Archive for the ‘Vermeer’ Category

h1

Vermeer and Rahmstorf paper rejected

January 31, 2014

Vermeer and Rahmstorf had a paper rejected by the journal “Climate of the Past.” This news is 16 months old, but I just heard about it, and could find very few references about it on the web.

This paper, On the differences between two semi-empirical sea level models for the last two millennia,  promoted their earlier sea level rise models.  They couldn’t seem to get traction with this paper.

Here are some reviewers’ comments…

One of the major problems with this work is the decidedly biased analysis and presentation.

Highly biased analysis and presentation.

It currently takes significant effort to figure out which pairs of models and training data sets the authors use, and whether they have evaluated all the relevant combinations of the same.

No surprise here.  Rahmstorf has a history of alluding to all kinds of data sets and implying that he has taken them into consideration, but only presenting results for those that support his thesis.

And the final blow…

In the light of the two negative reviews and one comment which all require new analyses and point to fundamental flaws in the methodology of the current paper, I regret to inform you that my conclusion is to support rejection. I strongly dissuade the authors from submitting responses and a revised version.

Here is the paper…

Click for full PDF version

Here is the reviewers’ discussion that lead to the the rejection.

Of course, Vermeer and Rahmstorf do not give up that easily, and similar papers have been shopped around to other journals

h1

Library of data for testing “robustness” of Rahmstorf models

September 5, 2012

This is part 3.5 of a multi-part series about “Testing the robustness of semi-empirical sea level projections,” Rahmstorf, et. al., Climate Dynamics, 2011. You can see an index of all parts here. I frequently refer to this paper as R2011.

I have finally published my small library of temperature, sea-level and sea-level modifier (reservoir storage, groundwater depletion, etc.)  data from various sources.

All of these data files have a consistent format which can be read by my code that calculates fit parameters for the Rahmstorf model relating sea level to temperature.  However, not all of the time series are long enough to be useful in that model.

You can see the data files here.

I am open to suggestions for additions to this list.  If you have any criticisms of the files, such as accuracy of the data, format, selection, anything – please leave a comment.  I will give due attention to any legitimate criticism that is aimed at improving the data.

Coming soon…

I am a slow worker, but I try to be thorough.

The first output from my code, using Rahmstorf’s preferred inputs (GISS temperature, Church and White 2006 sea level data, and the Chao reservoir correction) will be presented soon.  The goal of that presentation will be two-fold: to verify that of my model implementation are consistent with Rahmstorfs; to have a simple format for presenting those result.  That format can then be applied to the results of other input data.

h1

Rahmstorf (2011): Robust or Just Busted (Part 2) – Quadratic Fits of Laughter

July 6, 2012

This is part 2 of a multi-part series about “Testing the robustness of semi-empirical sea level projections,” Rahmstorf, et. al., Climate Dynamics, 2011. You can see an index of all parts here. I frequently refer to this paper as R2011.

I will refer to Stefan Rahmstorf’s “Testing the robustness of semi-empirical sea level projections”  as R2011 [1].

This post is all about fitting sea level data to a quadratic.

There is only one reason to fit sea level vs. time data to a quadratic: to highlight an acceleration trend.  It only makes sense to do so if you think that the trend is more or less uniform over time.  I have warned against reading too much into a quadratic fit, and especially against using a quadratic fit to imply a future trend in sea level.

I have seen something in R2011 that I have never seen before.  The use of a quadratic fit as a kind of “optical delusion.”

Consider the image at the right.  Do you see the triangle?  Sure you do.  Of course, it is not really there.  But what would you say if I insisted that the triangle really was there and said “The circles are shown merely to help the eye find the triangle?”

R2011 has done much the same thing with a quadratic data fit in their figure 1.   I would think what they have done was just a joke, if it weren’t such an obvious attempt to convince readers that the data says something that it does not say.  Take a look…

Figure 1 from "Testing the robustness of semi-empirical sea level projections" (Rahmstorf, et. al., Climate Dynamics, 2011)

Note the dashed grey lines through each data set.  As R2011 explains in their caption, these dashed  grey lines which pass through all the data sets, are actually the quadratic fit to just one of the data sets (CW06)[2].  They say

“The dashed grey line is a quadratic fit to the CW06 data, shown here merely to help the eye in the comparison of the data sets.”

The point the R2011 wants to make, of course, is that all of these data sets have the same acceleration trend as R2011′s preferred sea level data, CW06.

But that is not true.  In fact, if you fit any of the other data sets to a quadratic you will see that every single one of them has a lower trend than CW06 when projected through the 21st century. Every single one of them.

The following figure shows proper quadratic fits to all the sea level data sets used by R2011 in their figure 1.  The legend shows the sea level rise that would result for the period 2000 to 2100 if these quadratics were extrapolated to 2100.

Quadratic fits for all sea level data sets used by R2011 in their figure 1. The legend shows the sea level rise that would result for the period 2000 to 2100 if these quadratics were extrapolated to 2100
Quadratic fits for all sea level data sets used by R2011 in their figure 1. The legend shows the sea level rise that would result for the period 2000 to 2100 if these quadratics were extrapolated to 2100

Updated Holgate data

Science is about constant refinement of theories and data.  When Rahmstorf is faced with old data and new data from the same authors, he has a special method for deciding which data set is better.  The version that points to higher sea level rise in the 21st century is always considered to be better.  Thus his insistence that the 2006 Chuch and White sea level data is  better than the 2009 or 2011 Church and White data that incorporated Church’s and White’s data reduction improvements.

The same is true for Holgate’s sea level data.  Look at HW04 [3] plots in the above graphs.  This Holgate sea level data covers the mid-1950s to the mid-1990s.  It is a curious thing (not really curious if you understand Rahmstorf’s modus operandi) that R2011 chose this data over Holgate’s updated data from 2007 [4], which covers the entire 20th century.  What would happen if we replaced the HW04 data with the 2007 Holgate data (H07)?  Take a look…

Holgate data from 2004 has been replaces with Holgates updated data from 2007.
Holgate data from 2004 has been replaces with Holgates updated data from 2007.

Let me stress again, I do not recommend extrapolating sea level data with quadratic fit, and I am not endorsing any of the extrapolations shown above.  I am simply guffawing at Rahmstorf’s chuzpa in his figure 1.

______________________

1.  Rahmstorf, S., Perrette, M., and Vermeer, M., “Testing the robustness of semi-empirical sea level projections” Climate Dynamics, 2011

2. Church, J. A.,, and White,  N. J., “A 20th century acceleration in global sea-level rise,” Geophysical Research Letters, 33, 2006

3. Holgate, S. J., Woodworth, P.L., “Evidence for enhanced coastal sea level rise during the 1990s,” Geophysical Research Letters, 31, 2004

4. Holgate S., “On the decadal rates of sea level change during the twentieth century,” Geophysical Research Letters, 34, 2007
……..

Follow

Get every new post delivered to your Inbox.

Join 49 other followers