Friday, October 7, 2016

TempLS Surface temperature down 0.12°C in September

The Moyhu TempLS mesh index fell in September to 0.736°C, down from from 0.855°C in August. That still makes it the hottest September in the record. TempLS grid fell 0.04°C fro 0.785°C to 0.744°C. The recent ups and downs mainly relate to Antarctica, which was very cold in July, very warm (relatively) in August, and about normal (on average) in September. TempLS mesh followed this closely, while TempLS grid regards a lot of Antarctica as missing values, and so downweights the changes. This is reflected in the other indices - GISS and BEST rose like TempLS mesh, while NOAA (0.05°C) and HADCRUT changed mush less. I would expect GISS to also drop this month, but NOAA and HADCRUT maybe not.

In terms of regions, there isn't much unusual outside Antarctica. Siberia, Europe, E US and Alaska fairly warm, with just Australia on the cold side. I can vouch for that, though we were on the fringe of the cold region shown. With other indices, UAH lower trop was steady, while RSS rose by about 0.1. All seem set for a record warm 2016.

On housekeeping, Google says they are looking into the blogroll issues - still out.

The map is below the jump; report at the data page here.

Here is the spherical harmonics plot:



25 comments:

  1. BEST l/o Sept is down by 0.08 from Aug. Not as much as TempLSmesh, but I suspect that the latter (this month) suffer a little from SST being extrapolated over Arctic ice, whereas BEST extrapolates from the relatively warmer nearby met stations

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    1. Olof,
      Thanks for the note about BEST - interesting that BEST, after updating only occasionally, now seems to be first afer TempLS. Yes, it's true that TempLS doesn't control interpolation by source type, although it may be that sea ice should be somewhere between land and SST. Actually BEST had the same rise as TempLS previous month. So it mayb be that, or something else. It's not a big difference.

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    2. I think BEST is too early with their report, when all data isn't in yet. Last month they reported that August was up 0.22 from July, but with the present update the difference is only 0.15.

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  2. Japan has come out with an anomaly down by 0.01 from August. Other agencies will be following shortly.

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  3. Meeting of the cranks at Climate Etc with "Tomas Milanovic" and David Young pushing their agenda of asserting the uselessness of computational climate models.

    e.g. "The atmosphere is far harder of course because the eddy sizes range from 1000 kilometers to the microscopic so direct simulation is truly impossible."

    How little do they know ...

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    1. Since he first showed up there the GMST has gone up by .05 ℃ per year. Chaos bites master.

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    2. Apparently anything bigger a few meters in scale can not be simulated according to this "Tomas" genius.

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  4. Replies
    1. It's like 9 glasses of water a day... there was no scientific basis for it, and it dominated doctors' offices for decades. The IPCC describes the climate as a complex system. In everyday parlance, yes, but in chaos theory complex is a particular thing. Who decided the climate system is complex? What series of studies support that claim?

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    2. JCH asked "Who decided the climate system is complex? What series of studies support that claim?"

      Edward Lorenz decided it was complex according to his definition. That's when the toy problems started to spin out of control. The problem is that just because something is non-linear doesn't make it complexly chaotic.

      I have been working on two problems that are non-linear. First is QBO, which is a non-linear model yet has a strangely simple solution. It is nowhere near chaotic or complex but looks odd to most people's eyes. The second is ENSO, more complex via a nonlinear Mathieu equation, but which has as a solution a transcendental function - again, strange looking but not necessarily chaotic in outcome.

      IMO, there is a huge middle ground that certain aspects of climate science occupy -- somewhere in between the solution to a set of linear differential equations and that of tossing-in-the-towel-because-CHAOS.

      Curry and "Tomas" and their towel-boy Dan Hughes are comically inept at trying to scare people away by flaunting their uncertainty monster. Same with Lindzen, Tsonis, and others with the mess that they created.


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    3. Web - Lorenz was a meteorologist. Weather is complex. Even so, weather models are improving... good hours to three days, less proficient up to 7 days, and bad at 10 and out.

      It appears to me that climate is possibly not complex... in terms of the definition of complex used in chaos theory. I suspect many are assuming that because weather is complex, chaos theory, it automatically follows that climate is complex, chaos theory. But is it really?

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    4. "I suspect many are assuming that because weather is complex, chaos theory, it automatically follows that climate is complex, chaos theory. "
      There is the link that climate models work by generating weather, using a NWP. NWPs solve fluid flow, which is chaotic. But fluid flow is solved by averaging (eg RANS), so there is already a question of whether that removes that particular chaos. The averaged flows still behave chaotically, in the sense of weather being unpredictable for longer than ten days or whatever from initial conditions. But climate averages that, which is expected to overcome that aspect of chaos. Whether it does is really a matter of observation.

      Interesting here is decadal climate prediction, which seems to ask whether if you average a bit less, can you still get prediction on decadal timescales.

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    5. It's clear that weather on Earth is bounded even if chaotic. For example, temperatures in Antarctica in June are never going to be warmer than at sea level at the Equator. In the Uk it is nearly impossible for a December to average warmer than a July. That boundary seems like a good definition of climate. Just establishing the details of the boundary are very difficult.

      Would it make sense to think about climate in terms of probability rather than being strictly deterministic? On a global scale and over so many years there are so many dice throws going on that averaging nearly always returns a close relationship to what would be expected deterministically. It then requires a loading of the dice in some direction to see a change in the average.

      Seen in that way we can't exclude the possibility of an unpredictable climate outcome at some point, it's just spectacularly unlikely. And that's one question I have about what's being said by the likes of Tomas Milanovic and David Young. Are they arguing that climate is fundamentally unpredictable - that the appearance of predictability in the historical record is purely coincidental? Or are they simply arguing that unpredictable outcomes in climate exist within the realms of possibility? The latter I don't think would be hugely controversial.

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    6. Nick said "... fluid flow, which is chaotic"

      It may be that there has been a misguided focus on unconstrained or free fluid flow, as opposed to solving the dynamics of a Newtonian fluid within an enclosing container. Elsewhere in this thread I referenced the Rajchenbach article on Faraday waves.

      There is a telling assertion within that article:

      "For instance, to the best of our knowledge, the dispersion relation (relating angular frequency ω and wavenumber k) of parametrically forced water waves has astonishingly not been explicitly established hitherto. Indeed, this relation is often improperly identified with that of free unforced surface waves, despite experimental evidence showing significant deviations"

      What they are suggesting is that too much focus has been placed on natural resonances and the dispersion relationships within a free fluid volume. Whereas the forced response is clearly as important if not more, and that the forcing will show through in the solution of the equations. I have been pursuing this strategy for a few years now, and the Rajchenbach article is the first case that I have found made of what I always thought should be an obvious premise. That's a peer-reviewed article and the fact that the reviewers allowed the "astonishingly" adjective in the paper is what makes it telling. It's astonishing in the equivalent sense that Rajchenbach & Clamond are pointing out that a pendulum's motion will be impacted by a periodic push. Astonishing in the sense that it should be patently obvious! Read through it and see if you come up with a similar understanding.

      The issue is that Tomas Milanovic and David Young and Lindzen and Tsonis don't want anything simplified or understand, as that goes against their political philosophies. This paper will not sit well with them.

      Chubbs and PaulS are exactly right in identifying seasonality as a fundamental driving force. What I am finding is that in the cases of ENSO and QBO, the seasonality does not jump out at you, but in fact is mixed into the stew and is not revealed by conventional methods. What you need are a good model of the physics and novel means of extracting the parameters from the dynamics. That's why it hasn't been obvious over the years, and the continuing claim being made that ENSO and QBO are driven by natural/chaotic resonances lives on ...

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    7. > Would it make sense to think about climate in terms of probability rather than being strictly deterministic?

      I think we could, in the same sense that we could classify Chess among stochastic games. Sometimes it's useful to do so:

      http://rutcor.rutgers.edu/~gurvich/BackGammon.pdf

      Sometimes it's only convenient to wave your arms around and declare that everything is so chaotic.

      Willard (@nevaudit)

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    8. Open that Backgammon PDF up and the first thing I see is mention of game theory. That's psychological reasoning and there is obviously no solution for that. So it has absolutely zero to do with climate science.


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    9. Weather: rain, snow, winds, daily max, daily min, sunny, cloudy, warm front, cold front, storms, etc. ... chaotic. Initial conditions... predictable by model to three days, less predictable to 5-7 days, and essentially unpredictable at 10 days and out.

      What are the climate's equivalents of the weather events that make up a standard weather forecast? Is the Younger Dryas the equivalent of a 3-day blizzard in North Dakota, or a 3-day blizzard in Cuba?

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    10. "What are the climate's equivalents of the weather events that make up a standard weather forecast? "

      Has to be ENSO. The claim is that they can't predict that much more than a year or two in advance.

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    11. ENSO is weather. Weather cannot reliably be predicted beyond 3-to-5 days. Right now some models predict a weak La Niña before the end of this year. I would say the earlier ENSO forecast/prediction for 2016 can fairly be characterized as being wrong. They don't have much experience with the positive phase of the PDO. They thought they were seeing that in the last decade or two; I don't think they were.

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    12. "ENSO is weather"

      Actually ENSO is geophysics. Its the interaction of a rotating contained fluid with external gravitational forces. Whatever weather derives from it is a pure side-effect.

      More on the "astonishingly" claim


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    13. Well, a lot of weather derives directly, and indirectly, from ENSO. The fact is, nobody at this time is reliably forecasting ENSO.

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    14. JCH said:
      "The fact is, nobody at this time is reliably forecasting ENSO."

      To be able to forecast anything, you have to first understand it. Most current weather forecasts are at the level of heuristics. A heuristic doesn't have to be based on science but only on the fact that it has worked sufficiently well in the past. The heuristic is obviously pretty bad for ENSO because the best I have seen works for only a few months in advance. IOW, it's essentially at the level of "slow train coming", to quote Dylan.

      That is changing for ENSO as we are developing a much better physical model. In this post, I include some ideas from the latest research on wave dynamics.

      The central premises to making the model work include:

      1. A biennial mode is assumed operating based on the doubling of the annual period.

      2. A phase inversion occurs between 1980 and 1996, justified by metastability of the biennial model with respect to even and odd starting years.

      3. Mathieu equation formulation for sloshing behavior.

      4. A right-hand-side (RHS) forcing due to known angular momentum and gravity terms, with additional seasonal aliasing of the tidal terms.

      Given the quality of the results, it won't be long before our understanding of ENSO approaches that of oceanic tides, and we know how well tides can be forecasted. That's essentially predictable for many years in advance, with precision down to the hour. In fact, anything even close to this will be a boon. Take a look at the detail of the fits in the linked post and you can see the potential predictability.

      BTW, I will present this research along with the equally impressive QBO results at the American Geophysical Union meeting this December.

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    15. I've been following the work you are doing.

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  5. JCH said "Lorenz was a meteorologist."

    Labels don't mean anything. No one would say that Pierre Laplace was anything but a mathematician, yet he came up with a model over 200 years ago that is still used by climatologists today. Apply his model and out pops how QBO works. Lorenz's face would be red, not to mention Lindzen's.

    Everything is driven by boundary conditions, and that is what always tends to realign and resynch various climate oscillations.

    Read this by some modern-day Frenchmen: http://contextearth.com/wp-content/uploads/2016/10/rajchenbach2015.pdf





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  6. The evidence from data and models indicates that climate is highly predictable. Just like the seasons, temperature follows changes in forcing. A big non-linearity is not going to come from chaos in fluid flow because there is a restoring force, as evidenced by the long-term stability over the Holocene. Instead surprises will come from a crossing a threshold leading to ice sheet collapse or some other big change in the fluid boundary condition.

    Chubbs

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