Guest Post by Willis Eschenbach
The lack of cycles in the solar wind isn’t surprising when you analyze this paper. There is very little sign of any kind of annual cycle, which makes perfect sense because the sun doesn’t run by earthly clocks … the sun doesn’t know much about “one year for earthlings”.
Over at the Hockey Schtick, I saw a post discussing a new study (paywalled here) of the solar wind as a possible amplifying mechanism for the sun’s effect on climate. It’s called “Effects on winter circulation of short and long term solar wind changes”, by Zhou, Tinsley, and Huang (hereinafter ZTH2014). To support their hypothesis that solar wind affects the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO), they’ve stacked the records of times of low solar wind, aligned at the minimum in the wind speed. Well, not exactly the minimums of the wind speed, come to find out it’s the minimums of a most strange triangular filter of the wind speed. But only in the winter, not the summer. Well, not exactly the winter, but the five month period November-May. Then they sub-divided the stacks into times of “low volcanic activity” and “high-volcanic activity”. Then they further subdivided them into times when the interplanetary magnetic field (IMF) points up, and times when the IMF points down … seems like waterboarding the data to me, but I was born yesterday, what do I know? Here’s their money graph:
Figure 1. Fig. 2 from ZTH2014. “Stacked” analysis aligned on the minima of the solar wind speed in the winter months. “SWS_MIN” means minimum solar wind speed.
Figure 1 shows the claim they are making, that on a daily level the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) are affected by minima in the solar wind. Looking at the Hockey Schtick article, I realized I didn’t know much at all about the solar wind. I mean, I knew what most folks know, that the solar wind is the result of constantly varying high-speed ejection of a variety of charged particles from the sun. But I didn’t know how it changed over time, how fast it blew, what a solar wind gust or a gale looked like, nothing. So here’s what I found out.
As usual, I started by getting all the data. It took some digging, but I finally found the hourly data here. Of course, it’s in the form of a whole stack of individual files, one per year from 1963 to 2014 … so I had to write the code to download them all, and then extract the information I wanted. I ended up with 324,204 hourly observations of solar wind. I averaged them out day by day, to match the time intervals of the ZTH2014 study, and I ended up with the data shown in Figure 2.
Figure 2. All daily average solar wind observations in the OMNI-2 dataset. The “winter” data, shown in blue, uses the same definition of “winter” as is used in ZTH2014, viz November through March (5 months).
This is a most interesting graph, 51 years of data from more than a dozen satellites. First off, we can see the usual ~11-year sunspot cycle in the data, with a swing of about 50-100 km/sec.
Next, the solar wind has a clear minimum speed of around 300 kilometres per second. For those interested, this is about a million kilometres per hour … and it rarely blows much slower than that, summer or winter.
Next, they say that they have no less than 887 days that were identified as SWS_MIN, or solar wind speed minimums. As there are 51 years in the dataset, this means that over a typical winter there are 17 identified solar wind speed minima … and they are stacking them up 800 deep or so.
What I think I’ll do next is to see how the solar wind speed varies over the course of the year. Hang on … OK, I just created that graph, and it turns out I didn’t learn a whole lot in the process …
Figure 3. Solar wind speed by day of year. Portion of the year shown in blue is the “winter” (NDJFM) as defined in the study.
There is very little sign of any kind of annual cycle, which makes perfect sense because the sun doesn’t run by earthly clocks … the sun doesn’t know much about “one year for earthlings”.
So … we’ve seen the 51-year record of the solar wind, and the lack of an annual cycle. Let me move on to their physical explanation for the purported solar wind/atmospheric pressure connection. From the paper:
The responses on the day to day time scale have been shown to involve both the relativistic electron flux (REF), precipitating from the radiation belts at subauroral latitudes, and stratospheric volcanic aerosols. A strong correlation between the REF and the SWS has been examined by Li et al (2001a,b). Tinsley et al. (1994, 2012) described a link between space weather and lower atmospheric dynamics through the global electric circuit. Minima in the SWS and deep minima in the REF are associated with the HCS crossings, as shown by Tinsley et al. (1994, Fig. 5).
The REF can penetrate down to upper stratospheric levels, and the Bremsstrahlung radiation that they produce can impact the electric conductivity down to lower stratospheric levels and change the stratospheric electrical column resistance. The consequent changes in the ionosphere-earth current density (Jz) that flows as the downward return current in the global electric circuit was considered to be the physical link to the tropospheric cloud and dynamical changes, especially when there is high stratosphere aerosol loading due to volcanic eruptions, which will increase the proportion of the stratospheric column resistance to that of the whole atmosphere column. Observations of minima in tropospheric potential gradient and Jz at HCS crossings have been reported by Reiter (1977), and Fischer and Muhleisen (1980) also observed such potential gradient minima.
Now, is their explanation possible?
Sure. Lots of things are possible. I have long held that the electromagnetic aspects of weather and climate were the unknown unknowns in the climate game. For example, to many scientists’ surprise, it was discovered within the last decade or so that the cloud nuclei, the seeds that cloud droplets form around, are not mainly dust or sea salt crystals as was once thought … much of the cloud nuclei are microbes of various kinds. Which led to a new question … how did they get up so high in the sky? Turns out that the electrical forces are what make thunderstorms able to loft these tiny creatures that high up into the atmosphere …
So I don’t have a problem with the idea that electromagnetic forces are way understudied in the climate system, and thus may play a larger role in climate than is immediately apparent.
The part I’m missing in their explanation, however, is the connection of the solar wind to the variations in pressure that make up the NAO.
Finally, the most important question … does their study hold water? In regards to this question, let me list my objections to their study. Note that these are not objections to the results, these are objections before we’ve gotten to their results. Here, in no particular order, are the problems that I have with the study.
• No Archiving Of Data As Used: First and foremost, they have not archived the 887 magical dates on which they claim that there are “solar wind minima”. Without that, there’s no way to determine if they’ve made any errors. As a result, to date it’s just advertising, not science.
• High number of “minima”: Next, the “winter” portion of the dataset contains 6,684 days with data. There are 887 days they call “solar wind speed minima” during the winter. That means that a “minimum” occurs every 6,684 days / 887 minima equals 7.5 days per minimum, about once a fricken’ week …
Once a week? Give me a break. I realized this was a problem as soon as I looked at Figure 1 at the head of this post. I thought, 887 wintertime “minima” in half a century? That’s about eighteen minima every winter …
• Divide and Conquer: This study employs a much-abused technique I call “Divide and Conquer”. It works like this: you look for a theorized effect. But you can’t find it in the data. So then you divide the data into two piles, say into winter and summer data. Then you look for the effect again.
But you still can’t find the theorized effect in the data. So then you sub-divide the data again, say into “volcanic” and “non-volcanic” data. Now you have four piles of data. But you still can’t find the effect. So then you divide the data into maxima and minima, that gives you eight piles of data. You ignore the maxima, presumable because they didn’t show the effect.
So then you divide the minimum data into 887 overlapping two-month-long chunks centered on some subset of all of the minima, and you average the chunks together … at which point you find something and declare that your study is a resounding success …
I’m sure you can see the problem with this kind of analysis. If you keep dividing, eventually you will find something. No surprise.
• Bad Statistics, No Cookies: However, if you insist on using the “divide and conquer” plan as they have done, each time you subdivide the data you need to adjust the threshold for statistical significance. In climate science, the usual level for assigning statistical significance is a “p-value” of 0.05. That’s one in twenty. But if you look in more and more places, to be significant, the p-value needs to be lower. How much lower? Glad you asked. Here’s a handy chart … for mathematicians, the p-value is calculated as
p-value = 1 – 10^( log(1-p) / n )
where “n” is the number of trials, “p” is the single-trial p-value (0.05 in this case) and log is logarithm base 10.
Figure 4. Change in the required p-value to be significant at the single-trial 0.05 level with a given number of trials.
In this case, they have the original data, and then the two halves split summer/winter. Then they have four quarters after they’ve sub-spit by volcanic/non-volcanic. Then they’ve divided off the minimum values from the maximum values … already they’ve looked in fifteen different places for the claimed effect. So if they find something, in order for it to be significant it has to have a p-value of less than 0.004 … four in a thousand …
• Length of “Winter”: Picking five months for “winter” gives every appearance of special pleading. I mean, the first thing you’d try for “winter” is December-January-February. Then maybe the six months between the equinoxes, October to March. Either of those might be OK, although you’d need to adjust the significance threshold as required … but using a five-month winter is just fine-tuning the results.
• Proportionality of Effect: One of the ways we determine if there is causal relationship between A and B is that there is some kind of proportionality, whether linear or non-linear, between the cause and the effect. In their case, they are claiming that variations in maximum solar wind speeds don’t affect the North Atlantic Oscillation, but variations in minimum solar wind speeds do affect the NAO … how is that supposed to work? It seems odd, particularly when the solar wind minima vary so much less than the solar wind maxima.
• Width of Stacked Data: To dig out the signal, they’ve “stacked” the data. This means that they have aligned a number of years of results based on the minima in the wind speed. This is shown in Figure 1. It’s a legitimate technique, but note that their stacks are 2 months in width. This means that each individual layer in the stack contains on average eight different minima (60 days divided by 7.5 days per minimum).
• Uneven Duplication of Stacked Data: Like the minimum years, on average, every day in the dataset appears in the full stacked data about 8 times. However, the number of times that a given day appears in the total 887-layer stack is quite variable. Days during periods where a number of minima are in close succession will be over-represented in the stack, and vice versa.
• Missing Data: The early years have a lot of missing data. Coverage of 365 days/year is not achieved until 1995. It’s not clear what effect this has on their calculation of “minima”.
• Calculation of Minima: The previous problems are bad enough. But here’s where they go totally off the rails. In the ZTH2014 paywalled study they say they use the method for calculating minima from a previous paywalled study. The method of determining the location and depth of the minima in that study turns out to be quite baroque, viz:
The minima and their relative depth are selected with reference to a sliding window of 13 days, with the preceding and following ‘shoulder’ values (ps) being the mean for days 1 through 3 and 11 through 13, and the deviation from the shoulders (pm) being the mean for days 6 through 8, so that the percentage deviation is: y = ((pm-ps)/ ps) 100%.
Dear heavens … do you see what they are doing? I get a thrill when I see a bizarre mathematical transformation like that, it’s like coming across some strange new primitive life form. That is an extremely crude method of fitting a sawtooth wave to the data, one that will function as a strange form of triangular filter. Since the centers of the two ends of the filter (points 1-3 and 11-13) are 11 days apart, I thought that it would emphasize any cycles in the data with a period of 11 days, although from the description the frequency response of such an odd creature could only be guessed at. When I read that, I could hardly wait to see how their “minima finder” algorithm munges some real data. Before we get to the real data, however, here’s the bandpass of their triangular “minima” filter. It shows the amplitude of sinusoidal signals after they have been savaged by their method.
Figure 5. Bandpass of their 13-point-wide filter. Values are given as a percentage of the maximum.
That is one strange bandpass filter. As I suspected, the maximum bandpass is at a period of 11 days … and it has a curious problem in the present application. Solar wind data has a clear ~27-28 day cycle. This is the result of the ~27-28 day rotation period of the sun. Unfortunately, the amplitude this 28-day cycle is severely attenuated by their procedure, down to about a third of its original value. So their filter is minimizing a real cycle in the data, while artificially enlarging any random 11-day cycles. Most curiously, it totally wipes out all 3-day and 5-day cycles. I suspect that this has to do with the fact that they are not using some of the 13 points of the filter width—points 4-5 and 9-10 are not involved in the calculation. But that’s a guess.
Having seen all of that, without further ado, it’s time to look at real data. Here’s a typical winter from the OMNI-2 solar wind dataset. The time of the winter is 1998-1999, merely because it happens to be the first one I picked. This one has the full complement of 154 days of data, so it should have 154 days divided by 7.5 days per minimum equals about twenty minima. So I’ve included their bizarre “minima” calculations as well, scaled to the same mean and standard deviation as the solar wind data for easy comparison … hold your nose, here we go …
Figure 6. Daily average solar wind data (blue) and calculated “minima” (red). Minima calculated using the procedure quoted just above. The one gold, two tan, one blue, and two violet shaded areas show sections of particular interest. “Minima” are scaled to the mean and standard deviation of the solar wind speed data.
Like I feared when I first read their description, this procedure does indeed do weird things to data … to start with, in the right hand tan shaded area is what was the lowest minimum speed of the entire winter (blue line), a day when the solar wind dropped below 300 kilometres per second, a relative calm spell … with the wind only blowing a mere million kilometres per hour or so …
But once their procedure gets through with it, the red line shows that what was the record minimum of the period is now about the tenth lowest minimum. And the two minima in the other tan area have suffered the same fate, reduced to insignificance.
The violet shaded areas show the opposite effect. In the right hand violet shaded area, there was no real minimum of any kind (blue line). But under the new regime (red line), it’s the fourth largest minimum in the record. And it’s the same in the left hand violet shaded area. A significant false minimum has been created out of nothingness.
Next, the gold shaded area (center) shows what was a fairly minor player in the original data (blue line). But after their triangular filter works it over (red line), it becomes the deepest, most evident minimum of the winter.
Finally, the most outré part. See the blue shaded area? Their whizbang method actually shifts the dates of the two actual minima during that time (blue line) by two days each …
Like I said, it’s a most baroque method for picking “minima”, one that manufactures minima where none exist in the data, distorts the actual sizes of the minima, turns the deepest minimum into a minor player, and shifts the dates of some of the minima but not others, all the while minimizing the natural ~27-28 day cycle that actually exists in the data.
Conclusions? Other than the fact that looking at this study for four days now makes my head ache? Well, between all of the problems, that’s enough for me to say that the study is definitely not ready for publication. To recap, those problems were:
• No Archiving Of Data As Used
• High Number of “Minima”
• Uses a “Divide and Conquer” Method
• Bad Statistics
• Strange 5-month Length of “Winter”
• No Proportionality of Effect
• About Eight Minima in Each Layer of the Stacked Sections of Data
• Uneven Duplication of Stacked Data
• Missing Data
• Mondo Bizarro Method of Minima Calculations
Best thing about their study? I understand much, much more about the solar wind than I did a week ago.
Finally, people often read more into my statements than I intend. For example, when I say I can’t find an 11-year cycle in the 10Be data used as a proxy for cosmic rays, people interpret it as if I had said there are no cycles at all in climate data. Generally, I mean what I say, and not some generalization of my statement.
So please note that in this case, I am NOT saying that solar wind has no effect on the climate. It may well have such an effect, although the lack of any 11-year signal in temperature datasets argues strongly against it.
What I am saying is that the manifold flaws and problems in the study of Zhou, Tinsley, and Huang 2014 mean that they are a long ways from demonstrating that such a purported effect actually exists
My best wishes to each of you,
w.
The Usual Request: If you disagree with something I’ve said, please quote the exact words you disagree with. That avoids lots of misunderstanding.
Data: The press release at the Hockey Schtick post is here, my thanks for the discussion of the solar wind study. I have collated the OMNI-2 data into a single CSV file containing the daily average solar wind speed data called OMNI-2 Solar Wind.csv
Willis, would it be fair to say some of these people are out of their league! Or meddling where they should not. Or looking for the accolades.
Glad to see that once again the science is “settled”, like the weather. Thanks for the read.
I remember a wonderful statement by an older geology professor to his younger colleague: “Most studies are pure crapola!”
His younger colleague was incredulous, saying something like: “You mean more than half?”
To which the older professor replied: “Oooooh, no, more like 80-90%. Remember, a “C” grade is average, and a “C” grade student becomes a “C” grade scientist who will publish a “C” grade study which will be CRAP. Science is hard. Even an “A” student will still produce a crap study if he or she isn’t careful.”
The young professor said: “You sound really cynical.”
The old professor laughed, saying: “It’s called experience. Talk to me in a couple decades and see how cynical you’ve become!”
Comparison of solar wind ‘changes’ affect on the geomagnetic field (Look at the magnitude of the changes of AP which is how the solar wind speed change affects the geomagnetic field. Ap events and the time between Ap events is the variable to plot not solar wind speed (Blue graph). I will provide an over of the mechanism in the next couple of comments.
In May 16, 2005 the average of the three hour ap indices was 105.4
In May 17, 2014 the average of the three hour ap indices was 5.4
2005 May 15 Vs 2014 May 16
http://www.solen.info/solar/old_reports/2005/may/20050516.html
Solar flux measured at 20h UTC on 2.8 GHz was 103.0. The planetary A index was 105 (STAR Ap – based on the mean of three hour interval ap indices: 105.4).
Three hour interval K indices: 55984445 (planetary), 56973345 (Boulder).
http://www.solen.info/solar/
Last major update issued on May 17, 2014 at 06:20 UTC.
Recent activity
The geomagnetic field was quiet on May 16. Solar wind speed at SOHO ranged between 336 and 429 km/s.
Solar flux at 20h UTC on 2.8 GHz was 138.7 (decreasing 30.6 over the last solar rotation). The 90 day 10.7 flux at 1 AU was 149.3. The Potsdam WDC planetary A index was 5 (STAR Ap – based on the mean of three hour interval ap indices: 5.4). Three hour interval K indices: 22112221 (planetary), 12112311 (Boulder).
http://www.google.ca/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CCgQFjAA&url=http%3A%2F%2Fsait.oat.ts.astro.it%2FMSAIt760405%2FPDF%2F2005MmSAI..76..969G.pdf&ei=vyJ3U4maH8_woATknYCwBg&usg=AFQjCNE1HIIaQdO213fgDBS9nT2fvY3-Rg&bvm=bv.66917471,d.cGU&cad=rja
Once again about global warming and solar activity
We show that the index commonly used for quantifying long-term changes in solar activity, the sunspot number, accounts for only one part of solar activity and using this index leads to the underestimation of the role of solar activity in the global warming in the recent decades. A more suitable index is the geomagnetic activity which reflects all solar activity, and it is highly correlated to global temperature variations in the whole period for which we have data.
The real terrestrial impact of the different solar drivers depends not only on the average geoffectiveness of a single event but also on the number of events. Figure 5 presents the yearly number of CHs, CMEs and MCs in the period 1992-2002. On the descending phase of the sunspot cycle, the greatest part of high speed solar wind streams affecting the Earth comes from coronal holes (Figure 5), in this period their speed is higher than the speed of the solar wind originating from other regions, and their geoffectiveness is the highest. Therefore, when speaking about the influence of solar activity on the Earth, we cannot neglect the contribution of the solar wind originating from coronal holes. However, these open magnetic field regions are not connected in any way to sunspots, so their contribution is totally neglected when we use the sunspot number as a measure of solar activity.
Plain ‘common garden’ solar wind calculations are the most likely waste of time.
If there is an effect it is via CMEs solar flairs records. These tend to coincide with SS cycles but are shifted towards falling side.
Effect can be observed via the Ap index, but again that is even more controversial matter.
If we take so called Gleissberg cycle of about ~78 years, and ‘cherry pick’ one from early 1880s to 1960, then available AP monthly data can be broken in three long sections. Using 15 year moving average , than by a simple ‘fiddle’ with the data, as it is clearly shown in the graph a reasonable (if one is not to allergic to the ‘fiddle’) agreement with land temperature data can be obtained.
It would require lot of explanations, sadly they are not currently available, but at least a possibility of a link exists.
Willis
It seems to me that there are quite a few scientists who are trying to enhance their own innate pattern recognition skills with partially digested signal analysis to find what they want to find. It’s a confirmation bias positive feedback.
We all have a tendency to find confirmation of that which we already believe, which is why there are studies like this all of the time.
There are people who blame peer review, but my view is that if scientists were paid as much to check other people’s work and publish the results, yes there would be more bun-fights but there would also be fewer, better scientific papers.
That said, using a guillotine on the data just focussing on 5 months of the year and then a bizarre filter which does not maximize the signal being sought means that this paper should have been sent back to the authors.
Experimental data is a precious limited resource, and a competent scientist doesn’t throw away any data without good cause.
Dear Willis, an excellent peer review of the solar wind article. There seems to be a lot of “wind” in their methodology. thanks.
This paper is a significant advancement in helping us determine the things that don’t make a difference.
Hey Willis, you have my grateful and welcome thanks for creating that OMNI daily solar wind speed file. I have been looking at different daily files of solar outputs and could only find the hourly ones of the solar wind, and I have been tediously going through them working out daily averages…now you have saved me tons of work. Great! Thanks again!
Divide and conquer was used rather aggressively to produce one of the “97%” studies. Nuff said 🙂
http://wattsupwiththat.com/2012/07/18/about-that-overwhelming-98-number-of-scientists-consensus/
At one time early in the essay a five-month period of November through May is referred to, later corrected to November through March; just a typo to fix. Aside from that, interesting and well-written. Thanks for the article!
““Effects on *winter* circulation of short and long term solar wind changes”, by Zhou, Tinsley, and Huang.” ….. “Well, not exactly the winter, but the five month period November-May.”
Since they specified that their months of *winter* are: Nov-May, I guess they were taking measurements from somewhere in the Northern Hemisphere. .. Anyway, just like there is no *annual signature in the data, there should not be any difference (from the Sun’s point of view) between the winter and summer of the Earth’s Northern Hemisphere. … Makes me wonder if they would get similar results from somewhere in the *Southern Hemisphere !!
(maybe I am being a little sarcastic!)
holts7 says:
May 17, 2014 at 2:33 am
You’re welcome, holts, my pleasure.
w.
Peter Yates says:
May 17, 2014 at 3:19 am
Thanks, Peter. I thought that as well, then I realized that they are looking at the effect of solar wind on the NAO, which if it existed presumably might be different winter/summer …
w.
Peter Yates says:
May 17, 2014 at 3:19 am
Anyway, just like there is no *annual signature in the data, there should not be any difference (from the Sun’s point of view) between the winter and summer of the Earth’s Northern Hemisphere. …
Yes, there is, see Svalgaard’s papers on the subject, in mean time here is what the Ap index show:
http://www.vukcevic.talktalk.net/Ap-Bz.htm
When I first saw the title, I thought you were going to comment on this paper (which thankfully is not paywalled). Scott et. al. claim to have found a 120-day solar wind cycle centered around a very sharp fluctuation (down them up) in the solar wind speed, and linked that to frequency of lighting strikes in the 40 days following the fluctuation. I know zippo about solar physics so I have no idea whether there is anything known which exhibits a 120-day cycle, but their “money graph” sure looks convincing. Can you say after your look at solar wind data whether the 120-day cycle is real?
One thing I’ve learned reading WUWT and Climate Audit discussing the ways raw data is manipulated is don’t trust anyone’s money graph until you’ve read all the fine print. In studies like this one, researchers’ “raw data” resembles real data the way Cheese Whiz resembles cheese.
Thanks for another fine read.
” Turns out that the electrical forces are what make thunderstorms able to loft these tiny creatures that high up into the atmosphere …”
Just one more reason why I find it easy to believe that it does occasionally rain fish or frogs. 😉 Even so, those claims still sound so apocryphal!
“p-value = 1 – 10^( log(1-p) / n )”
I have but a layman’s understanding of high level statistics. But can I ask a simple question to see if I understand the substance of that equation?
Example: trial A gives you p=0.05; trial B gives you p=0.05; a meta analysis will necessarily give you p<0.05. Is that – more or less – what you're saying? If so, then I understand the concept.
BTW I see an obvious correlation in the right half of figure 1. If sub-dividing data can make the data fit an arbitrary hypothesis, then why isn't the left half equally correlated? I do follow most of what you're saying, and you aren't making any definite claims, but to my untrained eyes, it seems that there is a case to be made.
Thanks Willis, this was really interesting. I feel I learned a lot about statistics and what NOT to do. Sometimes the best learning comes from looking at bad examples. Hopefully the authors see this analysis and get back to you?
Gee if I wanted to publish something of real discovery, I would get it reviewed here first. Well done Willis I hope leif aint grinding his teeth in [jealousy] (joke). LOL
Willis,
In your figure 3, the average solar wind speed seems to take a jump up from about 415 Km/s to about 425 Km/sec (values are hard to pick off your graph) on the first of the year. Is the Sun making whoopee on New Years eve, or is that an artifact of your filter?
Willis says:
“This is a most interesting graph, 51 years of data from more than a dozen satellites. First off, we can see the usual ~11-year sunspot cycle in the data, with a swing of about 50-100 km/sec.”
To be honest, if the dates were not there, I’m not so sure from the velocity data alone that you would be able to say for sure where the sunspot cycles are:
http://snag.gy/uIZON.jpg
Daily velocity has a swing of ~ +/- 250km/s.
“for mathematicians, the p-value is calculated as
p-value = 1 – 10^( log(1-p) / n )”
For non-mathematicians, you can match the results in Willis’ Figure 4 to within 2% by the somewhat easier formula p = 0.05/n. (the Bonferroni correction).
n Bonferroni Willis error
1 0.0500 0.0500 0.000
2 0.0250 0.0253 0.013
3 0.0167 0.0170 0.017
4 0.0125 0.0127 0.019
5 0.0100 0.0102 0.021
6 0.0083 0.0085 0.021
7 0.0071 0.0073 0.022
8 0.0063 0.0064 0.023
9 0.0056 0.0057 0.023
10 0.0050 0.0051 0.023
11 0.0045 0.0047 0.023
12 0.0042 0.0043 0.024
13 0.0038 0.0039 0.024
14 0.0036 0.0037 0.024
15 0.0033 0.0034 0.024
The increase in pressure over the South Pole as a result of blocking the polar vortex in the stratosphere, caused an increase in temperature and decrease in growth ice.
The magnetic field of the solar wind reduces the cosmic ionizing radiation in the zone ozone.
http://www.cpc.ncep.noaa.gov/products/stratosphere/strat_a_f/gif_files/gfs_t70_sh_f00.gif
http://www.cpc.ncep.noaa.gov/products/intraseasonal/temp50anim.gif
http://www.cpc.ncep.noaa.gov/products/intraseasonal/z200anim.gif
http://arctic.atmos.uiuc.edu/cryosphere/antarctic.sea.ice.interactive.html
I couldn’t finish reading your post Willis, after reading this.
“”””Next, the solar wind has a clear minimum speed of around 300 kilometres per second. For those interested, this is about a million kilometres per hour … and it rarely blows much slower than that, summer or winter.””””
Try this.
Use the solar wind speed of solar cycle 24 and you should have found that it REGULARY during this cycles min and beyond dropped below 300 km/s.
See Ulrichs post.. 6:03am
The Earth’s magnetosphere undergoes physical changes between fast and slow solar wind. The configuration is spending more time in its slower speed configuration during cycle 24. Less blow back, less time spent recovering, less rigid? (Dr. S.). The angle at which solar wind and plasma interact from the magnetosphere on down changes..Being somewhat more collapsed and relaxed..less flexed..
more fun stuff
Even the north magnetic pole slowed down that ought to tell us something about the change in rigidity and angle of solar [wind] interactions..
Thanks Willis, more good stuff.
Sho nuf! Its’n elephant, and its wriggling its trunk!
But the best part came later when “Possibility Vuk” came up with his alternate route to wriggling the elephant’s trunk post. Come on Vuk. You can’t be serious.
“The part I’m missing in their explanation, however, is the connection of the solar wind to the variations in pressure that make up the NAO.”
Willis the NAO is a statistical construction of pressure centers that does not have a synoptic reality -see Leroux- thus it is unsurprising one would have trouble finding a physical connection between a real physical process -solar wind and its consequence- and NAO. What would be more interesting indeed is the relation with strength and frequency of Mobile Polar Highs expulsions from the poles in relation to solar wind and electromagnetic processes.
Small chance of El Niño.
http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_update/sstweek_c.gif
http://earth.nullschool.net/#current/wind/isobaric/70hPa/orthographic=-84.33,-54.24,553
Weakened polar vortex at an altitude of 17 km cools the Pacific.
The diagram shows the relationship between the number of neutrons at the surface of Kp. Short strong increases netronów occur after strong explosions X in the sun.
http://neutronm.bartol.udel.edu/~pyle/EndPlot2.png
Thanks, Willis. What a trip!
Idiot wind, sang Bob Dylan:
“Someone’s got it in for me, they’re planting stories in the press
Whoever it is I wish they’d cut it out but when they will I can only guess”
I’ll let Willis answer, but I was under the impression that the formula isn’t used to calculate the actual p-value. I think it’s a formula for determining the threshold for declaring something statistically significant. In other words, using all the data, a p-value < 0.05 would imply significance. Breaking the data down once would require a p-value < 0.0253 in order to imply significance. Breaking the data down again would require a p-value < 0.0170.
Can any stats experts confirm this? And can a stats experts comment on using this formula for other types of data mining?
This study employs a much-abused technique I call “Divide and Conquer”.
Good name. In medical research it corresponds to subgroup analysis.
Mathematically, if you have a huge cloud of data in multiple dimensions, you can eventually find a plane that divides the cloud into two halves, for which the distance between the means is large compared to the mean distance between the points and mean of each group: voila! you have a “statistically significant” result, even though the actual p-value is 1 since you can always do this, even if the data be pure noise.
Alternatively, as here, you can move around within subspaces of the data, until you find a subspace within which, when you view from the proper angle, you can see more of something on the left than the right: voila! another statistically significant difference in the “something” dependent on the attributes used to define the region and the correct viewing angle. Again, since you can always do this if there are enough dimensions, the actual p-value is 1.
You went into this in the related case of time series that are short compared to the hypothesized period.
This is among the reasons that there is about a 40% rate of non-reproduceability in medical research.
As usual, I enjoyed your post.
Peter Yates says:
May 17, 2014 at 3:19 am
“Anyway, just like there is no *annual signature in the data, there should not be any difference (from the Sun’s point of view) between the winter and summer of the Earth’s Northern Hemisphere”
The angle of the sun goes from lowest to highest. Why would this not cause a difference?
There is a pronounced seasonal change in the NAO, I assume related to the above. The Summer NAO is of less amplitude and located farther north(as one would expect). It also plays a less important role effecting weather(as one would expect).
http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.loading.shtml
The NAO is influenced by the AMO(Atlantic Multidecadal Oscillation).
Global climate models have predicted more positive NAO’s in Winter from greenhouse gas warming. In the Winter of 2009/10, we had the most extremely negative NAO ever recorded and the Winter of 2010/11 saw a repeat. There seems to have been a decadal shift from +NAO’s to -NAO’s recently.
If I had to project the next decade, it would would feature more -NAO’s than we had during the mild Winters(with global warming) in the 1980’s/90’s. Spikes with the opposite sign of the Winter NAO during individual Winters do occur(Winter of 95/96).
ftp://ftp.cpc.ncep.noaa.gov/wd52dg/data/indices/tele_index.nh
http://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml
http://www.cru.uea.ac.uk/~timo/datapages/naoi.htm
There is a strong correlation between -NAO’s/-AO’s in Winter and cold for many mid latitude regions of the US and Europe. However, this past Winter’s frigid weather in the middle and eastern parts of the US did not feature the extreme -NAO. It was the result of a massive ridge in the Northeast Pacific to Siberia and downstream trough/upper low that at times, resulted in the so called “Polar Vortex” shifting very far south, in Canada and even the northern US.
This, in contrast to the blocking Greenland High couplet involved with the -NAO which results in Europe also receiving a dominant meridional(north to south) flow…….which was not the case this past Winter.
p-value = 1 – 10^( log(1-p) / n )
Taking p/n (for the criterion) works well: this is discussed in the book by Kass, Eden and Brown (“Analysis of Neural Data”) that I referred you to once.
The difficulty in using these formulas is that the many tests are not independent. Just getting an awareness of the problem (called the “multiplicity” problem) is the hardest step.
Thanks Willis.
—————————
William Astley at 1:58 inserts a link (third one) that redirects here:
http://sait.oat.ts.astro.it/MSAIt760405/PDF/2005MmSAI..76..969G.pdf
This paper has a date of 2005 and mentions the Hoyt & Schatten 1998 Sunspot series. Also they use global temperature anomalies from Jones and Moberg (2003) of the Climatic Research Unit. The temperature series ends in the year 2000. They claim that “Sunspots themselves are not geoeffective.” …and further … “Geoeffective are the solar active regions in which sunspots are embedded.”
The paper’s title is “Once again about global warming and solar activity” – as found in the William Astley comment at 1:58. Direct quotes from the paper follow in that comment.
I wonder if (1) this paper has been reviewed anywhere, (2) if one would find the same results using data series out to the current time, and (3) the H & S sunspot series is, I think, one that is considered incorrect by Leif Svalgaard and others.
“”””So I don’t have a problem with the idea that electromagnetic forces are way understudied in the climate system, and thus may play a larger role in climate than is immediately apparent.
The part I’m missing in their explanation, however, is the connection of the solar wind to the variations in pressure that make up the NAO.”””
__________________________
What about the solar wind dynamic pressure changes and how they affect Earth rotation. Is it 6 ms, over a regular med. high solar cycle that it varies?
Maybe at the equator that is not much, but polar regions might be more sensitive to these perturbations and wobbles..
And is it 5 or more geomagnetic jerks, since around 1999?
Willis, Why do I see the El Niño pattern in that data? Inverted.
Alan Watt, Climate Denialist Level 7 says:
May 17, 2014 at 4:23 am
Thanks for the comment, Alan. There’s a discussion of that study on WUWT, my comment is here. More junk, I fear.
w.
It will be the difference between winter and summer, because ozone is more sensitive to radiation GCR during the polar night, and GCR depends on the magnetic field of the solar wind and Earth’s magnetic field. This change of temperature in the stratosphere lead to changes in the pressure difference between the high and medium geographical latitudes.
I think Zhou, Tinsley and Huang have been looking for the links between the sun and climate for a long time in their own ways, and it it easy to understand why. There is ample evidence that the sun drives our climate, it is just the mechanism that is not known. this lack of knowledge is too much for some people it seems.. we are supposed to know it all! or at least thats the way the ipcc and friends present it.
Because the current climate gurus cant find the true answer, they just make up graphs like the hockey stick or push variables (fudge factors) such as aerosol impacts to make an answer.
What they should be doing is trying to find the true answer, not defend the junk they made up and is now obviously falsified, so when i see papers that at least attempt to find the truth and are readily falsifiable, then I am far more content.
“The part I’m missing in their explanation, however, is the connection of the solar wind to the variations in pressure that make up the NAO”
the way I read it, they are pointing to –
“A strong correlation between the REF and the SWS has been examined by Li et al (2001a,b). Tinsley et al. (1994, 2012) described a link between space weather and lower atmospheric dynamics through the global electric circuit. Minima in the SWS and deep minima in the REF are associated with the HCS crossings, as shown by Tinsley et al. (1994, Fig. 5)”
I have not read their papers, so cant comment on them, but I do know that the REF is directly affected by both the wind speed and min/max eg-
http://acdb-ext.gsfc.nasa.gov/People/Jackman/Gaines_1995.pdf
“Enhancements in relativistic electron fluxes continue to command interest in the magnetospheric physics community and may be an important source of energy input and chem-
ical change to the middle atmosphere [Thorne, 1980; Baker et al., 1987, 1990; Callis et al., 1991; Jackman, 1991]. These electrons are believed to be accelerated as a result of high-speed solar wind streams interacting with the magneto-sphere [Paulikas and Blake, 1979; Baker et al., 1994] and may appear more frequently near solar minimum than solar maximum [Baker et al., 1986]. “
Why do not you want to see this? Is it not the result of pressure changes in the stratosphere above the Arctic Circle? Is ozone does not depend on the sun? Maybe you need different glasses?
http://www.cpc.ncep.noaa.gov/products/precip/CWlink/blocking/real_time_sh/500gz_anomalies_sh.gif
This may volcanic eruption. You have heard about this?
Excellent take down, Willis!
I have a thought though…, now, don’t laugh!
You said, “Turns out that the electrical forces are what make thunderstorms able to loft these tiny creatures that high up into the atmosphere …”
Could the “electrification” of the planet, from high tension wires to microwave transmissions have some effect on climate as well?
In the case of the former example, I always get an electrical shock when I touch something made of metal under high tension wires (not the towers, a car or some such).
Could microbes be subject to the same forces?
Maybe it’s not just thunderstorms doing the “lofting”?
ren,
I’ve think you’re on to something significant.
Willis Eschenbach will you answer the question of what is blocking south polar vortex?
http://www.cpc.ncep.noaa.gov/products/stratosphere/strat_a_f/gif_files/gfs_o3mr_30_sh_f00.gif
Peter Yates says:
May 17, 2014 at 3:19 am
““Effects on *winter* circulation of short and long term solar wind changes”, by Zhou, Tinsley, and Huang.” ….. “Well, not exactly the winter, but the five month period November-May.”
Since they specified that their months of *winter* are: Nov-May, I guess they were taking measurements from somewhere in the Northern Hemisphere. .. Anyway, just like there is no *annual signature in the data, there should not be any difference (from the Sun’s point of view) between the winter and summer of the Earth’s Northern Hemisphere. … Makes me wonder if they would get similar results from somewhere in the *Southern Hemisphere !!
(maybe I am being a little sarcastic!)
______________________
Actually, there is a semi- annual solar axial effect, apparent in both northern and southern hemispheres.
http://www.leif.org/research/Semiannual-Comment.pdf
William Astley says:
May 17, 2014 at 1:58 am
“Comparison of solar wind ‘changes’ affect on the geomagnetic field (Look at the magnitude of the changes of AP which is how the solar wind speed change affects the geomagnetic field.”
A non sequitur with regard to the subject topic: for me, an interesting thing to look at would be changes in the strength of the geomagnetic field vis a vis the extent of the ozone hole in the Antarctic. I’ve argued (with little success so far) given that all atmospheric gases except O2 are diamagnetic (repelled by a magnetic field) that at least some component of the phenomenon is at play in creating an ozone hole (which would also be a coincident CO2, N2, Noble gas and Methane hole replaced by higher O2) with a corresponding relative concentration of the missing gases in the temperate to tropical zones. The ozone “collar” one sees in NASA images tends to support the idea. Weather obviously confounds the results somewhat away from the poles. It is argued the polar vortex is a significant player but I think there should be some evidence of magnetics being at least a small player since the effect is real. I requested data from NASA re distribution of atmospheric gases to see if their is a “hole” with the others and got a reply on a host of pollutant gases but not the main ones – presumably it isn’t measured because they don’t see a reason for variation in non-polllutant gases like O2 , N2, and noble gases. A magnetic field strength correlation would, however provide satisfactory info.
Willis,
You’ve been absent for awhile and when you’ve done that in past, you’ve usually been busy preparing some juicy repast for us and you sure enough did it, again. Thanks.
Wow Vuk. I take it back. You’ve been outdone!
Pamela Gray says:
May 17, 2014 at 7:46 am
Sho nuf! “Possibility Vuk”. Come on Vuk. You can’t be serious.
……..
Hi Ms Gray
If something is possible it is [not] necessarily likely.
Lot of people do science and non-science for living, such probably take it seriously, very seriously. I did good old solid engineering for living, where things had not only to be possible and likely, but had to work, and work making profit, else I wouldn’t survive for over 30 years, with a world class company, exporting its product to more than 100 countries, with USA being the biggest overseas customer.
Now, I am enjoying fruits of those decades of good work and it is time to have some fun. You appear to be a learned lady, and no way I would be inclined to direct your opinion on mine or anyone else’s comments here.
Am I serious? Look up this , it may help you decide.
All best to you and yours.
The solar wind bursts (rate of change rather than speed of the wind is more important in terms of the magnitude of the effect, as well as the density of the wind, and the charge composition in the wind) create a space charge differential in the ionosphere which in turn removes ions from high latitude regions and increases ions in the equatorial regions.
It is important when reviewing/analyzing the effects of the solar magnetic cycle on the planet’s climate to include effect of GCR changes (galactic cosmic rays, mostly high speed protons, also called cosmic flux) which are modulated by the solar heliosphere. The GCR strike the atmosphere and create ions which modulate the amount of planetary clouds. Due to the strength and orientation of the earth’s magnetic field, solar heliosphere modulation of GCR mostly affects high latitude regions.
As this graph illustrates we are at the highest point in solar magnetic cycle 24 and GCR has not dropped off as in past cycles, as solar magnetic cycle 24 is the weakest cycle in 100 years based on the idiotic and purposeless sun spot counting. The drop in the Ap index is due to the fact that solar heliosphere density has dropped by 40%. It appears, we are observing a once in 6000 to 8000 year solar magnetic cycle interruption. More on what to expect when there is public discussion of solar magnetic cycle anomalies and public discussion of unexpected planetary cooling and changes in weather patterns.
During the last 7 or 8 years the solar magnetic cycle’s effect on planetary climate has been inhibited. The inhibiting mechanism is abating. Observations to support that assertion is the sudden increase in sea ice in the Antarctic and the cooling of the Arctic in summer due to increase cloud cover.
It will be interesting to see if the reduction in intensity of solar wind bursts inhibits the predicted El Niño. The electrical charge movement from high latitude to equatorial regions reduces cloud cover in high latitude regions and changes droplet size in the equatorial clouds. The droplet size of the clouds in the equator affects how upwelling long radiation can pass through the cloud in question.
http://cosmicrays.oulu.fi/webform/query.cgi?startday=27&startmonth=03&startyear=1975&starttime=00%3A00&endday=27&endmonth=04&endyear=2014&endtime=00%3A00&resolution=Automatic+choice&picture=on
This review paper discusses some of the effects and mechanisms.
http://www.utdallas.edu/physics/pdf/Atmos_060302.pdf
Atmospheric Ionization and Clouds as Links Between Solar Activity and Climate
Observations of changes in cloud properties that correlate with the 11-year cycles in space particle fluxes are reviewed. The correlations can be understood in terms of one or both of two microphysical processes; ion mediated nucleation (IMN) and electroscavenging. IMN relies on the presence of ions to provide the condensation sites for sulfuric acid and water vapors to produce new aerosol particles, which, under certain conditions, might grow into sizes that can be activated as cloud condensation nuclei (CCN). Electroscavenging depends on the buildup of space charge at the tops and bottoms of clouds as the vertical current density (Jz) in the global electric circuit encounters the increased electrical resistivity of the clouds. Space charge is electrostatic charge density due to a difference between the concentrations of positive and negative ions. Calculations indicate that this electrostatic charge on aerosol particles can enhance the rate at which they are scavenged by cloud droplets. The aerosol particles for which scavenging is important are those that act as insitu ice forming nuclei (IFN) and CCN. Both IMN and electroscavenging depend on the presence of atmospheric ions that are generated, in regions of the atmosphere relevant for effects on clouds, by galactic cosmic rays (GCR). The space charge depends, in addition, on the magnitude of Jz. The magnitude of Jz depends not only on the GCR flux, but also on the fluxes of MeV electrons from the radiation belts, and the ionospheric potentials generated by the solar wind, that can vary independently of the GCR flux. The roles of GCR and Jz in cloud processes are the speculative links in a series connecting solar activity, the solar wind, GCR, clouds and climate. This article reviews the correlated cloud variations and the two mechanisms proposed as possible explanations for these links.
As I noted in my comment above. We are at the peak of solar magnetic cycle 24, yet the proxy variable Ap (Ap is a measurement of much the geomagnetic field changes in a three hour period when there is a solar wind burst. Leif incorrect uses the day average geomagnetic field change which not isolate the rate of change of the solar wind which causes the space charge differential in the ionosphere) which is a proxy measure of how the solar wind changes affect planetary climate has dropped by a factor of 20.
correction
If something is possible it is not necessarily likely.
Sarah Ineson presented this figure, (courtesy of Lesley Gray, University of Oxford), which explains a top-down mechanism for how solar cycle variability in stratospheric ozone and heating can induce planetary wave propagation through two routes to produce a positive (labeled +ve in the figure) NAO response.
http://lasp.colorado.edu/home/sorce/files/2013/10/summary_Ineson.jpeg
I can’t believe you did this much work or this one article, wow.
But what this all comes down to is now a days scientists don’t TEST a hypothesis they set out to PROVE the hypothesis by any means necessary. Statistics isn’t a tool to ANALYZE data it is a tool to MANIPULATE the data. Some how most science PhDs have managed to get their degrees without understanding how science works.
vukcevic says:
May 17, 2014 at 12:23 pm
correction
If something is possible it is not necessarily likely.
___________________
Whew!
ren says:
May 17, 2014 at 12:43 pm
I’ve seen that diagram from Sarah Ineson before but at solar maximum it refers to more UV, more ozone and higher temperatures in the stratosphere.
However, when the sun was more active the stratosphere cooled and with the less active sun that cooling has stopped and there may now be warming.
The sign of the stratospheric response to solar changes needs to be reversed.
tgasloli: But what this all comes down to is now a days scientists don’t TEST a hypothesis they set out to PROVE the hypothesis by any means necessary.
I have called it “rescuing” a hypothesis.
Alan Robertson says @ vukcevic:
Whew!
Alan
Be courteous to all and one
Trust a whew
Do wrong to none.
All the best to you
vukcevic says:
May 17, 2014 at 1:47 pm
Alan Robertson says @ vukcevic:
Whew!
Alan
Be courteous to all and one
Trust a whew
Do wrong to none.
All the best to you
_____________________
I do hope that you did not take offense and that our problem derives from the language barrier.
In English, “Whew!” is used as an expression of great relief and was expressed as a joke response to your corrected line.
“If something is possible it is not necessarily likely.”
Which with uncorrected assertion would be: “A meteor strike to my forehead is possible and ___ necessarily likely”.
Ah heck, if I have to explain it…
Just an observation.
Last Summer, extreme negative temperature anomalies persisted in the Arctic long enough for it to catch my attention. At the same time, in the Southern Hemisphere, during its Winter, there was one of the strongest meridional flow patterns in decades as Antarctic cold was displaced toward the equator. Argentina and S.Brazil saw record cold and snow.
When the seasons flipped, the exact same weather pattern/effects flipped hemisphere’s. Extreme cold anomalies persisted over the Antarctic for months during Summer. At the same time, in the Northern Hemisphere’s Winter, a powerful, persistent pattern with a massive northeast Pacific ridge extending to Siberia at times and downstream trough, focused a meridional, north to south flow aimed at Canada and much of the US(east of the Rockies).
The Great Lakes region saw one of its coldest Winters the last Century.
This could be a coincidence. It could be connected but the powerful connection not understood and on a short enough time scale that it will be gone before we can even make the connection.
We are in the seasonal time frame for the effect to flip, if there is an effect(vs random variation/coincidence). The Antarctic, at least at the moment, suggests the next couple of weeks will continue to feature a flip to extreme warm anomalies.
The Arctic, after it’s extremely warm anomalies this past Winter, may be in transition. My bias is leading me in a direction before there is evidence to properly assess the Arctic Summer, so the best thing to do in this case, is wait for MUCH more data……….especially if the early part of Summer in the Arctic is cool and revs up that bias.
Alan Robertson says:
May 17, 2014 at 2:17 pm
I do hope that you did not take offense
Whew!
Willis, and Peter Yates – If I have understood this correctly, the study selects solar wind data from November to May only. Yes they say they are looking for its effect on Earth and the period “Nov-May” is meaningful on Earth, and only the “Nov-May” solar wind reaches Earth during Nov-May. BUT, if you are looking for a cycle in the solar wind which has an effect on Earth that for some reason shows up in Nov-May, it makes absolutely no sense at all to examine only the Nov-May solar wind, because Nov-May has no meaning on the sun. If there is a solar cycle that shows up in Earth’s Nov-May, it must exist equally at all other times. Therefore the study should use all solar wind data.
Another way of looking at this is that if there is a reason for an effect showing on Earth in Nov-May and not in other months, then that reason has to be an Earth-based reason not a Sun-based reason, because the Sun doesn’t know what “Nov-May” is. Thus selection of Nov-May solar data is nuts.
(I tried to find a more scientific-sounding word than “nuts”, but none of them seemed to fit.)
ren says:
May 17, 2014 at 8:10 am
Small chance of El Niño.
http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_update/sstweek_c.gif
http://earth.nullschool.net/#current/wind/isobaric/70hPa/orthographic=-84.33,-54.24,553
Weakened polar vortex at an altitude of 17 km cools the Pacific.
________________________________
Doesn’t look weak to me ?
Has that huge flux tube running into the So. Pacific at 10hPa (16 mi.) The end of it looks like around only
24 S. of equator.
http://earth.nullschool.net/#current/wind/isobaric/10hPa/overlay=temp/orthographic=-101.37,-51.45,554
vukcevic says:
May 17, 2014 at 10:58 am
Say what? It’s possible that I might win the lottery … but that doesn’t make it likely that I’ll win. What am I missing here?
w.
William Astley says:
May 17, 2014 at 11:50 am
William, on my planet I call what you’ve done “science by assertion”. Without citations or other support, you’re moving your lips, but nothing’s coming out …
w.
vukcevic says:
May 17, 2014 at 12:23 pm
I knew I was missing something … fixed.
w.
@Mike Jonas
_”Willis, and Peter Yates – If I have understood this correctly, the study selects solar wind data from November to May only.”_
Thanks. You explained it all better than I did. .. I was looking at the study from the Sun’s point of view, and thinking that it is a similar situation to there being no annual cycle in the OMNI-2 data. ….
_”There is very little sign of any kind of annual cycle, which makes perfect sense because the sun doesn’t run by earthly clocks … the sun doesn’t know much about ‘one year for earthlings’. (Willis)_
Willis wrote in his reply to my original post that they were looking at the effects of the solar wind on the North Atlantic Oscillation (NAO). It seems that the authors concentrated on the winter months in the Northern Hemisphere because the NAO can have a large effect on the winter weather, depending on its positive or negative phases. …. “The NAO is the *dominant mode* of winter climate variability in the North Atlantic region ranging from central North America to Europe and much into Northern Asia.” ….www.ldeo.columbia.edu/res/pi/NAO/
But, I agree it does make more sense to use the solar wind data for the whole year. .. At least to confirm the differences that there are in the solar wind reaching the atmosphere over the North Atlantic during the summer and winter months. …. _”The angle of the sun goes from lowest to highest. Why would this not cause a difference?” (Mike Maguire)_
Thanks also to: @vukcevic @MikeMaguire @AlanRobertson
From ‘The Hockey Schtick’ article: …. _”The authors propose these effects are related to ‘A connection via the global atmospheric electric circuit and cloud microphysical changes’ [similar but not the same as the cloud seeding hypothesis of Svensmark et al].” …. hockeyschtick.blogspot.com/2013/09/new-paper-finds-another-amplification.html
By the way, @JohnMWare pointed out that the ‘Nov-May’ period is a typo. It should have been ‘Nov-Mar’ — the 5 month period: November to March.
ren says:
May 17, 2014 at 10:20 am
Not a clue. Truly.
w.
Willis Eschenbach whether blocking the polar vortex has an effect on climate phenomena, especially when repeated over several years? Whether solar activity has an effect on distribution of temperature and ozone, or not?
Carla from my observation is that deepen the temperature difference between the eastern and western Pacific because can be seen along the South American wind from the south, and a large area of low clouds.
http://www.sat24.com/world.aspx?region=am
That is my opinion, but I could be wrong.
Peter Yates – The study was of the speed of the solar wind. You quote ”The angle of the sun goes from lowest to highest. Why would this not cause a difference?” (Mike Maguire). The answer is because the angle of Earth has no effect on the speed of the solar wind. It is conceptually possible that passing through Earth’s atmosphere affects the observed solar wind speed, but even that would have no significance wrt this study. It’s still nuts!
Peter Yates – Yes, Nov-Mar, thx. But of course it doesn’t matter what months are used, selecting any months is nonsensical. Solar cycles can only have a periodicity that is of significance at the sun. Earth years, seasons, months and days have no significance at the sun. Anything with these periodicities must have an Earth-based cause.
Mike Jonas says:
May 18, 2014 at 2:49 am
………..
If solar wind velocity is measured within magnetosphere the annual effect can’t be ignored due to the tilt of the Earth’s axis.
Carla strongest ionization in the vortex is at a height of about 20 km. Blockade is stronger at a height of 70 to 30 hPa. The above also works, and is, contrary to appearances, very strongly.
A question for Willis, but maybe Dr. Svalgaard would have more insight….how does solar wind speed link to dynamic pressure? Anthony’s solar page contains and interesting graphic of solar magnetic field, wind speed, and (what I assume is ) dynamic pressure as measured against the earths atmosphere. I have see points of relatively ‘higher’ speed, but no corresponding increase in pressure; and vice versa. I would think the velocity of the solar wind is only part of the picture.
vuk – Thx for the magnetosphere info – but as I said, it has no significance wrt this study. The tilt of the Earth varies from month to month but it is the same each year. ie, every Nov-Mar it does exactly the same thing (and every Apr-Oct too of course) so using only Nov-Mar to look for interannual solar cycles is still nuts. Every cycle based on something Earth does is irrelevant at the sun. The sun has never heard about “Nov-Mar”, has no idea what it means, and certainly doesn’t break its wind for it.
[apologies to anyone whose first language isn’t english]
ren says:
May 17, 2014 at 10:36 pm
Of course blocking the polar vortex has an effect on climate. Everything “has an effect” on climate. The question is only “how much an effect”, not whether there is an effect.
It’s totally unclear what you mean by “solar activity”. Sunspots? Solar wind? Variations in magnetism?
As to whether the sun “has an effect on distribution of temperature”, sure—where the sun shines more, it tends to be hotter.
Again, I’m sorry, ren, but your questions don’t make any sense as stated, so I have no clue about the real answer.
w.
Thanks, ren. Actually, I do have a different opinion. Let me count the ways that stratospheric temperature is affected other than by ionization.
• Stratospheric temperature is also a function of the amount of aerosols in the stratosphere, as is demonstrated by the temperature rises in 1991 and 1982 after the volcanic eruptions.
• In addition, the tropical thunderstorms regularly punch through the tropopause, delivering both warm air and moisture to the stratosphere.
• The stratosphere is generally isolated from the troposphere, but it is not physically distinct. There is no physical barrier between stratosphere and troposphere. Not only that, but the interface between them is as big as … well, it’s as big as the surface of the planet. As a result, there is a slow exchange of both energy and molecules of all kinds between the troposphere and the stratosphere.
• While the stratosphere doesn’t contain a lot of either GHGs or airborne particles, it does have some. As a result, just like the troposphere, the stratosphere absorbs a certain amount of upwelling thermal longwave from the surface.
• Finally, consider the not un-common phenomenon of stratospheric clouds, particularly in the polar regions. Known as “nacreous clouds”, they are quite effective at absorbing upwelling LW radiation, and they form another way that the temperature of the stratosphere is affected by things other than ionization.
There are likely others, nature is endlessly ingenious.
Mmmm … I would phrase that a bit differently. GCR changes depend directly on the strength of the heliocentric magnetic field, because the field diverts them away from the solar system. But although UV varies generally in sync with the sunspot cycle (and with the magnetic field), it is not directly controlled by the interplanetary magnetic field as are the GCRs.
You are welcome.
w.
Sorry Willis.
It seemed to me that the temperature of the tropopause is nearly constant at about -50 degrees C. As these charts are able to be wrong.
What temperature is no cloud in the stratosphere?
Not to mention the volcanoes.
[Thanks for that, Ren. I’ve brought the graphic inline, it’s an interesting one. -w.]
ren says:
May 21, 2014 at 12:59 pm
Good question, always more for me to learn. The “tropopause” is where the temperature of the atmosphere stops dropping with increasing altitude. If you look at your cited chart of Arctic atmospheric temperatures, in the summer the temperature of the troposphere bottoms out at around 15 km. of altitude and a temperature of -45° to -50°C, and then starts rising with altitude.
But in the winter, the temperature of the tropopause is much colder (shown as white in your graph), at times below -70°C. The tropopause is also much higher in winter, up around 25 km in December, then dropping in January, then rising again to about 30 km in February..
I don’t know if there is a lower temperature limit for nacreous polar clouds, as they are composed of ice.
Sorry, that last part doesn’t make sense.
Regards,
w.
What I mean is, like a volcano warms the stratosphere, when the temperature drops gradually in the troposphere when the pressure changes to -70 degrees C (above the equator)? Begins to rise gradually from 20 km altitude (above the equator).
http://www.cpc.ncep.noaa.gov/products/stratosphere/strat-trop/gif_files/time_pres_TEMP_MEAN_ALL_EQ_2013.gif
Regards.
Data Suggest That Solar Wind Impacts Global Temperature
Figure 2 is a plot of the solar wind (inverted) and sea surface temperature since 1963 (three-month centered averages ).
http://notrickszone.com/wp-content/uploads/2014/05/Caryl_21.gif
http://notrickszone.com/2014/05/22/data-suggest-that-solar-wind-impacts-global-temperature/