This December was crazy hot. Most readers are aware of how unusually warm it was last month in the eastern U.S., but it was just as crazy hot — maybe more so — in England.
As a new year arrives, organizations which track climate release complete data for the preceding year. One of the first to do so, and the first I acquired, was daily Central England Temperature. It reports daily mean temperature since 1772, nearly 250 years’ worth.
That enables me to compute temperature anomaly (the difference between a given day’s temperature, and what’s typical for that day of the year), and to calculate monthly averages of same. This tells us how much hotter or colder than average was each month. I won’t keep you in suspense, here’s the December monthly temperature anomaly for all 244 years of record:
The final value, for December 2015, is circled in red at the right. It’s the hottest December on record. By a long shot. Here’s a histogram of December temperature anomalies:
The loner on the right, circled in red, is for a single value: December 2015. No other December got as hot as 4 deg.C anomaly, but this one exceeded 5.
Prior to 2015, the hottest December in the CET record was for 1934 — but it edged out 2nd-place 1974 by the narrowest of margins, a mere 0.003 deg.C. This year took 1st place, beating now-2nd-place 1934 by a whopping 1.58 deg.C.
It wasn’t just the hottest December on record, it’s the hottest monthly anomaly on record. By a long shot.
The final value, circled in red on the right, is for December 2015. It beat the now-2nd-place record by a whopping 1.38 deg.C. Here’s a histogram of all monthly temperature anomalies:
The circle on the right is for a single value: December 2015. Since it’s only 1 out of 2928 months on record, the bar representing it is too short to see. Only one other month exceeded 4 deg.C anomaly, and that by a little; this one exceeded 5, by a substantial margin.
I’m sure the deniers want to talk about how there are cold months too — even recently. But none have been as cold as this one was hot. Still, there is a good point to make: that we should put more emphasis on the trend than on the fluctuations. Lord knows I’ve emphasized that point myself often enough.
Climate is generally defined over 30-year periods. Maybe it’s a good idea to compute 30-year moving averages, to see what the recent trend value looks like. Even the most recent value will be only slightly influenced by this December’s record heat, it’ll be dominated by the other 359 months making up a 30-year period. Here ya go:
We haven’t just seen an astounding record-breaking December temperature in Central England. We’ve also seen a shocking upward trend.
Deniers love to find a cold month — or day — or snowball, if you’re a politician — and bleat about how it contradicts global warming. They love to complain when a super-hot month draws attention to global warming. They avoid the fact that the hots are hotter but the colds not quite so cold. And if they talk about trend at all, they’ll pick some all-too-brief span of time, and cherry-pick the start time, just so they can use the word “trend” without embarrassing their denial of man-made climate change. But when you look at trends which are long enough to tell the real story, you usually get a picture like the one above.
The plotted time is the mid-point of each 30-year period; the latest value represents 2001, covering the time from January 1986 through December 2015. If we want an estimate which goes up to the present, we can use a good smoothing method. I applied a modified lowess smooth on a 30-year time scale, giving this (plotted in red, I’ve superimposed it on the 30-year moving averages which are in black):
Whether you look at the most recent month, or the recent trend, it’s a bad time for global warming deniers in England.
Come to think of it, it’s a bad time for global warming deniers everywhere.
But, they haven’t had their last hurrah yet. Fluctuations will keep fluctuating, sometimes up (like now) and sometimes down. When the fluctuation goes down, they’ll have more to bleat about. And bleat they will. They’ll even sucker some people — after all, you really can fool some of the people all of the time.
But people are starting to notice. Even in the U.S.A. People are starting to “get it” — and even when the fluctuation goes down, more of them will remember rather than forget. They’ll realize, even when the cold comes, that it’s not quite as cold, but the hots are hotter. Some may even remember that it’s the trend that counts, and that ain’t goin’ away. It’s goin’ up.
After all — you can’t fool all of the people all of the time.
Thanks for the analysis–I am looking forward to more data from 2015, a remarkable and scary year in earth’s weather history.
Just most of the people, most of the time.
… And, especially given the evidence of 50 years of scientific counselling on the matter to the government, when they’d prefer to find a plausible excuse for *not* believing it rather than changing behavior. (“Someone else’s problem.”)
There’s a term I learned when taking some hydrogeology courses: NIMTO Not In My Term of Office
The prof used to testify about the dysfunctional and unsustainable nature of water rights management in Texas, which the legislators acknowledged, but didn’t want to do anything about it which could threaten them politically.
Just 50% plus one of the voters in any non-presidential election, after the recounting is done.
And the UK Met Office is suggesting 2016 will be even hotter. Surprising really as they tend to be rather conservative in their forecasts. http://www.carbonbrief.org/met-office-forecasts-2016-to-be-hottest-year-on-record
Looking at selected areas in eastern North America from Louisiana to Florida to Minnesota to Quebec, many appear to have broken December monthly temperature records by 2 to 3°C. Note: not surpassing the average monthly temperatures by 2 to 3°C, but the *record* values.
The 30 year moving average can be used to create a prediction envelope. So, given the trends in the anomalies and contingent upon the continuation of +ENSO, I wonder what the 50% prediction interval for next summer in, say, the USA looks like, atop “typical” temperatures.
Globally, too, it was very hot. I integrate the NCEP/NCAR reanalysis data here, and December beat the previous October highest by over 0.05°C. Prediction for GISS is over 1.1°C.
The NCEP/NCAR reanalysis v1 global average for October was stupidly hot at 14.82°C, which is 1.07°C above the 1961-1990 average. (So hot that I suspected some glitch or issue when I saw it.)
The ESRL site is down (yet again!) so I can’t check December, but taking your word for +0.05°C on the October anomaly, that really is in the “crazy” class.
Monthly global average NCEP/NCAR surface temperatures are (sometimes) available from here: http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries.pl?ntype=1&var=Air+Temperature&level=2000&lat1=-90&lat2=90&lon1=0&lon2=360&iseas=0&mon1=0&mon2=0&iarea=1&typeout=1&Submit=Create+Timeseries
“we should put more emphasis on the trend than on the fluctuations.”
I don’t think that is always the case.
Sure, when you are battling with folk who are still denying that warming is occurring, then the trend is your friend. But when you are trying to live with, or plan for, the fluctuations about that trend, then it is the fluctuations that assume greater importance.
Take your graph and histogram of Central England December anomalies. The average temperature in December 2015 was warmest at +9.7C and plots on the extreme right of the blue histogram. But just five year ago December 2010 similarly stood out as the second coldest in the series, at -0.7C, a difference of more than 10degC and it plots on the extreme left.
That is difficult enough for humans to plan for: how much road salt to buy, how many winter coats to manufacture etc., but for wildlife it can be lethal. If you are a mountain hare that turned white this winter in anticipation of snow on the hills to hide you from the eagles eyes, then this last December must have been a hard time, whereas hares that turned white later would have survived more easily. If we get another snowy December like 2010, then those same hares that stay brown longer would suffer.
The trend of warming is bad enough to cope with: some creatures will diminish, others will increase if there is steady warming. But if fluctuations are increasing, on top of an inexorable warming trend, then it becomes much more difficult to adapt.
So, please, let’s also emphasise the fluctuations. The question I would then ask is: are the fluctuations increasing?
For the reasons that Slioch mentioned and more, it’s the increase in the number and severity of the extremes that will do a lot of the pruning of populations in the coming decades and centuries, no matter the more gentle progress of the means.
I agree that trend is useful whereas records are the essential data- and particularly in the UK: given the countries climate we build everything to fit in a narrow comfortable band- never too hot, or too cold or too wet or too dry- we have a whole infrastructure, agriculture, and homes that just about cope with variability- the wrong snow, or minor heat wave and we don’t cope.
The first flooding just went over the new flood defenses, and that is the problem- the heatwave just has to be a little longer to buckle rail tracks or melt tarmac roads that cope with normal cold and heat- or flooding just a tiny bit more than the dam or defenses can cope with.
Planning as you say needs to cope with the worst.
I am informed that a lot of the nweer flood defence stuff added 20% for climate change, yet has already been overtopped or nearly overtopped. That things would get this messy so soon was not expected, although obviously some of it is surely just down to the old 1 in whatever number of years sort of occurence.
Again, I think that order statistics would be an interesting way to analyze extreme weather events–it offers somewhat better statistics that might make a change in distribution more evident sooner. And, after all, the fourth worst storm in a hundred years is still gonna be one helluva bitch.
Not sure I really understand the concept of ‘order statistics’, but it sparked an interesting idea–well, interesting to me, anyway.
So I downloaded UAH data, used Excel to generate annual averages, which were then graphed. I then ranked the monthly anomalies, using the rank function, binned the monthly data into 44-month segments, and calculated the mean rank for the bin. For display purposes, I then inverted the mean value by subtracting it from 440. The result:
It certainly minimizes the variation in the data quite a bit, but I’m not sure it really adds enough value to justify the effort. Then again, if I knew how to use Excel more efficiently…
The post below indicates that you do understand at least the basics of order statistics. The basic concept is that you rank the data smallest to largest and then you look for how the data trend. For instance, let’s say that you want to see if the data scale according to a particular distribution–you can look at how the 10 highest scale, and see if it is consistent with an exponential.
If you wanted to look and see if there is a change, you could then divide the data at a candidate change point and see if the support for a change is significant.
Basically, order stats are a generalization of extreme value stats, but they leave you with more of the distribution from which to draw conclusions.
Well, glad I wasn’t totally out in the weeds somewhere.
One interesting aspect of the news coverage of the recent floods here in various parts of the UK has been the routine mentioning of climate change, which hasn’t usually been the case in the past. Also, the very visible flowering of spring plants such as daffodils two months earlier than normal has meant that even the most inattentive people have realised that something is amiss.
In our garden, we have had roses flowering at Christmas for about the 5th year running. In the previous few years, it’s only been one or two plants, but this winter, we have had four flowering. I’m sure we’re not unique in this respect. As you say, people are starting to “get it”, but then they can hardly miss it.
Yes, even the plants are in on the AGW scam. My daffodils are close to flowering in my garden in England, the clematis is budding leaves already, and rose bush outside my study window is already putting out new leaves.
However, nice as these anecdotes are, its the trend that needs to pummelled into the deniers arguments.
Q: What’s the difference between a climate change denier and a computer ?
A: You only have to punch the data into a computer once.
Indeed, over at Anthony Watts’s site (http://wattsupwiththat.com/2015/12/31/montreal-record-busting-snow-sours-the-mild-winter-climate-narrative), they apparently think the fact that Montreal finally got a decent snowfall and it was a record snow for that particular date negates the fact that we just had the warmest December on record for a huge part of Eastern North America, shattering the previous records by a wide margin at many, many sites.
Appears that the usual suspects are claiming that last year was not particularly warm at all.. Only third warmest or so.. Based on RSS satellite data.. No surprises there.. ;)
Tamino, Ron Clutz is continuing to claim a recovery of Arctic sea ice using his nonsensical annual average graph based on MASIE data, and it has again been taken up by the GWPF.
You have thoroughly taken this nonsense apart back in September (Epidemic of Denial), but now I’ve compared the MASIE annual average graph to those of other daily data sets, and they’re not in agreement (understatement): A difference in nonsense
It’s a bad time for everyone. And everything. All over the planet.
I think those who proclaim AGW wrong need to stand up and be counted and proffer the risk of being wrong for themselves, rather than insist that everyone else take the risk for them being wrong.
Not just bets, but prison time and even the death penalty for mass murder if their ignorance is shown for sufficiently egregious psychopathic greed rather than “genuine” belief.
Or would there be not enough electric chairs for the deniers whose actions are demonstrably (if we can get access to their effects) wanting people dead rather than potentially gain less money?
[Response: Let’s not punish people for being wrong. The action I advocate for deniers, is to vote them out of office.]
Wow: “Not just bets, but prison time and even the death penalty for mass murder if their ignorance…”
Do me a favor and either don’t be an idiot or get off of our side.
May I suggest deleting the comment of “Wow”. It is disgusting.
If the climate goes wildly astray while the current crop of deniers are still alive, then they may find being out of office the least of their worries.
Imagine you are at war, how would you treat those who fought against you from within? Global warming does not yet have the urgency of war, but try imagining how El Nino’s will be in 20 and 30 years. Maybe there is some urgency, and maybe its time to stop treating the enemy within with kid gloves.
“Indeed, over at Anthony Watts’s site… they apparently think…”
The heat is not “crazy” In the short term, CH4 is about 80 times more powerful as a greenhouse gas as CO2. Thus, with CH4 near 2 ppm, it contributes the equivalent of 160 ppmve of CO2, and total current year to year greenhouse gas atmospheric concentration is on the close order of 560 ppmve of CO2. This is one factor driving rapid warming that is not in the models.
We need to think very carefully about the assumptions in the climate. models, and what the models actually tell us.
If you take into account the general warming, December 2010 was freakishly cold. I wonder if there was a volcanic eruption or something around then that we can attribute it to?
It was crazy warm here in Poland as well. Record-breaking anomalies for December: +5.27K according to blog of Piotr Djakow (in Polish). http://meteomodel.pl/BLOG/?p=11638#more-11638.
Hottest year on record as well.
@Aaron lewis. Huh?
Yous appear to be saying forcing by methane is one factor not in the models. That is an untrue claim. Google and wikipedia will show you are just wrong. Not on;y do they include forcings by methane, but also the other GHGs. https://en.wikipedia.org/wiki/Radiative_forcing#IPCC_usage.
2010 was cold where?
Looks to have been cold and warm in various places. >Climate change<
On average however,
2010 NOAA has that year tied as the warmest on record (by a small margin)
“2010 was cold where?”
The CET temperature record shows it as being cold in December 2010. This is the same data that shows it as being warm in December 2015.
There may be no identifiable reason for the cold, but that is no reason not to ask.
Greg – I think you’re missing the point. Even with global warming we will have hot and cold years, but the warm years will be more often record warm and the cold years will less often be record cold.
So 2015 is a record warm year – was 2010 a record cold year? It looks to be about tied for 8th to me. In fact, where very cold years used to be 6C below normal, in the past 50 years they only reach -5C. So the cold years *also* show warming.
Whatever the meteorological reasons for the ‘hot’ of Dec 2015 and the ‘cold’ of Dec 2010 in the CET record, they are not actually equivalent purely on statistical grounds.
There is a lot more variability in the winter month average temperatures than the summers. This extra variability is solely due to cold winters. Thus the maximum of monthly average temperature for all months sit in the range +3.4ºC to +4ºC above the average monthly average. There is no seasonality here but for minimums there is. The seasonal divergence-from-mean of minimum monthly average temperatures is much larger for winter months (-5ºC) than for summer (-2ºC). So the cold winter events like Dec 2010 should have larger negative anomalies than any hot winter event.
There numbers dependent on the how many years you average over, but the assertion holds in essence over the entire 1772-2014 period.
If you add 2015 into the analysis, the +5.5ºC anomaly now stands out as truly exceptional.
(Note that CET also provide ranked monthly anomalies. There is another anomaly that stands out, sitting more than 1ºC above its second rank – May 1833. A comparison of 1st & 20th ranks for each month does show a bit of variation for the months between summer (up to +2.1ºC) & winter (as low as +1.5ºC). Thus summer ‘hot’ months are less tightly grouped than winter ‘hot’ months, perhaps giving reason for May 1833. But Dec 2015 sits +2.9ºC above the 20th placed December, making a bit of a nonsense of an otherwise sweet seasonal variation level curve.)
Much of the variation in temperature in Britain is caused by the direction, and thus the source, of the wind. In December 2010 it was generally from NW to NE, thus bringing down dry Polar air. December 2015 has been predominately SW, bringing in moist air from the relatively warm Atlantic. Thus December 2010 was cold, dry and sunny, whilst December 2015 was mild, wet (very) and windy. To misquote Bob Dylan, in Britain, “You don’t need a weather vane to know which way the wind blows”: a thermometer is almost good enough.
The causes of those prolonged periods of Polar or Atlantic air appear to be associated with a stuck jet stream, which itself appears connected to a decreased temperature gradient between the North Pole and the Tropics, due to relatively rapid warming of the polar region. Those fluctuations have huge consequences, with the devastating floods of December 2015 being an example. Fluctuations matter.
I had in mind the Eyjafjallajökull eruption, but that was in April of 2010. I doubt that would have much influence in December, but I’m not certain.
Yes, December 2010 was not a record low, but if you account for the ~1 K warming we had then, it was pretty close. Without checking, I would guess that many of the earlier great lows were due to volcanoes.
So, with no other candidates offered, I’ll tentatively chalk it up to weather.
Slioch has it – the cold winter of 2010 was a result of the antics that global warming are playing with a warming pole.
The North Pole itself was experiencing the ongoing global warming in 2010, but the jet stream pattern forced a lot of the Arctic’s air over the UK, where, although relatively warm by Arctic standards, it was anomalously cold when it landed over Old Blighty.
It’s basically the same story as the anomalously cold patch of water in the North Atlantic. The water is colder than usual for that location, but it’s warmer than the ice from which it was derived by melting in the Arctic/Greenland regions.
Anomalies are great for standardiing comparisons of trends, but they can mask the fact that apparent cold at particular locations might not be inconsistent with an overall heating of the planet – it just depends on where the measured mass originates. Or to put it another way, it’s possible for something (eg air or water) to warm, but if it’s simultaneously moved to somewhere else that’s even warmer, then the result is an apparent cooling.
As Slioch notes, fluctuations matter – and so do anomalous changes in the context of geographical mobility/frames-of-reference…
Rather, the models use the long term equivalent between CH4 and CO2 (~20), rather then the higher short term value of between 80 and 90..
Do you have a source for this? Isn’t the whole point of running monte carlo simulations so that you don’t have to make approximations of this kind but instead can execute a sampling of what you believe to be a more accurate nonlinear model? For that reason it would surprise me.
I have to echo Douglas McClean’s concerns here. As I understand it, the major global climate models are based on physics. They calculate how spectra will be absorbed by atmospheric constituents, how aerosols get distributed by atmospheric circulation and so on. Saying that they use a “long term equivalent” reminds me of the claim by climate denialists that the models simply assume a climate sensitivity rather than performing calculations based on physics where climate sensitivity is simply a good way of summarizing how a model behaves — after the actual, physical calculations. Averaged over runs, the climate sensitivity of a given model tends to be relatively stable across a broad range of conditions — which is why it can be used to summarize.
Sorry Aaron, wrong, for the CMIP5 models at least. They use GHG/aerosol concentrations directly, not approximate aggregated radiative forcings. A reasonably approachable description of the CMIP5 design is here*: http://www.clivar.org/node/236
The x20 vs x80 thing is more relevant to the policy debate, where “CO2e” is, unfortunately, popular. Eventually folks will need to understand that the very long atmospheric lifetime of CO2 makes it by far the most intractable and dangerous pollutant. We do not have a good record dealing with pollutants with substantial fractional lifetimes of thousands of years (see e.g. nuclear waste).
(* From way way back in 2010. Does anyone else get this feeling of hopeless inertia … every time you even glance back at the literature.)
The last week of sea surface temperatures for the Nino3.4 region are in.
Weekly Oceanic Niño Index (ONI) for the 3.4 region (temperature anomaly for 5°N-5°S, 120°-170°W) is in, and at this point, at the weekly, monthly and tri-monthly levels, the current El Niño maxima exceed those of the 1997 El Niño.
Would anyone know what significant records are left for this El Niño to beat?
Would anyone know what significant records are left for this El Niño to beat?
According to those indices, Nino 1+2 and Nino 3, which were much warmer in 1997. Is there something special about 3.4?
NOV1997: 4.04 C
NOV2015: 2.24 C
Those results are fairly consistent for previous months of the respective years for Nino 1+2 and 3.
Nino 3 is the SST anomaly region 5N-5S, 150W-90W: Nino 1+2 is a smaller region off the West coast of S. America.
Here’s a map of the regions: http://ggweather.com/enso/nino_regions.gif
Barry, regarding why NINO3.4 gets used more so than other indices I found the following:
But what does Barnston mean when he states, “Later, an area called Niño3.4 was identified as being the most ENSO-representative (Barnston et al. 1997).”?
Fortunately the paper to which he refers is open access. I won’t quote it at length or attempt to summarize its argument. However, in the abstract it states that in contrast to the other Nino regions:
barry, you quoted at length from the article where it states in part:
My apologies, you are correct. The authors argue for more higher frequency extreme El Niño where the detrended temperature anomalies actually decrease. I misunderstood the article that I was citing. Perhaps the phrase “averaged over extreme El Niño events” helps to explain the difference as what I have focused on is the peak season, not averaging over the lifetime of the El Niño event. Regardless, it is obvious I have something to learn.
CORRECTION: I had written “The authors argue for more higher frequency extreme El Niño…” where I meant to write “The authors argue for a higher frequency of extreme El Niños…”
PS Even though November 2015 had a considerably higher ONI3.4 temperature anomaly (2.95°C) than December of 2015 (2.82°C), December 2015 easily beat the earlier monthly record (2.67°C) set back in December of 1997.
I have heard this El Niño referred to as Bruce Lee, Godzilla and Jurassic. Personally, I prefer the phrase “Jurassic El Niño” since it is suggestive of the fact that higher greenhouse gas levels are returning us to conditions not seen in thousands of years — and that the resulting higher global temperatures will result in more frequent and extreme El Niños. Of course, “Jurassic” may be a bit of an exaggeration at this point, but whether it remains so will depend on what we do…
You’re usually a pretty well-informed poster, Tim. So what, if you know, is the state of the art on the question of El Ninos as affected by warming? Last I heard, the research was still equivocal on that, but I don’t think I’m very well up to date on that particular question.
I’m a little skeptical of these hyperbolic calls. They seem a little bit like wishful thinking, as was evident with speculation about the 2014 el Nino that never materialized.
Here’s another index, tri-monthly Nino 3.4.
By that index we’ve twice in 2015 matched the warmth in the same 3-month periods in 1997. Otherwise, 1997 was warmer.
Would the uncertainties give us much ground to make definitive calls about the relative strength of el Nino 1997/2015?
Like Doc Snow, I thought the jury was well out on whether el Ninos would become more frequent and extreme in a warming world. I’d be interested in an update, too, Timothy.
Amendment (not to mention typos in my previous post):
“we’ve twice in 2015 matched the warmth in the same 3-month periods in 1997. Otherwise, 1997 was warmer.”
… except for the 3-month period AMJ: but, the 1997 el Nino had a later start than 2015. Still, I see no reason to revise reports from last year that this el Nino is nearly as strong as 1997(/98).
Barry, you write:
Warmer in terms of the detrended 3-month ONI index.
You will notice that the single decimal place accuracy ONI-index numbers correspond to the double here:
The method of detrending is mentioned on the page you cited:
As I had pointed out, in terms of the actual Niño3.4 region temperature anomaly for the OND-season during which both El Niños peaked, the 2015 El Niño was decidedly warmer, with 2015 at 2.74°C, 1997 at 2.63°C.
I regard the detrending as valid and as a distinct improvement over linear detrending, but it should be acknowledged.
Looking at the detrended ONI, 1997 is at 2.26 and 2015 is at 2.25, but 1982 is at 2.12. Thus while the record goes back to 1950, covering a span of 65 years, as measured by this index, all three super El Niños occurred in the past 33 years. The weakest of these occurred in 1982, and it was still nearly two tenths of a degree warmer than the next warmest El Niño. But the last two super El Niños, occurring within the last 18 years, had nearly identical detrended peak values (2.25 and 2.26) more than a tenth of a degree above the El Niño that peaked in 1982 (2.12). This would suggest that even with detrending extreme El Niños are becoming more common, or alternatively, more extreme.
Perhaps both the 1997 and 2015 El Niños were “Jurassic.”
PS A bit more on the detrending used in the Oceanic Niño Index and reasons behind it may be found here:
(If Tamino will permit the continued off-topic)
Timothy, I had assumed the data were the detrended values, and that you were talking about the relative strengths of the el Ninos rather than (‘absolute’) differences between SSTs.
News to me that the detrending method had changed, and I agree it seems to be a better one – overlapping 30-year baselines.
You wrote, “…resulting higher global temperatures will result in more frequent and extreme El Niños…”
The papers you cite consider the possibility of increased frequency of intense ENSO events, but do not suggest that the intensity will increase (in terms of relative SSTs, the metric we’re using here).
The weakening of the SST gradients is induced by faster warming in the background state along the equatorial than in the off-equatorial Pacific, and in the eastern equatorial Pacific than in the west […] leading to increased extreme El Niño occurrences even though neither the average amplitude of El Niño-related SST anomalies nor the frequency of El Niño is substantially changed.
The increased extreme El Niño events do not simply result from an increasing climatological rainfall, but from enhanced probability of the establishment of atmospheric deep convection in the eastern equatorial Pacific through the change in background conditions: as the Equator warms more rapidly than the SSTs at the climatological position of the ITCZ, it takes a relatively weaker SST anomaly as compared with the control period to establish the warmest water over the equatorial eastern Pacific. Detrended SST anomalies averaged over extreme El Niño events are indeed slightly smaller in the climate change period than those in the control period. There is virtually no change in occurrences concurrent with high SST anomalies (for example,>2 C), and most of the increased occurrences of extreme El Niño are associated with smaller SST anomalies.
Cai, Wenju, et al. “Increasing frequency of extreme El Niño events due to greenhouse warming.” Nature Climate Change 4.2 (2014): 111-116.
It will not take stronger el Ninos (or la Ninas) to cause stronger impacts in a warming world, particularly regarding rainfall. As el Nino/la Nina events are associated with greater rainfall and flooding in different regions for each (el Ninos also temporarily raise GSL), the possibility of greater frequency of intense events is a concern, but more concerning is that ENSO intensity (in terms of relative SSTs) will not even have to be so strong to cause severe impacts as the globe warms.
barry, you quote me:
The problem I see with what I had stated lies in why “frequent” refers to. For comparison, the number of precipitation events or hurricanes may decrease, yet the frequency of extreme precipitation events or strong hurricanes increase. Similarly, the frequency of El Niños may remain the same or even decrease while the frequency of extreme El Niños increases. What the authors are concerned with is an increase in the frequency of extreme El Niños.
When I was writing that particular sentence I was thinking of “more frequent” as referring to “extreme El Niños,” not “El Niños” but I see that it would normally be understood the other way.
I agree that the papers stated their arguments in terms of the increase in frequency of extreme El Niños. However, as I understand it, as with precipitation events or hurricanes, there is a distribution of El Niños along a dimension of strength or intensity. If the frequency of extreme El Niños increases, then the frequency of extreme-plus El Niños also increases. But the El Niños themselves aren’t tagged as it were, such that we know that a given extreme-plus wouldn’t have existed were it not for global warming.
It could either be understood that the extreme-plus El Niño would not have existed, or alternatively, that it would have existed but have only been extreme rather than extreme-plus. So what is understood as an increase in frequency of the extreme-plus may also be understood as an increase in the intensity of the extreme. It is more a matter of linguistics, or how we choose to divide in thought an undivided world. What empirical science is concerned with is how global warming changes in the distribution of El Niños, not how it creates or changes individual El Niños.
Barry, you state:
Agreed. As I understand it, the absolute humidity of saturation increases roughly as an exponential function of temperature, doubling with every 10°C. While wind speeds depend on the relative difference in temperature (which incidentally is why an El Niño never formed in 2014 – we had record high temperatures in the East Pacific – but the Pacific was pretty much warm all over), rainfall will be more a function of the higher absolute temperatures.
Anyway, I don’t think we were that far off from the main topic of Crazy Hot December. It wasn’t just crazy hot in the eastern US or England, or more recently, the Arctic, but also in the NINO3.4 region. And this in turn means that we can expect it to be crazy hot globally in the next few months.
I am certainly no expert in this area. I remember that there were those who argue that the Pacific will tend towards a semi-permanent state of El Niño-like conditions, others a La Nina-like conditions (the latter based in part upon paleoclimate data). There is also the argument that data suggests global warming will shift us from the classical East Pacific warm pool El Niño to the Central Pacific warm pool El Niño Modoki, although from what I have read El Niño Modokis tend to evolve into classical El Niños, as was the case most recently, with a Central Pacific warm pool that was the farthest West that we have seen of any El Niño Modoki.
However, I was thinking principally of the relatively recent, yet well-cited:
Cai, Wenju, et al. “Increasing frequency of extreme El Niño events due to greenhouse warming.” Nature Climate Change 4.2 (2014): 111-116.
… and what could very well be a companion piece:
Cai, Wenju, et al. “Increased frequency of extreme La Niña events under greenhouse warming.” Nature Climate Change 5.2 (2015): 132-137.
A more recent review by many of the same authors however reminds us that while recent models tend to agree that global warming will weaken the Walker Circulation, leading to more frequent and extreme El Niños (as well as La Niñas), in fact what we had seen quite recently was a record strengthening of the Walker Circulation. Thus the need for more research.
Cai, Wenju, et al. “ENSO and greenhouse warming.” Nature Climate Change (2015).
So I believe I could have been more careful regarding changes in the frequency of extreme El Niños under global warming.
Thanks for the cites!
There is a paper about heat in the Atlantic off Brazil causing high winds blowing west across the equatorial Pacific off Peru… England’s anomalous winds. This caused a dominance of La Nina and apparently extra ocean heat uptake. Sounded like a plausible mechanism. The winds are back to normal. That was quickly followed by the “blob” in the northeastern Pacific, and the PDO index went positive, Can there could be a La Nina and a solidly positive PDO index at the same time? If so, an unusually warm year during a La Nina event might be possible.
I missed the submission cut-off for the 2015 Recap thread, so I thought that I’d post an update response here to Wookey’s comment about the death toll from the UK storms.
Currently the toll is eight.
Reblogged this on The Lost City of Carcosa and commented:
We live in interesting times.
In response to the “but it’s been colder than usual at xyz locations” argument used by deniers when confronted with record hot temperatures, I thought that a strong argument _ similar to what BernardJ stated above, if I understood it _ would be to say that there are no sources of cold; there’s no giant air-conditioner in space blowing cold air at the planet. Colder temperatures in places where it’s usually warmer is merely the shifting of colder air or water by currents _ internal processes which are affected by global warming but says nothing about the causes. On the other hand, the planet heating up and heat records being broken cannot be from anything else but external forcings. And extra solar input and internal heat from undersea volcanoes have been eliminated as heat sources.
As a layman I’ve only got a shallow understanding of the whole issue so I’m wondering if this a valid argument, because I’ve often seen the “there are more heat records than cold records” rebuttal but I can’t remember seeing the points I’ve just made used to rebutt the “it’s been cold here” meme.
I must reluctantly say I think your argument fails–or at least is less clear than it could be–since advection can and does raise local temps (even on a planetary scale, since El Niños such as the present one are in crucial part advertise processes.) So the real issue, it seems to me, is one of scale, not of warming versus cooling.
Damn auto-correct anyway.
Thanks for the input, Doc Snow.
El Ninos are cyclical and occur in the timeframe of decades, so not relevant to the rising trend in temperatures over the last 150 years. Would that be correct?
In the context of whether hot record temps or cold record temps are meaningful, it doesn’t seem logical to me to not associate the multitudes of record hot temperatures around the world (which, if I’ve got my fact right have mostly happened in the last few years) to the rising trend in global temperatures.
If the trend was flat and there was not warming, wouldn’t records be broken randomly on the timeline due to purely random weather events, and not bunched up, as they are, at the end of the trendline?
Reading the last sentence of my last post, I’m not sure it’s making any sense. Sorry, I could be a bit confused.
Ig, if there were no warming trend, the ratio of record highs to record lows would be roughly 1:1 and their would be fewer record highs and lows as time goes on.
This isn’t what we are seeing:
“El Ninos are cyclical and occur in the timeframe of decades, so not relevant to the rising trend in temperatures over the last 150 years. Would that be correct?”
Yes, just right–which goes to the ‘scale’ issue. They are also an example of advection warming the entire planet, though, which goes to the heating versus cooling issue.
“In the context of whether hot record temps or cold record temps are meaningful, it doesn’t seem logical to me to not associate the multitudes of record hot temperatures around the world (which, if I’ve got my fact right have mostly happened in the last few years) to the rising trend in global temperatures.”
“If the trend was flat and there was not warming, wouldn’t records be broken randomly on the timeline due to purely random weather events, and not bunched up, as they are, at the end of the trendline?”
Yes, that’s correct, too. Without a trend, the distribution of cold versus hot records would be quite different than what we observe. And that, I think, is an argument that does *not* fail.
Somewhat OT for this post, but I would love to see Tamino’s trend analysis of the data behind the graph in this article about UK rainfall records:
Well I’ve just now learned that “Tamino” is the name of the lead character in Mozart’s opera “The Magic Flute” (while actually listening to it).
What’s up with that? (Pardon the expression)
[Response: It’s one of my favorite operas.]
Also, in the opera, Tamino must overcome deceit, fear and ignorance in order to arrive at the truth. Somehow, that seems familiar.
In Germany the December was also the hottest one on record, beating the previous record by +1.7 deg.C. The anomaly was +5.6 deg.C. For a while it looks like it could not only be the greatest positive anomaly ever, but it could beat the 2015 November also in absolute temperature!
It happens some times in the temperature record, that the December was warmer as the November, if the November was rather cold.
But this time the November was also a new record!