"chemist" wrote in message
...
On Apr 5, 4:11 pm, Roger Coppock wrote:
To confirm what several other people posted,
the continental USA is warming faster than the rest of the globe.

According to the satellite Microwave Sounding Unit data
from Remote Sensing Systems, the globe from 82 degrees
North to 70 degrees South latitude warmed at 1.8 K per
century, while the continental USA warmed at 2.8K per
century. (RSS avoids a known problem MSU that occurs
when the microwave beam reflects off ice surfaces by
excluding the poles.)

Classic global warming theory from Arrhenius predicts
greater warming rates in dry areas like the American West
and heartland than more most regions.

These lower troposphere data come from the third and ninth
columns of:

http://www.remss.com/data/msu/monthl...onthly_MSU_AMS...

Though the continental USA is only about 1.5% of the globe's
area, there are more than enough data to support this statement.

=-=-=-=-=-=-=-=-=
Call:
lm(formula = LaN825S700 ~ YEARMON)

Residuals:
Min 1Q Median 3Q Max
-0.41589 -0.11629 -0.00948 0.10907 0.73922

Coefficients:
Estimate Std. Error t value Pr(|t|)
(Intercept) -35.1291 2.2028 -15.9 2e-16 ***
YEARMON 0.0177 0.0011 16.0 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.175 on 349 degrees of freedom
Multiple R-Squared: 0.423, Adjusted R-squared: 0.421
F-statistic: 255 on 1 and 349 DF, p-value: 2e-16

- - - -

fitted.model - lm(ContUSA ~ YEARMON)
summary(fitted.model)

Call:
lm(formula = ContUSA ~ YEARMON)

Residuals:
Min 1Q Median 3Q Max
-3.0723 -0.4895 0.0287 0.5624 2.2018

Coefficients:
Estimate Std. Error t value Pr(|t|)
(Intercept) -55.26373 10.64006 -5.19 3.5e-07 ***
YEARMON 0.02779 0.00534 5.21 3.3e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.844 on 349 degrees of freedom
Multiple R-Squared: 0.0721, Adjusted R-squared: 0.0694
F-statistic: 27.1 on 1 and 349 DF, p-value: 3.29e-07

The temperatures are highly suspect Google "Watts Up"

http://wattsupwiththat.wordpress.com...ment-with-uah/
Feb 2008 RSS global temperature anomaly near zero and in good agreement with UAH
Last week I posted the University of Alabama, Huntsville (UAH) Microwave Sounder Unit
(MSU) global temperature anomaly data for February 2008 with a note that it showed only a
marginal increase from January 2008 data, and remained near zero.

The February 2008 global temperature anomaly data from RSS (Remote Sensing Systems of
Santa Rosa, CA) is out, and is in good agreement with that. You can see it the raw RSS
data yourself here

First here is UAH satellite derived temperature anomaly. For February 2008, it shows a
slight rebound from the -0.046°C value of January 2008 to 0.016°C for a slight change (?T)
of .062°C upwards.

or:

http://wattsupwiththat.wordpress.com...etrics-part-2/
A look at temperature anomalies for all 4 global metrics: Part 2
NOTE: This article was to be followed by a part 3, which has not been completed yet due
to my attention being turned to other more important work. I will revisit this series at a
future date. - Anthony

Before I left on my trip to New York, I published part 1 of this series looking at the
temperature anomalies between the 4 global temperature metrics from 1979-January 2008. The
first post I made on the subject used the unadjusted global temperature anomaly data to do
the comparisons. I also wanted to do the same comparisons using anomaly data adjusted to a
common reference baseline. But unfortunately ran out of time to complete all of the
histograms for the next data set before I left on the trip.

In the meantime, while I was traveling, the first post, missing the all important part 2,
generated some controversy, and some accusations that I was misrepresenting the data by
not showing it adjusted to a common baseline.

It was a mistake on my part to not have them both available at the same time, and for that
I apologize to anyone whom was misled by the lack of part2. Atmoz did a quick study of the
issue also and illustrated what I wanted to do for part2 with a simple graph, and while it
would have been easy to simply use his, I wanted to complete what I started using the same
presentation style. Recognizing that having part1 only was misleading to some, I put part
1 back on the shelf until I could return from my trip and finish part 2, so that I could
show what happens when all four metrics are adjusted to the same base period.

That is complete, the Part1 article has been restored, and below is the new adjusted
information as it compares to part1.

Here is the first graph, the unadjusted raw anomaly data as it was published in February
by the four metrics from UAH, RSS, GISS and HadCRUT. Note that while there is pattern
agreement to the 4 metrics, there is an amplitude difference.



Here is the source data file for this plot and subsequent unadjusted plots.
4metrics_temp_anomalies.txt

Here is the same data, but adjusted to a reference period of 1979-1990:

Click for a larger image

Here is the data used: 4metrics_temp_anomalies_refto1979-1990.txt


Now we can see that the agreement of the 4 metrics is better using the data adjusted to a
common baseline period.


The difference between these metrics is of course the source data, but more importantly,
two are measured by satellite (UAH, RSS) and two are land-ocean surface temperature
measurements (GISS, HadCRUT).

One of the first comments from my post on the 4 global temperature metrics came from Jeff
in Seattle who said:

Seems like GISS is the odd man out and should be discarded as an "adjustment".

That is no longer the case once the adjusted data is presented. The trend and amplitude
agreements are very good with all four metrics.

In my previous post on this in part 1 I mentioned I had never seen a histogram comparison
done on all four data-sets simultaneously. The first set of histograms showed a wide
disagreement, particularly in the land-ocean metrics from HadCRUT and GISS.