Posts Tagged ‘Sea Level Rise’

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The Search for Acceleration, part 6, Australia

July 17, 2013

magnifying glass 145This is part 6 of a series of posts in which I am searching for a large acceleration in sea level rise rate in the latter part of the 20th century that could reconcile the 1.8 mm per year average rise rate for the century attributed to tide gauge data and the approximately 3 mm per year rise rate for the tail end of the century attributed to the satellite data.

Australia

Australia has only 5 tide gauge stations with data sets that are at least 90% complete going back to 1960, but four of those go back to 1940 or earlier.  I will analyse this data in my usual way (detrend, weight, average, and derivative).

Regional sea level rise rates are usually swamped by things other than just global effects.  In the case of Australia we may be able to disentangle one of these effects – the El Nino Southern Oscillation.  I will also consider the component of the Australian sea level data that is orthogonal to the ENSO3.4 sea surface temperature.

The slide show shows my standard analyse.

This slideshow requires JavaScript.

ENSO

The El Nino Southern Oscillation dominates the sea level around Australia.  The following plot shows an overlay of the detrended weighted average of the five Australian tide gauge sites and the NINO3.4 index from the Hadley Centre.  I am including tide gauge data after 1915 which include at least two tide gauge sites at all times and no large data gaps.  The similarities are obvious.

ENSO sea level overlay

Let’s try to remove the ENSO effect from the sea level around Australia. I will do that by breaking the sea level data down into an ENSO correlated and ENSO orthogonal parts. If the ENSO orthogonal part of the sea level is truly independent of ENSO, then it shows what the sea level around Australia would look like without an ENSO effect.  Here is the formula for finding the ENSO orthogonal component of the of the sea level data.

orthogonal formula440

The top of each of the following slides shows the weighted, detrended, averaged Australian sea level (white), ENSO3.4 sea surface temperature (blue),  and the component of sea level data that is orthogonal to the ENSO3.4 data (red).  The bottom of each slide shows the corresponding relative rise rates associated with sea level (white) and with the ENSO orthogonal component of the sea level (red).  Each successive slide shows the same original data with increasing Gaussian smoothing.

The most important thing to notice is that when the ENSO influence is removed the sea level rise rate at the end of the century is significantly reduced.

ENSO and global warming

If the higher relative rise rates at the end of the century are due to ENSO, then it is interesting to ask whether ENSO fluctuations are greater now (because of global warming?) than in the past.  The best answer to this question can be found in Highly Variable El Niño-Southern Oscillation Throughout the Holocene (Cobb, et. al., Science, 339, 1/4/13).

The abstract states…

Twentieth-century ENSO variance is significantly higher than average fossil coral ENSO variance but is not unprecedented. Our results suggest that forced changes in ENSO, whether natural or anthropogenic, may be difficult to detect against a background of large internal variability.

and the body of the paper mentions…

[T]he detection (and attribution) of any changes in ENSO properties would require very long time series spanning many centuries, to the extent that detection of such changes is even possible.

[M]uch of the observed differences in ENSO variance over the past 7 ky reflect strong internal variability… Relatively robust 20th-century ENSO variability may reflect a sensitivity to anthropogenic greenhouse forcing, but definitive proof of such an effect requires much longer data sets than are currently available, given the large range of natural ENSO variability implied by the available fossil coral data.

Conclusion

According to my usual analysis the rise rate at the end of the century was clearly higher than the average (from 1940 to present), but no higher than the 1940s.   Does the reconcile the satellite data and tide gauge data?  Yes.

But, when the part of the detrended sea level that is correlated to ENSO3.4 is removed, the remaining orthogonal part of the rise rate appears to be lower at the end of the century than during the 1940s, and not particularly high compared to the rest of the century. So if my removal of the ENSO effect is correct, then there was nothing “unusual” about the rise rate at the end of the century
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Sources

20th century rise rate average of 1.8 mm/year

1. Church and White Global Mean Sea Level Reconstruction

2. Links to Church and White sea level data

Satellite data (about 3 mm/year): CU Sea Level Research Group

RLR tide gauge data: Permanent Service For Mean Sea Level

ENSO/Global warming relationship: Cobb, et. al., Science, 339, 1/4/13

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The Search for Acceleration, part 5, The Netherlands

July 6, 2013

magnifying glass 145This is part 5 of a series of posts in which I am searching for a large acceleration in sea level rise rate in the latter part of the 20th century that could reconcile the 1.8 mm per year average rise rate for the century attributed to tide gauge data and the approximately 3 mm per year rise rate for the tail end of the century attributed to the satellite data.

The global sea level rise rate is swamped by other effects.  In most locations the yearly rise and fall of the oceans is greater than the 18 cm of sea level rise during the entire 20th century.  Geologic effects (e.g. glacial isostatic adjustment or plate tectonics) add to local and regional rise rates, making them deviate greatly from the global rise rate.

I am working under the theory that by detrending sea level data from individual (local) sites and averaging with other regional sites it should be possible to extract changes in regional sea level rise rates while bypassing the question of what the “true” sea level rise rate is in that region.

The Netherlands

Netherlands elevation

Elevation and tide gauge locations for The Netherlands.

Nobody cares more about sea level rise than the folks in The Netherlands. They have been dealing with the issue long before anybody was worried about global warming, since 20% of the country’s area is below sea level.  They have excellent sea level data spanning nearly 150 years.  This map shows land elevations in the Netherlands as well as the location of seven high quality tide gauge stations.

Here is the PSMSL data for those seven locations…

Netherlands Raw Spread

Tide gauge data for the Netherlands.

As I have mentioned before, I am not concerned with finding the sea level rise rate, but rather the change in sea level rise rate. But this set of data averages out to have a 20th century rise rate very close to the commonly reported tide gauge derived average of 1.8 mm/year. (Click on image if animation does not advance.)

sea level annotated 450ani

These seven stations also have very coherent yearly signals, created from the 2, 3, 4, 6 & 12 month Fourier components.  Note that the magnitude of the yearly signal is nearly the same as the entire average sea level rise for the entire 20th century.

Netherlands Yearly signal

Now, lets consider the weighted, detrended data to derive the relative acceleration. (Click on image if animation does not work.)

Netherlands weighted and detrened 450ani

Conclusion

The Netherlands tide gauge data if of the highest quality and long duration.  All seven stations cover 1870 to the present.  The detrended sea level rise rate does indicate that the overall sea level rise rate for last two decades of the 20th century was a few mm per year greater than the century’s average.  However, this very reliable data also indicates that the sea level rise rate at the beginning of the century was just as high as the end of the century.

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Sources

20th century rise rate average of 1.8 mm/year

1. Church and White Global Mean Sea Level Reconstruction

2. Links to Church and White sea level data

Satellite data (about 3 mm/year)

CU Sea Level Research Group

RLR tide gauge data

Permanent Service For Mean Sea Level

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The Search for Acceleration, part 4: Mea Culpa

June 30, 2013

magnifying glass 145I had a big mistake in my last two posts…

The Search for Acceleration, part 2: East Coast of North America

and

The Search for Acceleration, part 3: Japan

The error caused my rise rate calculations to be off by a factor of 12! This was because I failed to account for the monthly increments in the RLR data.  This mistake caused large errors on my conclusions, which have now been corrected.

I use National Instruments LabVIEW software for all of my coding.  LabVIEW is an advanced graphical programming platform that makes it possible to write sophisticated code in a completely graphical environment.  That is, no lines of text as in the more traditional languages like Fortran or C.  Instead, various sub-programs (or “sub-VIs” in LabView parlance) can be wired together to create complex programs that would take much longer to write other languages.

The image below shows the mistake I made.  Mea Culpa.

LabView error

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The Search for Acceleration, part 2: East Coast of North America

June 24, 2013

magnifying glass 145

CORRECTION: 6/30/13

The original detrended sea level rise rate graphs for this post was off by a factor of 12!.  This greatly changes my conclusion.  Incorrect information is now crossed out and is followed by corrected information in red.

This is part 2 of a series of posts in which I am searching for a large acceleration in sea level rise rate in the latter part of the 20th century that could reconcile the 1.8 mm per year average rise rate for the century attributed to tide gauge data and the approximately 3 mm per year rise rate for the tail end of the century attributed to the satellite data.

The global sea level rise rate is swamped by other effects.  In most locations the yearly rise and fall of the oceans is greater than the 18 cm of sea level rise during the entire 20th century.  Geologic effects (e.g. glacial isostatic adjustment or plate tectonics) add to local and regional rise rates, making them deviate greatly from the global rise rate.

I am working under the theory that by detrending sea level data from individual (local) sites and averaging with other regional sites it should be possible to extract changes in regional sea level rise rates while bypassing the question of what the “true” sea level rise rate is in that region.

East Coast of North America

Conclusion: There is no sign of an acceleration in the sea level rise rate in the tide gauge data from the East Coast of North America.

Conclusion:  The tide gauge data for the East Coast of North America that covers that satellite sea level data era (1993 to present) does show a rise rate that is significantly higher than the tide gauge data rise rate for the 20th century.  But the sea level rise rate in the 1930s through 1940s and around 1970 was as high or higher.Whether or not this data reconciles the difference between the 20th century tide gauge rise rate average and the satellite rise rate average is still ambiguous.

I have selected the East Coast of North America, for no particular reason, as the first region to analyse.  I looked for tide gauge data along the coast such that it covered at least the period from 1960 to 2008 with 90% of all monthly data accounted for.  Usable sites ranged from Nova Scotia to Georgia.

Click on any animations or graphs to enlarge.
East Coast North America 90p 1960-2008 Map

The following plot shows the qualifying data spread out for easy comparison.  The key at the right shows the associate RLR data files.

East Coast North America 90p 1960-2008 Raw Spread

Averaged data

As I mentioned above, I am not concerned with finding the sea level rise rate, but rather the change in sea level rise rate. However the following data for the East Coast of North America is interesting because it shows an averaged sea level rise rate for the 20th century that is close to the satellite derived sea rate for the end of the 20th century.  This is will not be the case for most regions around the world.  If you squint the right way you can also see the change in rise rate around 1930 that shows up in the various iterations of Church and White’s derivations of 20th century sea levels.

East Coast North America 90p 1960-2008 Avg 450ani2

Detrended data

East Coast North America 90p 1960-2008 450ani corrected

The last frame of the detrended data animation is worth repeating (see below).  Notice that there is no evidence of an extreme or consistent increase in the sea level rise rate in the last two decades.  The rise rates were as great or greater in the 1940s, 1950s and 1970s than they were in the 1980s, 1990s and 2000s.  However, at least part of the satellite era (1993 to present) tide gauge data may be more than 2 mm/year greater than the average for the 20th century.  It is safe to say that the tide gauge data from the East Coast of the North America does not reconcile the difference between the 20th century rise rate average (about 1.8 mm/year) and the satellite measured average (about 3 mm/year) Whether or not this data reconciles the difference between the 20th century tide gauge rise rate average and the satellite rise rate average is still ambiguous.

East Coast North America 90p 1960-2008 Detrended Acceleration
corrected East Coast North America 90p 1960-2008 Detrended Acceleration

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Rahmstorf (2011): Robust or Just Busted (Part 7): The Irony of Jevrejeva’s Data.

January 7, 2013

This is part 7 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.

Let’s talk a little more about the irony of using the Jevrejeva’s 2008 sea level data, which I will refer to as JE08[1], to confirm Rahmstorf’s sea level projections for the 21st century.

As I have already explained, Rahmstorf claims in his 2011 paper (which I will refer to as R2011[2]), that his model is “robust,” meaning that variations of historical 20th century input sea level data yield essentially the same sea level rise projections for the 21st century.  R2011 graphically presents seven sources of sea level data  (while ignoring others) and implies their similarity by overlaying the same quadratic fit for all of them.  R2011 leads us to believe that the model is robust with, specifically, the input of these various sea level data sets.

R2011 presents the results of the model using only three of the seven sea level rise inputs.  Two of the three are by the same authors, Church and White[3][4],  who clearly believe their later version of the sea level data (CW11[4]) is an improvement over their earlier version (CW06[3]).  Then, R2011 cynically rejects the model results from Church’s and White’s better set of data because those results testify against R2011’s desired conclusion of extremely high sea level rises for the 21st century. 

Which brings us to Jevrejeva

The third data set that R2011 used is Jevrejeva’s.  So after all the blathering about the “robustness” of their model under a broad variety of inputs, R2011 is left with just two sea level data sets that they are satisfied with: Church’s and White’s earlier data set, CW06; and Jevrejeva’s 2008 data, JE08.   Figure 1, below shows R2011’s figures 1 and 9, with my annotation.

Figure 1.  R2011's figures 1 & 9 showing Rahmstorf's judgement about the quality of sea level sets.

Figure 1. R2011’s figures 1 & 9 showing Rahmstorf’s judgement about the quality of sea level sets.

Keep in mind that R2011’s objective in their claim of robustness was to prove that their earlier results [5], based on the CW06 were realistic.  So, in effect, after all the hand waving JE08 is the only one of the seven sea level data sources that fulfills that purpose.  That is why we are taking a little closer look at JE08.

Let’s start by looking at an overlay of JE08, CW06 and CW11 in figure 2.  If Rahmstorf’s model were “robust,” as R2011 claims, then all three of these data sets as input to the model should yield very similar sea level rise projections for the 21st century.  But one of them yields much lower results than the other two. The amazing thing is that the outlier is CW11, which  is nearly a twin to CW06, at least compared to JE08.  How can that be?

Figure 2
Figure 2

Let’s suspend our higher cognitive functions for the moment and agree with R2011’s reasoning.   That is, we will agree that the sea level rise projections for the 21st century based on CW11 input data must be rejected because they are much lower than the projections based on CW06 input data.  Inversely, we will agree that sea level rise projections for the 20th century based on JE08 input data must be accepted because they give high 21st century projections, just like the projections based on CW06 input data.

A closer look at JE08 sea level data

Since we have decided to mindlessly accept the usefulness of JE08 to back up Rahmstorf’s high sea level rise projections for the 21st century, then we should also accept some other interesting features of JE08.  So let’s take a closer look.

JE08 says their version of sea level data was in “good agreement with estimates of sea level rise during the period 1993–2003 from TOPEX/Poseidon satellite altimeter measurements.”  Figure 3, below, shows an overlay JE08 and the satellite altimeter data[6],…

Figure 3
Figure 3

It is quite striking that according to JE08 and the satellite data that the sea level rise rate for the middle third of the 20th century (1933 to 1966) is exactly the same as the sea level rise rate at the end of the 20th century and beginning of the 21st century.  How can this possibly be!?  How can this data that indicates no increase in the sea level rise rate for 80 years cause tremendous increases in the sea level rise rate for the 21st century when used as input to Rahmstorf’s model?

Stefan the Dart Thrower

Consider Stefan Rahmstorf the Dart Thrower.  He holds forth at the pub as the best thrower in the kingdom.  He brags about his precision, claiming “I can hit high numbers every time! My talent is robust!” Challenged by another annoyed pub patron to “put up or shut up,” Stefan grabs a handful of darts and goes to work.  He throws seven, but only three hit the board.  Two are on high numbers and one is on a low number, the rest are stuck in the wall.  “See!” he says triumphantly, pointing at the two darts on the high numbers.

The other patron points out the projectiles stuck in the wall.  “Bad darts” Stefan replies.

“What about this dart on the low number – it is identical to one of the darts on a high number” the incredulous patron points out. “Same length, same material, same weight, same manufacturer.”

“Obviously a bad dart, nevertheless” sniffs Stefan.  “If if were a good dart it would have landed on a high number.”

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[1] Jevrejeva, S., et. al. “Recent global sea level acceleration started over 200 years ago? ,”  Geophys. Res. Lett., 35, 2008

[2]  Rahmstorf, S., et. al., “Testing the robustness of semi-empirical sea level projections” Climate Dynamics, 2011

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

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

[5] See “Critique of “Global sea level linked to global temperature, by Vermeer and Rahmstorf

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Rahmstorf (2011): Robust or Just Busted (Part 6): Holgate’s sea level data

November 11, 2012

This is part 6 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.

Recall figure 1 from R2011[1]…

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

One of the primary points of this graphic is the quadratic fit of one data set (CW06) overlaid on all the other data sets.  The message that you are to receive is that these various sets of sea level data all tell the same essential story.  The falseness of this claim was discussed in “Quadratic fits of laughter.”

But let’s take Rahmstorf at his word.  Let’s agree with him that these sea level data sets all tell essentially the same story.  R2011’s big point is that the Rahmstorf model is “robust” given a variety of different historical data sources.  So it seems a tad bit strange that after going to all the trouble to point out these various sea level data sources and their similarities, he only gives the projection results of his model for three of them (CW06[2], CW11[3], and JE08[4]).

Of those three input sea level data sets, only two of them give similar sea level projections for the 21st century.  The outlier which results from CW11 shows significantly lower sea level projections.  Because of this, the outlier must be rejected (according to R2011), even though Church and White, the authors of both CW06 and CW11, clearly think the CW11 data is an improvement over their Cw06 data.

What about some of the other sea level rise data sets shown in R2011’s figure 1?  What type of 21st century sea level projections do they yield when inserted into Rahmstorf’s model?

Holgate’s sea level data

Let’s consider the sea level rise data of Simon Holgate.    The above image shows Holgate’s 2004 data[5], labeled HW04.  As I have previously pointed out, R2011 oddly includes Holgate’s 2004 data but ignores his 2007 data[6], H07.  I will consider both.  In my previous post I showed the results of Rahmstorf’s model when either CW06 and CW11 are input with six different combinations of reservoir storage and ground water depletion inputs.  The following two graphs show the results in the same format using HW04 and H07 (instead of CWo6 and CW11) with the same combination of reservoir storage and ground water depletion inputs.  I have kept the horizontal axis scaling the same as in the previous post to highlight the different results when Church and White data is used and when Holgate data is used.  Data files with all the specifics of this data are at the bottom of the post.

FIGURE 2. Sea level rise projections for the 21st century based on my implementation of Rahmstorf’s model under the RCP45 emissions scenario (Moss, 2010)[7] for Holgate sea level data coupled with various combinations of reservoir storage and groundwater depletion data inputs.
FIGURE 3. Sea level rise projections for the 21st century based on my implementation of Rahmstorf’s model under the RCP85 emissions scenario (Moss, 2010)[7] for Holgate sea level data coupled with various combinations of reservoir storage and groundwater depletion data inputs.

For comparison, here are the previously posted results using Church and White sea level data…

 RCP45

 RCP85

Hmmm…

Didn’t R2011 imply that those various sea level data sets shown if figure 1, above, told the same essential story?  Yes, I believe he did!  That is why they overlaid the same quadratic fit onto all of them.

And didn’t R2011 say that their model was “robust?”  Yes, I am quite certain that they did!  In fact the word “robust” was in the title of their paper, and they said…

“We determine the parameters of the semiempirical link between global temperature and global sea level in a wide variety of ways…We then compare projections of all these different model versions (over 30) for a moderate global warming scenario for the period 2000–2100. We find the projections are robust

and

“we will systematically explore how robust semi-empirical sea level projections are with respect  to the choice of data sets”

So, they claim to use “a wide variety of ways” to look at “all these different model versions (over 30).”  They show plots of seven different sea level data sets and imply their similarity.  But they only show projections based on three of them.  Then they reject the projections based on one of the three, even though it is arguably the best sea level data of the bunch.

What do they say about their model’s projections based on the “wide variety” other sea level data sets that look so good overlaid with the same quadratic fit…?

Cricket. Cricket.

How would R2011 reject the projections based on the Holgate data?

How would R2011 reject the projections based on the Holgate data that I have shown above in figures 2 and 3?  Well they would undoubtedly point out that the fit parameter, To (the so called baseline temperature, is way too low.  Recall, R2011 finds To to be on the order of -0.4 °C (below the 1950 to 1980 global average).  When Holgate’s sea level data is used, To is on the order of -4.0 °C.  Hey Rahmstorf, don’t blame me, its your model!

Maybe one of these days I will write a justification for a large negative To.  It is really quite simple.  But I am going to conclude for today.

Which of the many projections do I endorse?

Which projections are better – the ones based on CW06, CW11, JE08, HW04, or H07?  None of them.  As I have pointed out over and over, the Rahmstorf model is bogus, bogus, bogus.  I have now shown, again, that it is also not robust.  It is only marginally better than a random number generator.  HIgher temperatures would likely lead to higher sea levels, but Rahmstorf’s model is useless in determining how much.

Data files with specifics of of my implementation of Rahmstorf’s model using Holgate sea level data

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Chao 2oo8
Ground water depletion: none
Result files…
Summary: vr-summary-121110-165152.doc
Inputs: vr-input-image-121110-165152.png
Fit: vr-fit-image-121110-165152.png
Projections: vr-projections-image-121110-165152.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2010 extrapolated to 1880
Result files…
Summary: vr-summary-121029-132349.doc
Inputs: vr-input-image-121029-132349.png
Fit: vr-fit-image-121029-132349.png
Projections: vr-projections-image-121029-132349.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2010
Result files…
Summary: vr-summary-121029-132148.doc
Inputs: vr-input-image-121029-132148.png
Fit: vr-fit-image-121029-132148.png
Projections: vr-projections-image-121029-132148.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2012
Result files…
Summary: vr-summary-121105-230616.doc
Inputs: vr-input-image-121105-230616.png
Fit: vr-fit-image-121105-230616.png
Projections: vr-projections-image-121105-230616.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Pokhrel 2012 extrapolated back to 1900
Ground water depletion: Pokhrel 2012 extrapolated back to 1900
Result files…
Summary: vr-summary-121029-133403.doc
Inputs: vr-input-image-121029-133403.png
Fit: vr-fit-image-121029-133403.png
Projections: vr-projections-image-121029-133403.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Pokhrel 2012
Ground water depletion: Pokhrel 2012
Result files…
Summary: vr-summary-121029-132906.doc
Inputs: vr-input-image-121029-132906.png
Fit: vr-fit-image-121029-132906.png
Projections: vr-projections-image-121029-132906.png

Sea level data: Holgate 2007
Reservoir storage: Chao 2008
Ground water depletion: none
Result files…
Summary: vr-summary-121029-133753.doc
Inputs: vr-input-image-121029-133753.png
Fit: vr-fit-image-121029-133753.png
Projections: vr-projections-image-121029-133753.png

Sea level data: Holgate 2007
Reservoir storage: Chao 2008
Ground water depletion: Wada 2010 extrapolated to 1880
Result files…
Summary: vr-summary-121029-135519.doc
Inputs: vr-input-image-121029-135519.png
Fit: vr-fit-image-121029-135519.png
Projections: vr-projections-image-121029-135519.png

Sea level data: Holgate 2007
Reservoir storage: Chao 2008
Ground water depletion: Wada 2010
Result files…
Summary: vr-summary-121029-134334.doc
Inputs: vr-input-image-121029-134334.png
Fit: vr-fit-image-1209121029-134334.png
Projections: vr-projections-image-121029-134334.png

Sea level data: Holgate 2007
Reservoir storage: Chao 2008
Ground water depletion: Wada 2012
Result files…
Summary: vr-summary-121029-135834.doc
Inputs: vr-input-image-121029-135834.png
Fit: vr-fit-image-121029-135834.png
Projections: vr-projections-image-121029-135834.png

Sea level data: Holgate 2007
Reservoir storage: Pokhrel 2012 extrapolated to 1900
Ground water depletion: Pokhrel 2012 extrapolated to 1900
Result files…
Summary: vr-summary-121029-175833.doc
Inputs: vr-input-image-121029-175833.png
Fit: vr-fit-image-121029-175833.png
Projections: vr-projections-image-121029-175833.png

Sea level data: Holgate 2007
Reservoir storage: Pokhrel 2012
Ground water depletion: Pokhrel 2012
Result files…
Summary: vr-summary-121029-140159.doc
Inputs: vr-input-image-121029-140159.png
Fit: vr-fit-image-121029-140159.png
Projections: vr-projections-image-121029-140159.png

_________________________________

_________________________________

[1]  Rahmstorf, S., et. al., “Testing the robustness of semi-empirical sea level projections” Climate Dynamics, 2011

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

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

[4] Jevrejeva, S., et. al. “Recent global sea level acceleration started over 200 years ago? ,”  Geophys. Res. Lett., 35, 2008

[5] Holgate, S. J. and Woodworth, P.L., “Evidence for enhanced coastal sea level rise during the 1990s,” Geophys. Res. Lett., 31, 2004

[6] Holgate, S.J., “On the decadal rates of sea level change during the twentieth century,” Geophys. Res. Lett., 34, 2007

[7] Moss, et. al., “The next generation of scenarios for climate change research and assessment,” Nature, 463, 2010

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Rahmstorf (2011): Robust or Just Busted (Part 5): Why a paper about “robustness”

September 29, 2012

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

What does R2011 mean by “robust?”

What does Rahmstorf mean when he says his model linking sea level to temperature is “robust?”  Simply this: when the inputs that he deems acceptable are inserted into his model, he gets the results he likes.

How does he decide which inputs are acceptable?  Easy – if they yield the results he likes, then they are acceptable.  It is a very simple and efficient system of logic!

Why a paper about “robustness?”

Rahmstorf and his associates have a pressing need to defend their sea level rise projections.  I have presented a host of reasons why his model is bogus.  One of the most embarrassing is that one of his fit parameters, that he expected to be positive, is in fact negative for every combination of input tried.  This leads to all kinds of bizarre results (see here, here and here , for example).  The other is that his sea level projections dropped dramatically when his preferred source of 20th century historical input data updated their data set.

This “robustness” paper (R2011) is a stumbling attempt to dismiss the revised sea level data from the source that he had previously enthusiastically used.

A quick recap

Rahmstorf’s model, which I will refer to as the VR2009[2] model, attempts to relate global sea level rise to global temperature through the following formula…

where H is sea level and T is temperature.  Insert historical data for H and T,  and solve to a, b, and To.  Then insert projected temperatures for the 21st century and calculate projected sea level rises for the 21st century.  The VR2009 model and approach have an amazing number of problems and the list just keeps getting longer.  There is a whole family of realistic temperature scenarios for the 21st century that cause this model to yield ridiculous results (see here).  The root of most of these problems comes from the fact that every set of historical sea level inputs and temperatures that Rahmstorf and associates have tried result in a negative b.  That includes every set of input data considered in R2011 (see figure 1, below).

Model inputs and projections in R2011

(click to enlarge) …

FIGURE 1. R2011’s projections of 21st century sea level rise and baseline temperatures under the RCP45 emissions senario (Moss, 2010)[3] for various temperature and sea level input data sets.

I have circled the results R2011 likes.  As you can see, nothing involving the Church’s and White’s 2011 sea level data (CW11)[4] meets R2011’s  quality standard.  R2011 has determined that Church’s and  White’s 2006 sea level data (CW06)[5] is better than Church’s and White’s 2011 data, despite the fact that Church and White obviously think their updated 2011 data is better.

It comes down to To

Why does R2011 think the 2006 sea level data is better than the improved 2011 sea level data?  Well, I have already explained that – the 2006 Church and White sea level data gives the results that R2011 wants – higher sea level rise projections for the 21st century!

But they can’t really say that.  Instead they say that the 2011 Church and White data leads to a baseline temperature, To, that they insist is too low.  To is the steady-state temperature deviation from the 1950-1980 average temperature at which Rahmstorf’s model says the sea level would be unchanging.

Look at the right side of figure 1.  It shows the baseline temperature that R2011 derived with the various sets of input data.  The values of To that meet with R2011’s approval average out to about -0.43 degrees.  But those based on CW11 average out to about -0.62 degrees C.  A difference of less than two tenths of a degree.

If you were to ask the authors of R2011 what other evidence do they have that To must be about -0.43 degrees, they will refer you to “Climate related sea-level variations over the past two millennia[6],” which used evidence from two salt marshes in North Carolina to corroborate this global value.  And they have great confidence in this independent confirmation (because two out of three of the R2011 authors were also authors on this paper).  Hmmm.

I will have more to say about R2011’s preference for To in a later post.

A few input combinations that R2011 did not show you

R2011 implies that it has tried some vast universe of input sea level and temperature data combinations in their model. They say “We then compare projections of all these different model versions (over 30)…”  Wow! Count them – over 30!

But there are many more possible combinations than that.  R2011 has picked a few cherries from a very prolific tree.

In figures 2 and 3, below, I have run several temperature and sea level input data sets in my implementation of Rahmstorf’s model.  In some cases my input combinations are the same as some found in figure 1.  In some cases they are different.  I have arranged the input combinations in chronological order, with older versions of input data on the bottom.  Notice a trend?  Figure 2 and figure 3 give projections based on the RCP45  and RCP85 emission scenarios, respectively.

FIGURE 2. Sea level rise projections for the 21st century based on my implementation of Rahmstorf’s model under the RCP45 emissions scenario (Moss, 2010) for various temperature and sea level input data sets.
FIGURE 3. Sea level rise projections for the 21st century based on my implementation of Rahmstorf’s model under the RCP85 emissions scenario (Moss, 2010) for various temperature and sea level input data sets.

As you can see, newer sea level data (whether it is actually sea level (CW06 vs CH11, or reservoir storage (RS) or ground water depletion (GWD)  modifiers) tends to lead to lower 21st century projections when inserted into Rahmstorf’s model.

Which projection do I endorse? None of them.  Make no mistake – the Rahmstorf model is bogus, no matter what the inputs are.  I am just playing games with it.  The Rahmstorf model is an illusion that hooks you with a simple truth: It is a pretty good bet that higher temperatures lead to higher sea levels.  But the Rahmstorf model is not much better than a Ouija board for quantifying how much.

There is much to be said about the results in figures 2 and 3.  The 48 files below give the long story that is summarized in figures 2 and 3.

Much more to come in later posts

Sea level data: Church and White 2006
Reservoir storage: Chao 2oo8
Ground water depletion: none
Result files…
Summary: vr-summary-120923-091214.doc
Inputs: vr-input-image-120923-091214.png
Fit: vr-fit-image-120923-091214.png
Projections: vr-projections-image-120923-091214.png

Sea level data: Church and White 2006
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2010 extrapolated to 1880
Result files…
Summary: vr-summary-120923-091326.doc
Inputs: vr-input-image-120923-091326.png
Fit: vr-fit-image-120923-091326.png
Projections: vr-projections-image-120923-091326.png

Sea level data: Church and White 2006
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2010
Result files…
Summary: vr-summary-120923-091413.doc
Inputs: vr-input-image-120923-091413.png
Fit: vr-fit-image-120923-091413.png
Projections: vr-projections-image-120923-091413.png

Sea level data: Church and White 2006
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2012
Result files…
Summary: vr-summary-120923-091517.doc
Inputs: vr-input-image-120923-091517.png
Fit: vr-fit-image-120923-091517.png
Projections: vr-projections-image-120923-091517.png

Sea level data: Church and White 2006
Reservoir storage: Pokhrel 2012 extrapolated back to 1900
Ground water depletion: Pokhrel 2012 extrapolated back to 1900
Result files…
Summary: vr-summary-120923-091643.doc
Inputs: vr-input-image-120923-091643.png
Fit: vr-fit-image-120923-091643.png
Projections: vr-projections-image-120923-091643.png

Sea level data: Church and White 2006
Reservoir storage: Pokhrel 2012
Ground water depletion: Pokhrel 2012
Result files…
Summary: vr-summary-120923-091727.doc
Inputs: vr-input-image-120923-091727.png
Fit: vr-fit-image-120923-091727.png
Projections: vr-projections-image-120923-091727.png

Sea level data: Church and White 2011
Reservoir storage: Chao 2008
Ground water depletion: none
Result files…
Summary: vr-summary-120923-091904.doc
Inputs: vr-input-image-120923-091904.png
Fit: vr-fit-image-120923-091904.png
Projections: vr-projections-image-120923-091904.png

Sea level data: Church and White 2011
Reservoir storage: Chao 2008
Ground water depletion: Wada 2010 extrapolated to 1880
Result files…
Summary: vr-summary-120923-091956.doc
Inputs: vr-input-image-120923-091956.png
Fit: vr-fit-image-120923-091956.png
Projections: vr-projections-image-120923-091956.png

Sea level data: Church and White 2011
Reservoir storage: Chao 2008
Ground water depletion: Wada 2010
Result files…
Summary: vr-summary-120923-092105.doc
Inputs: vr-input-image-120923-092105.png
Fit: vr-fit-image-120923-092105.png
Projections: vr-projections-image-120923-092105.png

Sea level data: Church and White 2011
Reservoir storage: Chao 2008
Ground water depletion: Wada 2012
Result files…
Summary: vr-summary-120923-092202.doc
Inputs: vr-input-image-120923-092202.png
Fit: vr-fit-image-120923-092202.png
Projections: vr-projections-image-120923-092202.png

Sea level data: Church and White 2011
Reservoir storage: Pokhrel 2012 extrapolated to 1900
Ground water depletion: Pokhrel 2012 extrapolated to 1900
Result files…
Summary: vr-summary-120923-092330.doc
Inputs: vr-input-image-120923-092330.png
Fit: vr-fit-image-120923-092330.png
Projections: vr-projections-image-120923-092330.png

Sea level data: Church and White 2011
Reservoir storage: Pokhrel 2012
Ground water depletion: Pokhrel 2012
Result files…
Summary: vr-summary-120923-094501.doc
Inputs: vr-input-image-120923-094501.png
Fit: vr-fit-image-120923-094501.png
Projections: vr-projections-image-120923-094501.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] Moss, et. al., “The next generation of scenarios for climate change research and assessment,” Nature, 463, 2010

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

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

[6] Kemp, Horton, Donnelly, Mann, Vermeer & Rahmstorf,  “Climate related sea-level variations over the past two millennia,” PNAS, 2011