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Archive for the 'global climate change' Category

Apr4

Accounting For ENSO: Cochrane Orcutt

Issues and Resolutions:
My recent falsification of the IPCC AR4 projection of 2C/century was criticized as flawed because:

It did not properly account for ENSO.
Cochrane-Orcutt, and its uncertainty bands apply only when the noise is AR(1).

I have addressed both issues (details below), and find the falsification still holds. It is important to note that this falsification [...]

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Filed in: global climate change

Apr2

Roger Pielke Jrs’ letter: The modest proposal.

Nature Geoscience published a letter to the editor by Roger Pielke Jr.; the title is Climate predictions and observations. In his letter, Roger included a graphic illustrating IPCC temperature and sea level changes from the first through fourth assessement reports, and compared those to data.

Roger made some brief observations about the comparison, and [...]

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Filed in: global climate change


Apr1

Exploratory Statistics: Roger Cohen Looks at ENSO

My blog philosophy is to consider all possible physical explanations for the data we are examining, and see whether or not they seem to explain the data. As many know, climatologists tell us that much of variability in global mean surface temperature is driven by the ENSO cycle (i.e. the El Nino/La Nina [...]

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Filed in: Statistics global climate change

Mar27

Erhmm… it’s the IPCC AR4 projections that are falsified! :)

There seems to be some confusing about just which IPCC projections were falsified. In particular Tamino is misinformed. This misunderstanding is likely due to lack of clarity on my part. So, I’d like to clarify: It’s the AR4 predictions that are falsified by recent data — not the TAR.
So, criticism that, somehow, [...]

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Filed in: global climate change


Mar26

When were the models used in the TAR frozen? Around 2000.

Recently, I have been interested in the answer to these questions:
How does the IPCC really make projections? When were tuning parameters in models used to create projections in the TAR “frozen”?
Both questions were motivated by one of the many of the puzzling features of a recent paper by “The Rahmstorf Six Seven”, often [...]

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Filed in: global climate change

Mar25

Comparing IPCC Projections to Individual Measurement Systems.

Recently, the subject of using only one set of measurements to perform a hypothesis test arose. As many are aware, I prefer to average over instruments. But, I’m willing to consider each set individually. So, today I did that.
My main results are: Looking at the data 12 possible ways, I get 9 results [...]

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Filed in: global climate change


Mar24

The Teeter-Totter of Temperature!

I thought I’d fiddle with my spread sheet and create a graphic I’ll be able to easily update month to month. This way, when the temperature trends flip to positive as predicted we’ll see that. Later, if and when the trend begins to increase to the level predicted by the IPCC projects, we’ll see [...]

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Filed in: global climate change

Mar21

Rahmstorf et al. 2007: Where does their figure come from?

Several readers have requested I comment on Rahmstorf et al. 2007, which compares the TAR predictions to data. Rahmstorf is a brief one page paper, which provides a visual comparison between HadCrut measurements of the global mean surface temperature and IPCC projections.
Can anyone tell me precisely which figure in the TAR matches Rahmstorf’s temperature [...]

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Filed in: global climate change


Mar20

Can ENSO really explain away “the problem”? What about the PDO?

ATMOZ’ recently posted an interesting analysis that explains why one must always be aware of the properties of weather when doing statistics. I agree with that. I would go further. I would say one must always be aware of the properties of any underlying phenomena when doing statistics.
More specifically, ATMOZ suggested that maybe [...]

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Filed in: Statistics global climate change

Mar18

IPCC Falsification: Can We Identify Trends That Are Not Consistent With Noisy Data?

William Connolley seems to be having a little trouble understanding how one can apply statistics to a set consisting of a time series with many data pairs, and then state a range for climate trends that are consistent with the noisy data.
As it happens it’s easy using standard statistical techniques applied to data [...]

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Filed in: Statistics global climate change




 

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