Posts Tagged ‘Vermeer’

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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

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Rahmstorf (2011): Robust or Just Busted (Part 4): First results from new code

September 14, 2012

This is part 4 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].

The new code for consistent processing of temperature and sea level data according to the predominant Vermeer and Rahmstorf 2009 model (VR2009)[2] is complete.

It is written LabView V7.1.  There have been several upgrades to LabView since V7.1, but I believe my code will open in any of them.  I prefer this older version of LabView for a variety of reasons that I will not go into here.  But one advantage is that anyone who is interested in running this code can find a used student version of LabView on Ebay at a very reasonable cost.

My code can be downloaded here.

VR2009 input the GISS temperature, Church’s and White’s 2006 sea level data, and modified the sea level data with a correction for reservoir storage from Chao and determined the fit parameters, a, b, and To  for their model…

Rahmstorf and company figured that once a, b, and To were found they could insert hypothesized temperature scenarios for the 21st century into equation 1 and calculate the resulting sea levels.  I have provided a long list of criticisms of their logic.  One of the most devastating observations is that their own source of 20th century sea level data(Church and White, 2006[3]) had revised their data, and the new version of data (Church and White 2009[4] or Church and White 2011[5]) resulted in much lower sea levels by the end of the 21st century when inserted in to equation 1.

Two years ago I reproduced the VR2009 fit parameters, a, b, and To, to demonstrate that I could accurately reproduce their model.

In R2011 Rahmstorf re-works the numbers with the same inputs used in VR2009, and I have reworked the numbers with this new code.  And for the same inputs used back on VR2009, everything lines up within Rahmstorf’s stated uncertainties.  But that is a minor point.  Rahmstorf’s primary objective in R2011 is to defuse my observation that Church’s and White’s newer, more accurate sea level data causes Rahmstorf’s model to yield much lower sea level projections for the 21st century.  Plenty of time to deal with that issue later.

But for now and for the record: in VR2009 Vermeer and Rahmstorf found

a = 5.6 ± 0.5 mm/year/K

b= -49 ± 10 mm/K

To = -0.41 ± 0.03 K

In 2010, using my implementation of their model, I found

a = 5.6  mm/year/K

b= -52 mm/K

To = -0.42 K

In R2011 Rahmstorf presents slightly different numbers than he did in VR2009 for the same input conditions.  Similarly, with my new code I now get slightly different numbers for the same input conditions.

With the new code I found

a = 5.8  mm/year/K

b= -54 mm/K

To = -0.41 K

Presentation of my results

In R2011 Rahmstorf makes some claims based the same model as equation 1, but with various combinations of temperature and sea level data from different sources.  His claim is that he gets essentially the same results – no matter what inputs he uses – indicting that his model is “robust.”

I will also be presenting a lot of results for different possible inputs in the days to come.   But my results will be very detailed, complete, and entirely open for your examination.  You also have access to my complete code.

My code will always generate four files for any set of inputs.  Three of those files are images of: graphs of the input data;  graphs of the model fits to the input data (used to derive a, b, and To); and graphs of sea level projections based on various temperature scenarios for the 21st century, including the SRES emission scenarios used in VR2009 and the RCP45 and RCP85 scenarios used in R2011.  The fourth file is a tab delimited text file with all setup parameters, fit plots and results, and projections.

Note that the graph images of the 21st century sea level projections will not be autoscaled.  That is, the Y axis of the projection graphs will all have the same scaling.  This will make many of the graphs look crowded, but it will also be easy to make a qualitative comparison of the projections from different input data.   You can always open the tab delimited text file in the spreadsheet of your choice and replot the data as you see fit.

Below you can see an example of the graph images and the corresponding tab delimited text file that is generated by my code with the same input data used to find the model fit parameters listed above.  That is, I will use the  GISS temperature, Church and White’s 2006 sea level data and the Chao reservoir correction, which result in my values of a, b, and To, shown above.

The tab delimited text file is shown below.  I have truncated the columns of data (which could be thousands of rows long).   The headers and columns would line up better if you opened the file in a spreadsheet.

INPUTS
Temperature filename: T GISS Land Ocean.txt
Original source: http://data.giss.nasa.gov/gistemp/graphs_v3/Fig.A2.txt		

http://data.giss.nasa.gov/gistemp/graphs_v3/

Sea level filename: SL CW06.txt
Original source: http://www.psmsl.org/products/reconstructions/church_white_grl_gmsl.lis

Modifier filename: RS Chao 2008.txt
Original source: “Impact of Artificial Reservoir Water Impoundment on Global Sea Level”		
Chao, et al., Science 320, 212 (2008)

SETUP PARAMETERS
Minimizing residual: dH/dt
Extension (years): 15.0
Smoothing Gaussian FWHM (years): 15.0
input years used: 1880.0 - 2000.0

FIT PARAMETERS
a: 5.8
b: -54
To: -0.41
H mse: 1.986
dH/dt mse: 0.250

FIT CURVES
date	model H (mm)	data H (mm)	H residuals (mm)	model dH/dt (mm/year)	data dH/dt (mm/year)	dH/dt residuals (mm/year)
1880.050000	-76.997238	-76.648275	0.348963	1.252341	0.699570	-0.552771
1880.150000	-76.873236	-76.577572	0.295664	1.240020	0.714500	-0.525521
1880.250000	-76.750402	-76.505711	0.244692	1.228336	0.722720	-0.505615
    |               |                |              |              |                |                |      
    |               |                |              |              |                |                |    
PROJECTIONS
year	RCP45	RCP85	A1B max	A1B mid	A1B min	A1F1 max	A1F1 mid	A1F1 min	A1T max	A1T mid	A1T min	A2 max	A2 mid	A2 min	B1 max	B1 mid	B1 min	B2 max	B2 mid	B2 min
2000.500000	3.564485	3.462285	4.177685	4.330985	4.330985	4.841985	4.688685	4.586485	4.279885	4.228785	4.688685	4.126585	4.382085	4.790885	4.126585	4.841985	4.688685	4.841985	4.841985	4.790885
2001.500000	7.325070	7.132270	8.226370	8.413370	8.668870	8.815270	8.679370	8.997570	7.908170	8.169470	8.730470	8.181070	8.458670	9.178770	8.181070	9.019670	9.037070	8.917470	8.917470	8.923270
2002.500000	11.429255	11.515155	12.424755	12.588555	13.019455	12.938255	12.819755	13.511955	11.681455	12.169255	12.916155	12.283055	12.628055	13.567755	12.334155	13.170555	13.392355	12.568955	12.875555	13.085755
   |               |                |              |              |                |                |      |               |                |              |              |                |                |

Tab delimited text: VR summary 120913-212735.doc

The three associated graph images…

Input data image: http://climatesanity.files.wordpress.com/2012/09/vr-input-image-120913-212735.png

Fit image: http://climatesanity.files.wordpress.com/2012/09/vr-fit-image-120913-212735.png

projections image: http://climatesanity.files.wordpress.com/2012/09/vr-projections-image-120913-212735.png

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

[2] Vermeer, M., Rahmstorf, S., “Global sea level linked to global temperature,” PNAS, 2009

[3] Church, J. A., and N. J. White, “A 20th century acceleration in global sea-level rise“,  Geophys. Res. Lett., 33, 2006

[4] www.psmsl.org/products/reconstructions/church_white_new_gmsl.lis

[5] Church, J. A. and N.J. White, “Sea-level rise from the late 19th to  the early 21st Century“, Surveys in Geophysics, 2011

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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.

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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
……..

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Rahmstorf (2011): Robust or just busted (Part 1)

June 30, 2012

This is part 1 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 don’t get many readers at my little blog, but it is nice to know that Stefan Rahmstorf has been keeping up with it. He has a great desire to prove that his claims of extreme sea level rise, and my comments (and equations, graphs, data, logic, etc.) have cast his conclusions into grave doubt. Besides showing in multiple ways that his models don’t make mathematical sense, I have also shown that when the best data is applied to his (bogus) model his sea level rise projections for the 21st century are cut down to size.

So, it seems his recent outing in Climate Dynamics (“Testing the robustness of semi-empirical sea level projections,” Climate Dynamics, November, 2011) is aimed squarely at that point, which he makes clear in the fourth sentence of the abstract.

“Lower projections are obtained only if the correction for reservoir storage is ignored and/or the sea level data set of Church and White (Surv Geophys, 2011) is used.”

You see, once upon a time (2007, 2009 ) Rahmstorf thought that the 2006 version of sea level data from Church and White was surely the finest data for figuring out the relationship between sea level rise rate and global temperature. When he used it in his silly 2007 and 2009 models to project 21st century sea level rise, the models gave alarmingly high results. Ergo, the models and input sea level data must certainly be correct. The problem was that Church and White were not as confident in their own sea level data as Rahmstorf was. By the time Vermeer and Rahmstorf were penning their widely quoted 2009 PNAS paper, Church and White had made serious corrections to their sea level data. But that corrected data never made it into the Vermeer’s and Rahmstorf’s paper. If it had, their sea level rise projections would have been way lower.

I raked Rahmstorf and company over the coals on this point. I ran their own model with the corrected data from their own source (Church and White) and published the results online. The result: vastly lower sea level projections for the 21st century. Their response: silence.

The above abstract sentence would have been more accurate if it had said…

Much higher projections are obtained if Church’s and White’s older, self-rejected, data is used than if Church’s and White’s newer, corrected data is used.”

The meaning of his chosen words was Rahmstorf’s way of telling his sycophants to close their eyes and stop thinking. Church’s and White’s out-dated data gives much higher 21st century predictions than their newer corrected data. That’s all you need to know to tell you that the old data is better than the corrected data. “These are not the droids you’re looking for. Move along.”

As is my custom, I will write a series of posts concerning “Testing the robustness of semi-empirical sea level projections.”  Stay tuned.

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Updated PSMSL sea level video

March 11, 2012

The following video shows all the PSMSL tide gauge data so you can search for a sea level rise acceleration.  It replaces an earlier version that was taken down by youtube because of music license violations.  This version has music with Creative Commons license.  The text and data are the same as before.

Vermeer’s and Rahmstorf’s “Global sea level linked to global temperature” (PNAS, 2009) relied on Church’s and White’s “A 20th century acceleration in global sea-level rise” (GEOPHYSICAL RESEARCH LETTERS, VOL. 33,) for their sea level data.  Church and White built their sea level time series from the Permanent Service for Mean Sea Level (PSMSL) tide gauge data.

There is no attempt to analyse the data here, but I have started that process and will report on it later.  The first two minutes may be a little boring, but please read along.  It livens up later.   For now, sit back and enjoy.

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Rahmstorf vs. Rahmstorf

March 5, 2012

Oh, what a tangled web we create, when first we practice to exaggerate.

ClimateSanity
with apologies to Sir Walter Scott

Intrepid mathematician Stefan Rahmstorf has calculated the global temperature increase rate for the last 31 years.  (Global temperature evolution 1979–2010, Foster and Rahmstorf, Environ. Res. Lett. 6, 2011) For the fun of it, lets take him at his word.  The problem is that when his temperatures from this new paper are inserted into his sea level rise rate formula from one of his earlier papers (Global sea level linked to global temperature, Vermeer and Rahmstorf, PNAS, 2009), the calculated sea level rise rate isn’t anywhere close to reality.

These papers can’t both be correct.  My guess is that neither of them are. 

In the 2011 paper he starts with five different global temperature records and adds his version of corrections for volcanoes, el Nino and solar variations.  He then calculates the temperature rate of change per decade for each of the five temperature records.  The five ranged between 0.141 °C/decade to 0.175 ° C/decade, but the average was 0.163 °C/decade as shown in figure 1,  below.

He also calculated the temperature rise rate acceleration, and found none.  In his own words

“To look for changes in the warming rates over time, we computed the rate in adjusted data sets for different time intervals, for all start years from 1979 to 2005 and ending with the present. The results show no sign of a change in the warming rate during the period of common coverage.”

Figure 1 Rahmstorf's version of global temperature for 1979 to 2010. This is figure 4 and table 1 from Foster and Rahmstorf. Trendline, based on the average of table 1, added by ClimateSanity

You know what higher temperatures mean: higher sea level rise rates.  Nobody knows this better than Herr Rahmstorf, who has spent the better part of his career making the point.  He has even provided a formula in his 2009 paper to translate the global temperature to the sea level rise rate.

Some easy math

Assuming his calculated temperature increase rates for the last three decades are correct, what does his sea level rise rate formula tell us?  In Rahmstorf’s parlance H is the sea level and dH/dt is the sea level rise rate.  His formula, from which sprang the famous 1.8 meter sea level rise for the 21st century meme, looks like this…

From Rahmstorf’s graph of global temperature from 1979 to 2010 (figure 1, above), we see that his temperature and the rate of temperature change are given by …

 


Substituting equations II & III into equation I and gathering terms reveals


While equation IV won’t tell us the exact sea level rise rate for a particular year, it will tell use how much the sea level rise rate changes between two years.  That is


Let’s say that Rahmstorf’s temperature data from the his 2011 Environmental Research Letters paper is correct and his formula relating sea level rise rate from his 2009 PNAS paper is correct.  And let’s say that we wanted to know how  much the sea level rise rate had increased between (oh, I don’t know – how about) 1993 and 2010. Then equation V would tell us that the sea level rise rate should have increased by 1.55 mm/year (0.09128 mm/year X (2010-1993)). 

Comparing to reality

Lucky for us, we have measured sea level data to compare the calculated value to.  As figure 2, below makes abundantly clear, the sea leve rise rate has been about 3.1 mm/year over this time period.   The combination of Rahmstorf’s 2009 PNAS paper and 2011 Environmental Research Letters paper indicate that it should have increased by 1.55 mm/year (an additional 50%).
How can this discrepancy be explained?  Oh yeah, I almost forgot, we already know the Rahmstorf’s formula relating sea level rise rate to global temperature is totally bogus.

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