First They Came For the Muslims....

Ocean Heat Content Up for the Quarter, Down for the Year

Ocean heat content is heading back up again, after the El Nino apparently took a lot of heat out ocean and sent it into the atmosphere.

The latest numbers show the top 0-700 m region of the ocean gained 0.74 W/m2 compared to 3Q16, and the top 0-2000 m region gained 1.50 W/m2.

But compared to a year ago, 4Q16, they're down -0.55 W/m2 and -0.44 W/m2 respectively.

The acceleration of the heat content of the 0-2000 m region -- only for the direct measurements, not the pentadatal numbers -- is down to 0.01 ± 0.03 (W/m2)/yr (2σ uncertainty; no autocorrelation) -- barely positive.

I think the time period of the (good) Argo 0-2000 m data -- just 12 years -- is still too short to make meaningful conclusions about acceleration. Though, admittedly, that didn't stop me from doing so in the past.

Some graphs:

Powerful Documentary on Refugees and a Captain

This is a powerful short documentary by Daphne Matziaraki, published by the New York Times last September. I didn't see it until they reran it the other day, as it was just nominated for an Academy Award. Watching it brought up just about every emotion I have.

"Sources: Trump Administration Tells EPA To Cut Climate Page From Website"

It's happening: first the muzzling, now the censorship. It's like something out of the Soviet Union...or at least Canada under Steven Harper. But we're only 5.5 days in....

"Sources: Trump Administration Tells EPA To Cut Climate Page From Website"

http://www.huffingtonpost.com/entry/sources-trump-administration-tells-epa-to-cut-climate-page-from-website_us_588817a5e4b0441a8f71cd2f?5o7xenrbksq1moyldi

DOWNLOAD_HUFFPOST

How Are Climate Models Doing With Global Temperature?

Quite well, in fact.

Here are surface temperatures compared to CMIP5 models:

"CMIP" stands for Climate Model Intercomparison Project. It's a database containing results from climate models for many different scenarios, that climate modelers use to compare their results to each other and to observations. It's now on its 5th version. I talked to a climate modeler a while back, and she said modelers are usually more interested in how the models compare than how they match reality. The models all make different assumptions, so learning which model best forecast, say, the Atlantic Meridional Overturning Circulation, can give good clues. Or modelers might replace one component of their model to see how it compared to the earlier version.

Clearly, climate models are doing a pretty good job. At least for global mean surface temperature.

The model results for years prior to 2017 use "historical" forcings -- the actual forcings that occurred then, based on the measured values of greenhouse gases, etc. That's only fair -- it would make no sense to compare a 1990 model with a scenario that didn't happen. After all, no climate model can foresee the future of GHG emissions, volcanic eruptions, and changes in solar irradiance.  

And here are the results for HadCRUT alone:

Here are some explanations and caveats on the assumptions and methods, from Peter Stott. Worth reading.

So What Does This Mean?

Via Fred:

Is this why the Saudi's are investing heavily in solar energy?

Gas Prices Under Last Six US Administrations

"cur$" = current dollars (viz. as of Dec 2016).
"gal" = gallon = antiquated unit only used now by Liberia, Myanmar and one other country.
Data via TWIP and CPI.

Today at Mt Rushmore

via TED @laughbook.

More About Today's GISS/NOAA Press Conference

The graphs I posted earlier today are from the joint GISS/NOAA press conference this morning, announcing that 2016 is officially the warmest year in both their records.

All their slides and graphs can be found here.

It's only the warmest year in the Hadley Centre's records, which go back further. Warmest than 2015 by 0.01°C. Their error bars are ± 0.1°C, so they say 2016 was "nominally" the warmest, though the difference wasn't statistically significant.

The difference between the three datasets is mostly in how they treat the Arctic, where there are few temperature stations but which is now warming very fast. The Met Office explains here.

A few notes I took while listening:

• NOAA estimated the El Nino contributed about 1/4th to 1/3rd of their 2016-2015 difference. I didn't understand what GISS said about this, and will try to follow up.
• Journalists asked more than once what message they would send to the Trump administration, and both times Deke Arndt of NOAA cautiously said (paraphrasing), we produce our results for the American people to use as they see fit. 
• Gavin Schmidt, Director of GISS, said a few interesting things in response to questions.
• 2016 is likely the warmest year for "many hundreds of years."
• However, we're still not as warm as the Eemian, the last interglacial 125,000 yrs ago.
• We've "clearly passed 1°C warming, and unlikely we'll go below that."
• His personal prediction is that 2017 will be "still a top five year, I'm pretty confident, but unlikely to be a record year." And, "possibly the second warmest."
• The Arctic is warming at 2-3 times the rate of the global mean.
• Deke Arndt of NOAA gave a graph of their data with and without corrections ("adjustments," a word he didn't use). He stressed that the biggest difference between raw and corrected data is in sea surface temperatures, with a change in ship data collection from buckets thrown overboard to the engine intake method. And he and again reiterated that corrections reduce the long-term warming trend:

El Nino Years Compared

GISS, NOAA: 2016 Warmest Year on Record

NOAA:

GISS:

Global sea ice is at lowest level ever recorded | New Scientist

https://www.newscientist.com/article/2118093-global-sea-ice-is-at-lowest-level-ever-recorded/

Zinke: "The glacier receded during lunch"

Confirmation hearing for Ryan Zinke, nominee for the US Department of Interior.

Bernie Sanders: "Is climate change a hoax?"

Ryan Zinke: "Climate is changing. That's undisputable. I'm from Glacier National Park. When my family and I ate lunch over a glacier...the glacier receeded during lunch."

Another clip.

Julian Asange to Arrive in US Shortly

Right?

If Obama grants Manning clemency Assange will agree to US extradition despite clear unconstitutionality of DoJ case https://t.co/MZU30SlfGK

— WikiLeaks (@wikileaks) January 12, 2017

Wikileaks started out well. But in the end Julian Assange proved to be just another tool.

Another Sleazy Photoshop from Pierre Gosselin

When last we met Pierre Gosselin, a climate change denier in Germany who blogs at NoTricksZone.com, he was photoshopping pictures of the German countryside, adding fake wind turbines in order to conclude "Shocking Before-And-After Photos: How Wind Parks Are Devastating Idyllic German Countryside!"

Now he's add it again, photoshopping a screenshot of a famous James Hansen paper to try to make it look corrupt, provided by someone named Kenneth Richard:

And here's the actual Hansen paper:

Ha ha. 

Sure, the photoshop is obvious to me and you. (And more than the title has been altered.) But to other readers of his blog? New readers? To the worst kind of deniers?

What I can't understand is why a blogger thinks he can alter pictures and documents and still retain any credibility whatsoever.

The science needs better skeptics. As a first step, honest ones. 

Wacky Global Sea Ice

Here is the latest global sea ice extent, from the Arctic Sea Ice Blog:

Yes, Arctic SIE has been acting strangely, but Antarctic SIE has fallen very far:

I've read, on Twitter I think, someone speculate that changes in Arctic SIE looks like a signal, but the changes in Antarctic SIE looks like noise.

Or maybe this is what a tipping point looks like. (But someone told me several months ago that he thought the Arctic had already passed a tipping point.)

Stunning Sessions Remark about "Truth"

From Slate, on yesterday's confirmation hearings of Senator Jeff Sessions for Attorney General:

In what seemed to be the only moment gobsmacking enough to bring the Senate chamber to almost complete silence, in the late afternoon Sessions had this terse exchange with Sen. Sheldon Whitehouse of Rhode Island.

Whitehouse suggested that lists were already circulating suggesting there might be purges or demotions of certain career appointees in the Justice Department. Whitehouse wondered whether Sessions would have a problem with career lawyers “with secular beliefs,” having in the past criticized department attorneys for being secular. Sessions replied that he has used that language about secular attorneys to differentiate between people who recognize objective “truth” and those who take positions “in which truth is not sufficiently respected.”

Whitehouse replied, with a leading, and perhaps slightly conclusory question: “And a secular person has just as good a claim to understanding the truth as a person who is religious, correct?” At which point Sessions responded, “Well, I’m not sure.” For a few seconds the Senate chamber seemed to go completely silent.

Basic Energy Balance and the Famous Factor of 4

We all know the equation for the average surface temperature of a spinning Earth with no atmosphere, the so-called "brightness temperature":

or

for ε = 1, S = 1365 W/m2, and α = 0.3. The factor of four comes from accounting for the spherical, spinning Earth (see any climate science textbook, chapter 1 or 2).

So this is interesting:

"The spherical Earth assumption gives the well-known So/4 expression for mean solar irradiance, where So is the instantaneous solar irradiance at the TOA. When a more careful calculation is made by assuming the Earth is an oblate spheroid instead of a sphere, and the annual cycle in the Earth's declination angle and the Earth-sun distance are taken into account, the division factor becomes 4.0034 instead of 4."

https://ceres.larc.nasa.gov/documents/DQ_summaries/CERES_EBAF_Ed2.8_DQS.pdf, pg 7.

It'd be fun to calculate this, someday, when I have the time. But unfortunately I don't have it now.

When I was an undergraduate, I took undergraduate Classical Mechanics in my junior year, from a really great professor at UNM. Dr Finley taught many of the upper division undergraduate classes I took, and I learned more from him than any other teacher in my life, including in his graduate-level special relativity class my senior year, where he introduced us to four-vectors and tensors and their notations.

Dr Finley was fantastic. One of the most memorable things he did was, in junior year classical mechanics, introduce us to perturbation theory (and special functions) by calculating the gravitational field for a nonspherical Earth. First we did the oblate spheroid, but even better was for the pear-shaped Earth, a more realistic model of our planet.

These were the same calculations NASA had to do to launch rockets or send one to the Moon.

The UNM classroom we always used had chalkboards on all four sides of the classroom, and chairs/desks that swiveled. He'd start over on the far one side of the classroom, and by its end we'd all swiveled our desks 360 degrees to follow what him had calculated, all around the classroom.

I don't remember now exactly what special functions these perturbative calculations required -- Legendre polynomials, I think. But it was a wonderful introduction to not just realistic classical mechanics, but perturbation theory, which then was very handy later when learning quantum field theory, where scattering cross sections are calculated (for QED) one order of perturbation, in α (≈ 1/137), at a time.

When the department ordered a new computer -- this was 1981 -- and put it in his office, he let a good friend and I unpack it and set it up. Then he let us play with it. This was the day before Thanksgiving, and my friend Norman and I sat there for about 18 hours, figuring it out and its programming. IIRC, we calculated the scattering of electrons from various crystal types, ending up with a 2-D surface where the electrons had landed after scattering. When Dr Finley came back in the next morning, Thanksgiving morning, to pick something up, around 10 am, we were still there programming, having been up all night. He encouraged us to go home. I rode my bike the 10 miles back to my parents' house, and I think I slept all the way through Thanksgiving dinner.

Sometimes you only recognize when you were happy much after the fact. Or maybe you just forget all the problems you had then. Does the difference really matter, decades afterwards?

RSS Total Troposphere Temperature Set a Record in 2016

Unlike UAH, RSS found 2016 to be a record breaking year, +0.17°C (0.31°F) warmer than 1998. (2010 is third warmest.)

"In addition, 9 out of 12 months for 2016 were the warmest of that month ever recorded in the satellite record.....

"The record warmth was caused by long-term global warming combined with the strong El Niño event that occurred in the winter and spring of 2015-2016. "

They're measuring slightly different regions -- RSS's number is for the Temperature Total Troposphere (TTT), whereas UAH's number is for the lower troposphere. And slightly different sections of the globe -- RSS's measurements go from a latitude of 80 south to 80 north, whereas UAH covers the entire globe, 90S-90N.

(to be continued)

The Statistical Tie Fallacy

Regarding the question of whether UAH LT's annual average set a new record or not -- this question has come up before, in the context of political polling and who's ahead in the political race.

I remembered reading about it long ago, on Kevin Drum's blog, who was writing about two hypothetical political candidates where a poll showed their different percentages (of voters favoring them) less than the statistical error of the blog.

In fact, what we’re really interested in is the probability that the difference is greater than zero — in other words, that one candidate is genuinely ahead of the other. But this probability isn’t a cutoff, it’s a continuum: the bigger the lead, the more likely that someone is ahead and that the result isn’t just a polling fluke. So instead of lazily reporting any result within the MOE as a “tie,” which is statistically wrong anyway, it would be more informative to just go ahead and tell us how probable it is that a candidate is really ahead.

Drum asked two statistics professors at California State University, Chico, who gave him formulas to calculate this table:

I'm not sure if we can directly use this to calculate the UAH case or not. But if we take the percentage lead (which really should be labeled "percentage point lead") of 2%, and a margin of error of 5% (5 percentage points), we get a probablility of 65%, almost identical to my calculated value of 66%.

Drum followed this up with another post on the same subject a few days later, and over the years others have weighed in on the topic, all agreeing with him.

So now I'm pretty sure that UAH is wrong, 2016 and 1998 aren't in a statistical tie, and they were perhaps looking to spin the numbers toward the non-warming side. And I wonder, if 2016 had been 0.02°C cooler than 1998, if they'd have claimed it a "statistical tie," or just never mentioned it. 

UAH's 2016 Temperature: "Tied" with 1998, or a 66% Probability 2016 is Higher?

1/6: See update, below.

Yesterday Roy Spencer posted on his blog, with the headline "Global Satellites: 2016 not Statistically Warmer than 1998."

According to UAH's model, the average temperature of the lower troposphere for 2016 was 0.50°C, and for 1998 it was 0.48°C. UAH puts the uncertainty of the annual value at σ=0.05°C, so the 2σ error bars (which give (pretty approxiately) the 95% confidence limits), is 0.10°C.

So Roy concluded the two years are tied:

...they are basically tied, statistically. So to say 2016 is the warmest would be dishonest, since it ignores uncertainty in the measurements: a 0.02 deg. C change over 18 years cannot be reliably measured with any of our temperature monitoring systems.

John Christy apparently said the same.

Of course, 0.50°C is larger than 0.48°C, so I think there's some sleight of hand here, spun, I suspect, for the sake of headlines in Breitbart, Climate Depot, the Daily Caller and those kind of deniers.

I asked Roy what is the probability 2016 was the warmest year of the two years, but got no response from him. So I tried to calculate it myself; see what you think.

I assumed the two annual temperatures were each normally distributed, with the mean (best estimate) at the published numbers, 0.48°C and 0.50°C, and a standard deviation for each of σ=0.05°C.

So the picture is two Gaussian curves, side-by-side, with 2016's curve 0.02°C to the right of 1998's curve, both having a standard deviation of σ.

To calculate the probability that 1998 is the warmest year, I took it to be the area under the its Gaussian curve from 2016's best estimate, out to infinity.

0.02°C is a small difference between the two years' best estimates, but it's also 0.4 standard deviations (0.02°C/σ), and that isn't so small.

Normalizing the coordinates to unitless numbers, we want to area under the 1998 curve from x=0.4 to infinity.

The area of the normal distribution to the right of 0.4 is 0.3446, from this handy table. (It's straightforward to calculate, too, using the error function (erf(x)), but I got too tied up in getting the factors of 1/2 and √2π and the like correct, especially between the Wikipedia function and the Excel functions, so I just looked it up.) So

probability 1998 is the warmest year = 34%.

The probability 2016 was the warmest year is the complement of this, since we're only considering two possible years  (the third highest annual average, 2010, is 0.33°C, so not even close)

probability 2016 is the warmest year = 66%.

The chance 2016 was the warmest year in UAH's records is twice that of 1998.

This may not be the most mathematically rigorous way to do this, and I don't know if it's how Gavin Schmidt does it. But 66% isn't a surprising result; it "seems" believable (remember, it's 0.4 standard deviations higher).

So, statistical tie, or 2-1 odds?

----

Update, 1/6: Based on Nate's calculation on Roy Spencer's blog, I now think the right answer is his 61%. He used a 1-sigma margin of error of σ*sqrt(2), for the difference. For the difference of two numbers, D=Y-X, where X and Y each have a 1-sigma margin of error of σ, then the 1-sigma MOE of D is sqrt(σ²+σ²)=σ*sqrt(2) = 0.07°C in this case. Then we're looking for the probability that we're 0.02/0.05*sqrt(2)=0.28 standard deviations above zero, and the area to the right of that is, by the table listed above, 38.97%, so the complement of that, the probability that 2010 was the warmest year, is 61%.

----

This is worth reading; I'll write about it in my next post:

“The Myth Of The Statistical Tie,” David Drumm, jonathanturley.org, 10/6/2012
https://jonathanturley.org/2012/10/06/the-myth-of-the-statistical-tie/