If the homogeneized data are what Hansen and others use to build the global warming theory upon, then why shouldn’t I be looking at the same data to see if there’s a warming bias?

And indeed, the data that are used by Hansen and others show no warming bias in Marysville vs. Orland.

“But the issue of station siting remains.”

That’s backpedalling.

REPLY: No, its a basis, and it is reality. Look I get it, you don’t like me or any of the work I do and your mission is to discredit anything I say or do at any cost. So it wouldn’t really matter what I said or published. But, I’m hoping there is a reasonable person behind the affrontery you present, so I’ll try one more time.

You made a basic mistake, (even though you won’t admit it) and plotted homogenized data for two stations, making no point at all. So plot the raw data to actually show the differences (or sameness) between the stations which is the issue you raised. The issue has been and continues to be lack of siting compliance. Those differences (or sameness) at the scale we are working with, will show up in raw data, not homogenized data.

Plotting homogenized data between two stations is like trying to discern two shades of grey in resultant paint mixed from two cans each of black and white (hi and lo temp) and trying to determine what the component paint pigmentation levels were originally…you can’t, because GISS homogenization has mixed the starting four cans of paint, with other cans of paint within 250 kilometers. You won’t be able to tell if the four starting component paints before mixing were truly black, truly white, or something in between.

While that may not be a perfect analogy, it serves to illustrate the need to plot data that have not been homogenized in order to show the differences in the measurements at each site. The GISS homogenization routine is a regional smoothing routine, 250km. It’s not for small scale site to site comparisons.

I’ve been thinking about your block-out treatment of Mr. Goetz on your own website. Thus, it is clear that your agenda is to discredit, not to truly discuss or to carefully investigate. Otherwise, your response would be different.

You are welcome to come back when you get it right, and apply some fairness to commenters like Mr. Goetz. Thank you for your consideration. -Anthony

I noticed that with Petersons presentation. His point is that a bad station resembles a neighboring good station after homoginization but fails to mention that both stations were homoginized by averaging all of the local stations, what kind of a putz would think we cant figure that one out.

I explained to science dude about how OC California warms and cools with the PDO, I even pointed out specific points on his graph to demonstrate, he responded by saying that my comment “grossly mistated” Hartman / Wendler. Hartman Wendler was a study about Alaska, not California. The “Dude” simply threw out a scientific cite without even reading the paper, the abstract, or the title.

“What specific datasets did you use?”

Fair question. I’m using data sets that I wrote about before — that is, temperature records after homogeneity adjustments — and I’m uploading them.

“then block the responses from people you name?”

I have the right to block knee-jerk reactions and anything I deem to be dumb.

But whatever excuse to ignore the lack of warming bias, I suppose.

REPLY: OK I was pretty sure you plotted homogenized data, (the key is the “data_set=2″ in the links to GISS) but I had to ask to be totally sure. The point of which shows that all you’ve done is plotted data that has been “homogenized”, so no wonder they look alike, with diminished differences.

From Wiki:

Homogenization (or homogenisation) is a term used in many fields such as chemistry, agricultural science, food technology, sociology and cell biology. Homogenization is a term connoting a process that makes a mixture the same throughout the entire substance.

So, you’ve plotted data that’s been homogenized within a radius, using data trends within that radius, and you’ve found the differences data trend from two stations from the homogenized data set to have a slight cooling trend. Note that that data doesn’t represent JUST Marysville and Orland, it has quite a number of station data in the region mixed in. Some stations in the nearby Sierra Nevada (also within the GISS homogenization radius) have in fact cooled. To better understand the issue see this post:

http://wattsupwiththat.wordpress.com/2008/07/18/cedarville-sausage/

So it is no surprise in what you found. It also doesn’t prove your point because you are plotting data that is a mix of stations within the GISS homogenization radius. Try the raw data from NCDC, direct from the thermometers, without ANY adjustments or homogenizations from GISS, then you’ll actually be doing something that could show a difference between the stations that isn’t “homogenized” or adjusted. When you get that actual untouched raw data, please link to it.

But the issue of station siting remains. By NOAA and WMO standards, one station is sited poorly, one is not. When we get the significant majority of USHCN stations surveyed, then we’ll be able to answer the question for the entire dataset, which is what really is the most interesting and relevant issue.

It is unfortunate that you choose to block Mr. Goetz response, that demonstrates a lack of tolerance for differing views, such as we see regularly at RealClimate.

“What specific datasets did you use?”

Fair question. I’m using data sets that I wrote about before — that is, temperature records after homogeneity adjustments — and I’m uploading them.

“then block the responses from people you name?”

I have the right to block knee-jerk reactions and anything I deem to be dumb.

REPLY: You double posted this for some reason, see reply in other identical comment

Does this so-called “Urban Heat Island” effect cause a warming “bias” in Marysville, Watts’s poster child of ‘bad’ surface stations, as compared to Orland the ‘good’ station?

And the answer is no. There simply is no warming bias in Marysville as compared to Orland.

I repeat: There simply is no warming bias in Marysville as compared to Orland.

But I’m sure all the open-minded Galileo-like skeptics here will try to ignore or downplay this fact.

– bi, International Journal of Inactivism

REPLY: You neglect, as far as I can tell, in reporting something very basic. What specific datasets did you use? Citation with links to the datasets you used please.

And please explain why you won’t allow Mr. Goetz to post a response to this on your own blog. That hardly seems fair. You accuse him of “blowing smoke” yet delete his response to you as shown below:

frankbi said, on August 13th, 2008 at 03:07
(John Goetz: It’s clear you didn’t read this post before complaining that I wasn’t reading your post. That’s uncool, don’t you know?)

You appear to want discussion, and advertise for it here, but then block the responses from people you name? My goodness how convoluted that logic is.

I won’t bother commenting on your website if that’s the way you play.

Global warming is supposed to be exponentially occuring with the fastest rate in the past 2 decades … Santa Ana’s temperature record does not support this.

My earlier post was entended as humor. I’m glad that NOAA is at least taking stations like this out of service. Anyone who has calked their house knows the roof is something you work on on cloudy days or in the shade. With all the stations surveyed that show problems this station takes the cake.

More to the point, the AGW (CO2) crowd supports the ground station data by saying that Hansen has an “adjustment” that takes this and other such stations into account. Do we know what that is, and has it been checked by “Peer review”.

During an earlier life in radio, I had to go out into the field behind the studio to check the max and min in the “weather station”. I remember grumbling on those snowy days as I trudged out to reset the little magnetic wires in the tubes. That station was one of your 1 degree’ers. At least the farmers in Pullman, Washington had good data to go from at that time (late 60′s early 70′s).

I detect a bit of pique in your response, and it was intended as humor. Like some of the videos on television you have to wonder about things like this…

WHAT WERE THEY THINKING!!!!

Sorry if I upped your bloodpressure.