They either got it right, or they were wrong.

          • Not exactly. They have to state,in advance,the limits and so variance, of the prediction.
            If they confer a wide latitude to the limits, then the model is not skillful in predicting, so just another exercise.

          • I was addressing the truth, not the relative ease, of prediction. Increasing the variance tends to increase model skill rating, because skill is a measure of accuracy and it will be more likely to “get it right”, even if trivially.

            In any case, the outcome must still fall within any specified predicted limits. So it will still be plain to see and verify.

      • Thank you for the comment and link Johanus. The NAO is part of the ~60-year oscillation discovered by Schlesinger & Ramakutti in 1994. As any oscillation it is inherently predictable to a certain extent for as long as it is active.

        NAO is highly dependent on AO, which is highly dependent on solar activity, ENSO, and the Quasi-Biennial Oscillation, through their combined effect on the polar vortex. The weather in the North Atlantic region thus depends on a chaotic element (atmospheric circulation) over which two non-chaotic elements are acting, solar activity and the QBO, both of which are predictable to a certain extent.

        Smith is demonstrating skill in hindcasting the NAO. I’ll have to look how he incorporates this elements. What would be useful would be to know his forecasts.

        Myself am expecting a North American and European winter similar to the 2009-2010 shown in figure 1 of the paper you link. Some of the factors are present:
        -Low solar activity
        -QBO turning eastward (not yet there)
        What is not there is ENSO, as a La Niña is developing, so the winter might not be as harsh as the 2009-2010.

        The reason Smith et al. talk only about winter predictability and not year-round predictability is because the driver of this winter predictability is the transfer of energy towards the dark winter pole from the latitudinal insolation gradient through the latitudinal temperature gradient. This transfer takes place twice a year alternating the pole and is regulated by the zonal/meridional state of the atmospheric circulation. Thus only winter can be predicted because only during the winter that transfer of energy becomes dependent on solar activity, the QBO and ENSO. That is one of the reasons the solar signature on climate is so hard to find. It acts intermittently and is amplified or damped by the atmosphere. But when you know when and where to look the signal is there in all its glory:
        https://i.imgur.com/0fSLxDf.png
        This image shows the pressure anomaly (geopotential height) in the lower stratosphere during winters for the combined years with high solar activity and low solar activity (the right image corresponds to next winter).

  3. “ Hence 100 times more ensemble members are required to extract it, and additional steps are needed to balance the effects of winds and greenhouse gases. ”

    Or as we say in English, “send more money”.

  4. Decade long predictions…? Right, as a UK resident, I can confirm our Met Office can’t get next weeks weather prediction right very often.
    Hey ho, let’s be optimistic.

    • Having been a weather forecaster, I can tell you that computer models are garbage longer than 5-7 days. (Last January ALL the models had PDX with 0℉ or lower ten days out-it didn’t even hit freezing.) Have you seen NWS 30 day, 60 day, or 90 day outlooks? 70% chance of being colder than normal is the same as 30% chance of warmer than normal, so no matter what happens, they made their ‘forecast.’ Garbage!

    • ROD. For Heaven’s sake, give the author a break, this isn’t about predicting the exact weather in Cleethorpes on Christmas day 10 or 20 years hence. It’s about understanding how various long term factors can influence the weather. The better you understand that, the better you can make your short /medium term forecasts.

    • Agreed. It is a lot of talk but I want predictions. You know that nasty requirement of the scientific method. They seem to have forgot that part or maybe it’s behind the paywall?

      PS. How is the MET office vs Piers Morgan match going? Last I checked in it was 6-nil for Piers.

    • Flanders and Swan knew the answer:

      January brings the snow
      Makes your feet and fingers glow.
      February’s ice and sleet
      Freeze the toes right off your feet.
      Welcome March with wint’ry wind
      Would thou wert not so unkind.
      April brings the sweet Spring showers
      On and on for hours and hours.
      Farmers fear unkindly May
      Frost by night and hail by day.
      June just rains and never stops
      Thirty days and spoils the crops.
      In July the sun is hot.
      Is it shining? No, it’s not.
      August, cold and dank and wet,
      Brings more rain than any yet.
      Bleak September’s mist and mud
      Is enough to chill the blood.
      Then October adds a gale
      Wind and slush and rain and hail.
      Dark November brings the fog
      Should not do it to a dog.
      Freezing wet December; then
      Bloody January again!

      Try: https://www.youtube.com/watch?v=_eT40eV7OiI

    • They are not predicting next winter.
      they are trying to predict extreme decades.

      For example: will 2025 to 2035 be extreme? o or not

      “We focus on the boreal winter period (December to March),
      averaged over forecast years 2 to 9 to focus on decadal timescales
      rather than seasonal to annual predictability. ”

      Think of it this way.

      Your financial advisor may tell you to invest in bonds for a solid return 10 years
      from now. he wont tell you what the value will be next tuesday.

      he’s not predicting that

      your doctor might tell you “hey lose weight” or you will have health problems when you get into your 60s. He’s not telling you you will croak next week from that donut.

      when someone makes a claim about X, you actually have to pay attention to the claim they make.

  5. A week ago the Met Office and their supercomputers/models said 31st July would be cool/average ~23C in London.
    Now it’s expected to be the hottest day of the year so far, this morning they were predicting 36C in London.

    Yes climate models are somewhat different, but the institutional shortcomings aren’t; the Met Office is highly politicized and obsessed with promoting climate change .

    They have also come up with a brilliant tactic whereby they can make predictions for 5 years or whatever, then update them (pull them back into line with reality every year) so you never realise how bad they were!

    • exactly the way the NHC does it…..the claim they were accurate because the predicted land fall and intensity…..5 mins before

  6. Sooo, it has been revealed that atmospheric conditions oscillate on a decade by decade standard.
    * Published in Nature, the study analysed six decades of climate model data and suggests decadal variations in North Atlantic atmospheric pressure patterns (known as the North Atlantic Oscillation) are highly predictable, enabling advanced warning of whether winters IN THE COMING DECADE are likely to be stormy, warm and wet or calm, cold and dry. We’ve been fed a steady diet of YEARLY temperature numbers. Thereby make a FALSE case about global warming (or not) “trends”.

      • You hit it 🙂

        I was looking for someone to exactly mention this. But then again, the researchers could not be that ridiculous, so I hoped that Charles Rotter had just referenced wrongly.

        It is impossible that the researchers have taken model data to base their theory on. Their base must have been the historical weather data.

        The researchers may have created a good template for a decade’s forecasting, but before we let our economy rely on it, we should rather rely on extrapolation of historic data, until after a decade of testing their work.

        It is great if these fellows have put some formula to forecast the next decade’s weather and this could matter in some areas as food buffers and resource planning for road maintenance, etc. But insurance companies may not benefit much from a decade’s forecast, they mostly need a wider margin for error over a longer period for way tinier areas.

  7. How the hell can they “know” it will predict the future more accurately? They’re fitting is based on hindcasting. Now MAYBE if hindcasts are better forecasts will be better, but there’s no way to know the future until it comes. As Yogi said, “It’s hard to make predictions, especially about the future.”

    These guys call themselves scientists and they can say things like this with a straight face? Sheesh!!

    • @Meisha
      “How the hell can they “know” it will predict the future more accurately? “

      If weather events were completely random, then there would be no predictability at all. But there are well-known (and not so well-known) patterns and cycles, due to orbital mechanics, polar inclination, and other historically observable physical “oscillations”, which make it plausible to generalize these cycles into sets of rules and and equations (“models”). These models make predictions of future events, with some measurable accuracy (hits and misses, etc). Some models are better than others, but they are all wrong in the sense that no model is 100% accurate all of the time. “But some are useful.” [quoting George Box]

      So, to answer your question, there is really no way to predict that a model will be accurate in the future. But it is relatively easy to tell which models have performed poorly or superbly, in the past. :-]

      • I meant to say: “…there is really no way to guarantee that a model will be accurate in the future. “

      • “But it is relatively easy to tell which models have performed poorly or superbly, in the past.”

        ITYM ‘model’ singular. Isn’t it INM-4?

        JF

    • “How the hell can they “know” it will predict the future more accurately?”

      They can’t know. They are blowing smoke.

  8. I am not sure if they looked at any real data or not. It appears they were comparing to models. Since the AMO is a decade or more long, the only advantage is to know the first year, since after that, you already know that you will have several more years following that pattern.

    • Yes Loren, that’s what leapt out for me as well –
      “climate model DATA”
      Results of climate models (or any models) are numeric constructs, not DATA.

    • “I remember Met Offs 2 predictions half a year in advance about one winter, one summer, both failed 100 %”

      The authors say they: “will predict the future more accurately”, and you show that they missed the mark in their past predictions completely, so they don’t have far to go to be more accurate in the future than they were in the past.

  9. So with a thousand variables to play with they were able to come up with a good fit to 60 years, not of weather events (it would be impressive is they could achieve that for a month), but only of a fit to the seasonal variations in 60 years of weather averages.

    Von Neumann could have done it with six.

  10. Will they call it a “warming hole” when it cools in the North Atlantic? and other idiotic, avoid-the-use-of-cooling terms

  11. It may be true but the can only be confirmed with future observations. This is why the AGW models have failed because they were not able to predict the amount of warming.

  12. It is really is hard to believe a word of this press release, or indeed the paper, when the second sentence of the paper’s Abstract reads: “Although inter-model agreement is high for large-scale temperature signals,…”.

    Unless of course, they are not talking about temperature anomalies, but actual temperature, then maybe one degree difference after ten years could be called “high” agreement.

    I think what they are really saying is “we teased a prediction for the NAO from our model outputs that held for ten years.” Not that they have discovered a way to actually predict the NAO.

  13. ” The team showed that, by taking these deficiencies into account, skillful predictions of extreme European winter decades are possible.”

    I know the British are still under the impression that they’re in charge of the language thing, but somehow, possible still doesn’t mean likely, and skillful is an awfully long way from the same as accurate or reliable.

  14. Well, if it’s a computer model than of COURSE it is predictable – after all someone had to write the dang code. If it were not predictable it could not be “tuned” to historical data now could it?

    OMG, using model output instead of available real data…

    If they look hard enough I bet they find a bunch of intermixed Sine waves in the data (<– Yes, this is sarcasm as I am betting they do not know Numerical Methods either).

  15. ” …the study analysed six decades of climate model data…” so they modeled models? GIGO

  16. 100 times more climate model runs will NOT solve this new observational AMO problem, as asserted. 100x all wrong is Never on average ensemble right.

  17. I have a mate living on the outskirts of Bega on the south coast of NSW and you might recall that was bushfire country last summer in Oz. Well now anyone under 98 has never experienced a wetter July (take note ‘dams are never gunna fill’ Tim Flummery and Co)-
    https://www.weatherzone.com.au/news/bega-valley-farmers-rejoice-as-record-downpour-fills-dams-raises-hopes-for-la-nina/532202
    So those all those big trees and understory in the mountains roundabout are going to grow like crazy again after a very thirsty/blackened time and rinse repeat at some stage in the future. It’s what Gaia does but rest assured it will be a sign of the dooming again with all the Hanrahans-
    https://www.bushverse.com/said-hanrahan

  18. From the above article: “The team showed that, by taking these deficiencies into account, skillful predictions of extreme European winter decades are possible.”

    Now, where have I heard such claims before? I’ll believe it when I see it is confirmed some 20 to 30 years from now.

    Until then, it currently is—and will continue to be—GIGO (garbage in, “gospel” out*).

    *Tip of the hat to Willie Soon for this appropriate redefinition.

    • That means they can make a solid prediction of 1 bad winter in any 10 year period. It doesn’t mean they can tell exactly what year though.

  19. Weekly NAO/AO anomalies are discretely solar driven, and are predictable at any range. Blocking must be taken into account for regional weather prediction. With a northeast Pacific warm blob, when the AO goes negative, the NAO can remain neutral or even go positive, giving mild wet stormy conditions in the UK, but deep cold in the northeast US. I had the solar forecast correct for Jan-Feb 2014 but didn’t know about the blocking then and failed on the UK forecast. Last Autumn I spotted the warm blob and correctly predicted UK floods for mid November and mid December during the predicted negative AO episodes. Feb prediction failed due to an oversight, the remaining 5 months predictions were useful.

    https://www.linkedin.com/pulse/2019-2020-cold-season-arctic-oscillation-forecast-ulric-lyons

    Most of the severest winters in history have occurred at certain quadrupole Jovian alignments, notably at t-squares. No amount of decadal climate analysis can ever predict them.

    https://www.linkedin.com/pulse/major-heat-cold-waves-driven-key-heliocentric-alignments-ulric-lyons/

  20. I recommend that they make a whole bunch of their skillful quantitative predictions, have them publicly notarized, and archived.

    I’ll check back in , inshallah, some time around 2030 and see how they did.

    I also recommend that they think very carefully about what predictions they make. It would be a shame for them to waste more than a decade of their time by making predictions that are no more skillful than Kim Kardashian throwing dice. That’s how climate science was destroyed the first time around.

  21. This is touted as a climate prediction ‘breakthrough’, without any corroborating observation data from real locations on Planet Earth? Sounds more like unsupported speculation, to me.

    If there is no steak, it’s fraud to sell the sizzle!

  22. It appears someone ask where the money has gone after 6 years and they got this brain fart of predicting model data.

  23. Wow – “highly predictable” but “much smaller than it should be”???
    Well that’s Science for you.
    I am convinced but less convinced than maybe, perhaps than I should be!!!

  24. It sounds to me like if 100 times more ensemble members are required to calculate their “forecast” that it is extremely exposed to butterfly wings flapping in Brasil.

  25. I think some of you may be missing the point of this UK Met study.

    Yes, they are looking at “reanalyzed data”, which is generated by hind-casting historical data (using DA, data assimilation). Like any forecast, it is not always accurate, but it provides a convenient and plentiful platform for trying out testing out new algorithms and tools. But, the point you are missing, is that they noticed (about six years ago) that the models do not correctly predict the NAO patterns. (Surprise?) This current study announces that they have made a “fix” which enhances the accuracy of the model, compared to actual NAO trends. [This latest study paper is paywalled, so we are missing the complete details of the fix.] [I too am a skeptic of government “climate-scare” policies, but I also assume that there are some government researchers who are really dedicated to improving the accuracy of weather/climate forecasting tools.]

    Here is what the authors said:

    . Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude.

    The message from this study is double-edged: climate is much more predictable than we previously thought, but there is a clear need to improve how models simulate regional changes.

    This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models

    Now will they continue this study by making more predictions, into the future, and compare predictions to future weather results? That is a good question. I do not know answer.

    • I am also interested on the science behind the study. I posted a long comment above that went into moderation for unknown reasons.

      Here is a “freed” copy of the article for anybody interested:
      Smith et al., 2020. North Atlantic climate far more predictable than models imply.

      The article is quite critical of models:
      “Crucially, we find that the NAO signal is underestimated by an order of magnitude in the model ensemble. This adds to an increasing body of evidence that the signal-to-noise ratio is too small in climate models, as seen on seasonal20,35–37, interannual38 and decadal19,39,40 timescales. Consequently, the real world is more predictable than climate models suggest10,18 and uncertainties diagnosed from raw model simulations are too large. The cause of this error is not yet known, although there are several theories, including weak teleconnections to the quasi-biennial oscillation41, lack of persistence in the NAO42,43 and in weather regimes44, unresolved ocean–atmosphere interactions45 and weak transient eddy feedback46.
      A key question is whether climate models also underestimate sig- nals on timescales beyond a decade. There is some evidence that the response of atmospheric circulation to Arctic sea-ice loss47 and to exter- nal factors10 such as volcanic eruptions, solar variations and ozone changes are too weak in models. Models also appear to underestimate the magnitude of multi-decadal temperature variability48,49, especially for the North Atlantic50,51. Furthermore, model-simulated winter climate change signals in the North Atlantic increase substantially as resolution increases52, consistent with the suggestion that eddy feedbacks are inadequately resolved46. If this is robust, treating current model simula- tions at face value leads to misleading conclusions about uncertainties and irreducible internal variability.”

      What is disappointing is that they are missing totally the effect of solar activity on winter weather predictability. They won’t go far without it.

      • Javier,
        Thanks for “liberating” the subject study.

        Looking at it I find that the steps needed to repair the model are very simple and somewhat antiquated, at least for old-school practitioners of regression analysis like myself.

        [Some of subscripts are messed up. See page 7 for original] We therefore take the required NAO to be the ensemble-mean forecast NAO, adjusted to account for the underestimation of the predictable signal. This is achieved by multiplying the ensemble-mean NAO by RPS (equation (2)). To avoid overfitting to observations, we compute RPS for each hindcast start date separately using a cross-validation approach
        in which the required hindcast and those on either side are omitted. Our conclusions are robust to omitting more hindcasts (we tested up to 4 yr either side), although skill may be especially underestimated in these cases.
        The overall procedure is as follows. For each start date i:
        (1) Compute the signal-adjusted NAO index (described above)of the ensemble mean, NAOi.
        (2) Compute the NAO index for each ensemble member, NAOik.
        (3) For each ensemble member, calculate the difference NAO −i NAO ki.
        (4) Select the M = 20 ensemble members with the smallest absolute differences.
        We take the mean of this subset of M members and present standardized forecast anomalies (Fig. 3) or adjust its variance to be the same as observed (Fig. 2). This approach is applicable to forecasts as well as hindcasts. We present results for a subset of 20 members, but the results are similar for subsets of 10–40 members. This method relies on models simulating realistic NAO teleconnections (FkNAO). Further improvements may be possible by using the best models in this respect

        Seems like they performed the pre-processing analysis on this manually, which led to rules for selecting the optimal ensembles. There are tools to automate this, which would probably find additional parameters which can be optimized to futher increase predictability.

        For example, you might recall the analysis I did to find predictability in the Labitzke data, in which I used Cubist/M5 (a 30-year old, open source tool) to creat a detailed regression model (a piece-wise linear regression tree, with human-readable rules) to predict 30 hPa temperatures using sunspot features. [The “holy grail”? I do not think so. 30 hPa is in the middle of the stratosphere and has very little effect on Earth’s daily weather. :-]
        https://wattsupwiththat.com/2019/02/25/labitzke-meets-bonferroni/#comment-2641991

        • I didn’t recall it, but I have checked it again. Interesting, but as I said it is not the right analysis, so it is not surprising that did come negative. I showed the data in my comment:
          https://wattsupwiththat.com/2019/02/25/labitzke-meets-bonferroni/#comment-2640975

          The hypothesis that can be deduced from the data is that low solar activity results in very different 30 hPa conditions (geopotential height and temperature) over the winter North Pole depending on 30 hPa equatorial wind speed, and that the result is different when solar activity is high. If you don’t include the QBO you come out empty.

          30 hPa is in the middle of the stratosphere and has very little effect on Earth’s daily weather.

          Except during the winter, which is what we are talking about. The polar vortex extends all the way from the surface to the stratosphere. When is strong and well formed stays over the pole and sucks all the heat. At the same time creates a very cold pole and keeps the mid-latitudes in a warm winter. When is weak and disorganized the pole is warmer and the mid-latitudes colder. The association between Arctic winter temperatures and solar activity is well known and studied.
          Kobashi et al., 2015. <a href="https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2015GL064764"Modern solar maximum forced late twentieth century Greenland cooling.

  26. So what *IS* their prediction for Winter 2020-2021 for Northern Europe and the British Isles?
    Their ability to predict next winter’s severity for Northern Europe will be correct, except when it’s not. Then it’s just random chaos that made them miss the prediction.

    In reality what I see here is a massive Grift, or Rent-seeking if you will. Their statement:
    “Hence 100 times more ensemble members are required to extract it,…. “ is the tell.

    Bottom line: Send money. Lots of money.

  27. Wow! Something is predictable for decades.
    Well, we will know that in … a few decades.
    Beware of predictions.
    Especially about future!

  28. I love the abstract! My caps…

    “…Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the POOR PREDICTIVE ABILITY OF RAW MODEL OUTPUTS…”

    Nice admission that the models were garbage despite how they were portrayed. Not to mention individual simulations couldn’t agree on decadal variations of “stormy, warm and wet or calm, cold and dry” winters.

    This sounds pretty hokey, though…

    “…To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation…”

  29. Great! Let’s put their predictions to the test and see how they compare to observations over the next four or five decades. Validating theories is the keystone of the scientific method. Let’s try science for a change.

  30. I don’t understand some people here. They seem to be slagging off this paper purely because the UK Met office is fully signed up to the CAGW nonsense. This is a valuable piece of work that increases our understanding of how the atmosphere works.

    • Most people come for tribal reaffirmation. There used to be more people genuinely interested in the science of climate change.

      • Yes.

        This used to be better.

        I have abandoned this at times due to the US alt-right party politicals, which have no relevance to the science of climate.

        the science is patently not leftist or liberal, but science.

    • They are not looking at the discrete solar forcing of NOA/AO anomalies, so this must be about probabilities according to things like the AMO phase. That doesn’t explain anything about how the atmosphere works.

    • How does looking at climate models and then throwing out the ones that don’t agree with observations increase our understanding of how the atmosphere works? There are too many PhD academics and not enough intelligent thought to go around.

    • I have had much success in predicting NAO/AO variability at roughly weekly scales since 2008 at very long range by means of the heliocentric planetary ordering of solar activity. Kepler used the same method to predict the very cold winter of 1595.

      Day-to-day changes in the Arctic and North Atlantic Oscillations correlate with solar wind speed and relativistic electron precipitation.
      https://www.sciencedirect.com/science/article/pii/S0273117713005802

  31. They realise two things, for which they can be commended.

    First the “ The chaotic nature of the climate system”.

    Second that “the North Atlantic Oscillation [is] the leading mode of variability in North Atlantic atmospheric circulation”.

    Who knows – maybe they’ll even rediscover the concept of the null hypothesis?

  32. IMO the press release doesn’t find the core of the paper. The headline: “North Atlantic climate far more predictable than models imply” nails it. They find, that the NAO has a low frequency signal part which models don’t replicate, see fig.2a. They deduce, that CMIP5’s and 6’s do not show the climate of the real world when it comes to the dynamics of atmoshere. They find:” The fact that the NAO signal is much too weak in models implies that the effects of the NAO will be underestimated relative to other factors such as greenhouse gases. ”
    Furthermore: ” If this is robust, treating current model simulations at face value leads to misleading conclusions about uncertainties and irreducible internal variability.”
    An annoying comment in “Science” https://www.sciencemag.org/news/2020/07/missed-wind-patterns-are-throwing-climate-forecasts-rain-and-storms goes one step further:
    “The missing predictability also undermines so-called event attribution, which attempts to link extreme weather to climate change by using models to predict how sea surface warming is altering wind patterns. The changes in winds, in turn, affect the odds of extreme weather events, like hurricanes or floods. But the new work suggests “the probabilities they derive will probably not be correct,” Smith says.”
    This is an important outcome: Models do not show the real worlds climate and many “attribution” papers are not correct when the refer to model simulations.

  33. When I lived in the UK, I had no problem predicting the weather. I tossed a coin.
    Heads: dismal
    Tails: rotten

    I was nearly always right.

  34. As far as the accuracy of their forecasts are concerned, a stopped clock is accurate twice a day.
    Maybe they should have a look at Old Moore’s Almanac for information about future weather, it might be more (pun intended) accurate.

  35. I do hope that they are not looking at multiple model runs and then engaging in post-hoc screening to find the best fit to the actual observations.

    Really don’t see how the quote makes sense at all:

    Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude

    1. They claim “highly predictable” whilst asserting “lack of agreement between individual model simulations” and “poor predictive ability of raw model outputs”
    2. They admit “…current models underestimate the predictable signal…of the NAO…by an order of magnitude

    AN ORDER OF MAGNITUDE!

    Maybe that explains why MetOffice/IPCC (a) don’t talk about the NAO upswing cycle from 1910-1940s (because its mostly natural) and (b) assign all of the warming on the upswing cycle from the 1970s onwards to AGW.

  36. I don’t get the point of this study, surely if they improve their predictive skills they will no longer be able to claim:
    “Nobody saw this flood coming coz it’s CO2 wot dunnit”

  37. I used to think that the UK met office was incapable of even predicting weather 24 hours ahead. However after 6 decades of observation I realise they are incapable of accurately describing the current state of the atmosphere or even reading the data from their own radar. Decadal predictions? do me favour.

    • When I woke up yesterday my phone told me the rain would stop in 22 minutes. My eyes told me it sunny and dry. I don’t know which to believe.

  38. When I last looked 80-90% of their yearly temperature forecasts were outside the maximum error bars. They never admitted that. Instead they stopped publishing these forecasts so we couldn’t laugh at them.

    Without admitting their yearly forecasts were a failure, they now claim to be able to forecast on a decadal scale – which just means we’ll all be a decade older when we can laugh at them.

  39. Regardless of the study, the press on it just sounds like something Squealer from Animal Farm wrote.

    “Rejoice, comrades! Our science has determined what the winter will be for the coming decade. It was hard. The scientists found a signal – very faint- but it was there, and using difficult brain work they – after much labor and toil – were able to find it! That is why they need more resources than you. Their brainwork is very hard. They work themselves to the bone, so to speak! But it is all for YOU. All for the glory of Animal Farm.”

  40. The question really is whether this “signal” can detect the the North Atlantic Oscillation (or possibly an extraterrestrial alien invasion) ?

  41. “the study analysed six decades of climate model data and suggests decadal variations in North Atlantic atmospheric pressure patterns (known as the North Atlantic Oscillation) are highly predictable, enabling advanced warning of whether winters in the coming decade are likely to be stormy, warm and wet or calm, cold and dry.

    However, the study revealed that this predictable signal is much smaller than it should be in current climate models. Hence 100 times more ensemble members are required to extract it, and additional steps are needed to balance the effects of winds and greenhouse gases.”

    ????
    They analyzed sixty years of data and with extensive estimate adjustments managed to hindcast sixty years?
    This is worth a press release?
    Utter fools.

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