From Northeastern University via Eurekalert, and the department of modeling for 10 million dollars, this seems to be all they could come up with. Nature has a way however, of taking the the best laid plans and rendering them moot. I don’t think they’ve noted ‘the pause’ yet. There’s no paper listed, nor data references, nothing, making it one of the worst press releases I’ve seen in awhile. The press release upstream at the University is hardly any better, citing the 97% consensus as if it has anything to do with extremes modeling, but at least they gave a link to the paper where Eurekalert didn’t.
Big data confirms climate extremes are here to stay
In a paper published online today in the journal Scientific Reports, published by Nature, Northeastern researchers Evan Kodra and Auroop Ganguly found that while global temperature is indeed increasing, so too is the variability in temperature extremes. For instance, while each year’s average hottest and coldest temperatures will likely rise, those averages will also tend to fall within a wider range of potential high and low temperate extremes than are currently being observed. This means that even as overall temperatures rise, we may still continue to experience extreme cold snaps, said Kodra.
“Just because you have a year that’s colder than the usual over the last decade isn’t a rejection of the global warming hypothesis,” Kodra explained.
With funding from a $10-million multi-university Expeditions in Computing grant, the duo used computational tools from big data science for the first time in order to extract nuanced insights about climate extremes.
The research also opens new areas of interest for future work, both in climate and data science. It suggests that the natural processes that drive weather anomalies today could continue to do so in a warming future. For instance, the team speculates that ice melt in hotter years may cause colder subsequent winters, but these hypotheses can only be confirmed in physics-based studies.
The study used simulations from the most recent climate models developed by groups around the world for the Intergovernmental Panel on Climate Change and “reanalysis data sets,” which are generated by blending the best available weather observations with numerical weather models. The team combined a suite of methods in a relatively new way to characterize extremes and explain how their variability is influenced by things like the seasons, geographical region, and the land-sea interface. The analysis of multiple climate model runs and reanalysis data sets was necessary to account for uncertainties in the physics and model imperfections.
The new results provide important scientific as well as societal implications, Ganguly noted. For one thing, knowing that models project a wider range of extreme temperature behavior will allow sectors like agriculture, public health, and insurance planning to better prepare for the future. For example, Kodra said, “an agriculture insurance company wants to know next year what is the coldest snap we could see and hedge against that. So, if the range gets wider they have a broader array of policies to consider.”
The paper:
http://www.nature.com/srep/2014/140730/srep05884/full/srep05884.html
Asymmetry of projected increases in extreme temperature distributions
Evan Kodra & Auroop R. Ganguly
A statistical analysis reveals projections of consistently larger increases in the highest percentiles of summer and winter temperature maxima and minima versus the respective lowest percentiles, resulting in a wider range of temperature extremes in the future. These asymmetric changes in tail distributions of temperature appear robust when explored through 14 CMIP5 climate models and three reanalysis datasets. Asymmetry of projected increases in temperature extremes generalizes widely. Magnitude of the projected asymmetry depends significantly on region, season, land-ocean contrast, and climate model variability as well as whether the extremes of consideration are seasonal minima or maxima events. An assessment of potential physical mechanisms provides support for asymmetric tail increases and hence wider temperature extremes ranges, especially for northern winter extremes. These results offer statistically grounded perspectives on projected changes in the IPCC-recommended extremes indices relevant for impacts and adaptation studies.
Figure S1
Methodology aside, it seem like they may be laying the ground work, wittingly or un, for continuing the CAGW gravy train. I recall that someone here, possibly Willis, had found information that during the Little Ice Age, there were periods when very warm temperatures occured, even though the overall regime was colder. Now they may be trying to flip that and claim even though there may be colder periods that the overall regime will be warmer.
O.K. Somebody had to do it!
http://www.bishop-hill.net/blog/2013/6/19/here-come-de-heap-big-warmy.html
One of my favourite posts is where Willis Eschenbach replicates the ‘massively complex’ GISS model E, presumably running on a super computer somewhere, and produces essentially the same output, using Excel.
http://climateaudit.org/2011/05/15/willis-on-giss-model-e/
Give the 10 million to Willis. He’ll probably do something useful with it. 😉
I like the way the they conflate local weather distribution (“cold snaps” even as average temperature rises) with colder average temperatures, as if they are the same phenomenon:
The press release seems to put the equating of these very different phenomena directly into the mouth of Kodra, who is cited for both halves of it. Sorry, excursions FROM average temp and excursions OF average temp are not the same thing. Government funded “science” at work.
John at L du B :
Not everyone agrees that the world is warming. For example, the temperature record of the last seventeen years does not agree with you.
They forget to check with the real world. Extreme temperature records have become LESS common:
http://en.wikipedia.org/wiki/U.S._state_temperature_extremes
They also forgot to consult with a meteorology 101 handbook:
When you warm higher latitudes and decrease the meridional temperature gradient, you get less energy for storms/weather systems and less extreme weather.
Add water vapor to the air and guess what happens to diurnal temperature fluctuations?
They decrease. Dry air has less heat capacity.
Modest, beneficial global warming over the last century has done the complete opposite of what they are claiming.
Just another example of an expensive work of junk science designed to support the agenda that makes anybody that believes it even dumber about climate science and weather.
John in L du B says:
Are you kidding me!!!?? Does anyone actually do measurements anymore or work with real data? Everyone agrees that the world is warming…
John, I am part of the set ‘everyone’. So if I may falsify your conjecture:
http://www.woodfortrees.org/plot/rss/from:1997/plot/rss/from:1997.9/trend
See, not ‘everyone agrees’ that the world is warming. ^That link^ to satellite data shows pretty conclusively that the world is no longer warming. It shows us that the world stopped warming almost twenty years ago.
The Left has to hate Big Data, just like they hate Big Oil.
dbstealey says:
July 30, 2014 at 4:43 pm
“^That link^ to satellite data shows pretty conclusively that the world is no longer warming.
….
Wait a minute.
….
Look at this.
…
http://www.woodfortrees.org/plot/rss/from:1980/plot/rss/from:1981/trend
That satellite data of yours clearly shows “warming”
…
I think my “cherry” is sweeter than your cherry.
It depends on what the meaning of “is” is.
I.e., does “is” cover a 33-year trend, or only the most recent trend? If “is” means the present, as it normally does, then the most recent trend (flat) is the winner.
chuck says:
Wait a minute.
Ah. Cherry-picking again, I see.
Skeptics use Warmist Phil Jones’ definition of ‘no warming for 15 years’ after his beginning base year of 1997. Skeptics didn’t pick 1997, alarmists did.
Now you want to cherry-pick 1980. If you get to pick the starting year, you can show anything. But that is moving the goal posts — the hallmark of the alarmist crowd.
Since 1997 is the year designated bu über-Warmist Phil Jones, let’s use his starting year, OK? Alarmists made the rules, and for many years after 1997 that was the consensus. Now they’re howling because their feet are being held to the fire.
Live by the consensus, die by the consensus.
dbstealey says:
July 30, 2014 at 7:11 pm
” If you get to pick the starting year, you can show anything.” </b.
…
Yup, so I guess your pick of 17 years falls into that category, You must be an "alarmist.
Yo, dummy!
1997 was Phil Jones’ pick, not mine. He thought he was on safe ground in 1999 when he made that pick. Jones believed that global warming just had to resume before too long.
Well, Jones was wrong. Global warming has stopped.
If it had started up again, you would have been crowing about it, and 1997 would have been a great year for you. But Planet Earth is debunking the runaway global warming scare. Now your climate alarmist crowd doesn’t like it.
Suck it up. ☺
Mr dbstealey.
…
You are a fine example of someone committing the logical fallacy of false dichotomy. You have separated the world into “skeptics” and “alarmists.” Unfortunately, reality does not work that way, as you have excluded the person that does not adhere to either line of thinking. There is a third category of people (such as me) that do not accept the “alarmist” thinking, and does not accept your way of thinking.
It is very unfortunate that you take the stand, “If you are not with me, you are against me” You are alienating a very large group of people.
Brian says:
July 30, 2014 at 9:24 am
Could anything be more useless?
———————————————-
Senseless!!!
chuckles,
As long as you have a problem admitting that global warming has stopped — and clearly you do — then you are no skeptic.
Skeptics are the only honest kind of scientists. All good scientists are skeptics, first and foremost. Give that some thought.
dbstealey says:
July 30, 2014 at 7:23 pm
“As long as you have a problem admitting that global warming has stopped”
…
I don’t know if it has stopped. It may have. It may not have. You cannot prove it has stopped, and you cannot prove it continues. The jury is still out.
Let me say this about models. If models were able to get anything right, be it about the economy or the weather, I would be making an absolute fortune placing bets with my local bookmaker.
But the reality is that none of these models will ever be able to tell us what is going to happen in 100 years time let alone in one years time, one months time or even one weeks time.
The day these supercomputers can tell us, with a degree of certainty, that it is indeed going to rain or snow next Wednesday at such a place, and come next Wednesday it actually happens, that will be the day I take notice of these computers … and then only with regard to their forecasts for a few days ahead.
@Brian says:July 30, 2014 at 9:24 am
+100 , I got giant guffaw out of that one.
When ebola spreads beyond Africa, then they’ll have some big data to model – oh, wait, global warming causes ebola:
“Jun 26, 2014 – @voxdotcom my #science teacher taught me global warming causes ebola. Details Expand Collapse. Reply; Retweet Retweeted; Delete “
I don’t understand why Mosher hasn’t done a pro climate model driveby smarmy comment on this topic
I haven’t read this article, but generally you find in nature larger numbers give a larger standard deviation. So one would expect a larger temperature variation with CAGW models.
For instance high tide standard deviations are higher than low tide standard deviations. But when you divide each by its mean, the coefficient of variance is the same.
“I don’t know if it has stopped. It may have. It may not have. You cannot prove it has stopped, and you cannot prove it continues. The jury is still out.”
It warmed from about 1980 to about 1998. (18 years.) And it didn’t warm from about 1999 to 2014. (15 years). No jury required.
‘when explored through 14 CMIP5 climate models and three reanalysis datasets. ‘
How to build a better hockey stick Mk…?
Cherry picking reminds me of the rhetorical question, “How long is a piece of string?”
Given that a piece of string is twice the length from the middle and the RSS record has
a fixed start and contemporaneous end point, looking at trends from either end would seem
as useful a “methodology” as any other:
http://www.woodfortrees.org/plot/rss/from:1979/plot/rss/from:1979/to:1996.5/trend/plot/rss/from:1996.5/to/trend