Fierce fighting on SLR in North Carolina

Nature Climate Change just published a paper called “Hotspot of accelerated sea-level rise on the Atlantic coast of North America” written by Asbury H. Sallenger Jr, Kara S. Doran & Peter A. Howd, of the USGS. Hey, another climate scientist named Sallenger but not called Jim!

Is this paper a credible source? John Droz, jr, is spearheading support for proposed, unprecedented, “anti-green” legislation in North Carolina that would make it illegal for state agencies to use accelerated SLR projections as a basis for state rules and regulations. The bill is called HB-819.

Legislators are reeling from two months of a green backlash against the proposed legislation and now this “Hotspot” paper is giving them serious doubts about the wisdom of passing it. John’s asking for scientific or any other assistance. He writes:

Once the environmental movement heard about this threat to one of their key agendas, they were enraged. There have been hundreds of articles written attacking the legislators’ plan, worldwide. For those of us locally defending these efforts, it has been akin to being in caught up in a hurricane!

Two things that have struck me are that the message from these evangelists is so well-scripted — and also that it is almost entirely false.

If you want to see an accurate recounting of this situation, read this.

Anyway, where we are now is that: 1) the NC senate passed the proposed bill 35-12, and 2) the NC house is now debating a watered-down version.

The NC House leadership has evidently been shaken by the intensity of the backlash, and is concerned about the political fallout from going through with their initial plan.

Another stumbling block has been the (coincidental?) issuance of this report right in the middle of this whole matter. That report is being thrown in the legislators’ faces as an indication that what they are proposing flies in the face of scientific evidence.

As such, some legislators have asked me for commentary on that report — which I am asking for your help with.

Please let me know, ASAP, if you have done a critique of that report, or whether you are aware of any good ones being done elsewhere.

Thank you for your support.


Climate warming does not force sea-level rise (SLR) at the same rate everywhere. Rather, there are spatial variations of SLR superimposed on a global average rise. These variations are forced by dynamic processes, arising from circulation and variations in temperature and/or salinity, and by static equilibrium processes, arising from mass redistributions changing gravity and the Earth’s rotation and shape. These sea-level variations form unique spatial patterns, yet there are very few observations verifying predicted patterns or fingerprints6. Here, we present evidence of recently accelerated SLR in a unique 1,000-km-long hotspot on the highly populated North American Atlantic coast north of Cape Hatteras and show that it is consistent with a modelled fingerprint of dynamic SLR. Between 1950–1979 and 1980–2009, SLR rate increases in this northeast hotspot were ~ 3–4 times higher than the global average. Modelled dynamic plus steric SLR by 2100 at New York City ranges with Intergovernmental Panel on Climate Change scenario from 36 to 51 cm (ref. 3); lower emission scenarios project 24–36 cm (ref. 7). Extrapolations from data herein range from 20 to 29 cm. SLR superimposed on storm surge, wave run-up and set-up will increase the vulnerability of coastal cities to flooding, and beaches and wetlands to deterioration.

The bottom line appears to be that, to the projected SLR rise by 2100 under any IPCC scenario, we must add from 20 to 2 cm, but I’ve asked Sallenger to confirm.

How good is it? The predictions are all from models. I can see some weaknesses, foremost among them being their assumption of continued warming throughout the 21st century. Future SLR is dependent on some pretty vague statements like “could rise”, “could also reduce”, “may indicate”, “could slow AMOC”, “ice melt could freshen surface water”, “NAO rate differences may indicate changes in strength of the gyre system”, (although) “NAO may not contribute to forcing the NEH”, “Aerosols may also play a role in explaining variations in NEH SLRDs” (SLRD is sea level rate difference).

What’s causing the acceleration? They won’t tell you, so take your pick. The paper mentions the North Atlantic Oscillation, so is it liable to be cyclic?

Reading this paper is raising all kinds of red flags for me, but being unable to follow the technical information means I cannot describe its faults.

I’d like to help John Droz. The paper could cause a backdown in the legislature against world-leading planning legislation.

Any thoughts on the paper’s specific faults would be much appreciated.

UPDATE SAT 30 JUN 2012 1240 hrs

On 27 June I wrote to Dr Sallenger:

I wonder if you might have time to help me understand this paper’s conclusions, please? The abstract states:

“Modelled dynamic plus steric SLR by 2100 at New York City ranges with Intergovernmental Panel on Climate Change scenario from 36 to 51 cm (ref. 3); lower emission scenarios project 24–36 cm (ref. 7). Extrapolations from data herein range from 20 to 29 cm.”

Does this mean the paper concludes that, to the projected SLR rise by 2100 under any IPCC scenario, we should add from 20 to 29 cm?

On 29 June he replied:

We would not say that for any scenario you would add 20-29 cm. That range was merely to illustrate that projections from the observations are in the same general range as those predicted by the models. We are closest in line with the lower emissions values.

My thanks to Dr Sallenger, although I still find it difficult to take his statement to some more obvious conclusion.

Does anyone have an interpretation?

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38 Thoughts on “Fierce fighting on SLR in North Carolina

  1. Alexander K on 28/06/2012 at 4:49 pm said:

    I’d like to help, but this is way above my level of expertise BUT, IMHO, it sounds like classic alarmist BS based on what Willis Eschenbach enunciated so well some months ago – this report looks like a classic case of ‘models all the way down’ and belongs in the bin with most of the Gorean nonsense that the infamous Stephan Ramsdorf promotes.
    I linked to the article on WUWT that reveals corruption of science which is truly jaw-dropping!

  2. Billy on 28/06/2012 at 6:19 pm said:

    Yeah,way above me too.It WILL be BS,rest assured.But we got plenty of bright guys here who can kick their arses.Back to beetles etc,one thing that has amazed me over most of my life floating on water is the ability of the toredo worm to completely eat the inside out of hardwood piles.They look like a ball of snot,but wreak havock with hardwood.They line their tunnels with a hard lining.Calcium I think.Apparently in the old days they ate ships hulls,and the first thing you knew was your ship falling to bits.I have seen hardwood piles look like honeycomb from their attacks.O.K.guys,Won’t waste your time.Just appreciate being welcomed into the conversation on this site.If you guys want to set up a dieting site,go for it.LOL.But you will make fk all from me,unless you can suggest how I can gain 500 grams in 2 years.Now that WOULD be a bonus.PMSL

  3. Richard C (NZ) on 28/06/2012 at 7:28 pm said:

    Lot’s of linear trends in the paper:

    For 60 yr (1950–2009), the largest SLRDs occur from Cape Hatteras to Boston (mean SLRD=1.97±0.64 mm yr−1


    Mean NEH SLRD is a factor of ~ 3–4 larger than global SLRD. For the 60-yr window, the global SLRD during 1950–2009 is 0.59±0.26 mm yr−1 (using reconstructed time series14), compared with NEH SLRD of 1.97±0.64 mm yr−1. For the 40-yr window, global SLRD during 1970–2009 was 0.98±0.33 mm yr−1, compared with NEH SLRD of 3.80±1.06 mm yr−1

    Then along comes Steven Goddard with satellite trends:-

    North Carolina Sea Level Rising At Less Than One Half Of The Global Average Rate

    According to the University of Colorado, sea level along the North Carolina coast is rising at a rate of 1.4 mm/year. This is less than one half of their measured global rate of 3.1 mm/year.

    The graph below plots the grid cells at (32.5, 281.5) (33.5,282.5) (34.5,283.5) (34.5,284.5) and (35.5,285.5)

    More comment >>>>>>>>

    “3.1 mm/yr” is now invalid. Latest data brings that down just below 3 mm/yr.

    Then the paper gets into acceleration using quadratics – as they should – but only by referencing a different paper than their own:-

    The authors of ref. 16 reported ‘little regional dependence’ of SLR acceleration in the US counter to our detection of a NEH. They found mean negative acceleration for 57 US gauges, including 17 in our observed NEH. Fitting a single quadratic equation for the entire time series available at each station, they calculated average accelerations from gauges having record lengths from 60 to 156 yr and compared them. The spatially averaged SLRDs (and accelerations) in NEH are, however, dependent on time-series length (Fig. 3 and Supplementary Fig. S4).

    OK, “negative acceleration” (deceleration) for 60 to 156 yr in a referenced paper but no quadratic equations or dates provided.


    Statistically significant positive SLRDs were detectable in 40-yr (1970–2009) to 72-yr (1938–2009) windows

    But now they’re back to linear trends in their own paper, A “Statistically significant positive [linear] SLRD” is NOT AN ACCELERATION. An acceleration would require a quadratic trend as in the previous quote from the referenced paper.

    They push their case based on their linear analysis:-

    The timing of NEH formation can be inferred from Fig. 3, where the general increase in SLRDs from start dates in the 1930s–1970 (with uniform end dates of 2009) could reflect a recent increase in the rate of SLR. The magnitude of the SLRD would increase as the regression window narrows and the centre point of the window approaches the date of the rate increase (Fig. 3 and Supplementary Fig. S5). This suggests that the increase occurred about or after 1990 (that is, with an inflection point about or after midway of a window with start year 1970 and end year 2009). Hence, the rate increase is coincident with the onset of accelerating global SLR in the early 1990s (refs 14, 15).

    “…the increase occurred about or after 1990” What exactly, is the significance of the early 1990s? Nothing anthropogenic.

    Tamino (Grant Foster) had a blog post using exactly the same trickery. Over shorter recent time spans, there’s plenty of opportunity to pick out positive upticks and call them “accelerations” even when linear trends are used,

    I predict that sharper minds than mine will shred this paper.

    • Richard C (NZ) on 29/06/2012 at 11:07 am said:

      Oops I lied.

      ““3.1 mm/yr” is now invalid. Latest data brings that down just below 3 mm/yr.”

      That was a while ago, #version_2012_rel1 had trends of:-

      3.34mm/yr 1992.9595 to 2011.9631

      1.76mm/yr 2005.1761 to 2011.9631

      -0.13mm/yr 2010.1714 to 2011.9631

      And U of C does say 3.1 +/- 0.4 mm/ the upper limit of that is 3.5 mm/yr

      For comparison, the trend over the period 1998 El Nino to beginning of 2005 was 3.7 mm/yr.

      #version_2012_rel3 is now available

      New data rel2 and rel3 combined:-

      2011.9903 47.129
      2012.0174 50.074
      2012.0446 51.242
      2012.0717 56.084
      2012.0989 54.702
      2012.1260 53.676
      2012.1532 49.891
      2012.1803 45.511
      2012.2075 50.761
      2012.2346 56.283
      2012.2618 54.432
      2012.2889 52.382
      2012.3161 51.102

      2012 rel 2 & 3 new data average for 13 points: 51.79

      13 points prior to rel 2

      2011.6374 51.195
      2011.6645 48.560
      2011.6917 46.401
      2011.7188 44.973
      2011.7460 48.431
      2011.7731 53.461
      2011.8003 49.322
      2011.8274 44.083
      2011.8546 41.609
      2011.8817 42.603
      2011.9089 51.543
      2011.9360 52.490
      2011.9631 48.707

      2012 rel 3 average for 13 points prior to rel 2: 47.95

      Wow, a 3.84 mm rise in 0.353 of a year, a massive “acceleration”.(as Asbury et al would say).

      That’s 10.88 mm/yr, 108.88 mm/decade and 1.089 metres/century – the alarmists are right after all.

      Don’t know what the latest complete series linear trend is though because I haven’t got Excel installed at the moment (long story) and the Google Docs Spreadsheet isn’t as friendly yet. Suspect it’s around 3.4 but still decelerating using a polynomial.

  4. Richard C (NZ) on 28/06/2012 at 7:41 pm said:

    Just so this paper can be recognized when someone trots it out (or buries it) in abbreviated form, it’s:-

    Asbury et al, 2012

    Will probably come up in conversation, along with the EPA’s US federal appeals court win:-

    Comments are open.

    • Richard C (NZ) on 30/06/2012 at 2:02 pm said:

      Richard T has pointed out down-thread that the lead author is Asbury H.Sallenger. My error.

    • Andy on 29/06/2012 at 11:02 pm said:

      Thanks for the picture of the Kitesurfer at Lyall bay, Nick.
      It is a sport I do but I never have the balls to ride there.

      It looks nice from the Koru Lounge though

    • Richard C (NZ) on 30/06/2012 at 9:19 am said:

      8m massive? When Port of Tauranga has been closed, I think it took 13m swells to do it. No ill effects on the coast though.

      BTW, high-tide predictions for the next 100 years (2007–2107).at Bay of Plenty:-
      MHWS level for the Bay of Plenty

      Rob Bell, Matt Lewis
      Prepared for Environment Bay of Plenty

      NIWA Client Report: HAM2006-133
      October 2006

      In this report, we have coalesced alternative definitions of MHWS [Spring] for the open coast of Bay of Plenty onto a high-tide exceedance curve, which then provides the context for judging how often any defined MHWS level is exceeded. The exceedance curves provide the frequency at which a given high tide is exceeded based on high-tide predictions for the next 100 years (2007–2107). Tide predictions were based on NIWA’s New Zealand tidal model, and ground-truthed using a 19-year tidal analysis of measurements from the Moturiki sea-level gauge.

      These exceedance curves are provided for six sites (five on the open coast and one at the Port of Tauranga) in terms of high-tide height above the Mean Level of the Sea (MLOS). This means the exceedance curves can be used for several decades; with the only requirement to update the MLOS level (above Moturiki Vertical Datum–1953) when there has been sufficient change in MLOS due to long-term climate cycles or sea-level rise.
      Given SLR at Moturiki is all but undetectable now,

      The exceedance curves are probably valid for many years (decades possibly) to come without adjustment.

    • Richard C (NZ) on 30/06/2012 at 10:25 am said:

      Further anecdote. I worked with a guy who went bodysurfing with a handboard at the harbour entrance when the port was closed. Got taken under and caught on a rock for a while, nearly drowned. He decided to call it a day after that.

      When the port opened I went with the crowd to watch the ships leave that had been stuck in port because the swell was still huge. They were long swells but it still made quite a spectacle.

      The high tides that do the damage to the dunes are not necessarily when waves are huge. From what I’ve seen it’s when the waves come in at an angle to the beach that the along shore scouring happens. The dunes recover though, the entire suburb of Omanu-Papamoa is built on dunes that have built up from way back at the hills over time. You can see it in the early aerial photos before subdivision.

  5. Alexander K on 30/06/2012 at 12:06 pm said:

    Bob Tisdale (a regular guest scientist at WUWT who writes very readable books about this subject) has just posted a guest article on WUWT to assist the embattled John Droz and put this nonsense to flight. The alarmist paper in question has been created by dint of leaving inconvenient data out plus the practice, beloved of alarmists, of cherry-picking where they start and where they stop in the graphing of trends.
    That coastline of the USA is inexorably sinking, albeit incredibly slowly, as part of the continuing process of continental drift, which is not something one can pop out and actually observe during one’s lunch time – or even one’s lifetime!

    • Richard C (NZ) on 30/06/2012 at 1:24 pm said:

      Tisdale is citing the paper as Sallenger et al (2012), I thought the first name was usually the lead author and that was the convention for citation i.e. Asbury et al.

      Not in this paper though:-


      A.H.S. conceived the study, developed hypotheses and tests, supervised the work and wrote the main text. K.S.D. conducted the calculations, and posed and carried out sensitivity and statistical tests. P.A.H. designed statistical tests, developed/tested methods and wrote the Methods and Supplementary Information.

      This from Bob Tisdale makes some sense of it all:-

      Now we can understand why Sallenger et al (2012) were discussing a multidecadal signal. One very plainly exists.

      Figure 8

      Looking at the trailing decadal (120-month) trends, Figure 9, we can see very clearly that the trend of the most recent decade (through December 2008) is not as high as it has been in the past.

      Figure 9

      Quadratic trend analysis spanning the multidecadal series to uncover any real acceleration or deceleration would be more appropriate but Bob Tisdale has not done that. Sallenger et al have already cited another paper showing negative acceleration (deceleration). Which deflates their own paper somewhat.

    • Tisdale is citing the paper as Sallenger et al (2012), I thought the first name was usually the lead author and that was the convention for citation i.e. Asbury et al.

      His first name is Asbury. He signs himself “Asbury Sallenger, PhD”.

    • Richard C (NZ) on 30/06/2012 at 2:00 pm said:

      Thank you Richard Treadgold. I should have looked more closely.(and an engaged brain would have helped too).

    • Richard C (NZ) on 30/06/2012 at 2:10 pm said:

      The paper that Sallenger et al cite that shows a negative acceleration (deceleration) using quadratic trend analysis is (ref 16) Houston, J. R. & Dean, R. G. Sea-level acceleration based on US tide gauges and extensions of previous global-gauge analyses. J. Coastal Res. 27, 409–417 (2011).

      “The authors of ref. 16 reported ‘little regional dependence’ of SLR acceleration in the US counter to our detection of a NEH. They found mean negative acceleration for 57 US gauges, including 17 in our observed NEH. Fitting a single quadratic equation for the entire time series available at each station, they calculated average accelerations from gauges having record lengths from 60 to 156 yr and compared them”

      I get the impression that the purpose of the Sallenger et al paper is to relegate that finding as much as possible and supersede it in the minds of interested parties. Mr Droz would do well to study H & D 2011 too and to bring that paper front of mind to those deliberating over NEH .

  6. Alexander K on 02/07/2012 at 3:16 pm said:

    Bob Tisdale has today posted a second part to his earlier post on this on WUWT – well worth a read, even for lay people such as I. Hopefully, the legislators in Maryland won’t be swayed by the ardent doomsayers – Tisdale’s two pieces leave no doubts floating about.

    • Richard C (NZ) on 02/07/2012 at 5:16 pm said:

      Still in linear mode. How Sallenger can cite models as some sort of credible corroboration is beyond me in view of that. “Scientific” American looks a bit silly too.

      Part 2 here

    • Nick on 03/07/2012 at 8:16 pm said:

      Hi Richard C, can you explain why you don’t think positive SLRD is appropriate to demonstrate acceleration? Surly if the linear trend after 1990 is higher than the linear trend before the 1990 (with appropriate statistical analysis) that is sufficient to demonstrate acceleration?

    • Richard C (NZ) on 04/07/2012 at 8:41 am said:

      Nick, first it’s not a matter of what I “think”, it’s about the nature of acceleration and the role of quadratic equations in understanding acceleration starting with Galileo and Newton. I suggest you read something like this article 101 uses of a quadratic equation: Part II if you’ve forgotten all this from school.

      Second, a polynomial trend best represents fluctuating data because it returns an R squared value closer to 1 than a linear regression. A linear trend is only appropriate for data resembling a line and that is what Sallenger et al have done, they’ve cherry-picked a short-term uptick (plenty of those to choose from) that looks linear, slapped a linear trend on that portion of the series, compared it with an earlier portion similarly trended and said “hey, an acceleration” incorrectly because they don’t know the nature of acceleration. Houston and Dean (that Sallenger et al cite) do know the nature of acceleration on the other hand, they used quadratics for their analysis finding deceleration in NEH.

      Basically, there’s nothing linear in the nature of acceleration. All Sallenger et al have found is a short-term uptick (that as the dates show has nothing to do with anything anthropogenic).

    • Richard C (NZ) on 04/07/2012 at 2:46 pm said:

      The 3,1 mm/yr +/- 0.4 linear trend that UofC applies to satellite era GMSL data 1983 – present was a reasonable representation of the series early on because the data was basically linear but the linear trend is no longer valid.

      If you plot the data from here the best fit is now a polynomial. It’s negative therefore a deceleration.

      If you then apply tangents (just using a straightedge) to the poly trend curve moving with time, the slope of the tangents (instantaneous linear trends) progressively diverge below the 3.1 figure.

      In a few years time, the last tangent (instantaneous linear trend) will be flat on a projected poly curve. This is problematic for say the Antarctic Climate & Ecosystems Cooperative Research Centre (ACECRC) whose Report Card: Sea Level Rise 2012 (topical in Australia at present) states:-

      Future Sea-Level Rise

      Projections of the future sea level are derived from atmospheric and ocean temperatures simulated
      by ocean-atmosphere-climate models, which are driven by different scenarios of atmospheric CO2 and other greenhouse gases.

      No proven physical mechanism exists for this of course but the power of groupthink should never be underestimated

      How then does the ACECRC reconcile their CO2 rise based projections with the empirical deceleration of satellite era GMSL (and HadSST2/3) that is looking like topping out in a few years? Simple answer – they don’t. There’s only one possible driver for them – “scenarios of atmospheric CO2 and other greenhouse gases”, never mind the real world.

    • Richard C (NZ) on 04/07/2012 at 3:49 pm said:

      More to show linear analysis is a blunt instrument and that more sophisticated tools are available:-

      Detecting regime shifts in climate data – the modern warming regime ended in 1997

      The Analysis of the Global Change using Hurst Re Scaling

      S.I.Outcalt : Emeritus Professor of Physical Geography, University of Michigan

      Abstract: Three data sets used to document the case for anthropogenic global warming were analyzed using Hurst Rescaling. The analysis indicated that a more likely interpretation of the data is that the observed linear trend in global temperatures is an artifact of regime shifts. The dramatic “hockey stick” trace, which began in 1976 accompanied by a major transition in the Pacific Decadal Oscillation, ends at the onset of the 21st Century and might be better termed the modern warming regime. This regime was replaced by a pronounced cooling regime. These observations attenuate the demonic interpenetration of the linear trend in the historic global temperature data.

      Figure 3 indicates that a major transition occurred at the onset of the 21st Century. The global thermal response to this transition is somewhat muted. An inspection of the data displayed as Figure 1 shows only slight downturns near the end of the record in 2008. However, ground temperature data collected by Janke(2011) and analyzed by the author indicates a major shift from a warming to cooling regime in the early years of the 21st Century. This ground temperature data is based on the mean annual temperatures calculated from probes at 1 m intervals in three 6 m boreholes along Trail Ridge Road in Rocky Mountain Park, Colorado. The annual mean temperatures were calculated from hourly observations and are therefore extremely robust. The data were collected in mountain tundra terrain above treeline along an east / west ridge. The data from these boreholes is displayed as Figure 4.

      That is, fixation on linear trends gives the impression (widely disseminated) of gradual climate change. Better analysis using appropriate tools reveals climate shifts (regime shifts).

      Question is: are we on the cusp of a shift to a warmer regime than the first decade of the 21st century? Or a cooler regime? Or no change?

      And what are the probabilities to be allocated to each possibility for the decade 2010 – 2020? Here’s my guess:-

      0.1 warmer regime
      0.5 no change (same as last decade)
      0.4 cooler regime

    • Nick on 15/07/2012 at 8:03 pm said:

      Hi Richard C, I agree that a polynomial will give a better fit and that you can simply keep adding terms until it perfectly matches the data. The problem with this approach is that you are basically modeling the noise and it is fairly useless for identifying underling trends in any quantifiable way. Sure you can take the first or second derivative at any given point to identify the rate of change and acceleration but these values will vary wildly due to the noise that has been included.

      A good general rule of thumb that I’m sure you are aware of is to make things as complicated as necessarily but no more so. I suggest that comparing linear trends over different suitable sized windows to identify if acceleration exists and if so what the point of inflection is sufficient to demonstrate that what is happening in North Carolina matches what has been predicted by climate models.

      Your obsession with using polynomials to achieve the best fitting curve misses the point somewhat. When all you have is a hammer everything looks like a nail…

    • Richard C (NZ) on 15/07/2012 at 9:11 pm said:

      You STILL don’t know what an acceleration is in terms of mathematics and physics do you Nick?

      I’ve provided a link up-thread for that express purpose, why don’t you read it?

      You CANNOT escape the statistical fact (R squared values Nick) that a linear trend is inappropriate to represent data unless that data resembles a LINE. An acceleration does NOT resemble a line. If you can’t handle the added complexity of the other tools in the trend toolbox then how can you cope with actual data signal extraction tools (see below)? If you characterize a polynomial as a “hammer” then how will you characterize signal extraction tools?

      You say:-

      “The problem with this approach is that you are basically modeling the noise and it is fairly useless for identifying underling trends in any quantifiable way.”

      Rubbish. You are the one that insists on peer-reviewed papers but you can’t accept the ones that don’t tell the story you want when they use a polynomials appropriately instead of an inappropriate linear trend for fluctuating data e.g. Houston and Dean 2011 and Scafetta 2010, the empirical model in the latter currently beating the IPCC models hands down.

      These trend methods (polynomial, linear or moving average) are ALL extrinsically imposed. The only way to extract the intrinsic data signal from time varying data is to use a signal extraction method e.g. Empirical mode Decompostion (EMD). What this enables that extrinsic methods do not is to not only extract the overall residual signal that will show any major inflexion over long periods greater than 50 -60 yrs as per Douglas 1992 (HadSST2 132 yrs EMD now shows a negative inflexion when only a couple of yrs ago was rising positively) but will also reveal in the Intermediate Mode Frequencies (IMFs) the decadal and multideadal oscillations. The first few IMFs are noise but IMFs from about IMF5 will identify oscillations. All the short-term up-ticks and down-ticks at the NEH summarized here are just short-term oscillations

      Had SST2 EMD trend analysis compared to polynomial here


      “….what is happening in North Carolina matches what has been predicted by climate models”

      Baloney – prove it. And I repeat from a previous comment, before you do have a look at Bob Tisdale’s NEH models vs observations

    • Richard C (NZ) on 15/07/2012 at 10:09 pm said:

      Did the models predict this Nick (linear trends just as you prefer)?

      Figure 6: Sea level development of Tasmania during the past 200 years. Between 1900 and 1950 the sea level rose at a rate of 4.2 mm per year.. During the second half of the 20th. Century sea level rise slowed markedly, however, averaging only 0.7 mm per year. Figure source: Gehrels et al. (2012).

      From: Case studies from around the world show: No acceleration of sea level rise during the last 30 years

    • Nick on 20/07/2012 at 10:48 pm said:

      Hi Richard,
      Is it your opinion that your analysis using EMD would yield different results to Sallenger (using the same data set of course)?

      Specifically he finds the that sea levels have shown statistically significant acceleration since the early 1990s.

      If EMD shows something different please post it for me to have a look. Having seen the spreadsheet you presented via drop box below could I also request that you show your working and maybe label some of the data please.

    • Richard C (NZ) on 21/07/2012 at 8:49 am said:

      Nick you say:-

      “Is it your opinion that your analysis using EMD would yield different results to Sallenger (using the same data set of course)?”

      If you’ve seen the Dropbox plot (and you’ve indicated you have) then you can answer that yourself (BTW it’s nothing to do with my “opinion”).

      “If EMD shows something different please post it for me to have a look. Having seen the spreadsheet you presented via drop box below could I also request that you show your working and maybe label some of the data please.”

      EMD shows a negative inflexion in the most recent HadSST2 data (not a deceleration, this is signal we’re talking about now) in the century scale data. The results and data are in the spreadsheet, The columns are IMFs, the last being the residual. The result was generated using an EMD program, one of which is available here

      There’s also papers documenting EMD use in climate science if you care to look them up.

    • Richard C (NZ) on 21/07/2012 at 11:41 am said:

      I’ve expanded on the spreadsheet EMD analysis of HadSST2 but I put the comment in the wrong place, see here:-

    • Nick on 03/07/2012 at 8:27 pm said:

      Tamio’s analysis uses a quadratic fit which also shows acceleration.

      I think it is really just two different ways of showing the same thing, which is accelerating sea level rise. The real concern is that anyone would consider legislating against that. Parallels to King Canute have been made…

    • Richard C (NZ) on 04/07/2012 at 10:31 am said:

      I was referring to a much earlier Tamino post but never mind. In the post you link he uses the recent 60 year time span of Sallenger et al. Here’s what Houston and Dean 2011 say about that:-

      Douglas (1992) notes that sea-level trends obtained from tide-gauge records with lengths less than 50–60 years are significantly ‘‘corrupted’’ by decadal variations; therefore, we analyzed U.S. tide-gauge records having at least 60, an average of 82, and as many as 156 years (San Francisco, California) of data recorded at single locations and without significant tectonic activity that has produced vertical-datum shifts.

      That is, a less than 50-60 time span produces short-term variations (“upticks” and “downticks” – my terms) within the span that can be misleading. First Tamino finds a downtick in the short-term:

      I took the data since 1950 for all 20 stations in the hotspot, computed anomalies, smoothed them, then subtracted the linear trend line from them to show the departure from a linear trend. Here are all of them, plotted on the same graph:

      Most of them do indeed show a dip in the mid-1980s.

      Next he finds a short-term uptick:-

      But they also show genuine accleration, rising faster since about 1990 than they did before that

      So according to Tamino, the “genuine acceleration” started AFTER 1990 but then he contradicts himself when getting around to actually applying a quadratic (to his credit) to the series starting in 1950:-

      We can even take the aligned data and fit a quadratic polynomial, which also illustrates the presence of acceleration. It’s more clearly visible when plotted against annual averages rather than monthly:

      So in summary:-

      1993 – 2012 “genuine acceleration” by Tamino using data corrupted by decadal variations from cherry-picked time span.

      1983 – 1993 abrupt rise (“uptick”) by Tamino using same short-term variations.

      1963 – 1983 deceleration (“downtick”) by Tamino using same short-term variations.

      1950 – 1963 gradual fall (“downtick”) by Tamino using same short-term variations.

      1950 – 2012 quadratic acceleration by Tamino

      pre 1950 – 2009 quadratic deceleration by Houston and Dean.

      Basically the shorter the time span, the easier it gets to pick a period to support a view. For example, I can pick the period 2010 – 2012 from Tamino’s NEH plot here:-

      That shows an abrupt downtick so I can say that the most recent trend is significantly down and in no way an acceleration but of course this is misleading as is the other cherry-picked intervals.

      No-one is legislating against SLR Nick. What they are doing is looking for realistic measures of prediction that don’t produce nutcase policies that unnecessarily impose unrealistic regulations and send property values plummeting as has been happening around the world from the implementation of extreme (and alarmist) measures.

    • Nick on 03/07/2012 at 8:56 pm said:

      You also ask what the significance of 1990 is up thread. In Sallenger’s paper it is fairly clear that they consider the accelerating melting of the Greenland ice sheet which was first observed in the early 90s to be the likely cause of the accelerating sea level rise on the Atlantic coast of North America. This is in agreement with model projections.

    • Richard C (NZ) on 04/07/2012 at 10:49 am said:

      Let me get this straight Nick.

      Now you are implying that the “anthropocene” era started circa 1990?

      And the Greenland ice melt water (as cold as it is) ONLY accumulates in the NEH discounting any thermosteric rise?

      But that same Greenland melt water doesn’t accumulate over at the Indo-Pacific Warm Pool (rising at around 12 mm/yr 1993 – 2012)?

      And all of this “is in agreement with model projections”?

      Before you get too far in defense i suggest you read this post re Pinatubo eruption, models vs observations and the Scientific American blunder

    • Nick on 20/07/2012 at 10:51 pm said:

      Hi Richard,
      I’m not implying anything although you are free to draw your own conclusions. Apart from “is in agreement with model projections” you have got it mostly wrong though.

    • Richard C (NZ) on 21/07/2012 at 8:55 am said:

      Nick re “is in agreement with model projections” you say:-

      “…you have got it mostly wrong though”

      This the most limp and vacuous offering of hand waving you’ve come up with so far in your participation at this blog Nick. Are you trying to set the level of argument at the lowest possible level?

      If not, substance please.

    • Nick on 21/07/2012 at 9:12 pm said:

      Hi Richard, sorry if you don’t feel that the last comment is up to my normal standard of contribution.

      You asked if I was implying a number of points. My answer is no I am not implying any of those things.

      If you think my comments lead to those conclusions perhaps you could explain your reasoning and I’m happy to discuss it further.

      For example it is not clear to me why the observed onset of accelerated melting in Greenland in the 90s should signal the beginning of the Anthropocene when it is generally considered to start at the beginning of the industrial revolution or earlier.

    • Richard C (NZ) on 21/07/2012 at 11:36 am said:

      Perhaps I had better expand a little. Back a few years if you had done an EMD analysis of HadSST2 you would have got a residual that resembled the underlying positively rising quadratic of HadCRUT3 (natch because HadSST2 is the major component of HadCRUT3) that Scafetta found (and possibly Salinger although I don’t know what he used in whatever it is that you are referring to).

      I did a while ago but because EMD is very sensitive to new data I redo the analysis when new data comes in. I was quite surprised by the latest result (in Dropbox) because the residual is the inverse of anything I had done previously. It also calls into question Scafetta’s quadratic basis for his empirical model.

      Note that you can project a polynomial trend for prediction (sensibly) but you CANNOT project an EMD residual or IMF (Scafetta projects harmonic cycles). What happens in EMD analysis is that when new data is added there’s the possibility that a new IMF and residual will be extracted. This is exactly what happened in my last analysis of 162 yrs of data, where previously there were 6 IMFs and the residual, there were now 7 IMFs and a new residual. Basically, the old residual became IMF 7.

      IMF 5 is the multidecadal oscillation of SST in my estimation because none of the other IMFs exhibit that signal. That radical downturn at the end will turn up again (equally radically) eventually as new data comes in. The first few IMFs are just noise and I haven’t included IMF 1 for that reason.

      So the spreadsheet columns are (for the 162 yr analysis):-

      A – time
      B – HadSST2 anomaly
      C – IMF 2
      D – IMF 3
      E – IMF 4
      F – IMF 5 multidecadal oscillation
      G – IMF 6
      H – IMF 7
      I – residual trajectory

      Note that there are only 5 IMFs in the 30 yr analysis but the multidecadal oscillation occurs at this frequency (IMF 5) in both the 162 yr and 30 yr analyses.

    • Richard C (NZ) on 21/07/2012 at 11:44 am said:

      The above comment is out of place, it is actually a follow-on comment in response to Nick here:-

    • Richard C (NZ) on 21/07/2012 at 12:22 pm said:

      Nick you might be interested in these analyses:-

      Satellite GMSL EMD to 2010.7 (old data)

      GMSL polynomial and linear trends in TOPEX/Jason (Envisat has failed so ignore that)

      The underlying polynomial trends of Global Average Temperature (HadCRUT3) vs the equivalent for CO2

      That was back when the underlying trend of HadCRUT3 was actually a quadratic. Note how temperature LEADS CO2 by some 27 years at 1977.

    • Richard C (NZ) on 21/07/2012 at 12:32 pm said:

      Those linear trends in GMSL are intentionally cherry picked just to get a rough-as-guts handle on what’s been happening so I don’t attest to any validity except for the polynomial, that wont have changed much.

      Also there’s new data now and the most recent short-term data is back up so the most recent trends are somewhat misleading.

      The old data gets adjusted retroactively with each new revision release so that’s a trap too.

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