On Apr 11, 9:15 pm, Bill Ward wrote:
On Thu, 10 Apr 2008 11:14:20 -0700, 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.

Only if you can prove the assumption that all errors are symmetrically
distributed. Otherwise it's a fantasy. Or a hoax.

Ah. Another statistical illiterate crawls from the woodwork, to give
us his take on something he knows little or nothing about.

The manner in which the residuals are distributed is immaterial. It is
merely required that their distribution remains the same in repeat
samples.