Some people cite scientists saying there is a “CO2 control knob” for Earth. No doubt there is, but due to the logarithmic effect of CO2, I think of it like a fine tuning knob, not the main station tuner. That said, a new data picture is emerging of an even bigger knob and lever; a nice bright yellow one.
A few months back, I found a website from NOAA that provides an algorithm and downloadable program for spotting regime shifts in time series data. It was designed by Sergei Rodionov of the NOAA Bering Climate and Ecosystem Center for the purpose of detecting shifts in the Pacific Decadal Oscillation.
Regime shifts are defined as rapid reorganizations of ecosystems from one relatively stable state to another. In the marine environment, regimes may last for several decades and shifts often appear to be associated with changes in the climate system. In the North Pacific, climate regimes are typically described using the concept of Pacific Decadal Oscillation. Regime shifts were also found in many other variables as demonstrated in the Data section of this website (select a variable and then click “Recent trends”).
But data is data, and the program doesn’t care if it is ecosystem data, temperature data, population data, or solar data. It just looks for and identifies abrupt changes that stabilize at a new level. For example, a useful application of the program is to look for shifts in weather data, such as that caused by the PDO. Here we can clearly see the great Pacific Climate Shift of 1976/77:
Another useful application is to use it to identify station moves that result in a temperature shift. It might also be applied to proxy data, such as ice core Oxygen 18 isotope data.
But the program was developed around the PDO. What drives the PDO? Many say the sun, though there are other factors too. It follows to reason then the we might be able to look for solar regime shifts in PDO driven temperature data.
Alan of AppInSys found the same application and has done just that, and the results are quite interesting. The correlation is well aligned, and it demonstrates the solar to PDO connection quite well. I’ll let him tell his story of discovery below. – Anthony
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Climate Regime Shifts
The notion that climate variations often occur in the form of ‘‘regimes’’ began to become appreciated in the 1990s. This paradigm was inspired in large part by the rapid change of the North Pacific climate around 1977 [e.g., Kerr, 1992] and the identification of other abrupt shifts in association with the Pacific Decadal Oscillation (PDO) [Mantua et al., 1997].” [http://www.beringclimate.noaa.gov/regimes/Regime_shift_algorithm.pdf]
Pacific Regime Shifts
Hare and Mantua, 2000 (“Empirical evidence for North Pacific regime shifts in 1977 and 1989”): “It is now widely accepted that a climatic regime shift transpired in the North Pacific Ocean in the winter of 1976–77. This regime shift has had far reaching consequences for the large marine ecosystems of the North Pacific. Despite the strength and scope of the changes initiated by the shift, it was 10–15 years before it was fully recognized. Subsequent research has suggested that this event was not unique in the historical record but merely the latest in a succession of climatic regime shifts. In this study, we assembled 100 environmental time series, 31 climatic and 69 biological, to determine if there is evidence for common regime signals in the 1965–1997 period of record. Our analysis reproduces previously documented features of the 1977 regime shift, and identifies a further shift in 1989 in some components of the North Pacific ecosystem. The 1989 changes were neither as pervasive as the 1977 changes nor did they signal a simple return to pre-1977 conditions.”
[http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V7B-41FTS3S-2…]
Overland et al “North Pacific regime shifts: Definitions, issues and recent transitions”
[http://www.pmel.noaa.gov/foci/publications/2008/overN667.pdf]: “climate variables for the North Pacific display shifts near 1977, 1989 and 1998.”
The following figure from the above paper show analysis of PDO and Victoria Index using the Rodionov regime detection algorithm. A regime shift is also detected around 1947-48.
The following figure shows regime shift detection for the summer PDO, showing shifts at 1948, 1976 and 1998.
[http://www.beringclimate.noaa.gov/data/Images/PDOs_FigRegime.html]
(For detailed information on the 1976/77 climate shift,
see: http://www.appinsys.com/GlobalWarming/The1976-78ClimateShift.htm)
Regime Shift Detection in Annual Temperature Anomaly Data
The NOAA Bering Climate web site provides the algorithm for regime shift detection developed by Sergei Rodionov [http://www.beringclimate.noaa.gov/regimes/index.html]. The following analyses use the Excel VBA regime change algorithm version 3.2 from this web site.
The following figure shows the regime analysis of the HadCRUT3 annual global annual average temperature anomaly data from the Met Office Hadley Centre for 1895 to 2009 [http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/annual].
The analysis was run based on the mean using a significance level of 0.1, cut-off length of 10 and Huber weight parameter of 2 using red noise IP4 subsample size 6. Regime changes are identified in 1902, 1914, 1926, 1937, 1946, 1957, 1977, 1987, and 1997. Running the analysis based on the variance rather than the mean results in regime changes in the bold years listed above.
Regime Shift Relationship to Solar Cycle
The NASA Solar Physics web site provides the following figure showing sunspot area.
[http://solarscience.msfc.nasa.gov/SunspotCycle.shtml]
The following figure compares the Hadley (HadCrut3) monthly global average temperature (from [http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/]) overlaid with the regime change line (red line) shown previously, along with the sunspot area since 1900. The sunspot cycle is approximately 11 years. The sun’s magnetic field reverses with each sunspot cycle and thus after two sunspot cycles the magnetic field has completed a cycle – a Hale Cycle – and is back to where it started. Thus a complete magnetic sunspot cycle is approximately 22 years. The figure marks the onset of odd-numbered cycles with a vertical red line, even-numbered cycles with a green line.
From the figure above it can be seen that the regime changes correspond to the onset of solar cycles and occur when the “butterfly” is at its widest. The most significant warming regime shifts occur at the start of odd-numbered cycles (1937, 1957, 1977, 1997). Each odd-numbered cycle (red lines above) has resulted in a temperature-increase regime shift. Even-numbered cycles (green lines above) have been inconsistent, with some resulting in temperature-decrease regime shifts (1902, 1946) or minor temperature-increase shifts (1926, 1987).
An unusual one is the 1957 – 1966 cycle, which in the monthly data shown above visually looks like a temperature-increase shift in 1957 followed by a temperature-decrease shift in 1964 but the regime detection algorithm did not identify it. This is likely due to the use of annually averaged data in the regime detection algorithm.
The following figure shows the relative polarity of the Sun’s magnetic poles for recent sunspot cycles along with the solar magnetic flux [www.bu.edu/csp/nas/IHY_MagField.ppt]. The regime change periods are highlighted by the red and green boxes. Each one occurs on as the solar cycle is accelerating. The onset of an odd-numbered sunspot cycle (1977-78, 1997-98) results in the relative alignment of the Earth’s and the Sun’s magnetic fields (positive North pole on the Sun) allowing greater penetration of the geomagnetic storms into the Earth’s atmosphere. “Twenty times more solar particles cross the Earth’s leaky magnetic shield when the sun’s magnetic field is aligned with that of the Earth compared to when the two magnetic fields are oppositely directed” [http://www.nasa.gov/mission_pages/themis/news/themis_leaky_shield.html]
The following figure shows the longitudinally averaged solar magnetic field. This “magnetic butterfly diagram” shows that the sunspots are involved with transporting the field in its reversal. The Earth’s temperature regime shifts are indicated with the superimposed boxes – red on odd numbered solar cycles, green on even.
[http://solarphysics.livingreviews.org/open?pubNo=lrsp-2010-1&page=articlesu8.html]
The Earth’s temperature regime shift occurs as the solar magnetic field begins its reversal.
Solar Cycle 24
Solar cycle 24 is in its initial stage after getting off to a late start. An El Nino occurred in the first part of 2010. This may be the start of the next regime shift.
Climate Regime Shifts
[last update: 2010/07/04]
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“The notion that climate variations often occur in the form of ‘‘regimes’’ began to become appreciated in the 1990s. This paradigm was inspired in large part by the rapid change of the North Pacific climate around 1977 [e.g., Kerr, 1992] and the identification of other abrupt shifts in association with the Pacific Decadal Oscillation (PDO) [Mantua et al., 1997].” [http://www.beringclimate.noaa.gov/regimes/Regime_shift_algorithm.pdf]
|
|
Pacific Regime Shifts
Hare and Mantua, 2000 (“Empirical evidence for North Pacific regime shifts in 1977 and 1989”): “It is now widely accepted that a climatic regime shift transpired in the North Pacific Ocean in the winter of 1976–77. This regime shift has had far reaching consequences for the large marine ecosystems of the North Pacific. Despite the strength and scope of the changes initiated by the shift, it was 10–15 years before it was fully recognized. Subsequent research has suggested that this event was not unique in the historical record but merely the latest in a succession of climatic regime shifts. In this study, we assembled 100 environmental time series, 31 climatic and 69 biological, to determine if there is evidence for common regime signals in the 1965–1997 period of record. Our analysis reproduces previously documented features of the 1977 regime shift, and identifies a further shift in 1989 in some components of the North Pacific ecosystem. The 1989 changes were neither as pervasive as the 1977 changes nor did they signal a simple return to pre-1977 conditions.” [http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V7B-41FTS3S-2…]
Overland et al “North Pacific regime shifts: Definitions, issues and recent transitions” [http://www.pmel.noaa.gov/foci/publications/2008/overN667.pdf]: “climate variables for the North Pacific display shifts near 1977, 1989 and 1998.”
The following figure from the above paper show analysis of PDO and Victoria Index using the Rodionov regime detection algorithm. A regime shift is also detected around 1947-48.
The following figure shows regime shift detection for the summer PDO, showing shifts at 1948, 1976 and 1998. [http://www.beringclimate.noaa.gov/data/Images/PDOs_FigRegime.html]
(For detailed information on the 1976/77 climate shift, see: http://www.appinsys.com/GlobalWarming/The1976-78ClimateShift.htm)
|
|
Regime Shift Detection in Annual Temperature Anomaly Data
The NOAA Bering Climate web site provides the algorithm for regime shift detection developed by Sergei Rodionov [http://www.beringclimate.noaa.gov/regimes/index.html]. The following analyses use the Excel VBA regime change algorithm version 3.2 from this web site.
The following figure shows the regime analysis of the HadCRUT3 annual global annual average temperature anomaly data from the Met Office Hadley Centre for 1895 to 2009 [http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/annual].
The analysis was run based on the mean using a significance level of 0.1, cut-off length of 10 and Huber weight parameter of 2 using red noise IP4 subsample size 6. Regime changes are identified in 1902, 1914, 1926, 1937, 1946, 1957, 1977, 1987, and 1997. Running the analysis based on the variance rather than the mean results in regime changes in the bold years listed above.
|
|
Regime Shift Relationship to Solar Cycle
The NASA Solar Physics web site provides the following figure showing sunspot area. [http://solarscience.msfc.nasa.gov/SunspotCycle.shtml]
The following figure compares the Hadley (HadCrut3) monthly global average temperature (from [http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/]) overlaid with the regime change line (red line) shown previously, along with the sunspot area since 1900. The sunspot cycle is approximately 11 years. The sun’s magnetic field reverses with each sunspot cycle and thus after two sunspot cycles the magnetic field has completed a cycle – a Hale Cycle – and is back to where it started. Thus a complete magnetic sunspot cycle is approximately 22 years. The figure marks the onset of odd-numbered cycles with a vertical red line, even-numbered cycles with a green line.
From the figure above it can be seen that the regime changes correspond to the onset of solar cycles and occur when the “butterfly” is at its widest. The most significant warming regime shifts occur at the start of odd-numbered cycles (1937, 1957, 1977, 1997). Each odd-numbered cycle (red lines above) has resulted in a temperature-increase regime shift. Even-numbered cycles (green lines above) have been inconsistent, with some resulting in temperature-decrease regime shifts (1902, 1946) or minor temperature-increase shifts (1926, 1987).
An unusual one is the 1957 – 1966 cycle, which in the monthly data shown above visually looks like a temperature-increase shift in 1957 followed by a temperature-decrease shift in 1964 but the regime detection algorithm did not identify it. This is likely due to the use of annually averaged data in the regime detection algorithm.
The following figure shows the relative polarity of the Sun’s magnetic poles for recent sunspot cycles along with the solar magnetic flux [www.bu.edu/csp/nas/IHY_MagField.ppt]. The regime change periods are highlighted by the red and green boxes. Each one occurs on as the solar cycle is accelerating. The onset of an odd-numbered sunspot cycle (1977-78, 1997-98) results in the relative alignment of the Earth’s and the Sun’s magnetic fields (positive North pole on the Sun) allowing greater penetration of the geomagnetic storms into the Earth’s atmosphere. “Twenty times more solar particles cross the Earth’s leaky magnetic shield when the sun’s magnetic field is aligned with that of the Earth compared to when the two magnetic fields are oppositely directed” [http://www.nasa.gov/mission_pages/themis/news/themis_leaky_shield.html]
The following figure shows the longitudinally averaged solar magnetic field. This “magnetic butterfly diagram” shows that the sunspots are involved with transporting the field in its reversal. The Earth’s temperature regime shifts are indicated with the superimposed boxes – red on odd numbered solar cycles, green on even. [http://solarphysics.livingreviews.org/open?pubNo=lrsp-2010-1&page=articlesu8.html]
The Earth’s temperature regime shift occurs as the solar magnetic field begins its reversal.
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Solar Cycle 24
Solar cycle 24 is in its initial stage after getting off to a late start. An El Nino occurred in the first part of 2010. This may be the start of the next regime shift.
|
BarryW says:
July 5, 2010 at 5:09 am
Mosh
“I agree with you up to a point, but when you can hit parameters that match ten times in a row as opposed to the CO2 modeling with has to jump though hoops to even get close I find it a compelling argument.”
That’s why I note that this numerology is more interesting than other numerology.
WRT C02 “modelling”. I’ll take this as an inexact reference to GCMs. As far as models go GCMs Kick the BEJESUS out of any of these “toy” approaches. I don’t tire of asking:
1. How well does this model hindcast the past.
2. how well does this model predict precipitation.
etc..
The point being a GCM attempts to simulate the entire climate process. The model above does ONE THING. it shows that regime “shifts” are aligned. That’s it. No predictions about precipitations, about temperature LEVELS, etc. The other issue is one of falsifiability.
“Your UHI comment is also off base since it affects the trend, not the steps. I’d like to see the algorithm applied to a detrended data set.”
I’m not so easily convinced. The other issue is that the instructions for the program ( its been two years since I played with it ) suggested using variance when the measures were means from zero. In short, use variance when your dealing with an anomaly series. Somebody can go check the instructions. In any case, regime shift analysis is not a magic wand. It doesnt answer the basic fundamental question of “HOW” how do changes in this, product changes in that. It can give you a PATH for investigation, but it’s nothing more than that.
Finally, I’m ever amused by people who want to
1. Say there is no warming, and then try to explain the warming seen in the record
to the sun.
2. Say the record cannot be accurate to .1C and then embrace analysis that depends
upon detecting shifts of .1C
Innocentious says:
July 5, 2010 at 8:54 am
The real problem is that ‘temperatures’ correlate with CO2 rise and no matter how much it is shown that there is not a constant correlation, or question whether we are measuring temperature correctly it is almost impossible to separate the one from the other at this point in time. Perhaps that is all we need in the end, another century of observation to truly understand the role of CO2. In the meantime we will just have to put up with people who are on the gravy train.
______________________________________________
You are making the assumption that CO2 is an independent variable driving temperature. There is plenty of data from many sources that show it is not. To name just two:
As temperature rises you get more plant growth. The higher the temp AND CO2 the more absorbed by plants and the faster they grow, lowering the amount of CO2.
As the temperature rises the amount of CO2 that can be absorbed by water decreases.
If you’re an R fan you can do this yourself at home.
Install the package “strucchange”. Download Hadcrut3 (http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/monthly) and make a time-series object of it. Then run ‘breakpoints’ with h=0.05 (because the best solution is 13 segments). You’ll get much the same answers as above but also back to 1850. Unlike the one above, though, you get confidence intervals for the break points. They’re really tight for all the points after 1900. And the only parameter to tweak is the minimal segment size so you get a definite best model. I guess regime change algorithms will do fundamentally the same things but I find it interesting that two different methods give very similar answers.
I’ve got a picture but no idea how to include it.
hi tallbloke
“Has it occurred to Steven Mosher it might just be that the parameters fit the data because Alan Cheetham has zoomed in on the correct parameter values?”
There is no such thing as the correct parameters for detecting regime shifts. Just take a look at the underlying approach and you’ll see that’s its a form of data mining. In the end you cannot attribute any confidence to the overall result. It’s an investigative tool.
WRT the numerology insult. Of course numerologists will be insulted. But people who understand that science depends upon explanation will not be offended.
two sets of numbers are shown to have some sort of “similarity”. they “line up”. they “track each well”, they “correlate.” That’s an observation about NUMBERS.
Its’ not a physical theory. A physical theory would propose a mechanism and be testable. The numerology games of finding similarities between time series is a wonderful hobby. I find it amusing that people who claim the climate is too chaotic to predict or understand, will gladly accept a huge oversimplification if it matches their preconceptions about the role of the sun.
So, just to recap. The regime change approach gives you a place to START real science. It’s not a physical theory. without a physical theory its just numerology. Fun with numbers.
idlex says:
July 5, 2010 at 6:30 am
idlex, I like the way you’re approaching the problem. The model you describe for the input/output energy for the CO2 molecules is just the way I visualize the situation. The little computer simulation you describe would likely be just the first step in a long model simulation because from what I’ve read here, the feedback or secondary effects from CO2 re-radiation are the real drivers of overall global temperatures.
One thing that sticks in my mind is the fairly recent NASA images of CO2 in the atmosphere being “clumpy”. The images created show CO2 concentrations looking like floating hot dogs in the sky. These images make me think that drawing a Gaussian surface around the distinct clumps of CO2 and then assuming an evenly distributed re-radiation from the Gaussian surface would imply that a smaller percent of the energy would be directed back toward the earths surface. The majority of the energy leaving the surface would miss the earth and be lost to space. The devil will be in the details i.e. feedbacks.
Amino Acids in Meteorites says:
July 5, 2010 at 1:55 am
Steven mosher says:
July 5, 2010 at 1:41 am
Why is it when the sun influencing climate comes up it is shot down? The earth is in the sun’s atmosphere. Changes in the sun must make for changes on the earth. It doesn’t make sense that it would have no effect.
***************************************************************
Excellent point. I don’t, and leif does not, argue that the sun has No influence. That’s just a strawman.
1. Changes in the sun must make for changes on the earth.
This is so vague as to be “untestable” Which changes? that’s the first question.
The second question is the “MUST” question. There is no LOGICAL NECESSITY.
you have a reasonable assumption that changes there MAY lead to changes here.
The proper way to proceed is to establish a testable hypothesis.
2. It makes perfect sense that some changes would have no effect. Drop a ball
from your rooftop. measure the time to impact. Now change the mass of the ball.
That change should have an effect right?
So just to be clear. It seems perfectly reasonable to assume that some changes in the sun will lead to changes in the climate here. The issue is this. There is a difference between:
A. Observing an interesting relationship between two sets of data. A nice hobby.
B. Constructing a physical theory based on laws of physics that allows you to
EXPLAIN and QUANTIFY how changes in one time series produces changes in the other.
“A” is numerology. Sometimes good science starts with numerology. It never ENDS with numerology. It ends with B.
So, I see some interesting numbers in this post. Maybe somebody will create a physical theory that spits out predictions about the climate from this interesting fact about numbers.
(Leif will get this.) These types of ‘studies’ are merely and soley studies about ‘numbers’ and not what those numbers represent. That’s why I call them numerology. Because they are literally ABOUT NUMBERS.
REPLY: Mosh is right. Without the physical mechanism, the cause and effect becomes numeric speculation. All sorts of science began by finding patterns of numbers in data, quantifying it, and then proposing and finally proving a physical mechanism. This is no different. However, some other work is going to have to be done to establish the physical mechanism. While it would be tempting to imagine a giant Hurst Helios gear-shifter, it is much more nuanced than that 😉 – Anthony
It’s a “little cooling” in figure 3 since 2005?
http://www.beringclimate.noaa.gov/bering_status_overview.html
Interesting, isn’t? Would be a shift?
Leif Svalgaard says:
July 5, 2010 at 10:00 am
The Sunspot activity is slipping behind 1900. Just like your SC19 vs SC24 graph, SC23 came in lower and SC24 goes out lower than the 1900’s episode. This falling behind behavior has been a hallmark consistency of SC24.
The planet is in the process of cooling right now.
The bad thing is that certain scientists made a deal with the devil as far as the weather records go, so the compromised HADcrut3 will have to do.
When the climate records are searched out and put right (talk to Dr. Curry), then we will have a much better chance at answering global questions. In the meantime, we have the doctored climate records we have, not the ones we wish were not spoiled or sold for profits.
Mosh>
Do you always have to be so forthright? I see you popping up all over the place, and whilst you generally have a point, you also generally insist on smashing people over the head with it instead of discussing it politely. Standard MO in all these debates, though – you’re hardly alone. Please try not to do it, and we’ll all benefit.
I agree with you that ‘numerology’ is technically accurate, but it’s akin to calling someone ‘fat’ to their face. You may need to refer to their size, but there are ways to say it that don’t rub people up the wrong way.
The point for discussion is of course how much weight to put on this matter at this stage. On the basis solely of this one article, there’s no more than a ‘dig here’, but it’s interesting to see how these results came into being.
My personal opinion, based on little evidence bar a strong hunch, is that these graphs are too good to be true, and so if they show either that there is an incredibly strong correlation between solar activity and climate, or that the research tool will bring out pretty results appropriate for any theory you care to run through it, then I find the latter far more plausible in context, especially considering the unreliability of Hadcrut.
I know this is a bit off topic, but why are we showing the HADCRUT Global Temp anomaly of the Hadley Center??? Its obvious that Graph has been adjusted (Manipulated) over, and Over again, Mainly Before The Sattelite Era so why are we Using it to compare solar anomalies that could Match up better without the adjustments?? Maybe I’m Missing Something HUGE, and If so, I’m Sorry for Acting Like a complete Idiot.
Cheers,
Philly
Steve mosher (1:41): “it it became clear that I could tune the thing to fit my assumptions. Hint: if he set the cuttoff length at 11 instead of 10 the trick would have been too obvious.”
The cutoff length by definition does affect the results – that’s because the cutoff limit causes it to ignore any regimes shorter than the defined cutoff limit. Choosing a cutoff that is longer than solar cycles will by definition prevent the solar cycles from being identified. Using 11 instead of 10 makes only a slight change – in the 1914 – 1930 time frame when the solar sysles are weaker.
View this to see the effect of the cutoff length and noise parameters: http://www.appinsys.com/GlobalWarming/RegimeParams.htm
Re: Use of Hadcrut3 data: I tend to use the “official” data as much as possible. Even though it is adjusted and manipulated, using it removes the potential criticisms of selecting a data set to match the desired outcome.
REPLY: Supposedly HadCRUT is being “reworked” as a result of Climategate. You’ll be able to run it again when/if it becomes available. Weather balloon data might be another choice in the meantime. – Anthony
Dave (11:06): “these graphs are too good to be true, and so if they show either that there is an incredibly strong correlation between solar activity and climate, or that the research tool will bring out pretty results appropriate for any theory you care to run through it”
The Hadcrut3 data is easily downloaded from the link in the article; the algorithm is easily downloaded from its link in the article. Anyone can easily experiment with this. Use the algorithm right “out of the the box” (i.e. without adjusting anything) and you will see virtually the same results (only difference is in the 1914-1930 time frame when the solar cycles are weaker). Add their recommended noise filter and you get the results I have described. Try it. (Also see my previous response to mosher about the cutoff length.)
tallbloke:
Some stuff here about the jets having been in different latitudinal positions during the LIA:
http://www2.sunysuffolk.edu/mandias/lia/little_ice_age.html
“During the LIA, there was a high frequency of storms. As the cooler air began to move southward, the polar jet stream strengthened and followed, which directed a higher number of storms into the region. At least four sea floods of the Dutch and German coasts in the thirteenth century were reported to have caused the loss of around 100,000 lives. Sea level was likely increased by the long-term ice melt during the MWP which compounded the flooding. Storms that caused greater than 100,000 deaths were also reported in 1421, 1446, and 1570. Additionally, large hailstorms that wiped out farmland and killed great numbers of livestock occurred over much of Europe due to the very cold air aloft during the warmer months. Due to severe erosion of coastline and high winds, great sand storms developed which destroyed farmlands and reshaped coastal land regions. Impact of Glaciers
During the post-MWP cooling of the climate, glaciers in many parts of Europe began to advance. Glaciers negatively influenced almost every aspect of life for those unfortunate enough to be living in their path. Glacial advances throughout Europe destroyed farmland and caused massive flooding. On many occasions bishops and priests were called to bless the fields and to pray that the ice stopped grinding forward (Bryson, 1977.) Various tax records show glaciers over the years destroying whole towns caught in their path. A few major advances, as noted by Ladurie (1971), appear below.”
There are also ships logs showing storms well equatorward of those seen during the past 50 years and the Viking settlements in Greenland suggest the polar jet well poleward at that time.
So, lots of bits of data from a wide range of sources and evidence that the ITCZ was similarly involved so here’s a google search result for your use.
http://search.orange.co.uk/all?q=ITCZ+Little+Ice+Age&brand=ouk&tab=web&p=searchbox&pt=home_web&home=false&x=27&y=17
Leif (8:17: “At least try to get the facts straight: The reversal of the polar fields at the maximum of the even-numbered cycles results in the alignments, thus half a cycle before the offset.”
Not sure what facts you are referring to. If you look at the figure showing the longitudinally averaged solar magnetic field from 1975 – 2010 you can see when the field is polarized and when it starts its trend to reversal (i.e. the maximum subspot area occurs when the field is reversing at the suns equator).
Regarding the empirical aspect of this reasearch (since numerology is an inappropriate term here if you actually look up its definition)
Science is often empirical – starting with observations of a phenomenon. The lack of a known mechanism does not invalidate the observations.
If we had longer-term observations of various parameters (such as coronal mass ejections or magnetic clouds) we might be able to get closer to the mechanism.
A study of solar magnetic clouds during 1994 – 2002 by Wu, Lepping & Gopalswamy, “Solar Cycle Variations of Magnetic Clouds and CMEs” http://www.scostep.ucar.edu/archives/scostep11_lectures/Pap.pdf states: “The average occurrence rate is 9 magnetic clouds per year for the overall period (68 events/7.6 years). It is found that some of the frequency of occurrence anomalies were during the early part of Cycle 23: 1. Only 4 magnetic clouds were observed in 1999, and 2. An unusually large number of magnetic clouds (16 events) were observed in 1997 in which the Sun was beginning the rising of Cycle 23”
Steven mosher says:
July 5, 2010 at 10:36 am
I find it amusing that people who claim the climate is too chaotic to predict or understand, will gladly accept a huge oversimplification if it matches their preconceptions about the role of the sun.
But, but: D.A. claims it’s so simple that anybody can do it [even he].
Alan Cheetham says:
July 5, 2010 at 11:44 am
Leif (8:17: “At least try to get the facts straight: The reversal of the polar fields at the maximum of the even-numbered cycles results in the alignments, thus half a cycle before the offset.”
Not sure what facts you are referring to.
Read the article. It claims “The onset of an odd-numbered sunspot cycle (1977-78, 1997-98) results in the relative alignment of the Earth’s and the Sun’s magnetic fields” which is incorrect. But, perhaps, inaccuracies don’t matter much in this debate.
Flavio Feltrim says:
July 5, 2010 at 10:56 am
It’s a “little cooling” in figure 3 since 2005?
http://www.beringclimate.noaa.gov/bering_status_overview.html
Interesting, isn’t? Would be a shift?
___________________________________________________________
Am I missing something here???
The article says:
”In the past, the Bering Sea was known for large differences in weather conditions from year-to-year. Change in the last five years is characterized by the persistence in warm ocean temperatures and lack of sea ice in the southern Bering Sea. Without sea ice, the ocean can absorb more solar energy and provides resistance to ice formation in the following winter. There may be additional warm ocean temperatures brought by currents from the Gulf of Alaska. The changes in the Bering Sea are part of a large regional climate change from Siberia eastward to northern Canada. Thus, while it is impossible to predict future climate, the balance of the evidence suggests a continuation of current conditions. “
Yet the referenced graph shows the maximum (and minimum) temperatures has DECREASED for the last four years. Don’t they even bother to look at their own graphs?
Alan Cheetham says:
July 5, 2010 at 11:58 am
A study of solar magnetic clouds during 1994 – 2002 by Wu [..] “An unusually large number of magnetic clouds (16 events) were observed in 1997 in which the Sun was beginning the rising of Cycle 23”
unusual? for the short interval 1994-2002? What other rising cycles were there in 1994-2002 to compare with to make the statement that 1997 was unusual?
phil says:
July 5, 2010 at 11:07 am
You can always use this formula (and the idea of sorting according to solar cycle lengths) to check on your local climate area data. Data which you can check out by careful comparison with provenance.
After all, the most important piece of climate is where you live.
Enneagram says:
July 5, 2010 at 10:17 am
magnetism is produced by electrical fields
You are saying this is the mechanism?
Alan
I think it is an interesting analytical tool but as a hypothesis is a non starter.
I would like to see it backdated to 1650, we got sunspot numbers andthe Met Office CETs data.
As you can see here (bottom graph)
http://www.vukcevic.talktalk.net/CETlmt.htm
there was a very sharp jump in temperatures from 1685 to 1700 with no sunspots to speak off, no ‘gears to be shifted’.
In contrast period from 1740 to near 1900, there is a lot of solar activity, ‘plenty of gears’, but CETs barely moved relative to the late 1600’s and the early and late 1900’s.
For credibility you have to come up with something covering at least the known data range, not to mention the transfer mechanism!
Follow the money or follow the Sun?…That’s the question!☺
Gail Combs says:
July 5, 2010 at 12:04 pm
Yet the referenced graph shows the maximum (and minimum) temperatures has DECREASED for the last four years. Don’t they even bother to look at their own graphs?
Like they want you to accept the very opposite to the facts right before your eyes, but…
I SEE FOUR LIGHTS!
Steven mosher says:
July 5, 2010 at 10:54 am
So just to be clear. It seems perfectly reasonable to assume that some changes in the sun will lead to changes in the climate here. The issue is this. There is a difference between:
A. Observing an interesting relationship between two sets of data. A nice hobby.
B. Constructing a physical theory based on laws of physics that allows you to
EXPLAIN and QUANTIFY how changes in one time series produces changes in the other.
This explanation has a different feel to it then just calling it numerology. I think it was 1:30 am when you posted the numerology comment so at that hour you may not have wanted to expound. But now with this comment I can see I agree with you much more than I did last night.
Anthony’s explanation helped clear it up too:
REPLY: Mosh is right. Without the physical mechanism, the cause and effect becomes numeric speculation. All sorts of science began by finding patterns of numbers in data, quantifying it, and then proposing and finally proving a physical mechanism. This is no different. However, some other work is going to have to be done to establish the physical mechanism. While it would be tempting to imagine a giant Hurst Helios gear-shifter, it is much more nuanced than that 😉 – Anthony