Heap big data science at Northeastern University

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

srep05884-f1

The outer panel (a) shows how increases strictly in the location parameters for either tail would impact the distribution of extremes, and similarly panels (b) and (c) show the same for scale and shape parameters. Changes in location parameters correspond to shifts in typical or average extreme events, scale to changes in the width of the distribution of extremes, and shape to the behavior of the uppermost extremes. Baseline GEV distributions are shown in black and shifted distributions are shown in blue and red for simulated seasonal minima and maxima statistics, respectively. The SI gives details on the construction of the 6 side graphs, which are built with randomly simulated data from GEV models.

 

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Patrick

“Knowing that the models projecty . . . .” The models project nothing. At least nothing that can be relied upon.

Arthur

Here’s a rule about natural statistics: Once you start keeping track of highs and lows (of anything) on a global scale there will ALWAYS be a new higher and a new lower over any given time period. How is this news?

dp

“Just because you have a year that’s warmer than the usual over the last decade isn’t a validation of the global warming hypothesis,” Kodra explained.

There – I fixed it for ya.

JimS

The poor souls are contradicting IPCC predictions from 2007 for a warming world:
“There is likely to be a decline in the frequency of cold air outbreaks (i.e., periods of extreme cold lasting from several days to over a week) in NH winter in most areas.”
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/faq-10-1.html

latecommer2014

This falls under CYA protocol . Claim both ends of the spectrum and you can always be right. Psudo-Science at is best.

ddpalmer

“The analysis of multiple climate model runs and reanalysis data sets was necessary to account for uncertainties in the physics and model imperfections.”
Well except when all the models make the same assumptions. Then the use of multiple climate model runs is just GIGO.

M Courtney

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.

So their model diverges from reality and becomes more and more unstable.
So the world’s weather will become more and more unstable or they need a better model.

Dave

Would someone from the alarmist camp (surely there are plenty of you that visit this site) please explain what a “climate extreme” is?

Dave Wendt

Somebody needs to pull the feeding tubes and shut off the respirators on these bozos.

F. Ross

“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.” [+emphasis]
Oh, I get it; they extracted nuanced insights. Isn’t that special.
” It suggests that the natural processes that drive weather anomalies today could continue to do so in a warming future.”
What elses would drive weather anomalies? Unnatural processes? Devil worship?
Pure PUFFERY at best.

more soylent green!

Where are global temperatures increasing? In the models or do they have data they’re not sharing with us? Oh wait, I get it — the temps are increasing in the models. They take the output of the models and then model that. That explains it.

oMan

“…’reanalysis data sets,’ which are generated by blending the best available weather observations with numerical weather models.” Could somebody explain to me how that works? If you take (a) real-world data and (b) BS generated by your magical box, does that result in knowledge? Or more BS? For some reason I am thinking of pee in a swimming pool.

Rob Dawg

Surely when they ran cross checks on the input sources they must have discovered some suspicious concurrences. Indeed it would be very suspicious if they didn’t. That’s what big data is good for not validating models.

ren
Dave

Humanity and critters alike have always been at the mercy of the earths climate.
We now manage our local environments, heat or cool our living spaces to survive comfortably in the face somewhat harsh environments. I think this has reduced our tolerance and understanding of what a harsh place the earth can be.

Harold

Oh-oh. Shape shifters.

Sweet Old Bob

” We mixed 17 gallons of paint from different models and now we have the true color ”
And it is new and improved……buy some now…at your friendly climate science store, near you…
Limited time offer…

Gary Pearse

“duo used computational tools from big data science for the first time in order to extract nuanced insights about climate extremes.”
Man, if you need to use $10M computational tools to extract nuanced insights from the very rough, much diddled with temperature record with >50% error bars, you are wasting time and money. There are no nuances in this kind of data. Its like trying to extract the names of respondents from divorce statistics. How about the nuance of 18years and continuing of no warming that was totally unexpected. I hope your nuances account for increasing Arctic and Antarctic ice extents in the future, or will this be another big data surprise to show us after the fact.
How come after a couple decades of the this stuff the recognizable names in the heat-up industry have disappeared and they have taken to sacrificing a legion of young lambs like Kodra, Ganguly, and the recent legion of newbies. They must be behind the curtain pulling the strings on these innocent folks. Kids, get your asses out of there, you are at the bottom of the pyramid of the scam.

Dougmanxx

The problem I see: when you look at the min/max data you do NOT see more extremes. You see higher mins. The difference between the min and max has actually gotten SMALLER. In the raw data, the maxs are getting lower, while the mins are getting higher. I would call this the exact opposite of ‘more extreme”.

Harold

It seems like they’re making essentially the same argument that got Charles Murray tarred and feathered for making in a different context. Bell Curve Climate = good. Bell Curve IQ = stone the infidel.

Alan Robertson

Well diggers use thin plywood veneer to reinforce the walls of the hole as they dig deeper, lest they be buried under a collapse. The authors of this “paper” are using a veneer too thin for the task, but that hasn’t stopped them from digging.

Brian

Now they’re doing notional statistical analysis of the model outputs? Am I reading this right?
Could anything be more useless?

Latitude

pay no attention to the thermometer….your insurance rates are going up

Pamela Gray

Does he mean like these extremes? Oh. Wait. Wrong century.
http://www.weather.com/news/5-extreme-temperature-drops-20130118

“Big data confirms climate extremes are here to stay”
– Oh FFS. “Big data” could confirm almost anything – as Boyd and Crawford (2011) point out:
“It is the kind of data that encourages the practice of apophenia: seeing patterns where none actually exist, simply because massive quantities of data can offer connections that radiate in all directions. Due to this, it is crucial to begin asking questions about the analytic assumptions, methodological frameworks, and underlying biases embedded in the Big Data phenomenon.”
‘Big Data’ covers a hugely heterogeneous set of methodologies, technologies, assumptions, approaches and so on. What is it with these people? It reminds me of how the definite article is used when referring to “the science” as if it is a static thing self-evident to everyone. Whenever I see such phraseology it indicates to me that I’m dealing with a willful propagandist.

John West

“It suggests that the natural processes that drive weather anomalies today could continue to do so in a warming future.”
“It” in this case being the product of a 10 million dollar expenditure! “It” suggests that processes that have been around for billions of years will continue into the future. Give me 10 million dollars and I’ll build a fancy smancy climate data cruncher that will strongly suggest that the processes that effect weather today and have been since time immemorial will continue to effect weather in a [payer’s choice: warming/cooling/stagnant] world.

Chris4692

I was looking forward to reading the paper to see their analysis until I read that they analyzed model output rather than real data. Never mind.

I wonder if the authors are trying to lay the foundation, or if someone else will take it as one, for the next round of scare mongering.
“Well, sure the average temperature isn’t going up but that is not the problem. All that CO2, or something, is leading to higher highs and lower lows, and that will result in catastrophic losses in agriculture and public health. We have to reduce our CO2 emissions, or something, to keep them in a more normal range (whatever that is).”

“… There are no nuances in this kind of data. Its like trying to extract the names of respondents from divorce statistics. …”
Honky Cat says:
It’s like trying to find gold in a silver mine
It’s like trying to drink whisky from a bottle of wine

Harold

Latitude says:
July 30, 2014 at 9:25 am
pay no attention to the thermometer….your insurance rates are going up
—————————
Bingo. Stampede your competition into overestimating the risk. Everybody in the industry wins.

john robertson

Predicting the future from the intestines of small avian creatures is cheaper and more accurate.
After all a fat bird in the fall indicates the bird was ready for winter.
$10 million to produce this garbage?
Climatology has not improved since Roman times.

Pamela Gray

At first I thought that degrees of freedom, error bars, and tests of significance are so old school. Now I realize this is not post-normal science but pre-normal regression back to the halcyon days of restorative snake oil elixirs and grandpa’s recipe for what ails ya.
No need for unbiased, cold investigation. All you have to do is find yourself a fancy media wagon and start barkin out the back end of it. Crowds will gather and buy all you have to sell. But there is one essential difference. What tickles my funny bone is that the sheeple gathering round the wagon all have diplomas and letters after their names.

Resourceguy

Did John Kerry commission this in between foreign trips and sail boat escapades?

John in L du B

Are you kidding me!!!?? Does anyone actually do measurements anymore or work with real data? Everyone agrees that the world is warming so we’d expect asymmetry in the extremes. Do you need to crank “big data” to show this?
Can you get a graduate degree in Civil Engineering at Northwestern for this stuff? I’ve been contemplating a US road trip. Think I’ll avoid Illinois. Not sure about the bridges.

jhborn

John in L du B: “Can you get a graduate degree in Civil Engineering at Northwestern for this stuff?”
Northeastern as in Boston, not Northwestern as in Evanston.

Dave L

This crap is considered ‘science’?

bh2

“This crap is considered ‘science’?”
It is “science” if it pays well. It isn’t “science” if it does not.

joelobryan

quoting, “the team speculates that ice melt in hotter years may cause colder subsequent winters.”
The old “warming causes cooling” gag for the weak minded.

earwig42

Another fine entry for the Climate Agnotology Hall of Infamy. Meh.

Neil

They would do well to learn from Google and their flu predictions:
The Parable of Google Flu: Traps in Big Data Analysis
In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google executives or the creators of the flu tracking system would have hoped. Nature reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States. This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data, what lessons can we draw from this error?
http://www.sciencemag.org/content/343/6176/1203.summary

Neil

Well, speaking as an IT and database professional, I have to make this point: The biggest fiction about big data is that its a new concept. Its actually a new name for an old concept: statistical modelling.

joelobryan

quoting, “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. ”
those sectors would be better off with an Ouija Board than using that Big Data garbage generator.

Harold

“Heap big data”? So now Liz Warren is on the climate bandwagon?

It turns out the $10 million covers a lot more than this analysis. The full grant is described at http://www.nsf.gov/awardsearch/showAward?AWD_ID=1029711 which says in part:

Data driven methods that have been highly successful in other facets of the computational sciences are now being used in the environmental sciences with success. This Expedition project will significantly advance key challenges in climate change science developing exciting and innovative new data driven approaches that take advantage of the wealth of climate and ecosystem data now available from satellite and ground-based sensors, the observational record for atmospheric, oceanic, and terrestrial processes, and physics-based climate model simulations.
A primary focus of this Expedition project will be on uncertainty reduction, which can bring the complementary or supplementary skills of physics-based models together with data-guided insights regarding complex climate processes. The systematic evaluation of climate models and their component processes, as well as uncertainty assessments at regional and decadal scales is a fundamental problem that will be addressed.

I don’t know, it sounds like they’re finding greater uncertainty….
The grant lists 32 papers produced under it (it started in 2010). None seem very supportive of AGW, a lot seem rather neutral, e.g. Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes, NATURE CLIMATE CHANGE, v.2, 2012, p. 86-91. [I picked this because it seems to fit the study at hand.]
A graph-based approach to find teleconnections in climate data, Statistical Analysis and Data Mining, v.6, 2013, p. 158.
Intensity, duration, and frequency of precipitation extremes under 21st-century warming scenarios, Journal of Geophysical Research: Atmospheres, v.116, 2011, p. 14. [There’s some confirmation bias, they should look at cooling conditions too.
Sensitive and Specific Identification of Protein Complexes in “Perturbed” Protein Interaction Networks from Noisy Pull-Down Data, IPDPS, HiCOMB Workshop, 2011. [What!?]

Bill Illis

The paper is strictly based on model outputs.
No use of any actual climate measurements whatsoever.
There is so much money being wasted in this climate science industry, a complete dead-weight loss to the economy and government coffers,
It needs to end now. We do not need one more single run of any climate model for any purpose whatsoever. It has all be done before umpteen times. We just need to measure what is really happening. Fund somebody else besides climate modellers to carry out this work.

Jeff L

I love how quickly this blog can deconstruct a paper ! All my critical thoughts have already been posted by others !
Warmists either don’t recognize or choose not to acknowledge the intellect of skeptics & understand how easy it is to tear down almost all of their arguments.

Joseph Murphy

LOL, is about all I can muster anymore. I am in the wrong line of work (recycling).

John Greenfraud

The paper is basically a math problem.
Outrageous claims of climate extremes + Dumb people = Political power and wealth

BallBounces

“Big data confirms climate extremes are here to stay”.
Put a coin in the juke box. Cue the 45: scratch, scratch, scratch…
Climate change is here to stay, it will never die
It was meant to be that way, though I don’t know why
I don’t care what people say, climate change is here to stay
We don’t care what people say, climate change is here to stay
Climate change will always be our ticket to the end
It’ll go down in history, just you wait, my friend
Climate change will always be, it’ll go down in history
Climate change will always be, it’ll go down in history