Climate Gate, Getting deeper into the Detail (again I have no idea why I did not post this) MAy 29 2011

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I have been looking through the climate Gate stuff on the web with a little help from Wikileaks and
the clues provided are allowing me to reference the sort of detail one needs to look at the drive to parameter setting in modelling. Taleb is very much into statistical bias built into first principles in the Money Markets
Just Google Anti-Fragility.

I have all of these coding files so I googled one of the main code references and happily have found that someone has already started piecing together the Jigsaw. My first task then is to read through their notes.
I am doing this blog Highlighting key passages.
The first here is to do with Cloud and sun date which seems to be an anomaly. I am noting it as I am aware of two important pieces of work at least on Solar Magnetism and sunspot activity and also solar rays and Cloud formation. Cloud formation and Solar activity are very important, that there should be an anomaly is
So, to me this identifies it as the program we cannot use any more because
the coefficients were lost. As it says in the gridding read_me:

Bear in mind that there is no working synthetic method for cloud, because Mark New
lost the coefficients file and never found it again (despite searching on tape
archives at UEA) and never recreated it. This hasn’t mattered too much, because
the synthetic cloud grids had not been discarded for 1901-95, and after 1995
sunshine data is used instead of cloud data anyway.

But, (Lord how many times have I used ‘however’ or ‘but’ in this file?!!), when
you look in the program you find that the coefficient files are called:
Just jumping to a more general site also reading I’m going to jump back to the other one of a quick scan of this more general overview.;wap2

this statement suggests a very analytical approach to me , and I like that.While I like Tim’s work and he has a good careful style, it is clear he is working inside constraints set by others “in the literature” and these include some degree of “synthetic” data… (But don’t worry if you lost some of the method, it’s only used some of the time anyway… in other years you can use other synthetic data…)

AGREED APPROACH for cloud (5 Oct 06).

For 1901 to 1995 – stay with published data. No clear way to replicate
process as undocumented.

For 1996 to 2002:
1. convert sun database to pseudo-cloud using the f77 programs;
2. anomalise wrt 96-00 with anomdtb.f;
3. grid using (which will use 6190 norms);
4. calculate (mean9600 – mean6190) for monthly grids, using the
published cru_ts_2.0 cloud data;
5. add to gridded data from step 3.

This should approximate the correction needed.

From another forum this stff has been looked at in great depth this is a comment that strikes me as very succinct. A part quote of a long COmment on a long article.

climate data-set nature purpose
CL (climatology) The average climate in the recent past. These are high-resolution grids. Allows spatial comparisons of environmental features; the dependency of certain features on climate may be assessed.
TS (time-series) Month-by-month variations in climate over the last century or so. These are high-resolution grids. Allows the comparison of variations in climate with variations in other phenomena.
SC (scenarios) A set of scenarios of possible climates in the future, using data from climate models. These are high-resolution grids. Allows environmental impact models to consider month-by-month changes in climate from the past, through the present, and into the future. Future uncertainties are represented through scenarios.
CY (countries) Country averages, based on aggregating grid cells together from the grids in CL, TS, or SC. Allows international comparisons to be made, in conjunction with socio-economic data such as GDP, population, land area, etc.
Variable abbreviations
label variable units
cld cloud cover percentage
dtr diurnal temperature range degrees Celsius
frs frost day frequency days
pre precipitation millimetres
rhm relative humidity percentage
ssh sunshine duration hours
tmp daily mean temperature degrees Celsius
vap vapour pressure hecta-Pascals
wet wet day frequency days
wnd wind speed metres per second
When scientists submt papers to proper academic journals they are supposed to write up enough methodology so that someone else can replicate their results. In theory at least. In practice in much of modern science this is not adhered to, but in theory – as Feynman explained in “Cargo-cult Science” – what you should do is the following:
Details that could throw doubt on your interpretation must be given, if you know them. You must do the best you can–if you know anything at all wrong, or possibly wrong–to explain it. If you make a theory, for example, and advertise it, or put it out, then you must also put down all the facts that disagree with it, as well as those that agree with it. There is also a more subtle problem. When you have put a lot of ideas together to make an elaborate theory, you want to make sure, when explaining what it fits, that those things it fits are not just the things that gave you the idea for the theory; but that the finished theory makes something else come out right, in addition.
In summary, the idea is to try to give all of the information to help others to judge the value of your contribution; not just the information that leads to judgment in one particular direction or another.
The easiest way to explain this idea is to contrast it, for example, with advertising. Last night I heard that Wesson oil doesn’t soak through food. Well, that’s true. It’s not dishonest; but the thing I’m talking about is not just a matter of not being dishonest, it’s a matter of scientific integrity, which is another level. The fact that should be added to that advertising statement is that no oils soak through food, if operated at a certain temperature. If operated at another temperature, they all will– including Wesson oil. So it’s the implication which has been conveyed, not the fact, which is true, and the difference is what we have to deal with.
We’ve learned from experience that the truth will come out. Other experimenters will repeat your experiment and find out whether you were wrong or right. Nature’s phenomena will agree or they’ll disagree with your theory. And, although you may gain some temporary fame and excitement, you will not gain a good reputation as a scientist if you haven’t tried to be very careful in this kind of work. And it’s this type of integrity, this kind of care not to fool yourself, that is missing to a large extent in much of the research in cargo cult science.
Above quote taken from here.\

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