Guest Post by Willis Eschenbach
The recent post here on WUWT about the Pacific Decadal Oscillation (PDO) has a lot of folks claiming that the PDO is useful for predicting the future of the climate … I don’t think so myself, and this post is about why I don’t think the PDO predicts the climate in other than a general way. Let me talk a bit about what the PDO is, what it does, and how we measure it.
First, what is the PDO when it’s at home? It is a phenomenon which manifests itself as a swing between a “cold phase” and a “warm phase”. This swing seems to occur about every thirty or forty years. The changeover from one phase to the other was first noticed in 1976, when it was called the “Great Pacific Climate Shift”. The existence of the PDO itself, curiously, was first noticed in its effects on the salmon catches of the Pacific Northwest.
Figure 1. The phases of the PDO, showing the typical winds and temperatures associated with its two phases. The color scale shows the temperature anomalies in degrees C.
Figure 1 is a clear physical depiction of the two opposite ends of the PDO swing, based on how it manifests itself in terms of surface temperatures and winds. But to me that’s not the valuable definition. The valuable definition is a functional definition, based on what the PDO does rather than on how it manifests itself. In other words, a definition based on the effect that the PDO has on the functioning of the climate as a whole.
A Functional Definition of the PDO
To understand what the PDO is doing, you first need to understand how the planet keeps from overheating. The tropics doesn’t radiate all the heat it receives. If it did the tropics would be much, much hotter than it is. Instead, the planet keeps cool by constantly moving huge, almost unimaginably large amounts of heat from the tropics to the poles. At the poles, that heat is radiated back to space.
The transportation of the heat from the equator to the poles is done by both the atmosphere and the ocean. The atmosphere can move and respond quickly, so it controls the shorter-term variations in the poleward transport. However, the ocean can carry much more heat than the atmosphere, so it is doing the slower heavy lifting.
The heat is transported by the ocean to the poles in a couple of ways. One is that because the surface waters of the tropical oceans are warm, they expand. As a result, there is a permanent gravitational gradient from the tropics to the poles, and a corresponding slow movement of water following that gradient.
The major movement of heat by the ocean, however, is not gravitationally driven. It is the millions of tonnes of warm tropical Pacific water pumped to the poles by the alternation of the El Nino and La Nina conditions. I described in “The Tao of El Nino” http://wattsupwiththat.com/2013/01/28/the-tao-of-el-nino/ how this pump works. Briefly, the Nino/Nina alteration periodically pushes a huge mass of warm water westwards. At the western edge of the Pacific Ocean, the warm water splits, and moves polewards along the Asian and Australian coasts. Finally, at the poles it radiates its heat to space. Figure 1a from my previous post shows the action of the pump.
Figure 1a. 3D section of the Pacific Ocean looking westward alone the equator. Each 3D section covers the area eight degrees north and south of the equator, from 137° East (far end) to 95° West (near end), and down to 500 metres depth. Click on image for larger size.
Figure 1a shows a stretch of the top layer of the Pacific Ocean. It runs along the Equator all the way across the Pacific, from South America (near end of illustration) to Asia (far end of illustration). During the El Nino half of the pumping cycle, which corresponds to the input stroke of a pump, warm water builds up along the Equator as shown in the left 3D section. Then in the La Nina part of the cycle, the pressure stroke, that water is physically moved by the wind across the entire Pacific, where it splits and moves toward both poles.
Now, this El Nino/La Nina pumping action is not a simple feedback in any sense. It is a complex governing mechanism which kicks in periodically to remove excess heat from the tropical Pacific to the poles. As such it exerts control over the long-term energy content of the planet.
So here’s the first oddity about the PDO. The two alternate states of the PDO look very much like the two alternate states of El Nino/La Nina. In both, heat builds up in the eastern tropical Pacific, while the poles are cool. And in both, the alternate situation is where the heat is moved to the poles, residual warmth remains along the coasts of Asia and Australia, and the eastern tropical Pacific is cool.
This is an important observation because in addition to regulating the amount of incoming energy through the timing of the onset of the clouds and thunderstorms, the planet regulates its heat content by varying the rate of “throughput”. I am using “throughput” to mean the rate at which heat is moved from the equator to the poles. When the movement of heat to the poles slows, heat builds up. And when that pole-bound movement speeds up, the heat content of the planet is reduced through increased heat loss at the poles.
The rate of throughput of heat from the tropics to the poles is controlled at different time scales by different phenomena.
On an hourly/daily scale, the variations in the amount of heat moved are all in the atmospheric part of the system. The timing and amount of thunderstorms directly regulate the amount of heat leaving the surface to join the Hadley circulation to the poles.
On an inter annual basis, the throughput is regulated by the El Nino/La Nina pump.
And finally, on a decadal basis, the throughput is regulated by the PDO.
So as a functional definition, I would say that the PDO is a another part of the complex system which controls the planetary heat content. It is a rhythmic shift in the strength and location of the Pacific currents which alternately impedes or aids the flow of heat to the poles.
The Climate Effects of the PDO
As you might imagine, the state of the PDO has a huge effect on the climate, particularly in the nearby regions. The climate of Alaska, for example, is hugely influenced by the state of the PDO.
Nor is this the only effect. The PDO seems to move in some sense in phase with global temperatures. Since the Pacific covers about half the planet, this should come as no surprise.
How We Measure the PDO
The PDO was first measured in salmon catches. Historical records in British Columbia up in Canada showed a clear cyclical pattern … and since then, a number of other ways to measure the PDO have been created. Current usage seems to favor either the detrended North Pacific temperature, or alternately using the first “principle component” (PC) of that temperature. Since the first PC of a slowly trending time series is approximately the detrended series itself, these are quite similar.
To measure the PDO or the El Nino, I don’t like these types of temperature-based indices. For both theoretical and practical reasons, I prefer pressure-based indices.
The practical reason is that we don’t have much information about the North Pacific historical water temperatures. Sure, we have the output of the computer reanalysis models, but that’s computer model output based on very fragmentary input, and not data. As a result it’s hard to take a long-term look at the PDO using temperatures, which is important when a full cycle lasts sixty years or so.
The same issue doesn’t apply as much to pressure-based indices. The big difference is that the pressure field changes much more gradually than the temperature field at all spatial scales. If you move a thermometer a hundred metres you can get a very different temperature. That is not true about a barometer, you get the same pressure anywhere in town. Indeed, they don’t suffer from many of the problems in temperature based indices, in part because the instruments used to measure pressure are not subject to the micro-climate issues that bedevil temperature records. This means that you can directly compare say the pressure in Darwin and the pressure in Tahiti. So those two datasets are used to construct the pressure-based Southern Ocean Index.
As a result, it is much easier to construct an accurate estimate of the entire pressure field from say a few hundred stations than it is to estimate the temperature field. Indeed, this kind of estimation has been used for many decades before computers to construct the weather maps showing the high and low-pressure areas. This is because the surface pressure field, unlike the surface temperature field, is smooth and relatively computable from scattered ground stations.
The theoretical reason I don’t like temperature based indices is that people always want to subtract them from the global temperature for various reasons. I see this done all the time with temperature-based El Nino indices. It all seems too incestuous to me, removing temperature of the part from temperature of the whole.
The final theoretical reason I prefer pressure-based indices is that they integrate the data from a large area. For example, the Southern Ocean Index (which measures pressures in the Southern Hemisphere) reflects conditions all the way from Australia to Tahiti.
In any case, Figure 2 shows a typical PDO index. This is the one maintained by the Japanese at JISAO. It is temperature based.
Figure 2. The temperature-based JISAO Pacific Decadal Oscillation Index. It is calculated as the leading principal component of the North Pacific sea surface temperature.
As I mentioned, for the PDO, I much prefer pressure based indices. Here is the record of one of the pressure-based indices, the “North Pacific Index”. The information page says:
The North Pacific (NP) Index is the area-weighted sea level pressure over the region 30°N-65°N, 160°E-140°W.
Figure 3. The pressure-based North Pacific Index, calculated as detailed above.
As you can see, the sense of the NP Index is opposite to the sense of the JISAO PDO Index. They’ve indicated this in Figure 3 by putting the red (for warm) below the line and the blue (for cool) above the line, but this doesn’t matter, it’s just how the index is constructed. It moves roughly in parallel (after inversion) with the JISAO PDO Index shown in Figure 2.
Now, for me, both of those charts are totally uninteresting. Why? Because they don’t tell me when the regime changes. I mean, in Figure 3, was there some kind of reversal around 1990? 1950? It’s all a jumble, with no clear switch from one regime to the other.
To answer these types of questions, I’ve become accustomed to using a procedure that other folks don’t seem to utilize much. I’ve taken some grief for using it here on WUWT, but to me it is an invaluable procedure.
This is to look at the cumulative total of the index in question. A “cumulative total” is what we get when we start with the first value, and then add each succeeding value to the previous total. Why use the cumulative total of an index? Figure 4 shows why:
Figure 4. Cumulative North Pacific Index (inverted). The data have been normalized, so the units are standard deviations. The cumulative index is detrended, see Appendix for details.
I’ve inverted the cumulative NPI to make it run the same direction as the temperature. You can see the advantage of using the cumulative total of the index—it lays bare the timing of the fundamental shifts in the system.
Now, looking at the Pacific Decadal Oscillation in this way makes it a few things clear.
First, it establishes that there are two distinct states of the PDO. It’s either going up or going down.
In addition, it shows that the shift from one to the other is clearly threshold-based. Until a certain (unknown) threshold condition is reached, there is no sign of any change in the regime, and the motion up or down continues unabated.
But once that (unknown) threshold is passed, the entire direction of motion changes. Not only that, but the turnaround time is remarkably short. After only a few months in each case the other direction is established.
Finally, to me this shows the clear fingerprint of a governing mechanism. You can see the effects of the unknown “thermostat” switching the system from one state to the other.
RECAP
I’ve hypothesized that the Pacific Decadal Oscillation (PDO) is another one of the complex interlocking emergent mechanisms which regulate the temperature and the heat content of the climate system. They do this in part by regulating the “throughput”, the speed and volume of the movement of heat from the tropics to the poles via the atmosphere and the oceans.
These emergent mechanisms operate at a variety of spatial and temporal scales. At the small end, the scales are on the order of minutes and hundreds of metres for something like a dust devil (cooling the surface by moving heat skywards and eventually polewards).
On a daily scale, the tropical thunderstorms form the main driving force for the Hadley atmospheric circulation that moves heat polewards. Of course, the hotter the tropics get, the more thunderstorms form, and the more heat is moved polewards, keeping the tropical temperature relatively constant … quite convenient, no?
On an inter-annual scale, when heat builds up in the tropical Pacific, once it reaches a certain threshold the El Nino/La Nina alteration pumps a huge amount of warm water rapidly (months) to the poles.
Finally, on a decadal scale, the entire North Pacific Ocean reorganizes itself in some as-yet unknown fashion to either aid or impede the flow of heat from the tropics to the poles.
CONCLUSION
So … can the PDO help us to forecast the temperature? Hard to tell. It is sooo tempting to say yes … but the problem is, we simply don’t know. We don’t know what the threshold is which is passed at the warm end of the scale in Figure 4 to turn the PDO back downwards. We also don’t know what the other threshold is at the cool end that re-establishes the previous regime anew. Not only do we not know the threshold, we don’t know the domain of the threshold, although obviously it involves temperatures … but which temperatures where, and what else is involved?
And most importantly, we don’t know what the physical mechanisms involved in the shift might be. My speculation, and it is only that, is that there is some rapid and fundamental shift in the pattern of the currents carrying the heat polewards. The climate system is constantly evolving and reorganizing in response to changing conditions.
As a result, it makes perfect sense and is in accordance with the Constructal Law that when the sea temperature gradient from the tropics to the poles gets steep enough, the ocean currents will re-organize in a manner that increases the polewards heat flow. Conversely, when enough heat is moved polewards and the tropics-to-poles heat gradient decreases, the currents will return to their previous configuration.
But exactly what those reversal thresholds might be, and when we will strike the next one, remains unknown.
HOWEVER … all is not lost. The reversals in the state of the PDO can be definitively established in Figure 4. They occurred in 1923, 1945, 1976, and 2005. One thing that we do NOT see in the record is any reversal shorter than 22 years (except a two-year reversal 1988-1990) … and we’re about eight years into this one. So acting on way scanty information (only three intervals, with time between reversals of 22, 31, and 29 years), my educated guess would be that we will have this state of the PDO for another decade or two. I’ve sailed across the Pacific, it’s a huge place, things don’t change fast. So I find it hard to believe that the Pacific could gain or lose heat fast enough to turn the state of the PDO around in five or ten years, when we don’t see that kind of occurrence in a century of records.
Of course, nature is rarely that regular, so we may see a PDO reversal next month … which is why I say that tempting as it might be, I wouldn’t lay any big bets on the duration of the current phase of the PDO. History says it will continue for a decade or two … but in chaotic systems, history is notoriously unreliable.
w.
PS—This discussion of pressure-based indices makes me think that there should be some way to use pressure as a proxy for the temperature. This might aid in such quests as identifying jumps in the temperature record, or UHI in the cities, or the like. So many drummers … so little time.
MATH NOTE: The shape of the cumulative total is strongly dependent on the zero value used for the total. If all of the results are positive, for example, the cumulative total will look much like a straight line heading upwards to the right, and it will go downwards to the right if the values are all negative. As a result, it cannot be used to determine an underlying trend. The key to the puzzle is to detrend the cumulative total, because strangely, the detrended cumulative total is the same no matter what number is chosen for the zero value. Go figure.
So I just calculate the trend starting with the first point in whatever units I’m using, and then detrend the result.



(Paul Clark) says:
[ Greg, just a quick note to say here’s how to get a y=0 line:
http://www.woodfortrees.org/plot/jisao-pdo/integral/plot/jisao-pdo/scale
The rest, as my University computer support team, used to say, “Noted” 🙂 ]
Thanks for the tip, that does at least provide a reference for looking at rate of change +ve or -ve.
I hope you will find time to add some of the other things I mentioned.
thx.
Dan Evans, that’s a very good point to make. I’m all for Willis’ TS “governor” except that I think it’s more powerful than a governor, though that’s a good staring point.
However, I don’t think PDO is regulation , it is a measure of the controlled variable. Using NPI is a good idea. I don’t have any time for PDO or AMO, both “detrended” indices since there is not such thing as a linear “trend” in climate to be measured and subtracted. This is all borne of the failed hypothesis of a linear response to exponentially increasing CO2. This is essentially what they imagine they are splitting out.
To fit a linear trend you need to have a model that includes a linear trend. The a priori assumption for the last 30 years has be linear CO2 response + noise.
That model has failed and the recent volcano stack analysis proves it dead in the water.
Without the linear response there is no justification for linear “detrending” and thus AMO and PDO , as detrended indices, go out the window too.
If someone wants to suggest a slow rise sicne LIA we need to know what it really is before we can approximate it. ie where it tops out before we can use a linear as an approximation for that.
Now if we can free ourselves from all this baggage of preconcieved assumptions we may start to see what climate really does.
The lowest NPI monthly value each year is not always in January, and often correlates to the most negative monthly NAO value, suggesting a common driver:
http://snag.gy/OWNEs.jpg (NPI 1899.01 to 1948.12)
http://climatedataguide.ucar.edu/sites/default/files/cas_data_files/asphilli/npindex_monthly_1.txt
http://climatedataguide.ucar.edu/sites/default/files/cas_data_files/asphilli/nao_station_monthly_2.txt
“This discussion of pressure-based indices makes me think that there should be some way to use pressure as a proxy for the temperature.”
Compo et al 2013 did something similar. Bob covered this here:
http://wattsupwiththat.com/2013/04/08/a-preliminary-look-at-compo-et-al-2013/
“We use a completely different approach to investigate global land warming over the 20th century. We have ignored all air temperature observations and instead inferred them from observations of barometric pressure, sea surface temperature, and sea-ice concentration using a physically-based data assimilation system called the 20th Century Reanalysis.”
http://www.woodfortrees.org/plot/rss/from:1980/derivative/mean:12/mean:9/mean:7/plot/hadcrut3gl/from:1980/derivative/mean:12/mean:9/mean:7/plot/rss/scale/from:1980
Thanks to Paul Clark’s tip here’s rate of change of two surface temp series. Using the eye to ignore the bumps, it seems rate of change crossed from +ve to -ve in… 2005.
Paul C.
Thanks for adding the integral to w43s, long missed.
http://www.woodfortrees.org/plot/jisao-pdo/from:1900/normalise/integral/detrend:-10/normalise/plot/hadsst3gl/from:1900/mean:90/detrend:0.6/normalise
The integral of AMO does not make much sense since AMO is already the integral of ENSO,
http://virakkraft.com/Nino34-AMO-deriv.png (or maybe the AMO integral will anti-correlate arctic sea ice)
Remember where you saw it first Greg. (yes it’s exactly the same as Bob has been telling for years, just different 🙂
greg goodman says
http://wattsupwiththat.com/2013/06/08/decadal-oscillations-of-the-pacific-kind/#comment-1331971
henry says
from what time onward did we lose the idea of putting the (SI or other) dimension on the scale of the y-axis,
like I put in here?
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
I’ve just found the pattern that I got from the volcano stack. Spotted it in RSS
http://www.woodfortrees.org/plot/hadcrut3gl/from:1980/derivative/mean:12/mean:9/mean:7/plot/rss/scale/from:1980/plot/hadcrut3gl/derivative/mean:24/mean:17/mean:13/from:1983/to:2000
cf
http://climategrog.wordpress.com/?attachment_id=278
Now I’d already notices that the bumps looked like a full wave rectified (magnitude) cosine and that there were damn near four cycles in the 11 year interval between the higher peaks This suggests 11/4 or 11/2 as the the underlying cosine.
Looking at the RSS plot I realised it is two cosines added 11/3 and 11/2 = 3.7 and 5.5 years. In view of the crudity of this calculation, that’s the same as is found in W. Pacific wind speed.
http://climategrog.wordpress.com/?attachment_id=281
Now those two are mathematically equivalent to 2/(3/11+2/11) modulated by 2/(3/11-2/11) = 4.4 and 22 years
4.4 is very close to 8.85/2 =4.425 years, half the lunar aspides cycle. 22 years does not need any introduction.
Willis’ demonstration of the importance of tropics as general climate regulator explains the halving of that period. (cf sun passes over twice a year giving a strong six monthly signal).
The volcano stack shows that major eruptions synchronise with this sequence often enough for it to be the dominant pattern when they are averages together. So there’s a luni-solar link to the timing of those eruptions too.
Wow.
Thanks to Stuecker et al from drawing my attention to W. Pacific winds and to Willis for the idea of stacking volcanoes.
HenryP says:
June 9, 2013 at 11:29 pm
Henry@Phil.
you confuse E-UV (extreme UV) with F-UV (far UV)
No I don’t!
The ISO standard on determining solar irradiances (ISO-21348)[6] describes the following ranges:
Ultraviolet UV 400 – 100 nm 3.10 – 12.4 eV
Ultraviolet A UVA 400 – 315 nm 3.10 – 3.94 eV
Ultraviolet B UVB 315 – 280 nm 3.94 – 4.43 eV
Ultraviolet C UVC 280 – 100 nm 4.43 – 12.4 eV
Near Ultraviolet NUV 400 – 300 nm 3.10 – 4.13 eV
Middle Ultraviolet MUV 300 – 200 nm 4.13 – 6.20 eV
Far Ultraviolet FUV 200 – 122 nm 6.20 – 10.16 eV
Extreme Ultraviolet EUV 121 – 10 nm 10.25 – 124 eV
O2 absorbs by and is photo-dissociated into 2O by UV shorter than 242nm, i.e. UVC, F-UV and some E-UV.
O3 absorbs by and is photo-dissociated into O+O2 by UV shorter than 310nm, i.e. UVB & UVC
Because O2 and O3 can both absorb short wavelength UV radiation, no solar radiation with wavelengths less than 290 nm penetrates below the stratosphere.
As I understand, the E-UV is what forms the O3, HxOx and NxOx
The more E-UV, the less F-UV and normal UV will be coming through,
due to back radiation of this type of radiation by the increased O3, HxOx and NxOx
so, the less energy is coming into the oceans.
This is completely wrong, also since both O2 and O3 photo-dissociate there is no back radiation of UV, it ends up as kinetic energy, i.e. heat.
Greg Goodman says:
June 10, 2013 at 1:51 am
Gosh, Greg, if I had actually said that EOF detrends the data, you might actually have a point, and all of your succeeding rambling might have gone somewhere useful.
Unfortunately, I never said any such thing. Find me where I said “the EOF detrends the data” or anything like that. That’s just your fantasy. Provide a quote if you think it’s true.
Man, if you could read, you’d be dangerous. As it is, you’re just funny. I can defend my own statements. I can’t defend your fantasies about what I’ve said.
w.
woodfortrees (Paul Clark) says:
June 10, 2013 at 1:45 am
Fascinating, Paul. I can’t even begin to imagine what the dynamics might be in that relationship.
w.
Paul Vaughan says:
June 10, 2013 at 3:29 am
Paul, first, an actual citation to whatever previous work shows the same result that I have found would be good.
Why would it be good?
Because you’ve shown your word to be worthless, and so far all you’ve given me in support of your accusation of plagiarism is your big mouth.
You claim that the method I used, and the identification of the 2005 changepoint, is a “re-make of stuff others have shown here in the past”, and that it has been “pointed out many times over the last several years”.
That is a slimy accusation of plagiarism, Paul, without a scrap of evidence to back it up.
Typical of your bottom-feeding methods …
So here’s your ethical choices. You can either give us the citation to the “many times” that this finding or this method has been pointed out here on WUWT and show that I have stolen their ideas, or you can apologize for your untrue and baseless accusation.
However, you’ll likely take the unethical choice …
w.
Greg Goodman says:
June 10, 2013 at 8:38 am
Greg, I’d somehow missed your volcano stack post regarding SST. Nice stuff, well done.
w.
From Greg Goodman on June 10, 2013 at 8:38 am:
The only “RSS” there is a zero line. It shows you’ve applied your “special sauce” thrice-applied running means to show how well HADCRUT3gl can match HADCRUT3gl.
But it does highlight how much information your “special sauce” loses, distorting shape and amplitude, until the only trustworthy info it imparts for curve-matching is whether a lobe is pointing up or down.
I also noticed how you suppressed the range on the last plot element, when you also take that from 1980 to present it dramatically shows how the “special sauce” will screw up the same data until the curves stop matching, although it is the same underlying data. You have indeed discovered a great tool for finding a desired curve match.
Greg Goodman says:
June 10, 2013 at 4:56 am
So you’re willing to make accusations of plagiarism without providing a shred of evidence, just like Paul … nice.
Back it up or take it back, there’s a good fellow. I do my best to acknowledge all my sources, and have cited comments as touching off my posts.
w.
lgl says:
June 10, 2013 at 8:16 am
lgl, I don’t understand this at all, and the graph you cite doesn’t clarify. How exactly is the AMO the integral of ENSO?
w.
Paul Vaughan says:
June 10, 2013 at 5:28 am
Thanks, Paul. That’s no surprise, because the dataset that they used is some Hadley product. That’s why I used HadISST. I’d probably get closer with HadSST3. Unfortunately, all the website says is:
I think that they are referring to the now-deprecated UK SST product, but I haven’t had time or the interest to do the full analysis. The dataset is only available in gridded form. It is in four blocks in some text format.
I may redo the analysis using HadSST and Reynolds OI data … actually, as I recall the HadSST uses Reynolds OI data, so the HadSST dataset might do it on its own.
Always more to learn,
w.
henry@woodfortrees
Please explain to me as to why the y-axis does not show the dimensions (SI unit or other)
kakada says:
From Greg Goodman on June 10, 2013 at 8:38 am:
I’ve just found the pattern that I got from the volcano stack. Spotted it in RSS
http://www.woodfortrees.org/plot/hadcrut3gl/from:1980/derivative/mean:12/mean:9/mean:7/plot/rss/scale/from:1980/plot/hadcrut3gl/derivative/mean:24/mean:17/mean:13/from:1983/to:2000
The only “RSS” there is a zero line. It shows you’ve applied your “special sauce” thrice-applied running means to show how well HADCRUT3gl can match HADCRUT3gl.
But it does highlight how much information your “special sauce” loses, distorting shape and amplitude, until the only trustworthy info it imparts for curve-matching is whether a lobe is pointing up or down.
I also noticed how you suppressed the range on the last plot element, when you also take that from 1980 to present it dramatically shows how the “special sauce” will screw up the same data until the curves stop matching, although it is the same underlying data. You have indeed discovered a great tool for finding a desired curve match.
===
Well spotted, I retained hadcrut instead of RSS. Immaterial to the point of what I found.
RSS is there as the work around to get a straight line out of woodfortrees that the owner provided me with earlier. Messy but it seems the only way get a zero line and there’s no grid available on his plots.
If you have some intelligent objection to the triple running mean I’m very interested. Calling it a silly name does not impress me. If you read my page on why the filter is used you may learn something.
http://climategrog.wordpress.com/2013/05/19/triple-running-mean-filters/
“But it does highlight how much information your “special sauce” loses, distorting shape and amplitude,…”
That’s called filtering genius.
I limited the range to be about the same as what I used in the volcano stack plot. No underhand or special sauce reasons. Perhaps you’d like to replicate the volcano stack,run it back to 1980 and post back with a relevant comment.
On the other hand you can carry on making ill-informed, uneducated snipey remarks as usual. Seems to be about the limit of you intellect as evidenced so far.
Phil. says
O2 absorbs by and is photo-dissociated into 2O by UV shorter than 242nm, i.e. UVC, F-UV and some E-UV.
Henry says
some?
papers?
proof?
lgl says:
The integral of AMO does not make much sense since AMO is already the integral of ENSO,
http://virakkraft.com/Nino34-AMO-deriv.png (or maybe the AMO integral will anti-correlate arctic sea ice)
Here is d/dt sea ice against SST , both the derivative of what you were suggesting, so similar comparison. Long term the two run together but the dominant period in AMO does not match ice.
http://climategrog.wordpress.com/?attachment_id=160
However, that’s two more data sets showing a change of behaviour around 2005.
Willis
ENSO~AMO derivative, then ENSO Integral~AMO
A bit off in the 50s so add some NAO.
Willis, Degree or not, you are are an engineer’s engineer.
lgl says June 9, 2013 at 8:15 am, referring to Bob Tisdale:
“This recharges (or replenishes) the heat released during the El Niño.”
Oh not that nonsense again. El Niño heats the tropical Pacific, http://virakkraft.com/Rad-Temp-Trop-Pac.png
The graph you ar linking to I guess show SST combined with downward radiation, and of course showing that SST is higher during El Niñjo than during La Nina. As I understand Bob Tisdale he would not disagree with that. But when this heat enters the ocean is quite another matter, as this happens during a La Nina directly by the sun from a clear sky, gradually as the surface water is transported by the trade winds westward. And then it ends up in the West Pacific, warmer and reaching far deeper as it batters up. During an El Niñjo it sloshes back and spread out over the surface all the way to South Amercica, resulting in higher SST and releasing much of the heat to the atmosphere. So there is indeed a time scale combinded with some pure physical phenomena to be taken into consideration here in order to grasp the mechanism. That is what Tisdale very thorougly explains in this video as far as I understand him:
A time to time presumed relation between mean downwelling radiation and SST seems to miss the actual phenomenon.
Or dou you mean that the ocean heats more from backradiation from clouds During El Niñjo than from from a direct sun in a clear sky during La Nina?
From Greg Goodman on June 10, 2013 at 11:12 am: