Guest post by Bob Tisdale
This is a follow-up to my recent post On Sallenger et al (2012) – Hotspot of Accelerated Sea Level Rise on the Atlantic Coast of North America. It confirms a comment I made there and also takes a quick look at the satellite-based sea level trend maps. Sallenger et al (2012) also referred to climate models as if they have value, so I wanted to add a comment or three about the models used by the IPCC. Last, the post exposes the blunder of unusual size in the Scientific American post about Sallenger et al (2012).
INTRODUCTION
There’s been lots chatter around the blogosphere about sea level rise in response to legislation in North Carolina. Refer to the WattsUpWithThat posts here and here. It escalated last week with the release of the Sallenger et al (2012) paper Hotspot of Accelerated Sea Level Rise on the Atlantic Coast of North America. RealClimate had a post titled Far out in North Carolina. SkepticalScience had back-to-back sea level posts; the first North Carolina Lawmakers Turning a Blind Eye to Sea Level Reality? was followed a day later by Madness over sea level rise in North Carolina. Scientific American also jumped into the mix with North Carolina Sea Level Rises Despite State Senators. Not one of those posts investigated tidal gage sea level data for the region that was the focus of Sallenger et al (2012). In a preliminary investigation, I presented the sea level data from one North Carolina tidal-gage station and from seven stations with long-term, reasonably complete data that were included in the Sallenger et al (2012) east coast hot spot, the hotspot that wound up not looking too hot after all. Refer also to the comments in the cross post at WattsUpWithThat.
LONG-TERM VERSUS SHORT-TERM TRENDS
In my post, I presented a time-series graph of the average of the “Hotspot+1” sea level data. And stated that it appeared the average sea level anomalies for the “Hotspot+1” stations have been relatively flat since about 1996. Figure 1 confirms that comment. The long-term trend (1935-2008) of the “Hotspot+1” sea level data is about 3 cm/decade, while the short-term trend from 1996 to 2008 is less than 10% of the long-term trend at 0.24 cm/decade. I’ve also included the trend for the “Hotspot+1” data starting at the 1990 break point discovered by the Sallenger et al(2012) analysis. It shows an increase from the long-term trend of about 20%.
Figure 1
The more I look at Figure 1, the more it appears that I’m presenting a classic example of trend comparisons with cherry-picked start years. It might appear to some that Sallenger et al (2012) cherry-picked 1990 to front load the short-term data with the impact of the eruption of Mount Pinatubo, which would have driven the trend up of the data after 1990, while I picked 1996 to front load the data with the impact of the 1997/98 El Niño, which would drive the trend of the data after 1996 down . I’ll admit to my cherry-picked start year. Will Sallenger et al (2012) admit to theirs and its impact on their claim of accelerated sea levels? Sallenger et al (2012) briefly mentioned volcanic aerosols toward the end of their paper:
Aerosols may also play a role in explaining variations in NEH SLRDs. The mid-century low (Fig. 4) may have been forced by volcanic aerosols reflecting radiation and lowering air temperatures25 and slowing14 SLR.
But they never attempted to account for them, in the paper, to see how much the catastrophic eruption of Mount Pinatubo in 1991 could have impacted their claim of accelerating sea levels.
SATELLITE-BASED SEA LEVEL DATA
I had wanted to use the University of Colorado’s Interactive Sea Level Time Series Wizard to determine the satellite-based near-coast sea level rise along the east coast hotspot to see whether it confirmed the tidal gage data, similar to a post by Steve Goddard. Unfortunately, the Sea Level Time Series Wizard wasn’t working this weekend. So I downloaded the University of Colorado’s sea level 1993-2012 trend map in pdf form, zoomed in on the east coast of United States, and overlaid the color-coded trend scale—once again doing something similar to another recent post by Steve Goddard. See Figure 2. The trend of the satellite-based sea level data appears to confirm that the short-term tidal gage-based trend may be about right, but note how the trend is higher toward New York and Boston and relatively low around North Carolina. Too bad the Sea Level Time Series Wizard wasn’t working this weekend.
Figure 2
CLIMATE MODELS
Sallenger et al (2012) refer to climate models more than 20 times in a 2900 word document. It looks as though, if one were to delete all sentences with the word model or some form thereof, that there’d be little left of the paper, maybe 20% to 25% of the original word count. Apparently, the authors of Sallenger et al (2012) believe that climate models have skill at being able to hindcast and project ocean-related variables.
In a couple of posts over the past year (see here and here) and in my recent book, I’ve shown that the climate models used by the IPCC in their 4thAssessment Report (AR4) show no skill at being able to simulate satellite-era sea surface temperature anomalies. Yes, I understand that sea surface temperature and sea level are different datasets. I’m using sea surface temperatures as an example of an ocean climate variable, since model outputs and observed satellite-based sea level data are not available through the KNMI Climate Explorer for the term we’re interested in discussing.
Figure 3 illustrates the linear trends from January 1982 to April 2012 for the Pacific Ocean on a zonal (latitudinal) mean basis. (Not presented in an earlier post.) The trends for the Southern Ocean (near Antarctica) portion of the Pacific (125E-90W) are shown to the left, and to the right are the trends up to the latitude of the Bering Strait. The equator is at zero latitude. We can see that the trends for the average of the models used by the IPCC in AR4 to simulate sea surface temperatures bear no similarities to the observed trends. The observations portray a pattern associated with how the El Niño-Southern Oscillation (ENSO) redistributes warm water from the tropics toward the mid-latitudes, where it can release heat to the atmosphere more efficiently. But the models appear to portray a zonal mean pattern associated with the annual average sea surface temperatures (not anomalies) of the Pacific—warmer in the tropics than at the poles—as if the models are warming at a faster rate in the tropics in response to the warmer sea surface temperatures there and at slower rates toward the poles because it’s cooler there. That really looks odd.
Figure 3
The comparison of satellite-era trends for the Atlantic on a zonal mean basis, Figure 4, shows the model mean of the climate models used in the IPCC’s AR4 aren’t any better there for the past 30 years, the satellite era. The pattern of warming in the models again appears to represent the annual average sea surface temperatures (not anomalies), while the observations portray a pattern associated with the Atlantic Multidecadal Oscillation (AMO).
Figure 4
Why do I say the observations portray a pattern associated with the AMO? Let’s switch to a longer-term sea surface temperature dataset (HADISST), and look at the Atlantic Ocean sea surface temperature anomaly trends from 1944 to 1976 and from 1976 to 2010 on a zonal mean basis. Refer to Figure 5. We can see that the cooling pattern in the trends of North Atlantic sea surface temperature anomalies, from 1944 to 1976, opposes that of warm trends from 1976 to 2010. Notice also how the two curves diverge, not at the equator, but at the southern end of the tropics.
Figure 5
Referring back to Figure 4, you’ll note that the models do a reasonable job of matching the observed satellite-era sea surface temperature trends for the latitudes of about 33N-43N, which are the latitudes of the “hotspot” discussed in Sallenger et al (2012). So let’s compare the observed sea surface temperature trends for those latitudes to those of the IPCC AR4 climate model outputs on a meridional (longitudinal) basis from the east coast of the United States to the west coasts of Europe and Africa. Refer to the map in Figure 6. We’ll be looking first at the trends of the modeled and observed sea surface temperature anomalies from 1982 to 2011 for each of those grids. The grid farthest to the west captures the sea surface temperature anomalies from the coasts of Georgia/South Carolina north to Maryland and Delaware. The grid bordered by the coordinates of 33N-43N, 75W-70W captures the sea surface temperatures along the coasts from Delaware/New Jersey north to Massachusetts/New Hampshire.
Figure 6
For the period of 1982 to 2011, the trends of the IPCC’s AR4 models of sea surface temperatures between the latitudes of 33N-43N show a pretty uniform warming from west to east, but the observations do not. See Figure 7. In fact, toward the coasts of the Carolinas and Virginia, the observed sea surface temperature anomaly trends are negative. That is, sea surface temperature anomalies have cooled there. And the longitudes that contain the New Jersey, New York and New England shorelines show a positive (a warming) trend, but it’s about half the modeled trend.
Figure 7
The models don’t look so good at these latitudes during the last 30 years. And they performed poorly on a zonal mean basis, too. I wonder what they do simulate correctly. It certainly isn’t land surface temperatures on a regional basis around the globe. In general, the models performed poorly at simulating the regional land surface temperature trends in the Americas, Australia, Southern Africa and Southeast Asia.
One last graph: Now let’s start the meridional mean trend comparison for the latitudes of 33N-43N in 1990, Figure 8, which was the break year in the tidal gage-based sea level data found by Sallenger et al (2012), which, by some strange coincidence, just happens to be right before the largest explosive volcanic eruption of the 20thCentury. With this start year, the modeled trend agrees with the observed trend for the longitudes of the northern portion of the “hotspot”.
Figure 8
I’ll let readers speculate about that.
THE SCIENTIFIC AMERICAN BLUNDER
As noted in the opening, Scientific American published a post North Carolina Sea Level Rises Despite State Senators about the Sallenger et al (2012) paper. The subtitle is so blatantly wrong it’s laughable. It reads “Less than two weeks after the state’s senate passed a climate science-squelching bill, research shows that sea level along the coast between N.C. and Massachusetts is rising faster than anywhere on Earth.” Anywhere else on Earth? Tell that to the people along the coasts of the Indo-Pacific Warm Pool. See Figure 9.
Figure 9
CLOSING
I included the discussion of climate models with hope that someone from the climate science community would state something to the effect of, climate models have known problems and cannot simulate climate on regional or on short-term (multidecadal) bases. Because, then I’ll point them to Sallenger et al (2012) and ask why that paper discusses climate models as if they do have value on regional bases and over short time spans. The people of North Carolina are patiently waiting for that discussion.
ANOTHER SHAMELESS BOOK PLUG
My book If the IPCC was Selling Manmade Global Warming as a Product, Would the FTC Stop their deceptive Ads? is available in pdf and Kindle editions. An overview of my book is provided in the above-linked post. Amazon also provides a Kindle preview that runs from the introduction through a good portion of Section 2. That’s about the first 15% of it. Refer also to the introduction, table of contents, and closing in pdf form here.
I still plugging along on my upcoming book about El Niño-Southern Oscillation and hope to publish pdf and Kindle editions by late July, early August 2012.
SOURCES
The Reynolds OI.v2 sea surface temperature data was retrieved from the NOAA NOMADS website. The multi-model mean for the CMIP3 (20C3M/SRES A1B) outputs of sea surface temperature (TOS) were retrieved from the KNMI Climate Explorer.
I can believe that some places might have sea level higher than others due to gravity, winds etc but I doubt that one place can rise faster than another.
The “bulge” will flatten out rapidly !
Am I wrong ?
To hear the term ‘research’ applied to such a shoddy and deceptively presented paper is an insult to true researchers. There was no research here, merely a rehash of the tired old AGW mantra, dressed up with citations of other bogus output by the Team, topped of with the usual ‘models’. At least a model airplane looks like an airplane, while the only thing climate models look like is their alarmist fantasy of positive feedback and vague tipping points.
AGW has to be the biggest downside of computers since they were introduced 60 years ago.
The Proteus phenomenon which certainly applies here definitely provides irrefutable proof that AGW is more social than science.
Well I hate to ruin the climate kook sea-level party but there is another dynamic variable that may account for 100% (or more 😉 of the alleged sea-level rise.
This large slab of land we call North America isn’t bolted to an imaginary solid core at the center of the Earth. Instead, like all other parts of the crust, it floats on the mantle. Furthermore it isn’t ‘level’ perpendicularly to an imaginary line spearing the Earth’s center. No, in fact it is tilting, which means one end is rising and the other end is sinking. Guess which end is sinking.
From Wankerpedia …
So, up North (…to Alaska) the land is rising, below the Great lakes (this includes North Carolina naturally) it is sinking. So where do the retarded alarmist community decide to go cherry picking this time? Yep, to North Carolina. They are liars and scoundrels of the highest order.
It is entirely possible that sea-level ‘should be’ rising faster than we currently see. In other words it may not be rising fast enough. Its is likely that the only detectable warning signal that humans will observe indicating the winding down of the current Holocene interglacial will be the slowing of sea-level rise until it turns the corner and sea-level begins to decline (that would be actual bad news). This is because the one constant during the Holocene has been rising sea-levels since the last glaciation maximum. Why would any logical person worry about a few millimeters of sea-level rise?
Wankerpedia :: Post-Glacial Sea Level Rise
“I wonder what they do simulate correctly.”
Global metrics over long time scales.
Even here the word “correctly” is ill defined. In modelling the question relates to skill not correctness. Since all models are wrong, since no physical law matches observations perfectly, the better question is “does the model have skill” is it useful for a give well defined purpose.
By admission they dont do short time scales well, dont do regional spatial scales well, and
they admit to not doing regional sea level well.
That is why there is increased work ( see Ar5 ) going in to improving short time scales and regional spatial scales. It’s uncertain whether they will have success. As people note the climate system is complex.
In a nutshell, the models give us the best insight we have into GLOBAL metrics over long periods of time. When and if they become better at regional scales and decadel time spans, I imagine we can criticize them for not predicting my back yard at yearly time scales.
Is the best we have good enough? good enough for policy? That’s not a science question.
Do models have to work at all spatial and temporal scales to be useful?
Nope
Anthony (and moderators),
There are a few things I can see killing the loading of WUWT pages in the past few days.
trk.kissmetrics.com
host.sdo.gsfc.nasa.gov…
The 1st URL is absolute murder, adding 10 to 15 seconds to page loads on broadband.
The 2nd URL is incomplete but is probably related to a widget in the sidebar.
They both appear to be HTTPS if that helps at all. There are a few others also, but these are noteworthy.
It’s Gaia reacting! Now it can read!
Steven Mosher says: “…Do models have to work at all spatial and temporal scales to be useful? Nope.”
Right. The print-outs make dandy doorstops, and for lining my budgie’s cage, they simply can’t be beat.
“Do models have to work at all spatial and temporal scales to be useful?
Nope”
The IPCC is living proof that they are certainly useful to the IPCC.
How useful is it, and to whose benefit, to have models that predict the past?
Read this Anthony, you might enjoy it.
http://www.cs.princeton.edu/~ken/Langmuir/langmuir.htm
What would he have made of computer models?
Every region in the USA has been flooded with similar stories in the past three weeks . All virtually identical. This is clearly an orchestrated attempt to instill fear on a local level, the nation as a whole having lost interest in this obviously contrived, sometimes painfully, ‘science’ that will destroy town, jobs, and manufacturing that real people need.
OT
Latest SIDC sunspot number count for June is out at 64.5, slightly down on 69 for May.
http://www.vukcevic.talktalk.net/SSN.htm
A related matter.
How much of CAGW is a result of political beliefs? How credulous, if not delusional, are liberals in reporting upon the same?
Recently a study found that China was severely under-reporting CO2 emissions. The manner in which it was found was idiotically simple. Provincial reports were compared to the national government’s consensus report. The provincial reports exceeded the national reported amount by an amount equal to the entire emissions of Japan.
So what is a liberal to conclude from this? Why:
1. The provinces exaggerated their reported out-put (lol)
or
2. Whatever the actual amount, no-one can disagree that China has a very special CO2 absorption ability because the .actual amount in the atmosphere is not questioned. So it does not matter for China. Of course these figures are also reported by the national government.(lol)
The most obvious conclusion, Chinese lie about everything and anything seems to have escaped the brain-pan of these academics. Exactly how stupid are these people? Too stupid to be trusted.
“Warmed-up numbers
China may be severely under-reporting its carbon emissions”
http://www.economist.com/node/21557366
Due to the noisy behavior of these systems inside their oscillatory behavior, the best we can do is use analogue years and a statistical model with error bars, not a dynamical model. At least for the time being. The dynamical models are polluted with watermelon beliefs and should be thrown out till we have a longer run of statistical models to help us figure out what is at work here.
The models are useless except to the extent they are programmed to increase temperatures due to rising greenhouse gases. I don’t think climate models have provided any insight into any climate-related phenomenon ever, none that is. They are a program; programmed by humans.
What do the actual tide gauges say.
If the ice sheets start melting faster than they do now (or let’s say actually start melting) then sea level rise will increase above the 2 mm/yr that would be expected for this time period into a long interglacial. Let ‘s note that there are many areas which are currently glaciated that will not have glaciers if this interglacial lasts another 5,000 years. Southern Greenland, for example, is too far south to have glaciers in the long-run. They are only there because 4 km high glaciers have built up in the central interior for 100,000 out of every 115,000 years for the past 2.7 million years.
If I recall correctly Dr. Pielke Sr. has a number of papers demonstrating the climate models are useless on the regional scale
Blade says:
July 1, 2012 at 12:52 pm
FWIW:
The first is likely http://sdo.gsfc.nasa.gov/assets/img/latest/latest_256_4500.jpg which
is a 256×256 solar surface image (7,005 bytes at the moment).
The second doesn’t show up in my recent pages, but it has ties to Amazon Web Services (their cloud system):
tux:moneydance> host trk.kissmetrics.com
trk.kissmetrics.com is an alias for kmtrk-651295067.us-east-1.elb.amazonaws.com.
kmtrk-651295067.us-east-1.elb.amazonaws.com has address 107.22.237.163
kmtrk-651295067.us-east-1.elb.amazonaws.com has address 50.16.235.198
kmtrk-651295067.us-east-1.elb.amazonaws.com has address 184.72.228.210
kmtrk-651295067.us-east-1.elb.amazonaws.com has address 107.20.134.214
kmtrk-651295067.us-east-1.elb.amazonaws.com has address 107.22.249.24
kmtrk-651295067.us-east-1.elb.amazonaws.com has address 107.20.244.110
kmtrk-651295067.us-east-1.elb.amazonaws.com has address 107.20.221.117
kmtrk-651295067.us-east-1.elb.amazonaws.com has address 107.22.197.78
trk.kissmetrics.com is an alias for kmtrk-651295067.us-east-1.elb.amazonaws.com.
trk.kissmetrics.com is an alias for kmtrk-651295067.us-east-1.elb.amazonaws.com.
Ric Werme,
Could the trk.kissmetrics.com be related to the WordPress bar that appears within the page when you are logged in to a WordPress identity? Are you logged in to this WordPress thing?
I just logged out (page goes back to normal without the WordPress bar) and the page load appears faster and I didn’t see the kissmetrics thing.
These problems just come and go monthly or weekly. I swear, there isn’t a single BLOG or FORUM software in existence that is worth a damn anymore.
UPDATE: after logging back in I still don’t see those two URL’s anymore. Either it was a fleeting thing a few hours ago, or Anthony fixed something.
@Blade – I can’t fix anything. Being hosted on wordpress.com the code is out of my hands – Anthony
From Blade on July 1, 2012 at 12:52 pm:
Use a Mozilla-based browser like FireFox, or now Google Chrome.
Get Adblock Plus. Now, despite the name I won’t recommend it for blocking ads on WUWT as the site is hosted free on WordPress at the “cost” of WordPress’ ads.
But, it is excellent at blocking elements on pages. If something is taking too long to load or otherwise messing up a page, or just plain annoying like an unwanted pop-up toolbar, just block it. The wildcard control allows blocking of individual pieces, content from a part of a site (like ads-dot-site-dot-com), or entire addresses. You can also selectively block on different sites, like allowing something elsewhere but blocking it on WUWT, or blocking everywhere but on WUWT (exclusion rule).
Do you have any objections to having some more control over your own life, even if it’s just more control over what bits of the internet wind up on your computer?
Oh, there’s some kissmetrics stuff. It looks like something WordPress is using for tracking web page references. It’s under Javascript control, you can try disabling that, but so many things expect Javascript that you’ll have to turn it back on for a lot of tasks. I sometimes disable it because I think that’s behind a memory leak in my ancient Firefox. (I hope to replace the system in a few months).
I have the QuickJava extension that adds Java & Javascript on/off toggles at the bottom of the window. Handy little thing.
Blade says:
July 1, 2012 at 4:35 pm
> Could the trk.kissmetrics.com be related to the WordPress bar that appears within the page when you are logged in to a WordPress identity? Are you logged in to this WordPress thing?
Not directly – The code I saw was near the comment box, but it may be tied to the entity that people are logged in to. However, I suspect it’s to log what pages you’re reading. I don’t know what WordPress does with that data. I’ll resist the temptation to speculate.
> I just logged out (page goes back to normal without the WordPress bar) and the page load appears faster and I didn’t see the kissmetrics thing.
It may not be there all the time.
> These problems just come and go monthly or weekly. I swear, there isn’t a single BLOG or FORUM software in existence that is worth a damn anymore.
“Creeping featuritis.” Along with quite a bit of advertising, tracking, and who knows what these days. And all the stuff Anthony has in the rightside nav bar (more creeping featuritis). He did drop one section a while back, but a number of people missed it and he put it back.
> UPDATE: after logging back in I still don’t see those two URL’s anymore. Either it was a fleeting thing a few hours ago, or Anthony fixed something.
It’s much more likely they’re responding faster. The kissmetrics thing he has no control over, and thousands of people would miss the little SDO Sun image and link.
Blade says:July 1, 2012 at 12:43 pm
Geez Blade, ain’t it a bit rough to refer so extensively to Wikipedia and derisively rename it in your link?
I fully understand its limitations, but I still find use it as a quick first stop…..
It is what it is, but is still very useful.
A very interesting, educational, and relevant article on sea level rise along the east coast:
http://web.vims.edu/GreyLit/VIMS/sramsoe425.pdf
EXECUTIVE SUMMARY:
Ten Chesapeake Bay water level stations presently have a combined total of 647 years of water
level measurements with record lengths varying between 35 years (1975-2009) at the
Chesapeake Bay Bridge Tunnel, VA, and 107 years (1903-2009) at Baltimore, MD. All ten
stations, with the exception of Gloucester Point, VA, are active stations in the National Water
Level Observation Network of water level stations maintained by the U.S. National Oceanic and
Atmospheric Administration, Center for Operational Oceanographic Products and Services.
New technologies such as sea surface range measurements from earth-orbiting satellites now
provide a global assessment of absolute sea level (ASL) trends relative to the center of a
reference ellipsoid rather than fixed points on the earth’s surface to which relative sea level
(RSL) measurements refer. New methodologies have also been applied to derive spatial averages of ASL trends over large regions with greater accuracy. Notwithstanding these advances, there is still no substitute for an accurate time series of water level measurements obtained locally, preferably one spanning several decades, when assessing RSL trends that will affect a specific community or township in the coming decades. RSL trends will determine local inundation risk whether due to vertical land movement (emergence or subsidence) or the ASL trend found as the sum of RSL trend and land movement when both are measured positive upward. In Chesapeake Bay, RSL trends are consistently positive (rising) while land movement is negative (subsiding).
By choosing a common time span for the ten bay stations evaluated in this report, we are able to
compare differences in RSL rise rates with approximately the same degree of confidence at each station. Uncertainty has been reduced by extracting the decadal signal present at all ten stations before using linear regression to obtain new RSL rise rates with smaller than usual confidence intervals, permitting both temporal and spatial comparisons to be made.
Temporal comparisons at five bay stations over two periods, 1944-1975 and 1976-2007, suggest that, while RSL continues to rise at some of the highest rates found along the U.S. Atlantic coast, there is presently no evidence of a statistically significant increase marking an acceleration in RSL rise at any of the five bay stations. Small but steady increases in RSL rise rate with time are still a possibility as RSL trend confidence intervals remain too large for statistical inference. Spatial comparisons at ten stations for the 1976-2007 period provide new evidence on spatial variability of RSL rise rates within Chesapeake Bay. Global positioning system (GPS) data from ground stations further define the pattern of spatial variability and permit new estimates of ASL rise rates in the region, all of which are significantly less than the global ASL rise rate of 3.1 mm/yr over 1993 to 2003 reported in the IPCC Fourth Assessment Report. Present evidence suggests an ASL rise rate of about 1.8 mm/yr in Chesapeake Bay over the 1976-2007 period. Applying this rate uniformly throughout the bay, subsidence rates ranging from about -1.3 mm/yr to -4.0 mm/yr are found, leading to the general conclusion that about 53% of the RSL rise measured at bay water level stations is, on average, due to local subsidence. Outlook: Land subsidence in Chesapeake Bay is likely to continue at or near present rates. Future ASL rise in the bay region remains uncertain owing to diverse and possibly changing trends world-wide (see report cover). Their combination strongly suggests a need for future monitoring.
Yet another error-filled diatribe by Bob, e.g.
http://tamino.wordpress.com/2012/07/01/sea-level-rises-tisdale-falls/
Submit it for peer review or stop claiming you’ve actually “discovered” something new when
your methodology is obviously so flawed.
Sallenger et al. ignore geology. They miss a simple explanation: sediment compaction and subsidence from varying rates of groundwater withdrawal. Relative sea level depends in part on the geology of the area. That is superimposed on a regional, long-term sinking of the East Coast caused by isostatic rebound from the last glacial epoch, i.e., as the central part of North America rebounds from the weigh of the now melted continental ice sheet, it tilts the coast area into the ocean producing an apparent sea level rise.
Jerky says: “Yet another error-filled diatribe by Bob, e.g.”
Thanks for the link to another of Tamino’s classic misdirection posts, Jerky. Here’s the link to the post he was commenting about. It wasn’t this one, Jerky. You’ve put your comment on the wrong thread:
http://bobtisdale.wordpress.com/2012/06/29/on-sallenger-et-al-2012-hotspot-of-accelerated-sea-level-rise-on-the-atlantic-coast-of-north-america/
WUWT cross post:
http://wattsupwiththat.com/2012/06/29/cooling-that-east-coast-sea-level-hotspot/
I acknowledged the difference in trends before and after 1990 in the second paragraph, Jerky. In other words, I acknowledged the acceleration. So, for those of us who can read and comprehend English, Tamino’s statement, “Tisdale doesn’t buy it,” is obviously wrong.
And as you would have noted, if you had actually read and comprehended my post, Jerky, it was a preliminary investigation to illustrate and attempt to determine the possible causes of the multidecadal variability referred to by Sallenger et al (2012). After quoting Sallenger et al and their referenced paper Frankcombe and Dijkstra (2009), I stated the following:
Immediately, one wants to examine a time-series graph of the “Hotspot” sea level data in the Sallenger et al (2012) paper to get an idea of what the multidecadal variability in the data looks like.
Regarding Tamino’s comment about my using monthly data instead of annual data as Sallenger et al had done, I was looking for telltale signs of ENSO. I would not use annual data for that, so I used monthly data. I didn’t care if Sallenger used annual data. The intent of my post was not to duplicate their efforts. Regarding my use of KNMI where the data ends in 2008, this was a preliminary investigation, so I selected KNMI as a source since the data there is in an easy-to-use format. If I had not found evidence of the acceleration, I would have used more up-to-date data.
Tamino wasted his time and, since I’m responding to his nonsense, Tamino is wasting mine.
Adios, Jerky.
From Jerky on July 1, 2012 at 5:59 pm:
Obvious typo, Tami’s name is Grant Foster, not Bob.
That only works when the submitter is confirming the climate orthodoxy. For skeptics, your demand to “Submit or shut up!” is actually demanding one submit to an inquisition by the high priests of the religion. Then any that allow a skeptic’s heresy to be published are themselves branded as heretics and persecuted.
Besides, traditional peer review and publication is excruciatingly slow. Get with the times. Blog review is peer review and goes much faster.
BTW, where’s the beef? You didn’t provide any examples. Did you actually do any thinking yourself, or are you just saying “He said you were wrong so you are!”?
That’s how it goes sometimes. You want the beef, you get stuck with turkey jerky.
Jerky says, July 1, 2012 at 5:59 pm:
Yet another error-filled diatribe by Bob, e.g.
http://tamino.wordpress.com/2012/07/01/sea-level-rises-tisdale-falls/
Submit it for peer review or stop claiming you’ve actually “discovered” something new when
your methodology is obviously so flawed.
——————
Uhh ? Jerkov … Mr Bob is not claiming anything, merely demonstrating the lack of skill apparent in the fabulous models. Tamino needs to revise his paradigm, it’s old hat now.
Sorry, spelt Jerky’s name wrong … /sarc off.
Apologies to anyone who thought I was complaining, I wasn’t. I was only reporting an anomaly, just contributing a data point. If Anthony hears from lots of people over a period of time then he’ll have something useful to give to his blog host.
Thanks KD. Been at this game a loooong time myself. I have all four major browsers (Opera, FF, Chrome, MSIE) often open at the same time when developing pages though I prefer Opera for reading sites like this because of little things like the way it stores passwords and remembers thread positions (FF would be my next choice though). However there really isn’t anything to be fixed on the receiving end.
What we have (or had) here is/was a temporary upstream bottleneck (server side) so tinkering in local browser settings (client side) is counter-productive and at best will only mask the issue, so we’d never even know when it was fixed.
I do leave Javascript active and only use the built-in popup blockers to kill any secondary window popups which are truly evil. I don’t screen out too many URL’s like the ones for anonymous tracking analytics and inline advertisements because let’s face it, that’s the cost of a ‘free’ blog site and it somehow pays for the substantial work and equipment it takes to host a giant blog like Anthony’s.
But, when they (WordPress, not Anthony) screw the pooch because of some broken tracker or an advertisement served from a slow crawling host on a dial-up modem they need to be notified. I see download speeds rarely below a few MB/s, so very few of WUWT’s pages require even one second to load (ok, maybe some of Bob Tisdale’s 😉 But 2 seconds max! That one previously mentioned URL kicked it up to 15 seconds which is enough time to download a 50 MB file or more.
And there is always the possibility that one of the widgets there on the sidebar becomes FUBAR, for example a NASA page or something. So I just wanted to make sure Anthony heard from someone in case there is a problem that makes his site look bad.
P.S. Since I am in the sweltering NorthEast, it just might be the *unprecedented* never-before-seen-by-human-beings heat-wave and rising sea-levels that are killing the Internet trunk lines /SARC
Yeah, you know, stopped clock, twice a day. But point taken, thanks. I usually preface such cites as “Even Wikipedia gets this one right …”. But then I get lazy and just call it Wankerpedia (or worse on other blogs).
I agree that there are some great uses. Any page that relates to popular culture (as opposed to popular science or climate science) like music, TV, entertainment, the writers take great pains to detail every nuance of a subject. You want details on the Beatles or Jimi Hendrix or some TV show, then Wikipedia is the place. You want information on Climate then Wankerpedia sucks. Both things I linked to are more about geology and hard Science (although the brainwashed alarmists can be seen creeping in) than anything controversial. Really, after reading anything political over there I always swear I’ll never go back again. But then you find a fact here and there and it seems useful again. But then I’ll see a blog post detailing the handiwork of W.Connolley and all bets are off again. Truly, schizophrenia at its best.
And at the risk of causing a cosmic paradox, here is a link to buyer beware at, yes, Wikipedia 😉
FWIW, I learned about continents floating around on the planetary soft chewy center at least 50 years ago. That comment wasn’t really directed at you or any other normal person at WUWT, but instead at the alarmist cry-babies and their brainwashing handlers who have saturated our local and national media with scare stories for the past week or two up here in the sweltering and drowning NorthEast USA (/sarc). These under-educated sheep and the alarmist scoundrels that continually scare them seem to think we were born into a static Garden of Eden that man is corrupting. I guarantee that few of them even realize the very land they sit upon is floating, tilting, sinking and rising. Hence, the point of that comment. In a way, Wikipedia makes a perfect cite for this target audience. Think of it as a red pill for those enslaved minds in the alarmist Matrix.
[SNIP: Sorry, Pat, but this contributes nothing to the discussion. Let’s lift the discourse to a higher level. -REP]
[snip not interested in your comments nor Pat’s – take a hike with that fight -Anthony]
@Bob: “I acknowledged the difference in trends before and after 1990 in the second paragraph, Jerky.”
You seem to be backtracking since in the first post you said “The shift in trends around 1990 noted in Sallenger et al (2012) appears to be a function of the natural variability of the North Atlantic.” but in the second post you accuse Sallenger et al. of cherry picking that date: “It might appear to some that Sallenger et al (2012) cherry-picked 1990 to front load the short-term data with the impact of the eruption of Mount Pinatubo, which would have driven the trend up of the data after 1990, while I picked 1996 to front load the data with the impact of the 1997/98 El Niño, which would drive the trend of the data after 1996 down . I’ll admit to my cherry-picked start year. Will Sallenger et al (2012) admit to theirs and its impact on their claim of accelerated sea levels?”
It’s quite clear from Sallenger et al. that it wasn’t cherry picked. So why are you trying to distort their results and imply what they did was somehow insidious if you are truly so objective?
Mosher: “In modelling the question relates to skill not correctness.”
Same thing is true of con-artistry and politics.
I had a quick look at the Sallenger paper. Two observations.
Their model may have some predictive capability, but I doubt it. Looks to me like trend extrapolation, as per the climate models.
Local sea level changes (as opposed to isostatic changes) over the global average result from ocean circulation changes, and there will be limit to how much circulation changes can change sea level. Thus extrapolation isn’t appropriate.
Bob has failed to mention that Sallenger et al used annual average data, which is of course of low resolution. 1990-2009 comprises just 20 data points, rather than the 240 available if monthly was used. Furthermore, the PSMSL archive flags a gap (for that a year) if even one month is missing from the monthly data for that year. For their (in the supplement) example of New York, three years were missing from the data for 1990-2009, meaning that just 17 data points were available. This is an addition factor which has “enhanced” the statistical artefact of a 1980 “break” in trend,; there is no such break, just the lesser (than their claim) at 1990.
It’s surprising that the US Geological Survey failed spectacularly to take vertical land movement into account over the “hotspot”. By my reckoning it amounts to a fall of around 2mm/year or more over the latter part of their “windows”, an unknown but probably similar fall over the earlier parts. They should stick to rocks, which tell an unchanging story, rather than venture into statistics using coarse data which tell an apparently convincing story if you leave out inconvenient data like land movement..
Also, by just considering the “NEH” as they term it, they’ve missed a welcome and significant drop in trend over 1990-2009 (and to date) from the Mexican border right round the coast to the north-east coast of Florida, but then in this day and age, good news is no news at all.
Satellite MSL measurements would need to be compared to estimates of land level movements. Once you have done that any realisistic estimate of the measurement uncertainty will be WAY bigger than the quantity being measured.
Since the whole discussion in NC is about local effects on land and sea defences any discussion of any metrics other than the ACTUAL tide gauge measurements seems irrelevant.
The problem with tidal gauges is that they measure relative sea level changes. It could be that lowering of the coastline is the problem not sea level rise. A gauge will not tell which.
My memory of the Carolina coast is that is is very sandy with offshore sand bars. A coastline subject to deposition not erosion. Newly deposited sands will compress as they are loaded with more sediment, dewater and shrink. This will give the impression of sea level rise and display the mapped characteristics shown above
Jerky says: “It’s quite clear from Sallenger et al. that it wasn’t cherry picked. So why are you trying to distort their results and imply what they did was somehow insidious if you are truly so objective?”
Jerky, regardless of how they arrived at the breakpoint, Sallenger et al found a breakpoint in the sea level record with a cause that appears very obvious to many of us. They did not look for the cause of the obvious breakpoint, the 1991 eruption of Mount Pinatubo. They simply called the difference in trends an acceleration.
If some other group had performed a statistical analysis of the Hadley Centre’s HADCRUT3 global surface temperature record and their results were that the warming of global surface temperatures had decelerated starting about 1997 or 1998, there would be an uproar from anthropogenic global warming proponents. The AGW promoters would be saying that anyone with basic understanding of the instrument temperature record should know there is a breakpoint around those years, that the breakpoint is caused by the El Nino of 1997/98, and that 1997/98 is considered a cherry-picked start year.
Here is the data KNMI gives for Wilington NC. I cropped it before 1962 because there was a few gaps in the data (three missing months after that date were interpolate from the adjacent data).
http://i46.tinypic.com/bfrzmu.png
The plot shows the monthly rate of change filtered with a 12 month and 24 month gaussian filter.
Any persistent sea level rise would be seen as a positive offset in the graph. I don’t see any suggestion of that unless it is of the order of tenths of mm per year. Nothing to cause me to want to sell up my shorefront properties.
The only long term “trend” I can see is a notable reduction in the size of +ve and -ve swings.
Since 1998 sea level had been falling.
Streetcred says:
July 1, 2012 at 8:19 pm
Sorry, spelt Jerky’s name wrong … /sarc off.
============================================================================
That’s OK Streetcrud, accidents happen.
oops, I just checked back on the data at KNMI and it’s in cm not mm . So there is scope of an offset of the order of 0.1cm per year though any talk of an “average” on data with swings that are a factor of 20 times bigger will totally depend on where you start. Which is why any talk of “linear trends” as everyone seems so keen to do, is scientifically meaningless.
The 36 month filtered changes remain in the negative whatever the units.
Here is a similar plot with Hampton Road site added ( the “hottest” in the “hotspot”)
http://i48.tinypic.com/jqrdk8.png
Here fixed offset of 0.4 cm/year has been subtracted from Hampton Road. The residual shows warmer in 30’s, cooling to 1970 ; upward drift until mid 90’s and a downward drift since then.
So what is the 4mm/year background tide level rise across the last century?
Has the water been piling up up there?? Clearly not, it is the land falling. Some further investigation should show existing knowledge as to how much this may be land subsidence and how much post glacial movement in the mantle.
This is all pretty elementary geophysics. Calling this a “hotspot” is little more that stupidity.
CLOSING
I included the discussion of climate models with hope that someone from the climate science community would state something to the effect of, climate models have known problems and cannot simulate climate on regional or on short-term (multidecadal) bases.
=========
Gavin at RC appears to have said just that. See:
http://pielkeclimatesci.wordpress.com/
“Remarkable Admission By Gavin Schmidt In Response To The McKittrick and Tole 2012 Paper”
“The basic issue is that for short time scales (in this case 1979-2000), grid point temperature trends are not a strong function of the forcings – rather they are a function of the (unique realisation of) internal variability and are thus strongly stochastic”
Stochastic
http://en.wikipedia.org/wiki/Stochastic
Stochastic (from the Greek στόχος for aim or guess) is an adjective that refers to systems whose behavior is intrinsically non-deterministic, sporadic, and categorically not intermittent (i.e. random).
http://i47.tinypic.com/ao6rue.jpg
Taking this a bit further, here is as ensemble of the “hotspot” tidal guage records and the stable North Carolina , Wilmington site.
The legend shows the various offsets that have been subtracted from the “hotspot” records. Values vary between 0.1 and 0.4 cm/y. 2.4 mm/y seems a good average. Since the sea can’t be stacking up at Hampton Roads, most of this range of values probably represents land movement not sea level.
What is instantly clear is that the biggest variation is the peudo periodic one of about 12-13 years duration.
Also the warming ( positive rate of change) in the 30’s, decays to a minimum in the 60’s and increases again to the early 90’s and appears to peak in the late 90’s. This represents a smaller amplitude pseudo cycle of about 60 years duration. None of this is surprising in view of SST and land temperature data but shows in independant verification of these cycles by a physically different mechanism.
The long N.Y. record is significant in that is shows an offset of 2.5mm/y works right back to 1900 (in fact this works back to 1880 but I cropped the data due to missing data).
None of this seems to show any visible indication of a marked change in the rate of sea level rise coincident with the postwar boom in CO2 emmissions.
The main feature in all this is the notably larger amplitudes in this period, which probably is linked to with the recognised solar maximum.
Figure 1.
Gav sez: ..”rather they are a function of the (unique realisation of) internal variability and are thus strongly stochastic”
ie the models are a guess. Just sounds better is you say it in greek.
Looking at the graph from the Sallinger paper, they examine how “SLRD” (difference in sea level rate of change) varies with the window they use.
http://www.nature.com/nclimate/journal/vaop/ncurrent/images_article/nclimate1597-f3.jpg
In short if they start in 1930 or earlier it shows there is no difference in the “slope” of the first half versus the second half of the window.
This simply reiterates what I showed by directly plotting the rate of change. There is a c 60 year cycle in the data. If you use a “window” shorter than that you produce an artificial result by comparing different sections of the cycle. This is compounded by the presence of the shorter cycles.
Their results get bigger as they shorten the window and the combined effect of the two cycles I identifies can be seen clearly in their graph. All they demonstrate is how unstable their method is (although they explicitly claim the opposite !).
Indeed this is ALL that this paper shows. The rest of the mumbo jumbo about gyres , Coriolis, Atlantic currents, salinity, water temp, etc is just smoke and mirrors. They probably even confused themselves.
If you want to study rate of change, you take the differential and see what it looks like, you don’t take the linear regression of a arbitrary period in the time series.
They take no account of the strong cycle nature of the data, they do not even seem to notice its presence in their graph, thought the idea is hard new. If they would stop messing about “linear trends” on data that has nothing linear about it, they may do better.
BTW Bob , while attacking the “incomplete analysis and data presentation by Sallenger et al ” you really ought to be doing proper data processing yourself. In the other thread you link to here you present a graph of the Wilmington sea data:
http://bobtisdale.files.wordpress.com/2012/06/figure-111.png?w=640&h=416
This is (trailing) running mean filter of decadal “trends”. ie a running mean of a running mean that you seem to suggest shows the rate of change. I have several times pointed out how distorted just one pass of that so-called filter can be.
Now compare that to the same data from KNMI when I use the simple numerical differential (dx / dy) to get the trend and smooth with a real frequency filter, centred on actual data rather than trailing:
http://i46.tinypic.com/bfrzmu.png
They are vaguely similar but I would not have thought they were supposed to represent the same thing. You will note that my plot is smother with a 12m filter than yours is with 10 years !
You don’t have to adopt what I suggest but you ought to get a bit further than trend fitting in excel if you wish to criticise the work of others. There is a lot to criticise so I would only encourage you to do so and do it well.
best regards.
Fig. 5: without doing it properly, it looks like, from 1944 to 2010, there has been about a 0.1C increase in the SST of the world’s ocean’s. It also looks like the Northern oceans, 55* or greater, increases and decreases 3 or 4 times that variation as a natural, amplified general cycle. Thus explaining why Greenland was warm during the MWP while Mann et al claim the globe wasn’t so warm.
Which is a bullet in the brain for the warmist theory: if Greenland/the Arctic is naturally at a multiple of the world, then the alarm at the recent changes in the Arctic are not a presage of a terrible warming of the Earth, but of only the … Arctic. Just as they said the MWP was.
P. Solar says: “This is (trailing) running mean filter of decadal “trends”. ie a running mean of a running mean that you seem to suggest shows the rate of change.”
Wrong. It is a graph of a running 10-year (120-month) trends. It is not a running mean of a running mean. It is the same type of graph presented in Hansen et al (2011), their Figure 12:
http://www.columbia.edu/~jeh1/mailings/2011/20110415_EnergyImbalancePaper.pdf
Bob, I’m surprised that you think pointing to Hansen’s work is any kind of recommendation 😉 He does lots of questionable things, I don’t see this has any bearing except possibly that if Hansen does it, it is probably either wrong or misleading.
The point I am making is that if you 10 year “trend” starting at each year and slide along this is little different to doing a running mean. I think this is the point you failed to understand, I probably should have been more explicit.
You then do you usual running mean on you trend graph. This is effectively doing a running mean on a running mean as I said, it is not wrong.
All this “trend” fitting is fundamentally flawed. Climate science if full of it, that does not mean it is correct.
You have pointed out the Sallenger’s results depend on where you start, you have had run-ins with Grant Foster based on similar arguments.
The point is that niether position is correct, no one should be arguing about where to start because the method if fundamentally flawed and no one should be doing it.
In fitting a “trend” you are trying to fit a linear model to something that is not at all linear. There is NOTHING linear about any of these time series. That is why it depends totally on where you start and why the answer is of no use to anyone. Any arguments about where you start and why are a total waste of time. I suggest you stop expending energy in arguing with the other side about where to start fitting trends.
If you want to look at rate of change, use the d/dt , the differential. This is trivially simple calculate on evenly spaced data like we have here.
The graphs I linked above show how the rate of change varies over time A “linear trend” on such a graph would be a constant horezontal line, offset from zero. You can “detrend” data by subtracting a constant and it does not alter the shape of the graph (unlike detrending a time series which does change its shape).
The flaw in the Sallenger paper is that they clearly show that their result depends totally on window length and that if you take a long enough window there is no “acceleration”. This is shown in their graph that I linked about.
Despite this they claim their method is stable and robust and project the “acceleration” of the last 30-40 out to 2100. Plotting the rate of change directly shows this is unjustified.
http://i46.tinypic.com/bfrzmu.png
I would suggest that you start looking at rate of change directly when that is the quantity that you are interested in.
Fitting a linear model by least squares is a way of estimating the average slope. It is like finding the average (mean) rate of change. If you repeat that by shifting your start date each time, you are doing a sliding or running average of the slope. This is very close mathematically to taking the differential and doing a running mean. This may not have been obvious to you but this is what I was pointing out.
If you then do an actual running mean on your trend data (your 121 pt “filter”) you are effectively doing R-M on R-M .
Your graph “should” look similar to mine. The fact that it does not is due to the way RM distorts at the same time it (sort of) smoothes.
Thanks, Anthony.
Bob, you will notice in the composite graph I produced from the “hotspot” locations that there is a strong decadal scale cycle. This would very likely tie in with the AMO you are so interested in.
http://i47.tinypic.com/ao6rue.jpg
Note these plots do not have any shift due to processing so peaks are at the right date. You may want to compare this to rate of change of North Atlantic surface temps
My reason for encouraging you to try better filters is that RM will shift the position of peaks and sometimes invert them. This will severely impede any attempt to identify correlations and effects.
I think what you are doing is valuable and am trying to point you to using methods that will help you succeed.
Keep digging.
Best regards.
Is anyone studying localized salinity? Could be an issue in terms of how high water goes…