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Comment on Understanding Time of Observation Bias by Matthew R Marler

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bob Greene: Climate science seems to be a very different beast than any science I’ve been associated with.

It isn’t laboratory science. Not much is controlled, and not much is recorded accurately as wanted day in and day out, and the recording devices change irregularly without adequate documentation. I did pass introductory chemistry, and this is one of the ways that science has been done. It is more like the problems associated with dating specimens in paleontology than like measuring blood electrolytes.


Comment on Understanding Time of Observation Bias by Steven Mosher

Comment on Understanding Time of Observation Bias by kim

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Captain Stormuller’s Visit to Climate Heaven.
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Comment on Understanding Time of Observation Bias by Steven Mosher

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“More BS from Mosher. I have accumulated massive evidence that the US adjustments are bogus and incorrect. I would love testify and hope to have the opportunity. I can’t imagine anyone testifying under oath that they are correct”

That will be special. I hope the democrats call Anthony as a witness if you are called for the republicans.

Can you imagine being responsible for single handedly discreting the skeptics as a whole. Owngoal coming.. congress calls goddard to testify

And now if they DONT call you, you’ll know exactly what they think of you.

Comment on Understanding Time of Observation Bias by phi

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Zeke,

But it’s the result that counts.

There are two independent phenomena which by default are supposed to have random effects.
For historical reasons, the first seems to have an extraordinary directed effect.
It is not too problematic.
The second phenomenon, against all odds, is not random, very curious.
In addition, it is parallel to the first.
The assumption of independence is positively unacceptable.

Comment on Understanding Time of Observation Bias by Steven Mosher

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Wait it looks like Goddard fell for the taunt..
He has raised his hand to be called to Congress.

how did I know he could not resist.

Now of course there are two outcomes

A) they wont call him.. in which case he’s a nobody
B) they will call him and we can have skeptic versus skeptic..

Comment on Understanding Time of Observation Bias by Steven Mosher

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“And they aren’t controlling the narrative. Small fry. Fringe actors. The misplaced overconfidence of the consensus crowd is more problematic. Wouldn’t you agree, Steven?”

depending on the topic that case could be made.

Comment on Understanding Time of Observation Bias by Zeke Hausfather

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Phi,

Adjustments to U.S. temperatures are dominated by two large non-random systemic biases: changes from afternoon to morning observation times, and the CRS to MMTS transition. Neither would be expected to have random effects.


Comment on Understanding Time of Observation Bias by Zeke Hausfather

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Ken,

The effect of TOBs is indeed not universal. I could have created maps showing how changes from afternoon to morning across the CRN network (and tied it into Karl et al’s related discussion), but that was too much work for a blog post. On the other hand, I could just suggest that folks interested in the nitty gritty read Karl et al or Vose et al :-p
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David,

There is a reason why the ocean has little to no coverage: those are maps of land stations. For ocean temperature data go here: http://icoads.noaa.gov/

Comment on Understanding Time of Observation Bias by Steven Mosher

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cooling trends have been supposed for trees.
warming trends have been supposed for trees.

it could be trees. it could be unicorns.

Comment on Understanding Time of Observation Bias by Steven Mosher

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looked at rain data.
dont want to touch it.
the spatial variability is pretty scary (technical term)

Comment on Understanding Time of Observation Bias by KTM

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Thanks for the reply Zeke. As a thought experiment, let’s take a station that took readings in the afternoon, then changed to a morning observation. Before the change the maximum temperature series may be polluted by double-counts, but the minimum temperatures should be free of TOBS bias. After the change the minimum temps may be polluted by double-counts, but the maximum temps should be free of TOBS bias.

Every temperature series already splices the record together to account for “discontinuities”, and every temperature record already reports anomalies. So why not take each such station, use the minimum temperature anomalies up until the change, then do a one-time shift to maximum temperature anomalies? That way, each station has one single change, and there is no need to go back and “adjust” every single data point for TOBS. As a bonus, the underlying raw data is the best available, not polluted by the double-counts suspected to introduce a systemic bias.

At the very least, this type of analysis could serve as a reality check for the TOBS adjustments being applied to each station. If the TOBS adjustments are being properly applied, the two different approaches should lead to a very similar anomaly record.

Comment on Understanding Time of Observation Bias by Mark Silbert

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I don’t think I was as clear as I want to be in the above comments, so I will try again.

If you go to the Berkley Earth web site and click on Data/Results by Location, you get to a slick page that allows you to review the summary results for BEST’s temperature data reanalysis. You can look at it by City, Country, State or Station. The summary provides “regional warming since 1960 in deg. C per century. For example if you look up Canada you see 3.64 +/- .44. Abu Dhabi is 3.61 +/- .62. Bolivia is .67 +/- .29, and so on. This strikes me as an odd way to show the summary results of a data reanalysis project the intent of which was to determine whether or not other analyses of the data (collected between 1850 and 2014) were verifiable. If I understand what has been done, it appears that BEST took the “actual measured” temperature change between 1960 and 2014 and extrapolated it to 2060 and tabulated these results. Why wouldn’t they show the results of their data reanalysis for 1850 – 2014. If the answer is that they believe the measurements prior to 1960 were less reliable than those afterwards, then why wouldn’t they just show the summary results of their data reanalysis from 1960 – 2014? If they wanted to show a century long summary, why wouldn’t they have summarized the period from 1914 – 2014? By the way, all of the other summary data they present on other sections of their website cover only the measurement period and make no attempt to go beyond the present measured data. I am not accusing anybody of fraud or mannhandling the data or of using poor statistical methods. Others are doing a fine job of that. I am just saying that the way they are summarizing their results (which is what most people look at) can be confusing if not down right misleading.

I would hope that Zeke or Mosher would provide some clarification.

On another topic, it appears that error bars (+/-) in the summary tables is on average around .5 deg C (in my scan I have seen a range of .20 – .62). Seems low to me, but I’m sure that I could understand how they get there if I had the intestinal fortitude to dig through their code. It would be really helpful if either Zeke or Mosher could explain (in simple terms that this old reasonably well technically educated scientist/engineer can understand) how these error bars comport with the error bars of +/- .05 deg C that they associate with their “warmest year” analysis issued recently and highlighted on the web site.

Comment on Week in review by russellseitz

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How <i>original </i>of Anthony Watts to <a href="http://vvattsupwiththat.blogspot.com/2015/02/and-earth-stopped-moving.html" rel="nofollow"> place plate tectonics in the same boat as phlogiston.</a>

Comment on Understanding Time of Observation Bias by Steven Mosher

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Ya Matthew that’s my judgement.

If somebody asked me “Do you think that re doing the land temperature series YET AGAIN, will yield a result that changes something fundamental, I would say NO. ( oceans much more likely )

That is, people have sliced the data 10 different ways. NOAA, CRU, GISS, JMA, BE. Independents: Zeke, me, jeffid, nick stokes, chad and MORE.

People have averaged the data six ways from sunday.

People have adjusted different ways, not adjusted..

And today we still know what we knew when we started

A) C02 is a GHG. more will warm the planet all else remaining equal
B) How much? between 1.5 and 4.5 C per doubling
C) was the MWP warmer? hmm maybe, cant tell for sure.

So, I dont think anyone thinks that redoing the series one more time will yield any game changing insights.. otherwise they would fund it or some amatuer would do his own and be king temperature.


Comment on Understanding Time of Observation Bias by Steven Mosher

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Brandon you’ll be glad to hear that the web site is being re done.
It all depends on funding.

I too would love to have that level of documentation for you.
but you’ll have to live with what had to live with when I joined.
It was better than what I got from hansen or anyone else, so I dont want to make perfection the enemy of the good.

again, whatever suggestions, improvements, etc you have, they only get “tickets” if I get a mail.

Comment on Understanding Time of Observation Bias by Nick Stokes (@nstokesvic)

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“I looked at the daily precipitation data for several sites some years ago. It seemed to show such a TOB effect”
Rain per day is not a treasured statistic. Rain is cumulative – generally quoted in per annum. There is no min/max average, as with temp.

Comment on Understanding Time of Observation Bias by Zeke Hausfather

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KTM,

Perhaps I’m misunderstanding you, but thats exactly what is done. Minimum and maximum temperatures are analyzed separately, and the step change associated with the TOBs is removed for both. No other corrections beside the removal of this step change are done to account for TOBs.

Comment on Week in review by A fan of *MORE* discourse

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Kudos to kim and Forbes for showing Climate Etc readers the plain-talking common-sense approach to solving “wicked problems” … like climate-change and health-care!

From kim’s link:

Why Switzerland Has the World’s Best Health Care System
by Avik Roy, Forbes Staff

The Swiss system resembles that of Massachusetts and PPACA.

The Swiss have an individual mandate.

The government defines the minimum benefit package, which has been subject to expansion from special-interest lobbying, and is more comprehensive and less consumer-driven than it could be.

The government has enacted Medicare-style price controls for hospital and physician reimbursement.

Insurers must charge similar rates to the young and old (“community rating”), must cover pre-existing conditions, and must operate as non-profit entities.

Princeton economist Uwe Reinhardt describes Switzerland as “a de facto cartel of insurers and health care practitioners who transact with one another in a tight web of government regulations.”

Indeed, the fact that both liberals and conservatives would find objectionable elements to Switzerland is a large part of its appeal. It achieves the policy priorities of liberals (universal coverage; regulated insurance market) and of conservatives (low government health spending; privately-managed health care). Both sides could declare victory, and yet also have plenty to complain about.

In other words, Switzerland provides the contours of a bipartisan solution: one that stands a chance of gaining more than 60 votes in the Senate.

Purists on either side will object, but as an accomplished Saxon reformer once put it, “politics is the art of the possible.”

Good on `yah, Switzerland (and kim too!) for showing the world the common-sense non-ideological path by which “wicked problems” like climate-change and health-care solved get in practice

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Comment on Understanding Time of Observation Bias by Carrick

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Steven Mosher:

Now I want to find the best 25 correlators.
I can search all stations, but that will be a stupid waste of time.
I want to search fast. at 2500km the correlations are all low

My worry is that, once you go out far enough, you start getting correlations by chance. We can see this happens well beyond 1000-km from Robert’s analysis:

Probably if you did something besides ordering the top 30 by correlation (remember there is measurement error so the ordering is not accurate), you could get rid of bias, and end up with a measure that provides uncertainty bounds with it.

It’s the thing a good statistician could help you with in terms of devising improved testing (ideally unbiased central value plus uncertainty range associated with the empirical breakpoints).

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