RSS Satellite Data Clearly Show A Warming Global Climate

Analysis of satellite surface temperature proxy data
from Remote Sensing Systems shows a warming global
climate over the last 30 years and 7 months.

For background on the satellite temperature proxy please see:

http://en.wikipedia.org/wiki/Satelli...e_measurements

The Remote Sensing Systems Lower Troposphere (TLT) analysis
shows a 0.015+-0.001K/Year rise over the land and sea.

http://www.remss.com/data/msu/monthl...cean_v03_2.txt

The data from 82.5N to 70S are graphed he

http://members.cox.net/rcoppock/RSS-MSU.jpg

The regression statistics for the line in the graph above
are below.

Coefficients:
Estimate Std. Error t value Pr(|t|)
(Intercept) -30.38442 2.02506 -15.0 2e-16
YEARMON 0.01528 0.00102 15.1 3.8e-40

Residual standard error: 0.172 on 365 degrees of freedom
Multiple R-Squared: 0.38
F-statistic: 226 on 1 and 365 DF, p-value: 3.8e-40

=-=-=-=-=-=-=

In the real world,
outside the fossil fuel industry's spin and lies,
global mean surface temperatures continue to rise.
Please see:

http://www.metoffice.gov.uk/corporat...20080923c.html

On Aug 5, 7:16*am, Roger Coppock wrote:

More crap from an alarmist Kook site.

Bruce Richmond wrote:
On Aug 5, 7:16 am, Roger Coppock wrote:

More crap from an alarmist Kook site.

What you mean is, you can't refute a word of it - not one.

On Aug 5, 10:23*am, "Ouroboros Rex" wrote:
Bruce Richmond wrote:
On Aug 5, 7:16 am, Roger Coppock wrote:

More crap from an alarmist Kook site.

* What you mean is, you can't refute a word of it - not one.

No, what I mean is I can write the same thing you do and provide the
same justification. Or is your complaint about the way it is
presented. I should have called it a "lying k00ksite" like you do.

Bruce Richmond wrote:
On Aug 5, 10:23 am, "Ouroboros Rex" wrote:
Bruce Richmond wrote:
On Aug 5, 7:16 am, Roger Coppock wrote:

More crap from an alarmist Kook site.

What you mean is, you can't refute a word of it - not one.

No, what I mean is I can write the same thing you do and provide the
same justification. Or is your complaint about the way it is
presented. I should have called it a "lying k00ksite" like you do.

Baseless bull**** is baseless bull****. What you mean is, you can't
refute a word of it - not one.

On Aug 6, 10:45*am, "Ouroboros Rex" wrote:
Bruce Richmond wrote:
On Aug 5, 10:23 am, "Ouroboros Rex" wrote:
Bruce Richmond wrote:
On Aug 5, 7:16 am, Roger Coppock wrote:

More crap from an alarmist Kook site.

What you mean is, you can't refute a word of it - not one.

No, what I mean is I can write the same thing you do and provide the
same justification. *Or is your complaint about the way it is
presented. *I should have called it a "lying k00ksite" like you do.

* Baseless bull**** is baseless bull****. *What you mean is, you can't
refute a word of it - not one.

I will keep that in mind, and remind you of it the next time you make
one of your "lying k00ksite" posts. It works both ways.

Another fantasy from Coppock using Wikipedia, the Met office and his own
numbers and graphs as validation. LOL


Roger Coppock wrote:
RSS Satellite Data Clearly Show A Warming Global Climate

Analysis of satellite surface temperature proxy data
from Remote Sensing Systems shows a warming global
climate over the last 30 years and 7 months.

For background on the satellite temperature proxy please see:

http://en.wikipedia.org/wiki/Satelli...e_measurements

The Remote Sensing Systems Lower Troposphere (TLT) analysis
shows a 0.015+-0.001K/Year rise over the land and sea.

http://www.remss.com/data/msu/monthl...cean_v03_2.txt

The data from 82.5N to 70S are graphed he

http://members.cox.net/rcoppock/RSS-MSU.jpg

The regression statistics for the line in the graph above
are below.

Coefficients:
Estimate Std. Error t value Pr(|t|)
(Intercept) -30.38442 2.02506 -15.0 2e-16
YEARMON 0.01528 0.00102 15.1 3.8e-40

Residual standard error: 0.172 on 365 degrees of freedom
Multiple R-Squared: 0.38
F-statistic: 226 on 1 and 365 DF, p-value: 3.8e-40

=-=-=-=-=-=-=

In the real world,
outside the fossil fuel industry's spin and lies,
global mean surface temperatures continue to rise.
Please see:

http://www.metoffice.gov.uk/corporat...20080923c.html

On Wed, 5 Aug 2009 04:16:30 -0700 (PDT), Roger Coppock
wrote:

RSS Satellite Data Clearly Show A Warming Global Climate

Analysis of satellite surface temperature proxy data
from Remote Sensing Systems shows a warming global
climate over the last 30 years and 7 months.

For background on the satellite temperature proxy please see:

http://en.wikipedia.org/wiki/Satelli...e_measurements

The Remote Sensing Systems Lower Troposphere (TLT) analysis
shows a 0.015+-0.001K/Year rise over the land and sea.

http://www.remss.com/data/msu/monthl...cean_v03_2.txt

The data from 82.5N to 70S are graphed he

http://members.cox.net/rcoppock/RSS-MSU.jpg

The regression statistics for the line in the graph above
are below.

Coefficients:
Estimate Std. Error t value Pr(|t|)
(Intercept) -30.38442 2.02506 -15.0 2e-16
YEARMON 0.01528 0.00102 15.1 3.8e-40

Residual standard error: 0.172 on 365 degrees of freedom
Multiple R-Squared: 0.38
F-statistic: 226 on 1 and 365 DF, p-value: 3.8e-40

=-=-=-=-=-=-=

In the real world,
outside the fossil fuel industry's spin and lies,
global mean surface temperatures continue to rise.
Please see:

http://www.metoffice.gov.uk/corporat...20080923c.html

Where is the nines, woger?

Its so hot, I'm freezing,

Its so hot, I'm sneezing,

Its so hot, I'm Wheezing,

And its getting hotter all the time.

On Wed, 05 Aug 2009 04:16:30 -0700, Roger Coppock wrote:

RSS Satellite Data Clearly Show A Warming Global Climate
[...]
Coefficients:
Estimate Std. Error t value Pr(|t|)
(Intercept) -30.38442 2.02506 -15.0 2e-16
YEARMON 0.01528 0.00102 15.1 3.8e-40

Residual standard error: 0.172 on 365 degrees of freedom
Multiple R-Squared: 0.38
F-statistic: 226 on 1 and 365 DF, p-value: 3.8e-40

Why those much discussed trendlines are probably insignificant
--------------------------------------------------------------

Data sources:
-------------
UAH:
http://vortex.nsstc.uah.edu/public/m.../tltglhmam_5.2
RSS:
ftp://ftp.ssmi.com/msu/monthly_time_...cean_v03_2.txt

Regression:
-----------
UAH y = 0.01268 * x + -25.21167 ; r² = 0.26293 ; sd = 0.18073 ;
n1 = 68.08 ; n2 = 95.20

RSS y = 0.01528 * x + -30.38425 ; r² = 0.38279 ; sd = 0.17127 ;
n1 = 71.66 ; n2 = 94.82

Variables:
----------
x: the month (as a number, 2009.0 is January 2009, 2009.5 is July 2009,
half a year later)

y: expected value for month x (i.e. what the trendline says)

r²: correlation between time line and observed values (1 = perfect, 0 =
no correlation at all)

sd: standard deviation (calculated from the difference between observed
and expected values)

n1: percentage of values within plus/minus one standard deviation

n2: same for two standard deviations

The point is:
-------------
In theory, n2 is 95 percent, if the observed values are completely random
(no correlation, no causation, no real connection).

As the n2 values are in fact still near 95 percent, we still are on the
edge of pure noise. Or, maybe, the whole idea of a linear trend is just
not what's going on in the real world.

Joern

On Aug 5, 12:36*pm, Joern Abatz wrote:
On Wed, 05 Aug 2009 04:16:30 -0700, Roger Coppock wrote:
RSS Satellite Data Clearly Show A Warming Global Climate
[...]
Coefficients:
* * * * * * *Estimate Std. Error t value Pr(|t|)
(Intercept) -30.38442 * *2.02506 * -15.0 * 2e-16
YEARMON * * * 0.01528 * *0.00102 * *15.1 * 3.8e-40

Residual standard error: 0.172 on 365 degrees of freedom
Multiple R-Squared: 0.38
F-statistic: *226 on 1 and 365 DF, *p-value: 3.8e-40

Why those much discussed trendlines are probably insignificant
--------------------------------------------------------------

Data sources:
-------------
UAH:http://vortex.nsstc.uah.edu/public/m.../tltglhmam_5.2
RSS:ftp://ftp.ssmi.com/msu/monthly_time_...msu_amsu_chann....

Regression:
-----------
UAH y = *0.01268 * x + -25.21167 ; r² = *0.26293 ; sd = *0.18073 ;
* * n1 = 68.08 ; n2 = 95.20

RSS y = *0.01528 * x + -30.38425 ; r² = 0.38279 ; sd = *0.17127 ;
* * n1 = 71.66 ; n2 = 94.82

Variables:
----------
x: the month (as a number, 2009.0 is January 2009, 2009.5 is July 2009,
* *half a year later)

y: expected value for month x (i.e. what the trendline says)

r²: correlation between time line and observed values (1 = perfect, 0 =
* * no correlation at all)

sd: standard deviation (calculated from the difference between observed
* * and expected values)

n1: percentage of values within plus/minus one standard deviation

n2: same for two standard deviations

The point is:
-------------
In theory, n2 is 95 percent, if the observed values are completely random
(no correlation, no causation, no real connection).

As the n2 values are in fact still near 95 percent, we still are on the
edge of pure noise. Or, maybe, the whole idea of a linear trend is just
not what's going on in the real world.

Joern

Gee you're a good spin doctor, Joern!
Someone without any training in statistics
might think you found something wrong.
These data show a warming trend, PERIOD.