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Comment on Does the Aliasing Beast Feed the Uncertainty Monster? by Arcs_n_Sparks

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Aliasing is well understood by data acquisition, control, and signal processing engineers. The question posed by the OP was: does everyone else that manipulates sampled data understand that as well? From the comments here, that is not clear.

I certainly would like to have more confidence in the original proposition: man is warming the planet, before I embark on the second phase of your comment (cost/benefit). Apparently, California decided today that the evidence is clear and passed cap and trade. Thank goodness I moved.


Comment on Berkeley Surface Temperatures: Released by Tilo Reber

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AK: “You’re looking for built-up areas encroaching on the station, but isn’t the Urban Heat Island effect dependent on lots of buildings?”

No, you are confusing classifications with reality. Certainly it is true that the more built up an area is, the more UHI effect you would expect there. But all we are talking about with UHI is the effect on instruments that results from the addition of man made structures around the instrument. So, indeed, if you have an instrument on a farm and if you put a concrete parking lot next to it, the instrument is going to start yielding higher temperatures. And that is what we care about – not the fact that the name has “urban” in it. On the other hand, if you have a thermometer in the middle of a city and it’s already built up, you won’t see much change if you put up another building or parking lot a mile away. Of course total city build up will effect the temperature over time because the larger the warmed area is the harder for the heat to dissipate. But when you start to build in a rural area, immediately around the instrument, the effect can increase even faster than it can in an already built up urban area. And that rural area won’t change its classification status for a very long time and until the building gets really dense.

I’m only pulling this out of my backside, but I would guess that out of 39,000 thermometers in their study they would be lucky to have a thousand with no UHI effect. These things are almost never put in national wilderness areas. They are near roads, close to where someone is able to read them and maintain them. And such areas are naturally subject to population growth.

But really, do you need to know any more than that they came up with a conclusion of “none, or negative, UHI effect” to know that they are doing it wrong. Come on – a little common sense please.

Comment on Laframboise on the IPCC by Don Monfort

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carey,

Actually, it was Donna Laframboise who wrote the book that we have all been discussing here. You know, the one you didn’t read. So you agree with Martha; despite not having read the book, it still exceeded your wildest expectations.

If I may sum up: So what we have so far, is one very snide negative review written by a crybaby, who obviously did not read the book before he scribbled his tome to Amazon, commenting on a book that is not at all important enough for him to spend his time on. And we have a couple of whining copycats, who also have not read the book. The rest of us like it.

Comment on Laframboise on the IPCC by ikh

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Judith,

I wish that the structal flaw was the greatest weakness of the IPCC. But IMHO it is not. The whole idea of the IPCC is conceptually flawed. The idea that there should be a single organisation that authoritatively summarizes climate science is flawed becaues it then becomes argument from authority. Which it has.

If we want summaries of climate science then groups of climate scientists will publish meta-studies. Then we would now be seeing competing pro and skeptical CAGW competing and as evidence improved the answer would emerge. Just as it always has done in science.

The policy makers would hate this but tough. This is the real world

/ikh

Comment on Berkeley Surface Temperatures: Released by Vince whirlwind

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I guess since the “sceptics” were trumpeting the “unreliable temperature record” so loudly, the fact that Muller has proven this to not be the case should give many of them pause for thought, meaning this paper is significant to “sceptics”.
What remaining justification is there for denying what climate scientists have been telling us?

Comment on Berkeley Surface Temperatures: Released by Brandon Shollenberger

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David Young, it’s important to remember Figure 1 in that paper was made by using data from only 2,000 stations. It will be different than what is gotten when all stations are used.

Comment on Berkeley Surface Temperatures: Released by Tilo Reber

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Brandon: Mosher loves to hear himself talk. He’s so anxious to take off and show everyone how insightful he is that he misses the question or the subject much of the time.

Comment on Berkeley Surface Temperatures: Released by Tilo Reber

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I believe that their result is correct in a technical sense. It’s just that what they were checking had no correlation to checking for the effect of build on thermometers.


Comment on Berkeley Surface Temperatures: Released by Tilo Reber

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“Now, pending audit and review, AGW has a purpose-built dataset fit for use in climatology for the major AGW hypotheses, to sufficient precision and with sufficient accuracy.”

LOL. There is no new data set. It’s the same old stuff that has been around forever manipulated in new ways.

“by clarifying that I meant only the argument at WUWT that UHI could contribute significantly to the shift in global surface temperature was finally put to rest and buried. ”

That may have been the case if the BEST UHI test actually checked for UHI. Unfortunately, it did no such thing.

Comment on Berkeley Surface Temperatures: Released by Tilo Reber

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Zeke: Why would you think that the test that BEST ran has anything to do with checking for the effect of build on thermometers?

Comment on Berkeley Surface Temperatures: Released by A Lacis

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David,

I don’t see any reason why they would try to ‘de-trend’ the AMO index. Moreover, to first order, I would not expect there to be any long-term trend in the AMO index. I tend to think that the AMO and PDO, and the shorter period El Nino and La Nina variability represent natural (unforced) fluctuations and oscillations that the climate system undergoes about a zero reference point – hence, no long-term trend.

It is possible that global warming might induce some change in the amplitude, frequency, or pattern of these unforced fluctuations, but I have seen no evidence that that might be happening.

Comment on Berkeley Surface Temperatures: Released by Fred Moolten

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<a href="http://en.wikipedia.org/wiki/Atlantic_multidecadal_oscillation" rel="nofollow">AMO</a>

Comment on Berkeley Surface Temperatures: Released by Tilo Reber

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It doesn’t really matter about the comparisons between BEST and GISS regarding UHI. The simple matter is that the BEST UHI test does not come close to testing what they claim to be testing.

Comment on Berkeley Surface Temperatures: Released by Fred Moolten

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Also see <a href="http://www.nonlin-processes-geophys.net/18/469/2011/npg-18-469-2011.pdf" rel="nofollow">Is The AMO A Statistical Phantom?</a>

Comment on Berkeley Surface Temperatures: Released by Bruce

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Steve McIntyre said:

“I commented on one replication issue – the BEST assertion that, using the Anthony Watts classification, the trends at “good” USHCN stations was higher than the trends at “bad” USHCN stations. I attempted to replicate this aspect of the analysis and got an opposite result.”

If true, this demolishes BEST and those who helped them.

http://wattsupwiththat.com/2011/10/21/sceptical-berkeley-scientists-say-human-component-of-global-warming-may-be-somewhat-overstated/#comment-774358


Comment on Berkeley Surface Temperatures: Released by Geoff Larsen

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An interesting set of papers by BEST which reconfirms the other land surface temperature time series. I would like to comment on the UHI paper as I am surprised with the methodology they used.

Roy Spencer did some work on UHI early last year. He used NOAA’s International Surface Hourly (ISH) weather data from around the world during 2000 plus 1 km gridded global population density data.
http://www.drroyspencer.com/2010/03/the-global-average-urban-heat-island-effect-in-2000-estimated-from-station-temperatures-and-population-density-data/

His abstract:
“Global hourly surface temperature observations and 1 km resolution population density data for the year 2000 are used together to quantify the average urban heat island (UHI) effect. While the rate of warming with population increase is the greatest at the lowest population densities, some warming continues with population increases even for densely populated cities. Statistics like those presented here could be used to correct the surface temperature record for spurious warming caused by the UHI effect, providing better estimates of temperature trends”.

See the graphs of “station warm bias” versus “pop density”.
Other interesting analyses follow; scroll forward.

I suspect all BEST have done is pick out a low population density subset of stations which have a higher rate of warming over the time period than the total population and viola, these stations report a higher warming rate than the total population. I’m not surprised they got the results they did.

Comment on Berkeley Surface Temperatures: Released by Paul S

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The graph shows 12-month moving averages with the final data point appearing to show the average of July 2009 to June 2010, so in any case it doesn’t show a comparison of 2010 anomalies.

The most likely reason for the discrepancy is that BEST don’t have 2010 data finalised yet so in their comparison setup January to June 2010 monthly anomalies are set to zero, creating a downward diagonal in the moving average.

Also, the 2010 anomaly in UAH is in good agreement with the surface records.

Comment on Berkeley Surface Temperatures: Released by Don B

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On the other hand, if publishing the email exchange made her angry, she might not misquote Mosh ever again – because she would not contact him again. :)

Comment on Self-organizing model of the atmosphere by Count Iblis

Comment on Berkeley Surface Temperatures: Released by Nick Stokes

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Steven, I found 36736 stations in the inventory, and I’m now in the data file data.txt. 35121 stations there have at least one month with more than 10 days data.

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