Archive for the ‘rise’ Category


What is RealClimate afraid of?

December 10, 2010

I left a comment over at RealClimate on December 4th 6th and they deleted it.   I expected them to delete it, since that is what they have done before.  I had the foresight to take a screen shot of their page with the comment and you can read it by clicking on the following image.  Yes it was off-topic, but they don’t seem to delete other off-topic (sycophantic) comments.   You can make your own judgement about why they deleted it.   

My comment dealt with a very serious issue that needs to be addressed by Stefan Rahmstorf – he can only ignore it for so long.

The issues pointed out in the comment are covered in more depth here, here, and here.

If you have read the three above links, then please answer the following poll…

I’m sorry that I spelled “Rahmstorf” incorrectly in the salutation of my comment.  My name is also frequently spelled wrong, but I’m used to it.


Rahmstorf (2009): Off the mark again (part 10). Sea level projections exaggerated by factor of 2

November 28, 2010

This is part 10 of a series on Vermeer’s and Rahmstorf’s 2009 PNAS paper, “Global sea level linked to global temperature“  (referred to as “VR2009″ in this series of posts).

In my last post I pointed out that VR2009 used out-date sea-level data from Church and White, and did not include a correction for groundwater depletion.  Even if  you believe the validity of their very dubious model, these two flaws cause VR2009’s projections of sea level rise for the 21st century to be overstated by a factor of two.

VR2009 proposed a model linking sea level rise to global temperature based on the following equation…

When Vermeer and Rahmstorf used inadequate sea level data they found

a = 5.6 mm/year/K
b = -49 mm/K
To = -0.41 K

When I used the superior sea level data that included the Church and White sea level update and the Wada groundwater depletion correction I found

a = 3.1 mm/year/K
b = -52 mm/K
To = -0.71 K

VR2009 said that they applied their model with their fit parameters to 342 temperature scenarios.  How did they come up with 342?  They borrowed them from the IPCC, who applied six IPCC SRES emission scenarios to nineteen Atmosphere-Ocean General Circulation Models (AOGCM) with high, medium and low-carbon cycle feedbacks (6 x 19 x 3 = 342).

IPCC SRES emission scenarios

The six emission scenarios are the inventions of the IPCC and are summarized in the IPCC  SRES (Special Report on Emission scenarios).  Their differences lie in their assumptions about global economic, technological and social changes during the coming decades.  Each set of assumptions results in different levels of CO2 emissions.  Under some assumptions the use of fossil fuels will increase dramatically, but under others the use of fossil fuels will reach a peak in mid-century and then start to drop off.

Carbon Cycle feedbacks

The amount of predicted CO2 in the air during the 21st century depends on more than just the CO2 emissions. It also depends on carbon cycle feedbacks. For example, warmer oceans would remove CO2 from the atmosphere slower than colder oceans, everything else being equal. The possible feedbacks are not necessarily well understood or well quantified, and each AOGCM model handles them differently.

 Atmosphere-Ocean General Circulation Models (AOGCM)

There are about 2 dozen prominent Atmosphere-Ocean General Circulation Models (AOGCM) made by various groups around the world.  Each AOGCM purports to simulate the flow of energy and matter through atmosphere and oceans and therefore yield their evolution into the future.   The SRES emission scenarios and carbon cycle feedbacks can be plugged into each AOGCM, which calculate various parameters, including temperature, for each year of the 21st century. 

Combining IPCC SRES & Carbon Cycle feedbacks & AOGCMs

The IPCC 4th Assessment Report used 19 AOGCMs, three carbon cycle feedback schemes with six families of temperature scenarios, one for each SRES emission scenario (19 x 3 x 6 = 342).  These are the temperature scenarios used by VR2009.  These families of temperature scenarios are summed up in the following IPCC figure.

This is figure 10.26 from the IPCC AR4 Chapter 10, "Global Climate Projections." It shows the temperature projections for each of the six IPCC SRES emission scenarios averaged for the 19 AOGCM models and 3 carbon cycle feed backs and the standard deviations.

Figure 1. This is figure 10.26 from the IPCC AR4 Chapter 10, "Global Climate Projections." It shows the temperature projections for each of the six IPCC SRES emission scenarios averaged for the 19 AOGCM models and 3 carbon cycle feed backs and the standard deviations.

I do not have the 342 temperature  scenarios used to construct figure 1 and used by VR2009, but I am working on it.  The most extreme of these 342 temperature scenarios falls under the A1F1 emission scenario, and yields Vermeer’s and Rahmstorf’s widely echoed 1.8 meter sea level rise for the 21st century.  If I had the temperature data for that particular AOGCM/SRES emission scenario/carbon cycle feed back scenario, I would simply insert it into VR2009’s model using their fit parameters and then again using my fit parameters.  Their fit parameters would  yield 180 cm, and mine would yield about half of that.

Instead I have digitized the IPCC temperature data shown in figure 1, above.  My digitized version of the data is shown in figure 2, below.  Note that I have translated the temperatures about 0.25° higher than in figure 1 because the IPCC used the 1980-1999 temperature average for their zero point (see IPCC AR4, chapter 10, section 3.1), but VR2009 and I used the 1950 to 1980 temperature average as the zero point. The following image is a reproduction of the IPCC temperature data shown in figure 1, and the data can be downloaded here

Figure 2. Reproduction of IPCC AR4 figure 10.26 from data digitized from IPCC figure. I have added about 0.25 degrees to change the zero baseline from 1980-1999 to 1950-1980.

If VR2009’s model with their fit parameters (using the  out-dated Church and White sea level data without the Wada groundwater depletion correction) and my fit parameters (using updated Church and White sea level data and the Wada groundwater depletion correction) is applied to the average temperatures  (dark central curves) from the six scenarios in figures 1 or 2, then the difference in projected sea level rise is quite stark.

Figure 3. Sea level rises from averge temperatures in the six SRES scenarios.

Similarly, both sets of fit parameters can be used to calculate sea levels for the higher temperature scenarios that match the upper edge of the shaded areas in figures 1 and 2.

Figure 4. Sea level rises for higher temerature scenarios.

The Difference

This is pretty easy to see.  Figures 4 & 5 show that when the updated Church and White data are used and the Wada groundwater depletion correction is added the sea level rise rates are cut almost exactly in half…

Figure 5. Using the proper sea level data cuts VR2009's sea level rise projections in half.

It can be shown that this approximately 50% difference will occur for any of the 342 temperature scenarios the VR2009 used.


Vermeer’s and Rahmstorf’s model is bogus for the many reasons that I have explained in previous posts.  But even if the concept of their model were valid, it would still yield sea level rises that are two times too large when it starts with the out-dated version of Church and White sea data and neglects the correction for groundwater depletion.

Surely Vermeer and Rahmstorf are aware of the updated Church and White data.  That update occurred about the same time that VR2009 was published, and possibly before.  It would be a simple exercise for Vermeer and Rahmstorf  to update their fit parameters based on the updated Church and White data.  It would be instantly obvious to them that their extreme sea level rise projections are far too large.  Then they could write letters to the editors of the multiple publications that quoted their 1.8 meter projection and tell them about the lower numbers.  Or they could post some comments about the corrections on the endless list of blogs and websites that have repeated their extreme numbers. 

Heck, Stefan Rahmstorf even has the keys to the control panel over at  RealClimate is seen by at least a hundred times as many readers than my humble ClimateSanity.  Martin Vermeer has even held forth as a guest commentator at RealClimate with a self congradulatory love-fest over the publication of VR2009.   (Despite the all-star cast over at RealClimate, they do seem to have a slight problem handling non-sycophantic comments.)

You would think that Stefan and Martin could get together and post an article at RealClimate with corrected fit parameters for their profound dubious model.  They could bill it as “Good News:” maybe the world is not coming to an end after all. 

Nah, that wouldn’t be any fun.


Update 1/29/11

I realized that I inadvertently made my sea level calculations for the above for figures 3, 4, and 5 using To=-0.44 K.  I actually calculated To to be -0.71 K.  Mea culpa.   As of today, the graphs in figures 3 and 4, and the ratios in figure 5 are corrected to my calculated value of  To=-0.71 K.  It makes very little difference to the conclusions. (Tom Moriarty)


Rahmstorf (2009): Off the mark again (Part 6 and a half). Gory details

June 11, 2010

This is to fill in some of the details of the math used to reverse Vermeer’s and Rahmstorf’s model ( Global sea level linked to global temperature, 2009, PNAS) to give temperature as a function of sea level.  In my previous post I skipped over these details for the sake of brevity.

In various posts I have used Vermeer’s and Rahmsorf’s (VR2009 for rest of this post) model that relates sea level rise rate to global temperature to see how different temperature scenarios would result in sea level rise rates, according to VR2009.  In my previous post I inverted their model to calculate the temperature from satellite sea level data.  Here are the details of that inversion…

The Math

Starting with VR2009’s model…

Re-arranging equation 1 gives…

If we assume that dH/dt is a known function of t, then equation 2 is a first order linear differential equation.  So, multiplying both sides of equation 2 by exp(at/b) gives..

The left side of equation 3 can be re-written…

If both sides of equation 4 are integrated, then…

Solving for T….

Remember, we are assuming that dH/dt is a known function of t.   We will get that function by taking the derivative of a quadratic fit of satellite derived sea level data.   That is, the satellite sea level data will be fit to…

So, substituting equation 7 into equation 6 gives….

We can solve the integral on the right side of equation 8 as follows…

Substituting equation 9 into equation 8 gives…

So far, so good.

a, b, and T0 are given by VR2009.  c1 and c2 are determined from the best fit of H to a quadratic.  That leaves only c4 as an unknown.  If initial conditions (that is, the temperature, T’,  at time, t’) are known, then equation 10 can be solved for c4

Initial conditions

There are a variety of sources for getting initial conditions (temperature, T’,  at time, t’) to calculate c4 in equation 11.  However, the final results of the temperature that comes from equation 10 is highly sensitive to c4, which is in turn highly sensitive to the chosen initial conditions.  VR2009 used the GISS global temperature to derive their model, so we will first consider the GISS Monthly Mean Surface Land/Ocean Temperature Anomaly (which covers 1996 to the present).

For example, we could choose t’ = 1998.12 with T’ = 0.8 °C during the peak of an extreme El Nino.  In this case equation 10 would give a temperature rise of about 2 °C between 1996 and 2010.  Or we could choose t’ = 1999.38, when the global temperature was 0.21 °C  (according to GISS).  For this choice the temperature drops from about 1996 to 2001, and then rises about 0.5 °C by 2010.

These extreme initial condition choices seem to yield extreme results.  Perhaps it would be better to choose smoothed temperature data.  The following plot shows an overlay of the plain GISS Monthly Mean Surface Land/Ocean Temperature Anomaly, and with a 7 month running average (generated by me), as well as the GISS Annual Mean Land/Ocean Surface temperature anomaly.  It seems prudent to select an initial time where the monthly data, the 7 month smoothed data, and the annual mean data are all about the same, as marked in the image, below.

I decided to pick T’ = 2001.5 and t’ = 0.44 °C (GISS monthly T = 0.51 °C, GISS monthly T with 7 month average = 0.46 °C, GISS yearly average t = 0.48 °C, and GISS 5-year mean T = 0.44 °C).

Applying my choice of initial conditions to equation 11 to determining c4, inserting the result into equation 10, and plotting T vs. t from equation 10 for 1996 to the present gives the following result.

So, Vermeer’s and Rahmstorf’s model requires an unrealistic temperature rise from 1996 to the present to reproduce the sea level rise rate over that period.  The decade from 2000 to 2010 (during which the GISS data shows a more or less constant) would have required a temperature increase of almost 0.7 °C, according to VR2009.

This is just another reason to reject VR2009.

Try it yourself.

I have given any interested person with a basic understanding of calculus and differential equations everything needed to reproduce my results.  My conclusions are sound.  VR2009 is unrealistic.


Salmon and Sea-Level

August 8, 2009

I recently wrote about  the alarmist claim that sea level rise in British Columbia is going to have a serious negative impact on their Salmon population.  An environmental activist playing at journalist wrote for the Victoria Times Colonist:

“The spectre of rising sea levels and ecological change from climate disruption show land-use plans for Vancouver Island and the B.C. coast will need to be revisited and recalibrated to account for rapid and unabated climate change.”

“‘Once set in motion, sea-level rise is impossible to stop. The only chance we have to limit sea-level rise to manageable levels is to reduce emissions very quickly, early in this century. Later it will be too late to do much,’ says senior NASA scientist Stefan Rahmstorf in a recent article for the United Nations Office for the Co-ordination of Humanitarian Affairs.”

There may be a lot of man made obstacles to Salmon survival, such as dams, over-fishing, etc., but sea-level rise is not one of them. 

Let’s get right down to the nitty-gritty.

Salmon have been around for about 500,000 to 1,000,000 years, give or take a few hundred thousand.  This is not a praticularly long time, nevertheless, Pacific Salmon diversified into multiple species, including Cherry Salmon, Sockeye Salmon, Chinook Salmon, Pink Salmon, Chum Salmon, and Coho Salmon.  There are also Atlantic Salmon and even land-locked Salmon.

Will the sea level  rise of the 21st century end the salmon’s success?  Not likely.  Take a look at these sea-level rise rates from Alaska, one of the Salmon’s primary habitats:

Yes, that right, the sea level is dropping at almost all locations where it is measured in Alaska.  So, it doesn’t look like sea level rise is likely to be much of a threat to the salmon in Alaska or British Columbia

But let’s pretend for a moment that the seas will rise dramatically over the next century, or longer.  Would the Salmon survive this dire situation?   If the past is any indication, the Salmon should pull through.  Take a good look at the graph of Holocene sea-level in the graph below. 

Image created by Robert A. Rohde / Global Warming Art.  Go to

Image created by Robert A. Rohde / Global Warming Art. Go to

Notice that from about 12,000 14,000 years ago until about 8,000 years ago the sea rose about 120 100 meters.  So, the sea level rose about 2 meters per century for 40 60 straight centuries in the recent (geologically speaking) past!  But the Salmon somehow survived.

What effect did this sea-level rise have on the Salmon’s habitat?  The movie below shows Beringia, consisting of the eastern part of Siberia and Alaska from 21,000 years ago to the present.  Look what happens from 12,000 years ago to 8,000 years ago.  I would judge that as a pretty dramatic change of the Salmon habitat.  Yet they seem to have thrived.  I think they will survive sea-level rise this century.

Barengia 21,000 years ago to present. (NOAA)

Barengia 21,000 years ago to present. (NOAA)


Vancouver Underwater?

July 23, 2009

First Boston, now Vancouver.  According to the Times Colonist in Victoria, Canada, the folks in Vancouver and on Vancouver Island are in dire danger of sea level rise catastrophe.  They report:

“The spectre of rising sea levels and ecological change from climate disruption show land-use plans for Vancouver Island and the B.C. coast will need to be revisited and recalibrated to account for rapid and unabated climate change.”

“‘Once set in motion, sea-level rise is impossible to stop. The only chance we have to limit sea-level rise to manageable levels is to reduce emissions very quickly, early in this century. Later it will be too late to do much,’ says senior NASA scientist Stefan Rahmstorf in a recent article for the United Nations Office for the Co-ordination of Humanitarian Affairs.”

Really?  Here is 100 years worth of sea level rise data from the B.C. capital, Victoria, on Vancouver Island (Click on graphs to see full graph in its original context):

The sea level rise rate has not changed in Victoria in the last 100 years, even though CO2 levels have gone from about 290 ppm to about 380 ppm today.  Most of that CO2 increase occurred in the last 50 years.  You can see the danger that Victoria is in – I guess we better change the economy of the world in order to save them.  At the current rise rate the sea will rise 8cm (about 3 inches) in the next 100 years. 

If things are too scary in Victoria, then the folks living there might consider emigrating to the city of Vancouver, on the mainland about 50 miles north of Victoria.  They might feel better with the sea level rise rate there…

At the city of Vancouver the sea level has risen a whopping 3.7 (1.5 inches) cm in the last 100 years, and it doesn’t seem to be accelerating. 

But some of the folks in Victoria may not want to move to the mainland, preferring to stay on Vancouver Island.  If so, they could stay on the Island and move about 100 miles northwest to Tofino where they might finally feel safe from the terror of rising seas…

Alas, in Tofino the good people of Vancouver Island might have to contend with a dropping sea level.  At a rate of minus 1.59 mm per year, the ocean would drop 15.9 cm (about 6 inches) in the next 100 years. This dropping sea level might even be worse than a rising sea level, drying out estuaries and wetlands. Everybody knows the only safe sea level is a static sea level.

But seriously folks…

The rate of sea level rise varies form place to place and depends on a lot of factors.  Changes in ice inventories, currents, and geological effects, such as glacial isostatic adjustment all contribute and are worthy of study and measurement.  But they should no be used to foster panic for political ends.

Any serious discussion of the effect of sea level rise in Vancouver Island or the British Columbia sea coast would have to include  the data I have shown above.  So why isn’t this data even mentioned in the Times Colonist article?  You would think a journalist who is seeking the truth, wherever it may lead, would manage to find this data.  But it turns out that the author of the article is not a journalist, but rather Chris Genovali, the executive director of Raincoast Conservation.  Chris Genovali is probably a fine person, and Raincoast Conservation may be a fine organization – I don’t know.  But Genovali is not an objective person when it comes to the issue of sea-level rise in British Columbia or Vancouver Island.


My experience with Rahmstorf’s non-linear trend line

July 20, 2009

One of the original impetuses for me to start blogging was my experience with Stefan Rahmstorf concerning his 2007 paper “A Semi-Empirical Approach to Projecting Future Sea-Level Rise” (Science, 315, 2007).  I posted a several part critique on my old blogspot site, which I later ported over to this wordpress site. 

But this was only part of the story.  I  have decided to tell the rest of the story after reading “The Secret of the Rahmstorf ‘Non-Linear Trend Line’” at Steve McIntyre’s Climate Audit

Rahmstorf’s sea-level rise paper was based on plotting 120 years worth of sea -level rise rates vs each year’s corresponding global temperature.  Since both of these sets of data are quite noisy, Rahmstorf said ” Both temperature and sea-level curves were smoothed by computing nonlinear trend lines with an embedding period of 15 years.”

Rahmstorf referenced “New Tools for Analyzing Time Series Relationships and Trends” by Moore, et. al. (Eos, 86, 2005) for his nonlinear trend line smoothing technique.  This short paper refers to a variety of techniques for handling time series, including varieties of wavelet analysis and spectrum analysis.  The Moore paper invested several paragraphs on the use of Monte Carlo Single Spectrum Analysis for finding nonlinear trends in sea level and sea temperature, with the reader referred to a variety of  other papers to get the details. 

I waded hip deep into these papers  to get a handle on this new “nonlinear trend line” technique that led Rahmstorf to his startling projection of a huge sea level rise over this century.  I shouldn’t have wasted my time.  I found that I could essentially reproduce his results in an Excel spreadsheet by simply smoothing the original sea-level and temperature data with a 15 year FWHM Gaussian filter. 

Here is Rahmstorf’s sea-level rise rate vs. temperature after his nonlinear trend line smoothing and 5 year binning, followed by my sea-level rise rate vs. temperature after my 15 year FWHM Gaussian smoothing and 5 year binning, and finally, my version of the data without binning.

Rahmstorf's sea level rise vs T

Moriarty's sea level rise vs T binned

Moriarty's sea level rise vs T not binned

Rahmstorf binned his 120 data points into 24 bins containing 5 points each.   The binning was not needed to  remove noise that obfuscated his salient point – the data had already been smoothed through his non-linear trend line technique.     The binning could not be justified by claiming that it somehow made the plot of sea level rise rate vs temperature easier to read.  It actually reduced the amount of information to the reader by removing obvious real structure in the data.

I believe that Rahmstorf deliberately presented his data in a way calculated to deceive.  These are harsh words, and I say them with regret.

The only plausible reason that I can come up with for binning the 120 data points into 24 bins is because the resulting 24 points looked like they could conceivably be fit to a line without failing the laugh test.  Seeing the original 120 smoothed data points made it perfectly clear that there was not a linear relationship between the sea-level rise rate  and the temperature.  The full set of 120 data points also make it clear that when the temperature remains constant the sea level rise rate drops, in direct contradiction of one of Rahmstorf’s own working assumptions.

It turned out that Rahmstorf’s startling conclusion about extreme sea-level rise had nothing to do with any new sophisticated data analysis techniques for deriving nonlinear trend lines.  I got the same results as him using a simple spreadsheet.  Rather, his startling results came from his bogus interpretation.  Specifically, here are the three problems I identified:

1) The assumption that the time required to arrive at the new equilibrium is “on the order or millennia” is not borne out by the data. More…

2) Sea level rise rate vs. temperature is displayed in a way that erroneously implies that it is well fit to a line.  More…

3) Rahmstorf extrapolates out more than five times the measured temperature domain. More…

Rahmstorf’s code and peer review

In the midst of my wandering through a mathematical labyrinth to reproduce Rahmstorf’s results, before my simple excel spreadsheet approach, I asked Rahmstorf several questions via email.  Amazingly, he offered to send me his code, to which I happily accepted.  Here is what he said when he sent it (emphasis added by me):

From: Stefan Rahmstorf [mailto:rahmstorf@xxxxxxxxxxxx.xx]
Sent: Monday, August 20, 2007 13:20
To: Moriarty, Tom
Subject: Science paper

Dear Tom, see attached. Please report any issues you encounter, you are the first outside person to test this code.

Cheers, Stefan

Stefan Rahmstorf

So, the punchline is that although his data and results had been published a half a year before in the journal Science,  the highly regarded, unassailable, peer reviewed pinnacle of scientific research , I was “the first outside person to test his code.”

Again, I offer this harsh criticsm with regret, because Rahmstorf was, after all, kind enough to send me his code.


Impure thoughts about sea level rise

June 5, 2009

There has been some back and forth about the magnitude, consequences and proper response to sea level rise here, here, herehere and here. The alarmists would like to dismiss the evidence of man’s ability to cope. I have wondered why they think the history of free and motivated people pushing back against the ocean is irrelevant. But now this comment by Ed Darrell (from here) puts the alarmists’ mindset into clear focus.

Ed Darrel said:

Yeah, I saw the chart that said sea level is rising in Boston. It’s been rising as long as it’s been measured there, hasn’t it?

Not once did the harbormaster get together with the Brahmins of Boston to say, “We need to make Boston Neck thicker because of rising sea level.”

I didn’t say sea level didn’t rise. I said none of the landfills was done in response to rising sea level. The land was filled out for commercial needs, for commercial wants, and because when the weather created a bunch of new land, it could be used. Not once was any part of the harborscape built out to meet rising ocean levels.

So, to claim that Boston illustrates that the world can cope, is simply in error. Of course the world can cope in major harbors where there is plenty of commercial activity to combat a modest increase in ocean level.

What was your point?

So, apparently, Boston’s experience doesn’t count as evidence of man’s ability to push back against the ocean. Why? Because their actions were motivated by impure thoughts.

If I have properly deciphered Ed’s logic, then the following scenario does not show man’s ability to cope with the ocean:

Land in the Boston area is crowded and valuable. Engineers and the ‘Brahmins of Boston’ say “We could boost commerce by making Boston Neck thicker and recovering land from the sea.” Engineers design ways to push back the ocean and follow through on their plans.

But the following scenario would demonstrate man’s ability to cope with the ocean:

Land in the Boston area is crowded and valuable. Engineers and the ‘Brahmins of Boston’ say “We could fight against global warming by making Boston Neck thicker and recovering land from the sea.” Engineers design ways to push back the ocean and follow through on their plans.

Why would the second scenario illustrate man’s ability to cope with the ocean, but the first does not? In both cases they have the same problem and the same outcome. Here’s why: in the first scenario the engineers’ and brahmins’ motivations are impure, in the second scenario the engineers’ and brahmins’ motivations are pure.

Well, at least we have found some common ground. That is, we agree that the sea level has been rising near Boston, and we agree that Boston has been successful in pushing back the ocean.  But Ed can’t seem to understand that even if the ocean had not been rising near Boston for the last hundred years, their experience shows that they have the ability to cope if it started rising now.

Just Plain NutsVell, Mr. Darrell, I think vee have made some veal progress.  At our next session vee vill analyze your repression of impure thoughts concerning sea level vise.