I am a statistician and have specialized in time series analysis for a
number of years. I have often been "too busy" to participate in these kind
of dialogues. Perhaps it is time that I got "unbusy" and deliver some time
series expertise to the subject at hand. Let me state up front that I am
totally untrained with respect to the relevant underlying meteorological
"causes" for this data and simply stated "I walk (talk) where angels fear to
tread".
I thank others for pointing me to the raw data, 372 months (starting
1978/12) of 25 measurements of warming phenomena.
Using 372 monthly values of a single time series to draw inference can be
flawed for a number of reasons:
1. The time span is too short to capture longer cycles which might
explain some of the level shifts that are discussed below.
2. Using a single series to analyze/predict the future is analogous to
a car driver using the rear window to forecast future road conditions.
Tricky business indeed. Single series analysis(ARIMA) suggests somewhat
naively that the past causes the future while causal models (Transfer
Functions) embody the impact of user-suggested supporting variables. I did
not have access to possible causal series data and if any reader can help in
this regard, I would be willing to incorporate them and report back to the
list.
3. Analysts and most software packages often confuse trend with level
shifts. Level shifts and trends are both intercept changes but reflect
totally different impacts. It is necessary to clearly make this distinction.
Commentary like " This is not my area of expertise, but if you look at
the very informative graphs provided, there does seem to be a trend -
specifically - before 1995 the global temperatures are lower, and after 1995
they seem to be higher." Are descriptive in nature and often lead to
spurious conclusions as a before and after analysis/conclusion is not proof
of a trend but rather a statement of "mean shift".
I have analyzed the data and placed the results/graphs/reports on our web
site at http://www.autobox.com/warm.zip . The graphs and analyses clearly
suggest strong seasonal structure. The conclusions are (among others) that
approximately half the measures suggest a statistical level shift at or
about the beginning of 1998. These are Level or Step shifts not trends. The
csv files in the referenced URL support this conclusion.
I hope this helps our greater understanding of this data and I look forward
to comments on this work.
Dave Reilly
Automatic Forecasting Systems
http://www.autobox.com
Dave Reilly
Senior Vice President
Automatic Forecasting Systems
www.autobox.com
215-675-0652 (office)
215-353-7087 (cell)
-----Original Message-----
From: A UK-based worldwide e-mail broadcast system mailing list
[mailto:[log in to unmask]] On Behalf Of John McKellar
Sent: Monday, December 07, 2009 7:18 AM
To: [log in to unmask]
Subject: Re: Analysis of temperature on Earth
Dear AllStat,
Professor Zhigljavsky raises some valid concerns - though I suspect he's
fallen into the same error as everyone else of analysing inferior data.
The problem is inferior to what and how do we access sufficient data? Are
the ice cores from the arctic or Antarctic not pretty definitive?
Then, in such a complex model; there are bound to be many ways to analyse it
(under different assumptions); we need the results to be consistent to build
confidence.
Is there anyone on the list who feels able to comment on the statistical
analyses used in the climate debate?
As for the East Anglia debacle, where (depending on how you discuss it)
scientists hid data, changed data or questioned its usefulness. I'll never
describe transforming my data as "a trick" again!
Regards
John
-----Original Message-----
From: A UK-based worldwide e-mail broadcast system mailing list
[mailto:[log in to unmask]] On Behalf Of Kwaku Damoah
Sent: Monday, December 07, 2009 10:52 AM
To: [log in to unmask]
Subject: Re: Analysis of temperature on Earth
Dear Allstat,
Global warming is a phenomenon which is forecast over a long period of time
and as such more data is needed to be able to justify this conclusion, I
guess data over different sub-regions/continents for a period spanning not
less than 100 years is needed.
Kwaku Damoah
-----Original Message-----
From: A UK-based worldwide e-mail broadcast system mailing list
[mailto:[log in to unmask]] On Behalf Of Anatoly Zhigljavsky
Sent: 07 December 2009 09:45
To: [log in to unmask]
Subject: Analysis of temperature on Earth
Dear allstat fellows,
I though some of you might be interested in what I have done after I got
tired of listening about Global Warming and ClimatGate.
I decided to check the data myself. The result is the following website:
http://www.cf.ac.uk/maths/subsites/zhigljavskyaa/climatechange/
I did not find any signs of the Global Warming!
Sorry, the statistical part in my short report is poor (this report is not
for professional statisticians!)
Any comments?
Anatoly Zhigljavsky, Professor
Chair in Statistics
School of Mathematics
Cardiff University
CF24 4AG
Cardiff, UK
Tel. +44(0)2029875076
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