Posts Tagged ‘Chao’

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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

_________________________________

[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

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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

___________________________________

[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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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.

Conclusion

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.com.  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)

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