The Holocene Deniers

[thaumaturgy]

[FONT=&quot]Urban Heat Island Effect (UHIE):[/FONT]

[FONT=&quot]Apparently the UHIE has minimal impact on the overall estimation of trends in surface temperature increases.[/FONT]

[FONT=&quot]An article in Nature recently states this:[/FONT]

[FONT=&quot]

Controversy has persisted over the influence of urban warming on reported large-scale surface-air temperature trends. Urban heat islands occur mainly at night and are reduced in windy conditions. Here we show that, globally, temperatures over land have risen as much on windy nights as on calm nights, indicating that the observed overall warming is not a consequence of urban development.

[/FONT]

[FONT=&quot]Parker, D.E., Climate: Large scale warming is not urban, Nature 432, 290 (18 November 2004) (Source )[/FONT]

[FONT=&quot]An earlier study from Peterson in 2003 found :[/FONT]

[FONT=&quot]Contrary to generally accepted wisdom, no statistically significant impact of urbanization could be found in annual temperatures.

[/FONT]
[FONT=&quot]( Peterson, T.C., Assessment of urban vs rural in situ surface temperatures in the contiguous United States: No Difference Found, J. Climate, V16, pp2941-2959)[/FONT]
[FONT=&quot] (SOURCE) [/FONT]

[FONT=&quot]I am still reading through this article, but very interestingly in the Peterson article there’s this bit:[/FONT]

[FONT=&quot]To find out how contaminated global temperature trends were from the UHI, Peterson et al. (1999) identified each station in GHCN using both the map-based and the satellite-based metadata. Two time series were then created. One was the time series from the full dataset, the one used routinely to determine global temperature trends over land areas at the National Climatic Data Center (e.g., Lawrimore et al. 2001), and another one produced using only data from stations that were identified as rural by both techniques. The two time series were very similar. The linear trend from 1880 to 1998 was 0.65[sup]o[/sup]C century[sup]-1[/sup] for the full dataset and the slightly higher 0.70[sup]o[/sup]C century[sup]-1[/sup] for the rural-only subset. The resulting conclusion was that the well-known global temperature time series from in situ stations was not significantly impacted by urban warming.(ibid)

[FONT=&quot] (emphasis added)[/FONT][/FONT]
[FONT=&quot]I just downloaded this paper and am going to take a closer look at it. It seems pretty interesting overall![/FONT]
[FONT=&quot](And since we’ve wasted nearly 500 posts on discussions that have little if anything to do with how the data is actually treated, this should be a refreshing break.)[/FONT]

 

[thaumaturgy]

[FONT=&quot]How NASA GISS treats the data:
[/FONT] [FONT=&quot]from: Data @ NASA GISS: GISTEMP: Sources Documentation
[/FONT] [FONT=&quot]

The goal of the homogeneization effort is to avoid any impact (warming or cooling) of the changing environment that some stations experienced by changing the long term trend of any non-rural station to match the long term trend of their rural neighbors, while retaining the short term monthly and annual variations. If no such neighbors exist, the station is completely dropped, if the rural records are shorter, part of the non-rural record is dropped.

(emphasis added)
[/FONT] [FONT=&quot]First off: unless I'm very much mistaken, the urban HEAT island effect is generally agreed to be a warming phenomenon, ergo this homogenization step should, on average, decrease the temperature of urban stations I should think.
[/FONT] [FONT=&quot]Now the USHCN data we’ve been laboring over here is, according to the USHCN site:
[/FONT] [FONT=&quot]

The data have not been adjusted for station relocations, heat island effects, instrument changes, or time of observation biases.

(USHCN ORNL/CDIAC-118 NDP-070)
[/FONT] [FONT=&quot]Here is a list of QA (quality assurance) steps taken with regards to the HCN/D data set:
[/FONT] [FONT=&quot]

The following is a list of items from H92 that constitute some of the main human and automated QA checks performed on the data by NCDC.

[/FONT]

1. [FONT=&quot]Monthly mean values of maximum and minimum temperature, computed from the HCN/D data, were compared to their respective unadjusted monthly means from the HCN. All conflicts were investigated and resolved, with verification based on manuscript or published sources.
   [/FONT]
2. [FONT=&quot]Checks were performed to ensure that no monthly mean values of maximum and minimum temperature calculated from a station's daily data were above (below) the monthly state extremes of maximum (minimum) temperature.
   [/FONT]
3. [FONT=&quot]Any daily precipitation total exceeding 5 in. was verified against manuscript or published sources.
   [/FONT]
4. [FONT=&quot]Checks were implemented to ensure that maximum temperatures were never less than minimum temperatures on the day of occurrence, the preceding day, and the following day. Conversely, checks were performed to ensure that minimum temperatures were never greater than maximum temperatures on the day of occurrence, the preceding day, and the following day.
   [/FONT]
5. Temperature data from stations that took readings during the morning over some period have been checked for any date shifting resulting from observers assigning readings to the calendar day of occurrence (the previous day in the case of maximum temperature) rather than the observation day. Such readings were switched back to the day of observance as part of the manual QA checks on the HCN/D data.

 

[thaumaturgy]

The Great Unanswered Questions:

I am still waiting on Glenn to tell me where he followed through on the case where Excel somehow managed to clip/average/process 29,900 data points and reduce them down to 100 without Glenn realizing it:

Thau, I always will admit my errors and I screwed up the first plot. I admit it. Excel for some reason clips the number of points and I don't have a foggy clue as to why. But, I let that thing through so I will accept responsibility for it. It might take me a time or two to correct it but I always will.

(This after he complained so vociferously about my merely clipping the axes on a graph to make a point about the data around zero and his complaint about the borehole data that eliminated a lot of data, I thought he was serious about not liking clipping of data!)

But the second great question is...why did Frank evaporate after I read his recommended Drallos essay and I went through and addressed individual points?

I see now that you have already posted your "take" in post #448. THANKS! I will take my time to give your post a thoughtful read, see what I can learn from it, and then post back to you. So that I do not get distracted and off-track, I will not read or post anything else here until first I finish giving your critique due consideration. THANKS AGAIN!

-- Frank

I am always amazed at how someone can make a suggestion repeatedly and then when it is acted upon they just evaporate as if the only goal was to get me to follow their suggestion, not actually engage in a conversation.

But I must be patient, it's only been a day or two, so I'll just wait. But each passing day seems to me to be indication that I might be waiting a loooong time. But I look forward to being proven disastrously wrong.

 

[grmorton]

If you took the time to read and understand any posts in this thread, you would quickly realize that you don't, in fact, have to spend any time convincing anyone of that.

True, you prefer people like Frank to leave. I have no doubt you wish that for me. Unfortunately, I am not in the wish-granting business.

I think it was you who simply wanted me to believe what I was told by experts. I don't do that either without looking at the data.

 

[grmorton]

[FONT=&quot]Urban Heat Island Effect (UHIE):[/FONT]

[FONT=&quot]Apparently the UHIE has minimal impact on the overall estimation of trends in surface temperature increases.[/FONT]

[FONT=&quot]An article in Nature recently states this:[/FONT]

[FONT=&quot]An earlier study from Peterson in 2003 found :[/FONT]

[FONT=&quot]I am still reading through this article, but very interestingly in the Peterson article there’s this bit:
[FONT=&quot](emphasis added)[/FONT]
[FONT=&quot]I just downloaded this paper and am going to take a closer look at it. It seems pretty interesting overall![/FONT]
[FONT=&quot](And since we’ve wasted nearly 500 posts on discussions that have little if anything to do with how the data is actually treated, this should be a refreshing break.)[/FONT]

I find the claim that urban heat island is minimal ridiculous in light of NASA produced images of urban heat effects. Note that the yellows are 18 deg C and the red is about 30 deg C where the urbanizaiton of Atlanta is greatest. How someone can look at the IR photo below and say that urban heat effect is mostly night time is way beyond me. The data does't support that ridiculous claim.

You can read more at Urban Heat Island: Atlanta, Georgia : Image of the Day

I thought I would add that you can find a similar study of Salt Lake City in which the roof top temperatures in the daytime can reach 160 deg F.

The Urban Heat Island can also aggravate conditions during heat waves. The UHI is defined as the maximum difference in temperatures between the urban core and the surrounding rural lands. The replacement of vegetation by streets, buildings and asphalt, often lead to a greater absorption of sunlight during the day and a slow release of heat during the nighttime. Rooftop temperatures can reach over 160 F, as shown in a NASA overflight of Salt Lake City below http://instructional1.calstatela.edu/sladoch/Geog101/heatwave/science/science.htm

That page has a picture of the glowing roof tops--which of course, 160 deg F roof tops won't bother the out put of thermometers placed on them, like the one in Baltimore MD, at least according you you guys.

YOu can find the Baltimore thermometer about half way down the page at http://wattsupwiththat.com/2008/08/23/.

 

[grmorton]

[FONT=&quot]How NASA GISS treats the data:
[/FONT][FONT=&quot]from: Data @ NASA GISS: GISTEMP: Sources Documentation
[/FONT][FONT=&quot](emphasis added)
[/FONT][FONT=&quot]First off: unless I'm very much mistaken, the urban HEAT island effect is generally agreed to be a warming phenomenon, ergo this homogenization step should, on average, decrease the temperature of urban stations I should think.
[/FONT][FONT=&quot]Now the USHCN data we’ve been laboring over here is, according to the USHCN site:
[/FONT][FONT=&quot](USHCN ORNL/CDIAC-118 NDP-070)
[/FONT][FONT=&quot]Here is a list of QA (quality assurance) steps taken with regards to the HCN/D data set:
[/FONT]

Except that it is clearly adding heat in toto, according to the total correction GISS places on the raw data, making it .3 deg C hotter in 2000 than the correction was in 1900. And I show that the homogeneity filter in Eastern Colorado is used to make a cooling station warmer. HEre is the picture. It is off my blog.

The above is from a peer reviewed Bull American Meteorological Society.

 

[grmorton]

The Great Unanswered Questions:

I am still waiting on Glenn to tell me where he followed through on the case where Excel somehow managed to clip/average/process 29,900 data points and reduce them down to 100 without Glenn realizing it:

Clearly you can't read. Post 414 on page 42 a long time ago in this thread.
http://www.christianforums.com/t7394133-42/#post52889048

I admitted my error and you didn't bother even reading it. I think this may say a lot about how you handle data--you ignore it. It is just too good of a story line to keep saying that I didn't respond to that issue.

(This after he complained so vociferously about my merely clipping the axes on a graph to make a point about the data around zero and his complaint about the borehole data that eliminated a lot of data, I thought he was serious about not liking clipping of data!)

Hey ding dong. I already answered that. See you are so confident of your opinion that you don't even think it is possible for you to be wrong on anything. http://www.christianforums.com/t7394133-42/#post52889048

Post 414.

But the second great question is...why did Frank evaporate after I read his recommended Drallos essay and I went through and addressed individual points?

Ask Frank. I suspect he is very busy.

I am always amazed at how someone can make a suggestion repeatedly and then when it is acted upon they just evaporate as if the only goal was to get me to follow their suggestion, not actually engage in a conversation.

But I must be patient, it's only been a day or two, so I'll just wait. But each passing day seems to me to be indication that I might be waiting a loooong time. But I look forward to being proven disastrously wrong.

Don't gloat so early and don't gloat about me not answering questions when I clearly did. Post 414 Mr. gloating-while-he-is-wrong.

http://www.christianforums.com/t7394133-42/#post52889048

PS, I let you aske a couple of times just to show that you always think you are right, and don't ever entertain the possiiblity that you might be wrong. You are entirely wrong in your assumption that I didn't answer your point. In case you missed it, it is post 414.

Instead of dealing with the data and being honest about your mistakes (like your high school explanation of how heat moves) you prefer to gloat about my supposed inability to answer you when I made a mistake. I did make a mistake--my excel cut me off and I have no clue why. I still can't get it to work right. It might be a 64-bit issue as I have a 64 bit machine.

 

[thaumaturgy]

Clearly you can't read. Post 414 on page 42 a long time ago in this thread.
http://www.christianforums.com/t7394133-42/#post52889048

On that post you said:

Thau, I always will admit my errors and I screwed up the first plot. I admit it. Excel for some reason clips the number of points and I don't have a foggy clue as to why. But, I let that thing through so I will accept responsibility for it. It might take me a time or two to correct it but I always will.

(emphasis added)

To my knowledge you never replotted the data Okmulgee vs Okemah (x vs y).

So in fact you only explained that for some reason "Excel" clipped the data and you don't know why.

But you never replotted it or provided an explanation as to how you wound up with a 0.8 slope as opposed to much-closer-to-1 slope the unclipped, unedited, unprocessed data shows.

Just plotting other data or other versions of the same data is not the same as plotting the data "excel" messed up.

If you want to convince me you were serious about investigating the issue then why don't you show me the slope you get from plotting the data we were discussing in the format we were discussing it?

 

[thaumaturgy]

I find the claim that urban heat island is minimal ridiculous in light of NASA produced images of urban heat effects.

Did you read any of the Peterson article?

Note that the yellows are 18 deg C and the red is about 30 deg C where the urbanizaiton of Atlanta is greatest. How someone can look at the IR photo below and say that urban heat effect is mostly night time is way beyond me.

Well, sure, Glenn because you didn't bother to think about what is being said about the data. The point is not that the UHIE isn't real, it's that in the overall impact on the measured temperature data (for reasons described below) is possible less than the overall appearance of the heat island.

Here's Figure 4 and Fig 5 from the Peterson paper:

What this represents is a comparison of their selected TEST SITES for the urban and nearby rural sitings for this study (you'll have to read the paper for detail). The left graph is unadjusted temperatures. They have a statistically significant difference of 0.31[sup]o[/sup]C. But note the really interesting thing (you'll like this Glenn, you like to interpret stuff out in the tails): some of the urban stations were COOLER than the near by rural measurements!!!!

How could that be??? What does it mean? Well, thankfully we have statistics to help us know how to deal with the data.

Anyway the corrections applied in the right hand graph are related to:

• differences in elevation
• differences in latitude
• differences in time-of-observation
• differences in temperature equipment

Now the article itself describes quite extensively why and how the differences and corrections are calculated and the justification for assuming such corrections are useful and real.

But ultimately the suggestion of the Peterson paper (as I understand it) is that the overall impact of the UHIE is less important to the temperature measurements. NOT that the UHIE isn't real on what he calls the mesoscale, but rather that it is in some small part missed by the various microscale and local-scale climate effects in urban settings:

Some hypotheses as to why Peterson thinks this effect occurs:

Noteworthy is where temperature stations should be placed and what that entails:

If a station meets these guidelines or even if any attempt to come close to these guidelines was made, it is clear that a station would be far more likely to be located in a park cool island than an industrial hot spot.

(emphasis added)

The fact that the IR shows an overall heating effect from the urban setting doesn't mean that the temperatures measured in the urban areas will necessarily reflect the overall temperature of the urban island.

And this:

Park cool islands are not the only potential mitigating factor for in situ urban temperature observations. Oceans and large lakes can have a significant influence on the temperature of nearby land stations whether the station is rural or urban. The stations used in this analysis that were within 2 km of the shore of a large body of water disproportionally tended to be urban (5.8% of urban were coastal versus 2.4% of rural).

Peterson also states:

As examination of Figs. 4 and 5 indicates, site-specific local- and microscale effects will make some urban stations genuinely warmer than nearby rural stations and will also make some of them colder.

Peterson then states:

While analyses of inhomogeneous data cannot accurately assess the magnitude of urban heat islands, there are other types of accurate measurements of the real UHI phenomenon that also bias our expectations. These are analyses of in situ transects of urban areas and high-resolution IR satellite data. These data will accurately reveal that major urban highway intersections, industrial areas, and rooftops are indeed hot. But unless the meteorological station is located in an intersection, industrial area, or on a rooftop, the analyses should not be used to guide our expectations of urban biases at in situ observation sites.

(emphasis added)

The data does't support that ridiculous claim.

While I agree this is on the surface "counterintuitive" what Peterson is saying isn't that "weird", and clearly (if you read the article) the data in fact does support his contention.

I don't think Peterson or anyone else thinks Urban Heat Islands aren't real, but rather the temperature record we are dealing with, when treated for unrelated inhomogeneities reveals no statistically significant difference for several selected urban-rural data sets.

I would imagine you won't like the paper as it relies a lot on statistical analyses of data.

I find it fascinating that Peterson of the National Climate Data Center doesn't understand your point Glenn, that statistics really aren't important! Maybe you should write to him. I bet the second you show him your facility with standard deviations vs confidence intervals (see my post # 513) he'll be willing to abandon stats altogether and just rely solely on anecdotal data all the time!

It certainly seems to serve your purposes whenever you need to rely on it.

Maybe if all the climatologists went with anecdotal data they could make whatever point they wanted!

 

[thaumaturgy]

my excel cut me off and I have no clue why. I still can't get it to work right. It might be a 64-bit issue as I have a 64 bit machine.

Well, Glenn, you see, blaming excel, while possibly appropriate (I'm no Microsoft fan), it isn't the same as actually correcting the error. It is an excuse.

An actual correction would involve the following:

1. An actual plot of Okemaha on one axis and Okmulgee on the other
2. A linear regression and R[sup]2[/sup]

Until that time all I saw was you making an excuse.

I have little time for excuse-making. Especially when just about anyone could see that 100 data points looks dramatically different from 30,000 data points. And yet you crowed and crowed about "real" data during that exchange.*

Oh, yeah, if you want an alternate to Excel for plotting and dealing with data you can download R at

The Comprehensive R Archive Network

It's free and pretty powerful. It'll take you some time to learn how to use it but you can plot and regress to your heart's content.

(Personally when I work on this stuff I use:

• R
• JMP Statistics Program
• Excel

So it actually helps to do science if you have more than one tool at your disposal. But some folks like to limit themselves)

* Here's the Crowing Bit with emphasis added:

I am downloading the DAILY data, not the monthly. The monthly data isn't raw.
...
So, you are using data that has already been MANIPULATED. Notice the difference in your monthly scattergram vs the daily raw scattergram I posted. So, if you have been doing your analysis on data that has already been sanitized, your statistics are worthless for another reason.
...
Yeah, that is why what I am using is better than what you are using. You are using manipulated averages rather than looking at the raw data. The problem Thau is that you can go cherry picking for data that has been edited to make it all look fine and dandy but it says nothing about the quality of the real observations. You are not using observational data.
...
DAILY data. Not edited monthly data. The fact that your monthly data is so perfectly lined up along the slope =1 line and mine isn't says that there is a huge amount of editing done to the data to make it pretty before you download it. Then you do your thing and say, 'voila, my statistics show no problem'.
...
Use the raw data which is Daily data.

 

[thaumaturgy]

Except that it is clearly adding heat in toto, according to the total correction GISS places on the raw data, making it .3 deg C hotter in 2000 than the correction was in 1900. And I show that the homogeneity filter in Eastern Colorado is used to make a cooling station warmer. HEre is the picture. It is off my blog.

I noted in Peterson's paper that homogenization correction did result in some increase in temp of the average of the rural data and a cooling of average urban.

But then the "homogenization" concept is less "nefarious" than many skeptics make it out to be. It is not as if they are simply pushing the data to make it line up with their expectations. From the Peterson article you can get a good idea of why the homogenizations are not only necessary but justified.

Homogenization is hardly the monster the skeptics make it out to be.

 

[grmorton]

On that post you said:

(emphasis added)

To my knowledge you never replotted the data Okmulgee vs Okemah (x vs y).

So in fact you only explained that for some reason "Excel" clipped the data and you don't know why.

Sigh, can't you look a few posts down? GEEESH, what a dolt that keeps up at it. And I don't see you admitting that your two claims that I hadn't admitted the problem was wrong--it seems that you are incapable of acknowledging that YOU were wrong on anything.

I made an offhand comment to you the other day that I could put an open flame and it wouldn't bother you or shake your belief in anthropogenic global warming. Here is almost that situation from Tahoe City, California

I don't know how many of these stupid things it will take for you to realize that it is incredibly stupid to believe the output of the thermometers--which measure the maximum temperature of the day. On days that a burn is made, no doubt the temperature is higher. SHEESH--what faith you have in your religion.

Do you think this is a good way to do things?

As to things being cooler in urban settings, I find that ridiculous given the chart you never comment upon--it is the one that shows that mere editing warms the record today and doesn't change the record in the past. Yet you ignore this over and over and over.

40% of the warming is done in the editing. and you ignore that as you do that you were wrong about me not addressing my error.

 

[grmorton]

Homogenization is hardly the monster the skeptics make it out to be.

Then actually EXPLAIN where the .3 deg C additional heat correction for the present modern thermometers comes from-specifically which correction adds it?? It has been added. Of that there is no doubt.

 

[thaumaturgy]

Sigh, can't you look a few posts down? GEEESH, what a dolt that keeps up at it

Perhaps I am as dogged as you. And perhaps I don't like your attitude. And perhaps I'd like you to feel the way you make others feel?

I dunno.

But I looked down a few posts and I sure didn't see where you had re-plotted all 30,000 data points.

All I see, and all I continue to see is your excuse as to why 100 data points were plotted instead of 30,000.

. And I don't see you admitting that your two claims that I hadn't admitted the problem was wrong--it seems that you are incapable of acknowledging that YOU were wrong on anything.

I admit you did "cop" to the error. You also indicated you would address it. I didn't see it addressed since addressing an error is different from making an excuse about it.

This is really simple. All you need to do is replot the data. Easy-peasy!

You made big claims about how your data was real and you got a slope of 0.8 or so, and then you agreed something had gone wrong.

All I want is for you to replot the data. I'd just like for you to hold yourself to the same high standards you constantly bully others about!

That's it.

Do you think this is a good way to do things?

I don't know how many times I have to answer this question but I'll answer it as I have with all the other times I've answered it: NO. Emphatically NO.

But then you have yet to provide statistical proof that these are the "norm" and not just more anecdotal data.

You see, that's why the Peterson paper was a joy to read. He not only explained his points but supported them with statistical robustness.

But who am I to make such a judgement? I could go with a statistical report by a member of the Nat'l Climate Data Center who appears to understand the importance of statistics to dealing with data, or I could go with the guy who doesn't understand the difference between a confidence interval and a standard deviation. Who would you go with?

Just plot the data and tell me what slope you get and what your R^2 was. (I'll even wait for you to find a machine with working Excel on it, or you can step up to the plate and do it in R, it's free.)

 

[thaumaturgy]

Then actually EXPLAIN where the .3 deg C additional heat correction for the present modern thermometers comes from-specifically which correction adds it?? It has been added. Of that there is no doubt.

So you didn't read the Peterson paper?

SECTION d, page 2948-2951

It goes over the differences and biases and problems related to comparing/switching

• Hygrothermometers
• Liquid-in-Glass Thermometers
• Hygrothermographs
• MMTS

and some description of the issues around the housings of these.

 

[Thistlethorn]

True, you prefer people like Frank to leave. I have no doubt you wish that for me. Unfortunately, I am not in the wish-granting business.

I think it was you who simply wanted me to believe what I was told by experts. I don't do that either without looking at the data.

Please stay as long as you like. It's an absolute joy seeing your "argument" getting trashed over and over again by thaumaturgy, who is obviously a much better scientist than you. I'm not a scientist, and I can see right through your "points", and I think I made that clear earlier. Now I've taken a step back to enjoy the carnage.

 

[grmorton]

Perhaps I am as dogged as you. And perhaps I don't like your attitude. And perhaps I'd like you to feel the way you make others feel?

You sound like my mother. "Glenn, I don't like your attitude!!!" Wow! Am I subject to your discipline as well? Get real. As to making me feel like I make others feel, you will die trying. One has to actually care what you think about me in order for me to feel badly that you don't like what I am saying. Frankly, Thau, I gave up caring what you and a lot of the people here who won't look at the data, the ACTUAL data, say about me. I simply don't care. Call me what you want but you won't make me feel badly, CAUSE I DON"T CARE WHAT YOU THINK ABOUT ME!

You twice acted as if I hadn't responded to your correct complaint about my excel picture. The first time I told you that I had already dealt with it. You didn't have the curiosity to even go look. Then you came out again acting as if I had never dealt with it (post 414) and gloated publically when you were clearly wrong.

This, Thau, says that 1. you don't really do research into the data. 2. you are someone who thinks that they can't possibly ever be wrong. 3. ignore data, and 4. thus aren't worth paying much attention to.

I dunno.

But I looked down a few posts and I sure didn't see where you had re-plotted all 30,000 data points.

All I see, and all I continue to see is your excuse as to why 100 data points were plotted instead of 30,000.

It is what happened. I don't give a rats rear end about what you think about it. I did plot them again in a wee bit different form than you did but I did plot them. Clearly you can't do thorough research and we are supposed to believe that you know what is true about global warming?

You have not acknowledged the IR plots that I posted.

You have not explained why the modern thermometers are reading the temperature too cold and thus are in need of an uplift in heat (other than in a self destructive way saying that the 1900 numbers can't be corrected because we don't know the error in them.). If we dont' know how accurate the 1900 numbers are, we can't possibly know if the world has warmed or not. If the 1900 values are too cold and actually need more heat, then the warming is reduced. Your illogic is nutso.

You don't show why, if the weather service itself says that class 5 stations have a +5 deg C error (or more) and if 8% of the stations are class 5 why that doesn't mean that the average of the raw data should be DROPPED by .4 deg C (.08 x 5 = .4), for mathematically that is what should happen. Yet, NOAA ADDS .3 deg C to the data inspite of the above problem.

You claim that the world is warming but you can't show me that the thermometers are measuring anything more than heat from sidewalks and buildings which radiate heat as high as 160 deg F (as seen in those ignored IR photos I posted). You, sir, ignore data that you don't like. You don't mention it, you don't deal with it. You ignore it, like you did my post on the excel error. And you want me to pat you on the back and tell you how good your science is. It is lousy.

This might make you feel bad. but you know something? Feeling bad is not necessarily a bad thing. When I put out that erroneous graph, I felt bad. What did I do?????? I corrected it. I admitted my mistake. Now I feel good. I am human but you appear to think you are not human and are congenitally incapable of error in either math or judgement.

I admit you did "cop" to the error. You also indicated you would address it. I didn't see it addressed since addressing an error is different from making an excuse about it.

The cop was the addressing of it. and I did post a plot of all the data. You, sir ignore it and are too lazy to go find it.

This is really simple. All you need to do is replot the data. Easy-peasy!

I did it. and I am NOT going to tell you the post. If you are incapable of finding it, then why should I spoon feed someone who claims to do good research?

I don't know how many times I have to answer this question but I'll answer it as I have with all the other times I've answered it: NO. Emphatically NO.

Well you will have to answer it until there is data that shows that you actually understand that this kind of crap invalidates the entire temperature collection system. As I have mathematically pointed out, if 8% of a sample have +5+ deg C bias, that will affect the average with a +0.4+ deg C bias in the final average. Yet, when we look at what NOAA does with the data by merely subtracting the raw data from the final edited data, which will reveal ONLY the average editing input to the temperature stream, we find that not only do they NOT remove this bias from the temperature stream, they ADD EVEN MORE BIAS TO IT BY NOT CORRECTING THERMOMETERS FROM 1900 AND ADDING AN ADDITIONAL 0.3 DEG C TO THE TEMPERATURE!!!!!

Until you realize the corrosive impact of this long stream of crappy thermometer siting, which the idiots at GISS seem not to care about for they do nothing to correct it, I will continue to ask this quesiton.

You think statistics is the end all and be all of everything in the unvierse. It isn't. That is also why I keep asking you to acknowledge that thermomters next to air conditioners won't give you the correct temperature and given unknown station movements, buildings built next thermometers at unknown times, new pavements etc, the entire enterprise is an exercise in self-deception--except for the religious folk like you.

A religion being defined as a beleif that observational data can't dislodge.

But then you have yet to provide statistical proof that these are the "norm" and not just more anecdotal data.

I keep showing you the math for the impact of 8% having a +5 deg C bias to the average and you keep ignoring it and writing things like the above. Of course, you ignored my replots of the data, you ignored my admission of error, you ignore this as well.

You see, that's why the Peterson paper was a joy to read. He not only explained his points but supported them with statistical robustness.

But who am I to make such a judgement? I could go with a statistical report by a member of the Nat'l Climate Data Center who appears to understand the importance of statistics to dealing with data, or I could go with the guy who doesn't understand the difference between a confidence interval and a standard deviation. Who would you go with?

I go with what I conclude after looking at the data. I have seen too many oil wells that too many people said was bad come in gushers and too many prospects that couldn't miss come in dry. Just because a scientist beleives something doesn't make it true.

Michael Shermer has something to say about this and it is something everyone needs to guard against.

"This surety is called the confirmation bias, whereby we seek and find confirmatory evidence in support of already existing beliefs and ignore or reinterpret disconfirmatory evidence. Now a functional magnetic resonance imaging (MRI) study shows where in the brain the confirmation bias arises and how it is unconscious and driven by emotions. Psychologist Drew Westen led the study, conducted at Emory University, and the team presented the results t the 2006 annual conference of the Society for Personality and social Psychology." Michael Shermer, The Political Brain, Scientific American July 2006, p. 36

Given that I am the one who actually changed my mind from believing in AGW to now NOT beleiving in AGW (but still believing that the world has warmed over the past 300 years).



So do investment gurus:
“Overconfidence may be due, at least in part, to an error known as self-attribution bias. This refers to investors’ tendency to ascribe any success they have picking stocks t their own insight and any disasters to bad luck. Persistent application of such a rule will lead an investor to the pleasing but inaccurate conclusion that he is a genius; put differently, he will become overconfident about his ability.” Nicholas Barberis, “Investors seek lessons in Thinking,” Financial Times, Monday June 18, 2001 Part 6, p. 2

“Once they have formed an opinion, people are often unwilling to change it, even when they receive pertinent new information. Suppose that, based on its past performance, investors have decided that company A ahs merely average long-term earnings prospects. Suddenly, A posts much higher earnings than expected. Conservatism predicts that investors will persist in their belief that the company is only average and will not react sufficiently to the good news.” .” Nicholas Barberis, “Investors seek lessons in Thinking,” Financial Times, Monday June 18, 2001 Part 6, p. 3

But Tetlock is the master at showing that experts can be wrong

"In one part of this study, Tetlock asked experts years ago to predict outcomes on seven different issues. In 1988, for example, he asked 38 Soviet experts whether the Communist Party would still be in power in 1993; and he asked 34 American political experts in 1992 whether President Bush would be re-elected later that year.
After the events occurred, Tetlock then re-contacted the experts to ask them about their predictions. In all seven scenarios, only slightly more than half of the experts correctly predicted the events that occurred. Still, even those who were wrong had been quite confident in their predictions. Experts who said they were 80 percent or more confident in their predictions were correct only 45 percent of the time.
Science Blog -- Even When Wrong, Political Experts Say They Were 'Almost Right'

"Psychology and Political Science at Ohio State University. Experts who said they were 80 percent confident in their predictions ended up being right only about half the time. And even when they were wrong, experts minimized their errors." Science Blog -- Even When Wrong, Political Experts Say They Were 'Almost Right'


“Tetlock then cranked all those numbers through every kind of statistical thresher, flail, and grinder you can imagine, and the result was clear: Experts don't actually exist. Specifically, experts were no better than nonexperts at predicting the future. They weren't even as good as computer programs that merely extrapolate the past. The best experts could not explain more than 20% of the variability in outcomes, but crude algorithms could explain 25% to 30%, and sophisticated algorithms could explain 47%. Consider what this means. On all sorts of questions you care about-Where will the Dow be in two years? Will the federal deficit balloon as baby-boomers retire?-your judgment is as good as the experts'. Not almost as good. Every bit as good.”
“Which is not to say that experts are no different from you and me. They're very different. For example, they're much more confident in their predictions than nonexperts are, though they obviously have no reason to be. For example, the members of the American Political Science Association predicted in August 2000 that a Gore victory was a slam dunk.” Geoffrey Colvin, “Ditch the ‘Experts’” Fortune, Feb 6, 2006, p. 44

Just plot the data and tell me what slope you get and what your R^2 was. (I'll even wait for you to find a machine with working Excel on it, or you can step up to the plate and do it in R, it's free.)

Just go find the post where I did that and discussed the low temperature problems. It is not up to me to spoon feed someone like you.

 

[grmorton]

Please stay as long as you like. It's an absolute joy seeing your "argument" getting trashed over and over again by thaumaturgy, who is obviously a much better scientist than you. I'm not a scientist, and I can see right through your "points", and I think I made that clear earlier. Now I've taken a step back to enjoy the carnage.

this from the guy who claimed that if you are unlikeable nothing you say can be true.

And I love the confluence of two strains of thought in the above. First you claim that you are not a scientist , but, then you claim that you have the expertise to see through my arguments. Now, earlier in this thread you said that one should believe the experts, and here you, after claiming no expertise are claiming the ability to understand and judge various scientific arguments.

What I love about the above is the sheer hubris and hypocrisy. YOu say I should listen to the experts, yet you, lacking scientific expertise, feel quite smug in your abilities to understand science. WOW. WHAT LUNACY!

But keep amusing me.

 

[Gracchus]

If you took the time to read and understand any posts in this thread, you would quickly realize that you don't, in fact, have to spend any time convincing anyone of that.

He has one argument. It has been pointed out to him that climatologists and meteorologists are aware of the problems of the sites he has pointed out. They aren't ignoring it. And even if a thermometer was wrong by ten degrees, it could still track trends.

If he would acknowlege that, he would have no argument. He wouldn't be smarter and more knowledgeable than the experts. Can't have that, can we?

 

[thaumaturgy]

Frankly, Thau, I gave up caring what you and a lot of the people here who won't look at the data, the ACTUAL data, say about me

Now you and I and everybody else here knows I have been looking at your data with as much focus as you.

The fact that I look at the data using statistics (which as I pointed out earlier, is apparently quite integral to the whole study of this data, as the Peterson article shows) and that I don't fall for the "anecdotal" freshman failures your analysis suffers from is hardly reason to mischaracterize what has occurred here, Glenn.

You twice acted as if I hadn't responded to your correct complaint about my excel picture.

No you indicated you would correct it, which you never have.

Here's what you said in Post #414:

But, I let that thing through so I will accept responsibility for it. It might take me a time or two to correct it but I always will.

(emphasis added)

You have so far not corrected it. You have made an excuse that Excel fooled you into thinking 100 data points looks like 30,000 data points, and you plotted a different type of graph altogether, and demanded to know how it matched up with other plots.

An excuse is hardly a correction. Taking responsibility is hardly the same as a "correction".

This, Thau, says that 1. you don't really do research into the data.

Glenn, everyone who is reading this thread knows that is pure and utter mischaracterization of what has occured.

2. you are someone who thinks that they can't possibly ever be wrong.

What is your game here Glenn? I don't know how many times on this thread alone I have said explicitly that I could be quite mistaken on the numbers I am crunching. All I ask is that you prove I am wrong.

Your mischaracterizations are bordering on the pathological here, Glenn.

It is what happened. I don't give a rats rear end about what you think about it. I did plot them again in a wee bit different form

A "wee bit different form"???

So what you are saying is: you couldn't prove your contention that the data align with a slope 0.8 so you plotted it a completely different way to make your point?

Sorry, Glenn, but you clearly claimed that the two stations only lined up with a slope of about 0.8. You were wrong. You even took responsibility for your error and you said you would "fix it", so you opted to plot something completely different????

Sorry, Trusty, I don't have much time for folks who can't even support their own contention without monkeying with the data.

When you "correct" an error you don't just try to find a different way to prove you were right all along. That is not a definition of correction.

You have not acknowledged the IR plots that I posted.

Actually I addressed the IR plot and urban warming in detail by reference to the Peterson article. But I recognize the Peterson article is a bit more "involved" science than you like. You like cartoon anecdotal science.

You have not explained why the modern thermometers are reading the temperature too cold and thus are in need of an uplift in heat

Actually, again, you are mistaken. I reference the Peterson 2003 article section d on instrumentation.

You are free to read it.

You don't show why, if the weather service itself says that class 5 stations have a +5 deg C error (or more) and if 8% of the stations are class 5 why that doesn't mean that the average of the raw data should be DROPPED by .4 deg C (.08 x 5 = .4), for mathematically that is what should happen. Yet, NOAA ADDS .3 deg C to the data inspite of the above problem.

I'm glad you brought this up. I just found an article from 1998 about homogenization and the rationalization behind it. LINK (I'm starting to read through it, it looks quite interesting.

Do you know what an "homogenous climate time series" is, Glenn? Let' me give you the definition from 1950 (long before the deviltry of Big-Global Warming Mafia started up full force)

A homogeneous climate time series is defined as one where variations are caused only by variations in weather and climate (Conrad and Pollak, 1950) (Source: Peterson 1998)

So waaay back in 1950 those nefarious bad guys were planning on how to hurt you and America 50 years later by planting the seeds of how to monkey with the data set!

But, wait! Do you know why homogenous data sets are NECESSARY?

Climate data can provide a great deal of information about the atmospheric environment that impacts almost all aspects of human endeavour. For example. these data have been used to determine where to build homes by calculating the return periods of large floods, whether the length of the frost-free growing season in a region is increasing or decreasing, and the potential variability in demand for heating fuels.(Peterson 1998)

(emphasis added)

Gosh, those things don't have any real-world impact do they? Nah, I bet it's mostly important so the bad climate scientist "cabal" can make more grant money off of your fears!

You claim that the world is warming but you can't show me that the thermometers are measuring anything more than heat from sidewalks and buildings which radiate heat as high as 160 deg F (as seen in those ignored IR photos I posted).

Ha ha ha! That's pretty funny. I actually read the Peterson 2003 article. Did you?

You, sir, ignore data that you don't like. You don't mention it, you don't deal with it.

And interstingly you have ignored the multiple times I've pointed out your howling errors on statistics (Post #513). Shall I keep bumping that post? Certainly by now the other posters on here are familiar with it. Perhaps they can point you to it again.

You ignore it, like you did my post on the excel error. And you want me to pat you on the back and tell you how good your science is. It is lousy.

I don't want a pat on the back from you. I would, however, like for you to stop mischaracterizing what has occured on this thread, though. That would be nice.

This might make you feel bad. but you know something? Feeling bad is not necessarily a bad thing. When I put out that erroneous graph, I felt bad. What did I do?????? I corrected it.

No, Glenn, you plotted a DIFFERENT THING. A correction would be a graph with Okmulgee on one axis and Okemah on the other. THIS IS THE GRAPH YOU (er Excel) MESSED UP.

Honestly, Trusty, if you think "correction" means finding another way to get around your mistake, then you and I have very different versions of "correction".

You think statistics is the end all and be all of everything in the unvierse.

Glenn, you are like a man who is afraid of hammers and you're going to try to build a house using only a bubble level.

Sorry, but when dealing with data, statistics wins every time.

People who don't rely on statistics to deal with data and noisy data especially, are doomed to failure. Or at least doomed to interpreting noise as signal.

Typical freshman error.

It isn't.

I suspect that is your opinion because the only thing you appear to know about stats is "average and standard deviation". Clearly you have a high school level of statistical knowledge. Which is A-OK except you are telling me the stats are wrong. (POST # 513) -- keep ignoring it as you like.

You couldn't even actually correct a XvsY plot to show the right data! You had to plot it in a completely unrelated and different way! Why is that, Trusty?

Gimme a break.

I go with what I conclude after looking at the data. I have seen too many oil wells that too many people said was bad come in gushers

And you know what, Glenn. I've been in industrial R&D as well as governmnetal and academic R&D now for quite some time and I'll tell you, I've seen plenty of folks who don't know statistics from a hole in the ground. And I've seen people make horrible errors because they interpretted noise as signal.

“Once they have formed an opinion, people are often unwilling to change it, even when they receive pertinent new information.

Do you know why people believe in quack medical cures? Because they don't understand statistics.

"Psychology and Political Science at Ohio State University. Experts who said they were 80 percent confident in their predictions ended up being right only about half the time. And even when they were wrong, experts minimized their errors." Science Blog -- Even When Wrong, Political Experts Say They Were 'Almost Right'

This is bordering on horrible logic. Just because someone thinks they are right does not ipso facto mean they are wrong.

Please, graph these statements out before you try to make a ridiculous point.

Specifically, experts were no better than nonexperts at predicting the future.

NOTE TO GLENN'S EMPLOYER: He freely admits you pay him for something an untrained joe off the street could do.

QED.

Just go find the post where I did that and discussed the low temperature problems. It is not up to me to spoon feed someone like you.

But, I let that thing through so I will accept responsibility for it. It might take me a time or two to correct it but I always will.

Again, QED.

(*unless your definition of "correction" means plot it in however different ways it will support your erroneous conclusion. In the present case you told me the data do not have a slope of about 0.95. And to prove it you never posted the correct data to show that.)

HINT: Here's the graph under discussion:

In order to make the claim my slope was wrong you would have to plot a graph with Okmulgee on the x-axis and Okemah on the-Y axis.

Here's the graph you posted in Post #414 (I assume this must be what you call a "correction")