I don't think there is much doubt that there has been a
shift in mean. The question is what has chiefly contributed to it and/or did we
have a similar shift in medieval times where we don't have significant data
accurate to make a proper scientific judgement and comparison. Tree ring data
may provide the answer but this has not yet been made widely available by those
who have it. Clearly, we need to know.



Dr. Ed Goodall,

Centre for Statistics and Operational Research,

Department of Maths and Physics,

The Queen's University of Belfast,

N. Ireland











> Date: Mon, 7 Dec 2009 12:04:59 -0500
> From: [log in to unmask]
> Subject: Re: Analysis of temperature on Earth
> To: [log in to unmask]
> 
> 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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