The university of Colorado has recently updated their sea level graph from the TOPEX satellite data. The 60 day smoothed trend is still stalled and shows no rise over what was seen since the peak in mid 2010:
Data
Raw data (ASCII) | PDF | EPS
Here’s the same data with season variation retained, but the really interesting data is from ENVISAT, which shows no upward trend:
(Graph from Steve Goddard). Envisat data here: ftp://ftp.aviso.oceanobs.com/
Sea level is lower than eight years ago, and according to the graph above just passed the lowest annual peak in the Envisat record.
It’s damned inconvenient.
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The largest rise in sea level occurs in these parts twice a day, it’s about 5.3 meters, 530 centimeters, 5,300 millimeters but it does vary during the month, wind direction and barometric pressure.
Anything that I can think of probably already exists. Is there a thousand year old sea level data set averaged together and only from a few locations that are scattered around the world? For example they could be from England, Greece, Egypt, China, India.
And at what rate per century?
“1DandyTroll says:
February 14, 2012 at 3:04 pm
Where exactly have all that extra water, that’s been dumped into the ocean for the last 20 years, been amassing itself? Is there some great blob protruding from a secret place somewhere, waiting to deliver sudden flooding when doom finally strikes?”
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Very interesting graphic on all the earth’s water compared to the rest of the earth!
http://ga.water.usgs.gov/edu/earthhowmuch.html
To me, at least, the break with the trend started about 2006 where there appears to be a down step in the data, followed by a decreasing trend line.
James Sexton says:
February 14, 2012 at 3:28 pm
Here’s what I want to know…… why do people accept the idiotic conflated graph to begin with? They took 3 separate data sets, which each have 3 separate values and threw them together and no one says boo. Go to avisio and click on each one separately…… the values are entirely different. Given that methodology one can put anything together to show just about anything. Its stupid.
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Was it you or Steve that showed the graph with the correct y axis plotted?
If you start the Envisat record on the correct y axis, sea levels have been falling all along….
….you got that thing?
On the topic of dubious (a nice word for fraudulent) data, look what Steven Goddard and a commenter there have found:
http://www.real-science.com/smoking-gun-giss
How will they ever explain that?
I think people REALLY need to step back from this data and realize the TOPEX/Jason error bars are NOT being properly presented. For example:
http://www.tsgc.utexas.edu/topex/activities/elnino/sld006.html
“To get the height of the satellite above the ocean, the time for the pulse to return has to be converted to range using the speed of light. However, the speed of light is constant only in a vacuum. The radar pulse travels through the atmosphere twice, where it is refracted by air molecules, water vapor, free electrons, and is partially scattered by surface waves. The size of these errors add up to more than 3 meters. However, all of them can be measured or modeled.
Finally, the precise location of the satellite needs to be known, since the sea-level is the difference between the satellite location above the center of the Earth and the height of the satellite above the ocean. If the satellite location were only good to one meter, then the sea-level measurement would only be good to one meter.
But, how accurate is the image on the previous slide? The accuracy is amazing, considering all of these problems listed above: about 2 to 3 cm (1 in). ”
That’s 20-30 mm. That means for the Topex period there was statistically no increase.
The advertised precision is 3.3 cm (+/- 33 mm)
http://en.wikipedia.org/wiki/TOPEX/Poseidon#Measurements_Continue
When I see a graph where the two end points have overlapping error bars and someone claims there is a statistical difference I cringe.
“Sorry, been too long since statistics class. How do we get 0.4 mm/yr when we have positional error bars on the sat itself of 20mm. Did someone prove the positional errors cancel out with enough samples to obtain this precision?”
This is just oversampling. You can have detect changes smaller than the individual confidence intervals if the sample is large enough. Compare for example a hypertension clinical trial measuring small changes in blood pressure, even though the measurement instrument variability and inter- and intra-patient variability are quite large.
Burch says:
February 14, 2012 at 2:45 pm
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They claim this as a result of the average of large numbers.
There is a further problem, unlike measuring the land which is static, the sea is in a constant flux:.swell, waves, tides etc There is also tectonic plate movement altering the volume of the ocean and rebound from the ice age.
The idea that we can measure sea level changes to within a couple of mm is overly optomistic. .
Alcheson says:
February 14, 2012 at 1:34 pm
If the huge amount of missing heat that the earth is supposedly accumulating is going into the oceans, shouldn’t the oceans be rising substantially?
Yes they should. And they’re not. This is the single most important piece of evidence that climate warming has overturned and ended and that climate cooling has begun.
The acrid stench of establishment desperation is most clearly in evidence at the “Correction” of 0.3 mm/year added May, 5th 2011, due to a “Glacial Isostatic Adjustment (GIA)”.
Check out the global salinity map – the seas off Kamchatka, Alaska and California are practically fresh! Any connection with north Pacific sea ice?
http://www7320.nrlssc.navy.mil/global_ncom/glb8_3b/html/plots/glb/sss.gif
Also the colour map of sea level rise rate shows that Australia’s tectonic equator-ward dash seems to be making a bow-wave:
http://sealevel.colorado.edu/files/current/sl.jpg
while by contrast the descending north west Pacific seems to be inviting California to fall into it.
Al Gored says:
February 14, 2012 at 3:48 pm
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I seem to recall having read rather recently that the Icelandic Authorities do not accept the GISS data for Iceland. I may be mistaken but I am fairly convinced I have seen something to that effect.
James Sexton says:
February 14, 2012 at 3:28 pm
James, you made an excellent point and then followed it up with the exact same logic you used to criticize the 3 separate data sets. You plot sea-level change from 2005-2011. Variations over such a short time period mean nothing. Why not plot from 1900 or at least 1950. From your (kind of silly) graph, from mid 2006 through 2010 there was a catastrophic increase from 47.6 to 49.4 mm. Man the lifeboats. Then from 2010 to 2011 sea level went from 49.4 right back to 47.6 mm in one year! The world is saved. Unless the trend is real and linear forever. At that rate we’ll have no oceans by 2035. Unless that was a typo.
I read a book on Samuel de Champlain where his home town was a port in 1600 and today is located 2 km inland. With that kind of land movement, how can we even have a global sea-level (to within mm!!! updated every year – hahaha). But I liked your point about the 3 data sets meaning nothing.
Update: Jason-2 data is:
http://idn.ceos.org/portals/Metadata.do?Portal=idn_ceos&KeywordPath=|[Freetext%3D%27CNES%27]&NumericId=32577&MetadataView=Full&MetadataType=0&lbnode=mdlb1
“The sea surface height shall be provided with a global and ultimate rms accuracy of 3.4 cm (1 sigma) over 1 second averages along JASON-1 ground-tracks for typical sea-state conditions of 2 m SWH and 11 dB sigma-naught.”
+/- 34 mm. Call me foolish, but I see nothing but ghosts in the noise.
AJ check your email
Fresh water is densest at 4 degrees c. sea water gets denser as it cools towards it’s freezing point of about minus 2 degrees C. It is my belief that the missing ocean heat has been transmitted through the open Arctic sea water because of it’s lower than average sea ice coverage. Sea ice acts as an insulator.
AJStrata says:
February 14, 2012 at 3:52 pm
The 3 meter accuracy is probably in reference to the 1990s when the US military was dithering around with GPS accuracy. My $200 Garmin is probably within +/- 10 m and we have used a differential Garmin with base station correction to get to within cm. You can do better than cm but not after 3 cups of coffee.
Isn’t the graph just a caveat about fitting straight lines to things that are almost definitely not linear and then trying to draw a conclusion about the slope of the line???
As I recall, the TOPEX, Jason-1, Jason-2 chart declined from 3.2mm/year to 3.1mm/year quite some time ago. U. Colorado quietly posed the reduced number without announcement or fanfare at the time. When it dove down to 2.85mm/year in 2011, rather than posting the new numbers, U. Colorado Boulder changed their averaging formula to a “new and improved” version and added in a fudge factor (arbitrarily derived in my opinion) to account for “sea beds slumping from the added weight of water”. Between those two adjustments, the average rate of rise was magically restored to 3.2mm/year. In view of their having quietly in this most recent publication again lowered the rate to 3.1mm/year even with the changes in method and the “fudge factor” thrown in, I’d say the Envistat Unadjusted Sea Level chart comes pretty close to telling the truth.
Is it possible to describe a chaotic system with a statistical model? Perhaps the statistical model could be applied to the behavioral envelope which is remarkably static over human epochs, while the behavior is subject to temporally-constrained forecasts, since it is particularly dynamic, even within the scope of hours. I also wonder how much information is lost when we assume independent multi-variate distributions.
It is quite clear that the Earth system, including the climate subset, is best described by an ensemble of models. This is likely due to an incompletely, and the evidence would suggest insufficiently, characterized system. The inputs are characterized by subterranean, terrestrial, extraterrestrial, and conscious (e.g. human activity) effects. Not only is the system characterized by a diverse assortment of high-level features, but it is also unwieldy, which limits comprehension of its extended dynamics.
It would seem that the use of models would increase the risk in any forecast, with the risk approaching zero with a perfect model. Is that increased risk also considered when predictions are reviewed? At what point is action, especially radical action, considered justifiable? Also, if we acknowledge the system is chaotic, it would seem inappropriate to pursue unidirectional adaptation. That would also increase the risk associated with any mitigation efforts.
Why would sea level “co-operate” with carbon dioxide levels? That would require some sort of dreamed-up, shall we say, greenhouse effect. /sarc
Anyone who thinks about these points will realise there is no greenhouse effect …
(1) The direction of net radiative energy flow can be the opposite of the direction of heat transfer. If you have a warmer object (say 310 K) with low emissivity (say 0.2) and a cooler object (say 300 K) with much higher emissivity (say 0.9) then net radiative energy flow is from the cooler to the warmer object. Yet the Second Law says heat transfer is from hot to cold. So, there is no warming of the warmer body by any of the (net) radiative energy going into it.
(2) Any warming of a warmer surface by radiation from a cooler atmosphere violates the Second Law of Thermodynamics. Consider the situation when the surface is being warmed by the Sun at 11am somewhere. Its temperature is rising and net radiative energy flow is into the surface. How could additional thermal energy transfer from the cooler atmosphere to make the surface warm at a faster rate?
Clearly radiation from a cooler atmosphere cannot add thermal energy to a warmer surface. The surface molecules scatter radiation which has a peak frequency lower than the peak frequency of their own emission, and so no radiative energy is converted to thermal energy. (This was proved in Johnson’s Computational Blackbody Radiation.), So the atmospheric radiative greenhouse effect is a physical impossibility.
dorlomin says:
February 14, 2012 at 3:27 pm
Looks to me like the current rate of decline is…er…”unprecedented”.
I guess in the “perception is reality” category, how does one explain the smoothed red curve superimposed on the sea level data by Aviso in this plot?
http://www.aviso.oceanobs.com/fileadmin/images/news/indic/msl/MSL_Serie_EN_Global_IB_RWT_GIA_Adjust.png
Take a real close look at the right hand side and the smoothed curve relative to the latest data points.
James Sexton says:
February 14, 2012 at 3:28 pm
according to Envisat, we’ve had 7 years of declining sea levels.
And y = -0.0035x
Guess what? The temperature slope since 2005 is -0.00325098 per year
http://www.woodfortrees.org/plot/wti/from:1980/plot/wti/from:2005/trend
#Time series (wti) from 1979 to 2012
#Selected data from 2005
#Least squares trend line; slope = -0.00325098 per year
I know the units are different, however we would expect there to be a correlation between falling temperatures and falling sea levels. Now if we can only figure out the sea levels during the MWP and LIA, we can figure out how warm or cold it was then. Does anyone have any information here?
James Sexton says:
February 14, 2012 at 3:28 pm
“I know the units are different, however we would expect there to be a correlation between falling temperatures and falling sea levels. Now if we can only figure out the sea levels during the MWP and LIA, we can figure out how warm or cold it was then. Does anyone have any information here?”
Aren’t you forgetting there is supposedly an 800-year lag between atmospheric temperature changes and ocean responses? Wasn’t that the basis for the theory that historic CO2 variations were driven by atmospheric temperature variations rather than the other way around? (The solubility argument,)
The breakpoint at 2006 with the sudden decrease in slope is interesting. I suppose the ENSO has more than a little to do with this, but it shows the hazard of blind extrapolation. My visual optical minimum mean square line drawing devices (aka an eyeballing) shows a lot higher slope through 2006 even after the seasonal stuff is retained in the second chart. The step function between the end of Jason-1 and Jason-2 merits some attention. La Nina? Or something else? I am not enough of an oceanographer to make a good conjecture. An education is welcome.