Guest Post by Willis Eschenbach
It’s been a while since I played “Spot The Volcano”. The premise of the game is that the decrease in temperatures from volcanic eruptions is nowhere near as large as people claim. So I ask people to see if they can identify when a volcano erupted based on the temperature records of the time.
Now, I say that the main reason the temperature drop from volcanic eruptions is so small is that when we get a reduction in downwelling radiation from any cause, the equatorial oceans start to cool. When that happens the clouds form later in the day, allowing in more sunshine. And the net result is that any cooling from the volcanic eruption is mostly offset by the increase in incoming solar energy.
With that in mind, I thought I’d take a look to see what records we have for the largest volcanic eruption in modern times. This was the eruption of the Indonesian island of Tambora in April of 1815. To my surprise, I found that we have no less than forty-two temperature records from that time. As you might imagine, most of these are from Europe. The list of the forty-two stations is appended in the end-notes.
So I took the records for the period during which the Tambora eruption occurred, and I “standardized” them so that they all had an average value of zero and a standard deviation of one. Then I plotted them all on one graph. Here is that result.
Figure 1. Temperature records of forty-two temperature stations for a period during which the Tambora eruption occurred. Seasonal variations have been removed from the data, leaving only anomalies. DATA SOURCE
As you can see, there is good agreement between the various records, with the cold and warm years affecting most if not all of the records. And if that’s too fuzzy for you, here is the same data with the average of all forty-two of the stations overlaid in red on the individual station records.
Figure 2. As in Figure 1, but with the average overlaid in red.
You can see the problem. The largest eruption in modern times, and it is absolutely not obvious when it happened …
So when was the eruption? Well, it’s not where you’d expect, which would be just before one of the two biggest drops in temperature, shown on the left-hand side of the graph. Nor is it where the big temperature drop is on the far right of the graph. Nope. It’s in a very generic area where you’d never expect it to be found …
Figure 3. As in Figure 1, but with the years added.
Now, there are a couple things of note here. First, there are a number of temperature drops even in only this short record which are much larger than the temperature drop after the Tambora eruption.
Second, there are a number of cold temperature excursions even in this short record, some of which are much colder than during the period after the eruption.
My conclusion from this? Yes, there were likely areas in Europe and the US which were somewhat colder than usual after the Tambora eruption. But temperatures somewhat colder than usual occur every few years …
And overall, despite the size of the eruption, despite the megatonnes of sulfur dioxide that the eruption sent up into the stratosphere, despite the reduction in sunlight from that stratospheric dimming … despite all of that, the effect on temperature was indistinguishable from natural fluctuations in other parts of the record.
My very best to everyone,
w.
PS—As is my custom, I ask that when you comment you quote the exact words you are discussing, so that we can avoid at least some of the misunderstandings that plague the intarwebs.
DATA NOTES:
The following records were used in this analysis:
Basel Binningen, Switzerland
Berlin-Dahlem, Germany
Berlin-Tempel, Germany
Bologna Borgo, Italy
Budapest, Hungary
Chalons, France
De Bilt, Netherlands
Edinburgh Royal Obs., UK
Gdansk-Wrzeszcz, Poland
Geneve-Cointr, Switzerland
Gordon Castle, UK
Greenwich Maritime Muk, UK
Hohenpeissenb, Germany
Innsbruck University, Austria
Karlsruhe, Germany
Kobenhavn, Denmark
Kremsmuenster, Austria
Leobschutz, Czech Republic
Madras Minamb, India
Manchester Ai, UK
Milano Linate, Italy
Montdidier, France
Munchen Riem, Germany
New Haven Tweed, United States
Nice, France
Palermo, Italy
Paris Le Bourget, France
Praha Ruzyne, Czech Republic
Regensburg, Germany
St.Peterburg, Russia
Stockholm, Sweden
Strasbourg, France
Stuttgart, Germany
Torino Casell, Italy
Torneo, Finland
Trondheim Tyholt, Norway
Udine Campoformido, Italy
Vilnius, Lithuania
Warszawa-Okec, Poland
Wien Hohe War, Austria
Woro, Finland
Wroclaw Ii, Poland
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This is an interesting approach
https://iopscience.iop.org/article/10.1088/1748-9326/aa7a1b
using break in temperature reconstructions to derive dates of eruptions
One thing I have learned before wading into the data is to get a view of prior work.
Not only are there more stations in GHNC v4 but there is additional data
see the work below.
Lesson: if you want to challenge the science around how volcanos work and the challenges of detecting
that, you need to do a basic literature review
( see figure 9 in https://sci-hub.tw/10.5194/cp-8-1551-2012)
Some other work
https://iopscience.iop.org/article/10.1088/1748-9326/aac4db
https://sci-hub.tw/10.5194/cp-8-1551-2012
https://sci-hub.tw/10.1016/j.gloplacha.2017.01.006
‘Volcanic eruptions primarily impact the global radiative budget of the Earth,
leading to a global temperature drop, as described in the introduction and first noticed
by Lamb (1970). For example, the cooling impact of the Mt. Pinatubo eruption is
evaluated to be of around 0.5 K (Soden 2002). Brohan et al. (2012) used an
unprecedented collection of observations of log-books preserved in the British library to
estimate the response of the global climate to the 1815 Tambora and the 1809 unknown
eruptions. They found a global temperature response to these two eruptions of the same
order of magnitude, which can be interpreted as rather modest given the reconstructed
IVI of these eruptions. Nevertheless, it remains difficult to assess the exact temperature
response to a particular eruption solely from observations given that the forced volcanic
signal is superimposed upon natural variability, for example related to ENSO, AMO and
NAO among others (Zanchettin et al. 2013a), wwhich can be superimposed on volcanic
eruptions’ impacts (Lehner et al. 2016). In addition, Canty et al. (2013) argued that
taking into account the ocean circulation changes due to the eruptions could lower the
estimate of the radiative directly induced global temperature cooling by a factor of two.
Nevertheless, their analysis should be considered with caution because they used an
AMO index as a proxy of ocean circulation, while the latter includes by construction
(spatial average of SST anomalies) the radiative changes due to volcanic eruptions (this
effect is further discussed in section 5).
….
Until recently, the signature of very large volcanic
eruptions like Samalas or Tambora was not clearly visible in temperature
reconstructions of the last millennium, in particular from tree ring data, which is known
to capture particularly well interannual climatic variations. To explain this mismatch,
Mann et al. (2012) proposed that years with very cold anomalies, similar to the year
without a summer following the Tambora eruption in 1816 (Luterbacher & Pfister 2015),
may prevent trees from growing and de facto inhibit the production of any ring. Such an
issue would have a very strong impact on the estimation of the age of trees and
consequently on the related chronology in the climate reconstructions, since some years
may be missing in the account of layers.
Schurer et al. (2014) showed that volcanic eruptions can explain most of the
forced variability over the last millennium as compared to solar variations. These
findings were confirmed over the last two millennia by using continental scale
reconstructions by PAGES 2k–PMIP3 group (2015). Concurrently, climate models seem
to produce too strong surface cooling related to volcanic eruptions (Fernández-Donado
et al. 2013). An overestimation of Northern Hemisphere temperature response to
volcanic eruptions has also been found by Schurer et al. (2013) using detectionattribution analyses.
Brohan, P. et al., 2012. Constraining the temperature history of the past millennium using early instrumental
observations. Climate of the Past, 8(5), pp.1551–1563.
https://sci-hub.tw/10.5194/cp-8-1551-2012
Amongst the archives in the British Library (BL) in London
are some 4000 logbooks from ships in the service of the English East India Company (EEIC); each recording the details
and events of a voyage from England to the Indies (usually
India, China or both) and back, typically taking the best part
of two years. The EEIC received its charter from Elizabeth
I in 1600, and many of its earliest voyages became famous
because of their excellent records of new lands; for example
that by Henry Middleton to the Moluccas in 1604-6 (Foster,
2010). These early voyages were recorded in diaries; logbooks – formally prepared documents of a standard format
– did not begin to appear until the 1650s. Their preparation
was part of an officer’s duties until the gradual expansion of
the Company in the 1830s into a quasi-military and political
body responsible for overseeing British interests in India and
beyond. Those archived in the BL, therefore, extend from the
1600s through to the 1830s, and are well-known to historians
(Farrington, 1999). They document social conditions, discipline, medicine and health, the trade and transport of goods,
people and passengers. They touch on first contact with new
lands and peoples, convey colonial attitudes and cultures, and
describe long lost coastal towns and villages. Many even contain detailed drawings of coastlines, ships, mammals, birds
and sea creatures.
Ship’s logbooks are also valuable sources of historical
climate data (Chenoweth, 1996; Wheeler et al., 2006; Brohan et al., 2009, 2010), and the EEIC logbooks include
daily records of the weather along the routes taken by the
ships: they cover large parts of the Atlantic and Indian
Oceans, and include the occasional foray into the Pacific. All
the logbooks contain wind speed and direction records, as
this was vital information for early navigators, but the later
logs, starting in about 1790, are even more valuable, as some
of them contain daily thermometer and barometer observations as well as the wind reports. The principal instigator of
the addition of instrumental observations was Alexander Dalrymple – the Company’s, and later the Royal Navy’s, first
hydrographer. Dalrymple was both an explorer and an enthusiastic scientist, and, as hydrographer, he was responsible for
ensuring that the EEIC ships could transport goods to and
from England as quickly as possible and at minimum risk
of loss. With this in mind, he equipped the East Indiaman
Grenville with a set of meteorological instruments for her
voyage in 1775 under Captain Burnet Abercrombie (Dalrymple, 1778), and set a pattern to be later adopted by officers on
all EEIC ships.
Brohan 2012
1. Read the literature.
2. Best estimate of the response is around .5C
3. Global land records have uncertainties much higher than the signal
4. Look at the other data
“The records of the English East India Company (EEIC),
archived in the British Library, offer a remarkable new insight into the weather and climate of the late eighteenth and
early nineteenth centuries. Their archives include 891 ships’
logbooks containing daily temperature and pressure measurements, and wind-speed estimates, each covering a voyage from England to India or China and back. The 273 000 new weather observations extracted from those logs provide
material for detailed reconstructions of the weather and climate between 1789 and 1834 and offer new insights into
pre-industrial climate variability. For all three meteorological
variables studied (temperature, pressure and wind) it is clear
that the data can be used for investigating variability over
the period of measurement, though comparison with measurements made decades or centuries later will require close
attention to observational biases.
The observations demonstrate that the large-scale temperature change, over the Atlantic and Indian Oceans, associated
with the two big tropical volcanic eruptions in 1809 and 1815
was modest (perhaps 0.5 ◦C). Some of the GCM simulations
in the CMIP5 ensemble show much larger volcanic effects
than this – such simulations are unlikely to be accurate in
this respect. Recent annually-resolved proxy reconstructions
of Northern Hemisphere temperature show a varied but similarly modest volcanic response (about 0.2–0.7 ◦C); the new
observations therfore provide an out-of-sample validation for
the proxy reconstructions – supporting their use for longer term climate reconstructions.”
OR, you can look at a small noisy subset ( skepticsTM technique) and conclude the science is wrong
“Now, I say that the main reason the temperature drop from volcanic eruptions is so small is that when we get a reduction in downwelling radiation from any cause, the equatorial oceans start to cool. When that happens the clouds form later in the day, allowing in more sunshine. And the net result is that any cooling from the volcanic eruption is mostly offset by the increase in incoming solar energy.”
1. would you accept this hypothesis as a definitive test of your model?
2. Can you quantify
A) the cooling you expect from volcanos
B) the amount of cooling offset?
c) the “net” small cooling?
You see with a physics model you can do all this, and you can discover that “hey your estimated cooling is too much” and this leads to additional insights
A) the size of particles matters
B) the concomitant natural cycles matter, and may be influenced.
C) the observations may be biased.
This is what distinguishes a “just so” explanation ( some cooling, offest by more sunshine) from a physics
explanation which has to put numbers ( even if they are guesses) on the line.
The just so explanation is so fuzzy that it’s hard to modify or improve in light of data.
The physics approach ,which puts numbers on the line(even if they are gross estimations) can be modified
enhanced, constrained. some answers can be ruled out, while other remain as “consistent with”
the approach.
Steven, if we had a “physics model” I’d be glad to use it. Instead we have tinkertoy models that don’t include host of important phenomena and have very little to do with the physics.
Now, if you want numbers, I’ve been there and done that, as you’d know if you had, what did you call it … oh, yeah, “Read the literature.” I showed that a decrease in downwelling solar at the Mauna Loa observatory due to Pinatubo and El Chichon of up to 60 W/m2 had no visible effect on the Mauna Loa temperatures.
So piss off with your “This is what distinguishes a “just so” explanation ( some cooling, offest by more sunshine) from a physics explanation which has to put numbers ( even if they are guesses) on the line.” I’ve given you stacks of numbers over the years, including the very numbers you are now asking for, and you have roundly ignored them or dissed them or made one cryptic information-free comment and kept on with your nonsense.
w.
Large volcanic eruptions are, at most, short transient events in most temperature records. El Chichón and Pinatubo are most noticeable in the satellite stratospheric temperature data. Otherwise, they didn’t leave much of a mark.
Willis is spot on about Tambora. Also, the Pleistocene Toba eruption, which at one time was suspected of nearly wiping out our ancestors didn’t leave a noticeable tempeature mark in any of the ice cores.
Also, the Pleistocene Toba eruption, which at one time was suspected of nearly wiping out our ancestors didn’t leave a noticeable tempeature mark in any of the ice cores.
The period following the Toba eruption shows a prolonged temperature drop in the Vostok ice core.
Phil. January 27, 2019 at 10:50 am
Must be time for “Spot The Volcano, Toba Edition” …
Answer to follow …
w.
That looks like the period from 80,000 BP to 60,000 BP and Toba is dated to around 74,000 BP so that would put it during the first drop, there is evidence that Toba may have been as many as four events. Dating it precisely in the ice core records is difficult because there is no associated tephra so it’s done using sulphate and isotope measurements.
Thanks, Phil. Actually, these days it’s been dated a bit more accurately. From the paper:
Here’s the location …
Not seeing the claimed huge cooling …
w.
The 18 month post Tambora period seems to be the longest overall cooling trend in the graph.
efolding time of the aerosols are around 1-2 years
if they get to the stratosphere, otherwise they rain out quickly
Just more confirmation that no matter the concentrations of individual gases in the atmosphere, just one defines temperature.
Solar radiation volumes hitting the earth surface are controlled by h20 in a pretty narrow band.
A dim sun = less cloud, and a strong sun = more cloud.
Its seems to me a ”cycling speed” thing.
More energy absorbed and a faster cycle of transfer.
Hi Willis,
Century-scale volcanoes like El Chichon and Pinatubo are clearly evident when one plots the Nino34 Area Sea Surface Temperature, vs. the Global UAH LT temperature four months later.
https://wattsupwiththat.com/2018/09/20/icelands-monster-volcano-charging-up-for-eruption/#comment-2463203
It is known that major (century-scale) volcanoes cause about 0.5-0.6C of global cooling, due to the ejection of fine materials into the upper atmosphere, which take about 5 years to fully dissipate – see below for the evidence. These large volcanoes reportedly also emit large quantities of CO2.
It is obvious that the global cooling effect of the fine volcanic ejecta greatly overwhelms the global warming effect of the CO2. Quelle surprise!
…
Regards to all, Allan
Notes:
The Nino34 Area Sea Surface Temperature (the blue line in the following plot), adjusted by the Sato Global Mean Optical Depth Index (for major volcanoes – the yellow line), correlates quite well with the Global UAH LT temperature four months later (the red line).
https://www.facebook.com/photo.php?fbid=1527601687317388&set=a.1012901982120697.1073741826.100002027142240&type=3&theater
It is clear from the divergence of the red line (Global UAH LT temperature) below the blue line that (Nino34 SST) that El Chichon and Pinatubo caused about 0.5C to 0.6C of global cooling that took about 5 years to fully dissipate (warm up) in each case.
As I recall, Mt St Helens was probably large enough to cause cooling too, except that it blew sideways, not up – fatal for the observer located in that direction.
I think St Helens didn’t release much SO2 either. Those Indonesian volcanoes have a lot more.
I didn’t include references, but I wrote in http://wermenh.com/1816.html :
My reference link is stale, I don’t have time at the moment to hunt things down.
ALLAN MACRAE January 27, 2019 at 5:36 am
Sorry, Allen, not seeing it … here’s “the Nino34 Area Sea Surface Temperature, vs. the Global UAH LT temperature four months later.” Large red/black and blue/black dots are Pinatubo and El Chichon eruption dates, arrows show the two years following each one.
What am I missing?
w.
Hi Willis – can you see this plot, referenced above? If not, contact me through my website and I will email it to you with the spreadsheet.
See the places where the red and blue lines diverge – that is the magnitude of the volcano-induced cooling.
Best, Allan
https://www.facebook.com/photo.php?fbid=1527601687317388&set=a.1012901982120697.1073741826.100002027142240&type=3&theater
Allan, I can see it. A question—what is “Sato”?
w.
Hi Willis,
Sato Aerosol Optical Depth Volcanic Index:
http://data.giss.nasa.gov/modelforce/strataer/
https://data.giss.nasa.gov/modelforce/strataer/tau.line_2012.12.txt
Data goes back to 1850 but stops in 2012 – but no Century-scale volcanoes since then (I think).
Best, Allan
———————————————————–
I used the Sato to adjust the calculated UAHLT for the volcanic effect – that is the yellow line.
Note the divergence post 2016, where the yellow and blue lines sit below the red line – curiouser and curiouser.
Maybe the right chart, showing you what isn’t visible in yours?
https://drive.google.com/file/d/134HW_g8ensDzrWyHgHKWz45fR4UqGb_8/view
Please have a look at 18982/83 (St Helens, Chichon), 1992/93 (Pinatubo.
You clearly see the volcano influence many commenters were talking about.
And it’s off topic, but you see also that
– the tropospheric response to ENSO- is much smaller than that to ENSO+;
– 2016 was something unusual compared with 1998 (the LT signal was higher in 2016 then in 1998, despite the ENSO signal having been a lot weaker).
Bindidon, per your graph it looks like the volcano is warming the troposphere … no?
w.
Willis
No of course it doesn’t. How do you come to that strange conclusion?
You easily can see that exactly at the eruption points, the troposphere cools.
Would that not have been the case, then the tropsphere would have reached at that time the same level as MEI’s El Nino signal, just like in 1997/98.
You also easily can see in a comparison of UAH’s lower troposphere (LT) and lower stratosphere (LS), that at these eruption points, the stratosphere warms:
https://drive.google.com/file/d/1_ecu50TZYPYfr57XIWZ_rcu9p2trm2hy/view
Sources (column 3 in each):
– LT: https://www.nsstc.uah.edu/data/msu/v6.0/tlt/uahncdc_lt_6.0.txt
– LS: https://www.nsstc.uah.edu/data/msu/v6.0/tls/uahncdc_ls_6.0.txt
Thanks, I was reading it backwards.
w.
You’re welcome.
J.-P.
OK, I can see this chart. While initially there appears to be some congruence, I think Willis’ has the correct back-check on that, do a scatter-plot. It normalizes what you’re looking at. Wait a second…
@Willis, what if you take a difference, (somehow)… assume ENSO is a trend-line, how far does the GST vary from that trendline? A “de-trended” data set, IOW?
FB says I’m not part of your “audience”. Can you put it someplace else so all can see it?
Hi RedV – does this work for you? Please advise.
Willis, you are a bloody gem. Talk about throwing a hand grenade into the conversation, this is one of the best. I always knew that volcanic eruptions lowered the global temperature because I read it somewhere. Now I see that I may have been a lazy gullible. Keep up the good work.
Just found that study with references to mid-ocean seismicity and termohaline circulation.
Compiling all the stations into one graph hides any regional anomalies that might have occurred. Parts of New England, for example, had a very cold summer in 1816 with many days of freezing rain, snow and frost. One might make the case that the temperatures during 1816 were actually cooler than they might have been had the volcano not erupted.
Wayne Shepheard:
A volcanic eruption does not instantaneously affect average global temperatures, it typically takes about 12 months before its maximum cooling effect occurs, as its SO2 aerosols circle around the globe.
The cold 1816 summer was right on schedule for the April 1815 Tambora eruption.
There was a post awhile back, I think on here(?) about the “year without a summer”, and found while indeed there was at least one frost episode in every month that summer, if you turned the daily temperature into monthly averages (as we do to modern-day data) there was almost no difference between the summer of 1816 vs. 1815 or 1817.
This is a grim story – about 1816 – “The Year Without Summer”, following the eruption of Tambora in 1815.
https://en.wikipedia.org/wiki/Year_Without_a_Summer
The Year Without Summer was called “the last great subsistence crisis in the Western world”.
It was cold circa 1800 during the Dalton solar minimum – as Napoleon’s Grande Armée discovered in 1812 on their disastrous winter retreat from Moscow.
Britain (including Canada) and the USA engaged in the War of 1812. The Americans tried to keep warm by burning Toronto, and our side tried to keep warm by burning the White House. Since then, both sides have declared victory – Canadians resent Toronto and Americans resent the White House, so both sides think they got the better of that deal.
According to wiki:
“As a result of the series of volcanic eruptions, crops in the aforementioned areas had been poor for several years; the final blow came in 1815 with the eruption of Tambora. Europe, still recuperating from the Napoleonic Wars, suffered from food shortages. Food riots broke out in the United Kingdom and France, and grain warehouses were looted. The violence was worst in landlocked Switzerland, where famine caused the government to declare a national emergency. Huge storms and abnormal rainfall with flooding of Europe’s major rivers (including the Rhine) are attributed to the event, as is the August frost. A major typhus epidemic occurred in Ireland between 1816 and 1819, precipitated by the famine caused by the Year Without a Summer. An estimated 100,000 Irish perished during this period. A BBC documentary, using figures compiled in Switzerland, estimated that the fatality rates in 1816 were twice that of average years, giving an approximate European fatality total of 200,000 deaths.”
In New Hampshire, we did not have a July frost in the southern part of the state. There are claims they did in Franconia, in the White Mountains.
I think the polar jet stream was overall pushed south but also had a meridional flow that both let cold air go south, and hot air come north. The highest temperature that summer in southern NH was 100F on June 23rd. While that didn’t negate the killing frost earlier in the month, the heat wave help mask it in monthly averages.
Looks to me that some sort of integral or cumulative plot of the anomaly would be more revealing. I’ve seen lots of data that does not show up if the time domain is wrong.
I have done some work on GCRs nucleating not just clouds but magma gases as deep as 4.4 km.
So in our “disaster cycles” Quiet sun letting in GCRs causes dropping temperatures due to clouds and also increased earthquakes and vulcanism. It’s a double whammy.
The Hawaii volcano 2018 and it’s cyclical wee hours eruptions /EQ in the plus 5 range led me to this line of study. I need to do more mathmatically and statistically, but this month of work will not allow it. It’s a big deal though, and I am convinced (myself) it is true, but to what degree.
Why bother looking at monthly, or even daily or hourly, data to find an event that has a lifetime of one or two years (or maybe 3 for the really big ones). At least one should take annual data, at the shortest. Since el Nino is the biggest competitor to volcanoes for putting bumps in the record, and has a recurrence interval on the order of 5 years, a 5-year smoothing would remove much of the el Nino “noise”.
John Christy ran a 5-year running mean of several tropospheric data sets, including his own, and gets:
Can you spot the volcanoes?
Hint: there’s two of them.
Thanks, Richard. I made your graphic visible. Here’s the problem.
A “running mean” is the worst of all filters, because it turns peaks into troughs, and troughs into peaks.
Here is Christy’s lower troposphere temperature data (yellow), and that same data smoothed with a 5-year running mean (red).
As you can see, Pinatubo occurred right at a temperature peak … but after the running mean it’s at the bottom of a trough. And the opposite happened to El Chichon … it occurred at the bottom of a trough, and after the running mean it’s near a peak.
Running means are rubbish, and should NEVER be used to smooth data.
w.
Yeah, simple running means create more artifacts than most statistical shenanigans. Perhaps Christy should have used a gaussian or other smoother, but for his purposes the running mean sufficed to show his point – very powerfully!
It looks like he did a centered five year mean, which runs from Year-2 to Year+2, which means the effects of the volcano may show up 2 years before the blow-out! If you shift the smoothed curve two years later, to have a following mean from Year+0 to Year +4, the dips and peaks seem to line up a bit better (a quick glance here). Physically that makes sense.
Unfortunately, for the 5-year following means, el Chichon has no Year 0 five year mean, since it occurred 3 years after the data starts in 1979.
Willis
“Running means are rubbish, and should NEVER be used to smooth data.”
I made a different experience all the years when comparing time series.
While agreeing with you about running means being useless everywhere you need to go into little details, I think that they are conversely pretty good whenever you want to compare series behaving only superficially different.
Here is an example: a comparison of GHCN V3 with UAH 6.0 land-only:
https://drive.google.com/file/d/1aymAha2312Tiw8XqHrf6qIKaiN5RYbgt/view
Behind the inevitable differences in the standard deviations, which look like texts written using different dialects, the running means perfectly extract what the series really have in common.
Rgds,
J.-P.
Amateurish rubbish! Polarity reversal NEVER occurs in the low-frequency pass-band of running means, only for alternate higher-frequency side-lobes of the sinc-function-like frequency response H(f). While they’re very far from optimum as low-pass filters, the harmonically spaced zeros of H(f) are practically indispensable in TOTALLY eliminating strictly periodic (diurnal and seasonal) components of climate data , which otherwise would obscure the orders-of-magnitude smaller climate signal.
For those unfamiliar with the frequency response of N-term moving averages:
H(f) = sin(Npi*f)/[Nsin(pi*f)], for f in the interval [0, 0.5]
That occurs ONLY because an unintelligent choice of N was made, which put the high frequencies of volcanic effects on one of the negative side-lobes of H(f). Such are the hazards of analytically blind number-crunching. That unremitting blindness to Fourier synthesis and analysis of data is the entire basis of the Ocasio-Cortez-level populist appeal: “who are you gonna believe … 1sky1 or your own eyes?”
BTW, professionals in DSP have long recognized that running means are the OPTIMAL filters of given length for suppressing noise.
1sky1 February 4, 2019 at 2:58 pm
I just demonstrated, not claimed but demonstrated, that a running mean turns troughs into peaks and vice versa.
Now you come along and claim that’s perfectly OK because … well, something about polarity and side-lobes. Look, I don’t WANT peaks in my data turned into troughs and vice versa, no matter how much you may claim it is all perfectly fine.
And for all the rest of you good folks, who are you gonna believe … 1sky1 or your own eyes? LOOK AT THE ARROWS to see what a running mean does to a trough. In addition, the running mean has taken Pinatubo from occurring at a peak in the data (yellow line) to occurring at a trough in the running means (red line) … but no worries, 1sky1 assures us that’s no problem at all.
w.
My 4:36pm comment properly belongs here.
I was able to identify it in the first graph before looking forward.
Your position on this does not really appear to be very scientific and is aimed more as a propaganda ploy.
Yes, the climate or weather is very variable. I think most people can understand this.
but there are ways to extract the relative effects of volcanic eruptions by understanding some of the other drivers of climate and weather.
Oceans dominate Earth’s temperature stability. A short event like a volcano would have little effect on Earth’s average temperature.
But the wrong event on the wrong moment can be disastrous in an Europe recovering from 20 years of continuous wars with a shortage of able young men and horses.
“A short event like a volcano would have little effect on Earth’s average temperature.”
I don’t agree.
Because our climate primarily depends on solar radiation reaching the oceans.
Huge volcanic eruptions uniformly fill the atmosphere with aerosols.
Thus if you want to quantify volcano effects, the worst idea is to restrict your analysis on land surfaces.
Between 1250 and 1600, there was an endless series of huge eruptions (VEI 6 to 7), beginning with Samalas on Lombok Island (Indonesia).
The influence of the aerosol spread during two centuries certainly was far bigger for the oceans than for the land surfaces: while the latter quickly move from warm to cold and vice-versa, the oceans store heat for much longer time.
Vilnius, Lithuania
Warszawa-Okec, Poland
Wien Hohe War, Austria
Woro, Finland –>
Vilnius, Lithuania
Warszawa-Okec, Poland
Wien Hohe Warte, Austria
Woro, Finland
https://goo.gl/images/s7NknL
https://goo.gl/images/HqsNyi
Who is “we”? I’m surprised you didn’t use Gov William Plummer’s records from Epping NH. While I only created a spreadsheet for his April-September 1816 temperatures, his records are important as they’re at a highly impacted area.
There are also records lurking around from Massachusetts, Vermont (or just south), and maybe another good one in New Hampshire. I don’t know where they are and they may not even be scanned or the data digitized.
For anyone else interested, Plummer’s data is at http://wermenh.com/1816/ – There’s a lot of other stuff, including an NH report I wrote for a Geocache and a more scientific look that I wrote for WUWT et al for the 200th anniversary.