On Apr 10, 8:20 pm, "Paul E. Lehmann" wrote:
John M. wrote:
On Apr 10, 1:43 pm, "Paul E. Lehmann"
wrote:
Bill Ward wrote:
On Wed, 09 Apr 2008 13:12:25 -0700, Roger
Coppock wrote:

On Apr 9, 8:34 am, Bill Ward
wrote:
On Wed, 09 Apr 2008 07:04:24 -0700,
matt_sykes wrote:
On 9 Apr, 10:24, Roger Coppock
wrote:
On Apr 8, 8:01 pm, Poetic Justice
-n-

Dog.com wrote:
Roger Coppock wrote:
March ties for 3rd warmest on NASA's
129-year record.

Why is NASA the official keeper of the
temperature?

NASA Goddard Institute for Space Studies
offers data, as do several other
organizations. I use NASA's data
because GISS corrects for UHI using
nighttime earth shine, artificial
lighting, measured from satellites.
IMHO, this method is better than using
census data to locate urban areas.

That is a feeble way to adjust for UHI.

The ONLY way to adjust for UHI is to put
a station in a rural area near to the
urban
station to act as a control (being a
sicnetist you wold know this of course).

Mind you, one you have done that you
might as well ignore the urban station
data since rural data is true surface
temp.

And what happens when you do that? You
get
no warming trend. RURAL STATIONS ACROSS
THE GLOBE SHOW NO OVERALL TEMPERATURE
TREND.

Roger can't comprehend that bad data is
worse
than no data. Unless you're trying to
scare people, of course.

If you have better data, or a method for UHI
correction, you are more than
welcome to present them here. Until then
the data presented above are a better
indication of reality than your fantasies.

Fantasies aren't science, whether they're
mine
or NASA's. That's
the problem with trying to "correct" bad
data. If it's bad, it can't be
used - it's a fantasy based on invalid
assumptions. Averaging bad data with with
good data hides the problem, but doesn't fix
it.

It is even worse than that. I suspect there is
an
analogy with wine making. I knew of a
winemaker who had a small amount of wine made
from under
ripe grapes. He blended it (10%) with some
good
wine 90%). That small amount ruined the whole
lot. A "Little BAD Goes a LONG ways". I
suspect
the same is true of data. A little bad or
incorrect can have effects that are way beyond
suspected results.

Such are the musings of a statistical
illiterate. In actual practice, the way to avoid
problems from extraneous or erroneous data (ie.
bad) is to swamp it by using large sample sizes.
If you measure the height of 100 men taken at
random, the mean height will be virtually
unchanged should one or two of them be giants or
dwarves.

This is what happens in practice with
temperature data. Very large sample size ensures
that the famous UHIs will have little effect on
the calculated global means.

made a lot of money in the stock market, have you?

Why, yes, as matter of fact. It isn't particularly difficult to do.
Why do you ask?