Latest Global Temp. Anomaly (Dec. '16: +0.24°C) Global Satellites: 2016 not Statistically Warme

You really linked to Spencer, ewwww, hope I didn't catch anything checking, mojo, stay off the morphine, it makes you silly.

 

Spencer also is a Creationist:

"...for the creation model was actually better able to explain the physical and biological complexity in the world..."

The problem, of course, is that any reputable scientist understands what the evidence is saying about the climate.

 

Great, got the version 6 global TLT data. Here it is as annual averages, 1979 through 2016


The slope is +0.123 oC per decade.

If you work backwards from 2016, the only starting year that does not give a significant positive T slope is 1998. Start any other time and there it is . So, starting at specifically at 1998 undermines the meaning of the entire record.

I have asked Roy Spencer why he allows his fine work to be misused in this way. No reply yet.

Oh, and the message of the first post is that an isolated year 1998 was not warmer than an isolated year 1998 in this atmospheric T proxy.

 

I think his "beliefs" speak for themselves. Science does not care what you "believe".

 

Global temperature trends 1970 through 2016, oC per decade, by different compilations

Surface thermometers
BEST (0.173)
HADCRUT4 (0.177, 0.174)
GISTEMP (0.176, 0.174)
NOAA-NCDC (0.171)
NOAA-GHCN (---)
Japan Met Agency (---)

Satellite proxy TLT since 1979
UAH (0.123, 0.127)
RSS (0.126, 0.114)

+++
Start with the satellites (main topic here), these are the trends for entire records, original data processing by two different groups (UAH and RSS). If you took them in aggregate to be 0.12 oC per decade you'd not be far off. We have previously discussed how these records might matter to surface dwellers, and wondered why they jump so high for El Nino.

Surface compilations - there must be many thousands of people involved overall, from 'meter readers' to data handlers. I understand mojo's concern that all of them are somehow involved in a conspiracy, but I am not compelled. That no group has put forth a different compilation, well, they could and if very different slopes were presented, that would be something to talk about. If you took them in aggregate to be 0.17 oC per decade you'd not be far off.

So there is your T increase. It does not yet point to 3 oC this century. This is not in my hands.

I did not find a 'simple' version of GHCN, so perhaps another can assist. JMA website is either down, or blocked for me.

As far as preferences, I have no favorite surface compilation. All seem boringly similar. BobW likes BEST, AustinGreen likes GISTEMP, and mojo has posted HADCRUT4.

 

As you know I favor continuation of both. Since 1979, RSS and UAH have made use of 19 satellites (which have other functions as well). I am keen to know the costs of such things, because some people think that $2.5 billion per year is too much for US to spend on earth system science.


But 'costing' those babies is by no means simple for an outsider. I know that the most recent, NOAA-19 fell over in lab during assembly and repairs were $135 million. So the whole thing, plus launch plus ops must be a lot more.


It is an expensive game, to estimate temperatures from 53 gigahertz oxygen radiation, for a level of the atmosphere where T is about -30 oC. But I don't oppose it.


Sometime, y'all take a look at the maths required to derive T from those signals. Wow

 

We appreciate insights from both satellite and surface-T analyses, but wonder which may be more realistic or relevant. One way to consider that is how much Earth’s T can vary from one year to the next.

Earth terrestrial surface has thermal inertia, and oceans have more. If nothing else, intuition argues against rapid large changes. Let’s take a look.

During ‘satellite-T era’ 1979 to now, RSS TLT annual proxies went (at most) 0.45 oC warmer or cooler than previous year. UAH TLT annual proxies went (at most) 0.49 oC warmer or 0.50 cooler than previous year. Those seem large global changes, and one would be obliged to show where so much thermal energy came from or went to.

In contrast, HADCRUT4 surface-T compilations shifted by as much as +0.21 and -0.23 between years since 1979. Much smaller. For completeness, through its entire record since 1850, annual shifts were as much as +0.31 and -0.27 between years.

Larger annual changes in satellite-T proxies come during ENSO-cycle extremes. 1998 and 2016 were outstanding in that regard. Exclude ENSO extremes, and these very different T compilations snap into agreement. Ta da!

We don’t know why satellite-T proxies are more sensitive to ENSO than surface-T measurements. During extreme ENSO years, many other things change more than T at Earth surface. As a chaser of carbon, those things are of great interest to me.

Yet, a larger community sees T as the thing. So they ought to fairly compare these analyses, and decide whether T ‘where we live’ or ‘where we don’t’ are better measures. It is of little value to support one or the other only because it aligns with one’s hope (plan) for human carbon future.

 

NOAA Scientists Didn't Cook The Books On Climate Change, Study Finds | The Huffington Post

 

Publication is here

Assessing recent warming using instrumentally homogeneous sea surface temperature records | Science Advances

It recalculates sea-surface +T as 0.12 oC per decade instead of 0.07. All the values I listed above are land+sea, and sea alone is lower wherever it's determined..

Seems reasonable because there is always someplace for surface water warmth to go (down). In a way this may be like satellite T during El Nino. Warmth can always come up from surfaces to TLT level.

 

Free lesson

“The Greatest Scientific Fraud of All Time” sounds like quite a thing. If you could write a new-seeming internet piece about that, you could get it placed on an eager-for-clicks website for sure. Trappings of celebrity await…

But how, dang it? Exactly how to write such a thing? Relax, Francis Menton has revealed all:

The Greatest Scientific Fraud Of All Time -- Part XI — Manhattan Contrarian

First notice that there are two components; hard-hitting text and evocative graph. Get the graph right, first. Then, do whatever it takes to make yourself feel really angry. This will differ among persons, but once you get in the zone, text will fly from your figures.

It is with an evocative graph that Menton lays out the steps. Begin by comparing two processes that have different slopes. Two familiar ones are chosen here; GISTEMP and UAHTLTV6. UAH began in 1979 and from then until now has a slope of 0.123 oC per decade. GIS is longer, over the same time has a slope of 0.174 oC per decade. OK, different, but you may be thinking “how can I find the greatest fraud by comparing two similar-seeming positive slopes?” This is what Menton teaches.

Also realize that every temperature anomaly series uses some period (of years) as its basis. Anomalies may be higher or lower. It is no fraud that periods chosen or basis temperatures may differ. But nonetheless it is your key.

At this moment we introduce woodfortrees.org It puts several data series, analysis and graphing tools at your fingertips. Menton uses it and so shall we. A very nice feature is that graphs produced show ‘production steps’ and Menton’s are fully revealed here.

Begin with the slopes themselves. Not very interesting.



Now use ‘offset’ to bring the beginnings closer together. This does not seem misleading – why should we not want them to start in nearly the same place?



Now show the two datasets instead of their slopes and you get Menton’s graph:



From here, words can flow once you are sufficiently fired up. Datasets were initially so alike; GISTEMP must be cooking the books because just look at those late differences! Readers who see only the image and not the details will hop on board. Fake fake fake. Almost seems unnecessary to write Fake on the graph in big red letters. But remember your audience – Give them big letters and they just might not notice (and understand) the smaller ones.

That’s how to do it, friends. Crafting angry words is left to you, and I do not see at PriusChat an absence of ability. Menton frees you in another way. Here the fakeness is because of late ‘changes’ to GISTEMP. Earlier in his same series, Menton said cooking of books happened early and not late:

What Is The Greatest Scientific Fraud Of All Time? — Manhattan Contrarian

So consider yourselves freed from bounds of consistency. Do your work with graphs and angry words and most readers won’t notice.

Should you for whatever reason wish to point out Menton’s fake fakeness, expect an angry reply right back. Because that anger must be the focus of discussion, not any unfaking of fake fakeness.

Get on board y’all. The political pendulum has swung and there may never be a better time to make yourself an angry voice of the people. With graphs!

PS: if you go to woodfortrees and explore these yourself, I doubt you’d find a pair of offsets that do a better job making these datasets look similar at the beginning. This is key for making your point, so put in that extra effort.

 

Satellite T

Done by UAH and RSS, now with similar results. TLT = temperature lower troposphere, TMT = temperature middle troposphere. TLT centered at 3 km elevation, TMT at 5 km. Global surface T averages 14 oC (used to be 13), vertical lapse rate -6.5 oC per km. So, TLT looks at a level with avg. T of -5.5 oC, and TMT at -18.5 oC.

These are good reasons to focus on T anomalies in such data sets, because the actual recovered proxy-Ts would seem far from human experience. That’s OK, as long as it’s not forgotten.

Point here is to consider T measurements in their ‘vertical contexts’. Surface-T measurements have land or sea underneath; each with large thermal inertia (don’t change T quickly). Surface-T measurements also have cooler troposphere above, but because of underlying thermal inertia, they change relatively little from one year to next.

TLT has (warmer) air below and (cooler) higher troposphere above. They change much more, year to year, than to surface-T measurements. With the mechanism that air can remix vertically (when forces act on it), I am convinced this explains the larger variation in TLT compared to surface-T measurements. If you look at air at a particular altitude, its T is a result of vertical motions. In TLT, annual increases during El Nino years are particularly notable.

That’s OK, as well, as long as there is no effort to mislead by beginning at a warm El Nino year and claiming T decreased afterwards.

Satellite-T estimations are valuable, ought to continue, and actually extend much higher in the atmosphere. Revealing things we ought to know. But when your T-measurement altitude has air above and air below, you are measuring a slippery thing.

In contrast, surface-T measurements have a much longer history and are made where people are. All analyses of those show concordant trends. In the unlikely event that all surface-T analyzers are together ‘cooking the books’, it has always been possible for anyone to access original, global data and perform an independent analysis. This has been done by BEST, also showing concordance, and that attacked as well. So, why in the world would warming skeptics not undertake their own global analysis? Charity prevents me from speculating.

 

Not at all. First point is that all these global analyses are concordant, so doing innuendo on one or another doesn't accomplish much.

Second point is that there is, and always has been, the opportunity to get as much original data as one wants, and do a completely independent analysis. It is true that some original data would need to be purchased. Is it a fair complaint that no one who would benefit from kicking a brick out of climate science edifice has money? They do support NIPCC conferences among many other things.

But here is a simple exercise for the meanwhile. Take annual average T anomaly from UAH (or RSS) satellites. Compare them to ANY surface-T analysis. You will see a strong linear relationship, with extreme ENSO years appearing as outliers.

Before doing such an exercise, you can innuendo about surface-T analyses being cooked. After doing it, such would become much more difficult to assert.

Calling on mojo's bravery here.

 

"create an entire new science journal"@16. Anyone interested in learning about this journal would visit

Geography Journals | Peer review | Geoinformatics | Geostatistics

and determine for themselves what its main intention is.