Gummed by a tired truffle dog

Ah, I love it, seriously Gareth, this keeps me entertained of an afternoon.

Trufflehunter tries to have another crack after being caught overegging the global warming cake in his submissions to Parliament.

Taking issue with my assertions that Greenland is not wildly melting as Gareth has previously chirped, he writes:

To counter this, he quotes from an article in Science which discussed a paper at last year’s Fall Meeting of the American Geophysical Union, describing how glaciers in SE Greenland had slowed down after a period of “galloping” towards the sea. This, Wishart implies, means that the whole of Greenland has stopped melting.

Wishart doesn't imply the whole of Greenland has stopped melting at all. And if he'd read page 183 of Air Con where this issue is covered, Gareth would have seen that. It appears, by his own admission he spent too much time "harrumphing" and not enough time reading.

Because he then says:

It’s a pity Wishart didn’t look at some of the other papers presented at the Fall AGU — there were at least 25 covering Greenland and its melting ice cap. Here’s the abstract from Wouters et al:

The abstract isn't actually that important to my point here, because my point is that this is yet more evidence Truffle never properly read Air Con. How do I know? Because footnote 292 on page 183 is the Wouters paper he just accused me of not reading.

And in case Truffle doesn't explain it properly, Wouters et al's paper is helpfully entitled "GRACE observes small-scale mass loss in Greenland" [my emphasis on small scale]. The paper was not called "Panic Stations: All Hands To The Pumps!".

The central premise of page 183 is that Greenland's melt is not that spectacular, and nowhere near where it needs to be to cause massive sea level rise on both current temperatures and extrapolations.

Gareth can quote alarmist climate scientists till the cows come home who sombrely warn of a one metre rise by mid-century, but I do wonder precisely how that will happen in light of Swanson and Tsonis' paper published this year, which suggests Earth's climate underwent a seismic shift early this decade and now appears to have entered a cooling phase likely to continue until 2025, followed by a brief warm spell then cooling for the rest of the century.

Greenland and Antarctica would have an uphill battle on that basis, although I'd be the first to acknowledge there's a timelag built in to how fast oceans and ice react to historic warming.

Swanson and Tsonis say the shift appears to have been caused by a number of oceanic oscillations and other climate factors all peaking around the same time, and knocking the existing climate predicitons off their perch. They acknowledge (Gareth, Cindy, StephenR etc take note) that Earth may be radiating more heat out to space because of changes in the way clouds are behaving (which puts existing GCM climate models into disarray and supports what Roy Spencher and John Christy have been saying for some time).

On the issue of sea level rise, Gareth pokes me with this:

if we look at the graph, we see that the current rate of SLR is 3.2mm per year, and it hasn’t dropped recently to 2mm per year as Wishart asserts. Does he have trouble reading a graph, one wonders? Or perhaps his data was out of date?

Once again, Gareth et al, I do urge you to read Air Con, the current number one bestseller :), before rushing into print. Becausehere's what's in Air Con:

"Satellite samplings suggest an average sea level rise of 3mm a year, or 3cm a decade, which works out at 30cm a century. This is where the IPCC gets its estimates of a 20cm to 43cm increase in sea levels by 2100. The UN's own IPCC Fourth Assessment Report concedes that net sea level rise observed so far may only be as high as 1.3mm a year, equivalent to 13cm a century."

I then quoted a study from the journal Science in Air Con:

"The 3.2 + 0.2 millimetre per year blobal mean sea level rise observed by the Topex/Poseidon satellite over 1993-98 is fully explained by thermal expansion of the oceans...the 20th cenutry sea level rise estimated from tide gauge records may have been overestimated."

In other words, a large chunk of the 3mm a year sea level increase may simply be thermal expansion lag, rather than melt contribution. And, as we've covered previously, the ARGO survey is not detecting overall warming of the oceans this decade.

WHere does this take us in terms of Gareth's one to two metres of sea level increase this century, especially in face of the Tsonis paper suggesting a cooler 21st century? Well, I wouldn't be betting your royalties from Hot Topic sales on the outcome Gareth.

Oh, and for the record Truffle, the data on sea level rise slowing to 2mm a year was publishing by the University of Colorado, Boulder in late 2008. The accompanying graph is here, and you cn clearly see the slowdown:

 

UPDATE:

Oh, come on Truffle, is this the best you can do? If GRACE had found monster mass loss in Greenland they'd have been shouting it from the rooftops. Instead, they contented themselves with the melt around the edges. As you and I both know, Truff, Greenland's interior hasn't lost mass at all. And like I pointed out, a 0.5 millimetre contribution to sea levels every year [based on peak melt rates] will strike fear into the hearts of garden gnomes everywhere, equating as it does to 5cm a century.

I've yet to see you deal with any of the real points.

UPDATE TWO:

For the benefit of Greg, who asked about cooling trends. Relative to the highs of the late 90s early 2Ks, which corresponded to a sunspot maxima and major El Nino, average temperature peaks have fallen. This is loosely described as a cooling phase, but in terms of the climate debate beauty is in the eye of the beholder - the trend will depend on what your starting point is, what baseline average you are working from etc etc.

For example, 1998 was an El Nino spike and thus artificially high, so that even though 1999 onwards didn't hit that peak, they were still climbing relative to the early 90s...the momentum, or lag, built into this didn't really change until the early 2ks, where temperatures effectively plateaued then began to genuinely retreat, which the graph below tends to illustrate.

 

Now, it is worth noting that just as El Nino pumped up temperatures, its evil twin La Nina cools the planet down, so on the face of it global warming alarmists want to claim the "record years" in the name of global warming but write off the colder years as "merely La Nina".

You can't actually have your Truffle and eat it too, if the cooling is mostly written off to natural you can't claim the benefits of a natural El Nino as proof of man-made global warming.

Earth has been pulling out of the Little Ice Age since around 1800, entirely naturally, and the obvious consequence of that is that Earth will warm up. This is the major underlying trend at present, muddled by two factors - decreasing output from the sun since 2003 which historically is linked to lower temperatures, and the 'climate shift' theory of Swanson and Tsonis which suggests the warming cycle has been spiked by a 2002 shift in Earth's climate oscillation synergies.

Comments

[Iwi's hart.]

Ian. Don't be disingeneous, cite articles properly. You'd get an E, if you were a science student.

Anyway, here's one of the articles you refer to:

1
A new dynamical mechanism for major 1 climate shifts.
2
3 Anastasios A. Tsonis, Kyle Swanson, & Sergey Kravtsov
4
5 Department of Mathematical Sciences, Atmospheric Sciences Group, University of
6 Wisconsin-Milwaukee, Milwaukee WI 53201-0413
7
8 Abstract We construct a network of observed climate indices in the period 1900–2005
9 and investigate their collective behavior. The results indicate that this network
10 synchronized several times in this period. We find that in those cases where the
11 synchronous state was followed by a steady increase in the coupling strength between the
12 indices, the synchronous state was destroyed, after which a new climate state emerged.
13 These shifts are associated with significant changes in global temperature trend and in
14 ENSO variability. The latest such event is known as the great climate shift of the 1970s.
15 We also find the evidence for such type of behavior in two climate simulations using a
16 state-of-the-art model. This is the first time that this mechanism, which is consistent with
17 the theory of synchronized chaos, is discovered in a physical system of the size and
18 complexity of the climate system.
19
20 1. Introduction
21 One of the most important and mysterious events in recent climate history is the climate
22 shift in the mid-1970s [Graham, 1994]. In the northern hemisphere 500-hPa atmospheric
23 flow the shift manifested itself as a collapse of a persistent wave-3 anomaly pattern and
24 the emergence of a strong wave-2 pattern. The shift was accompanied by sea-surface
25 temperature (SST) cooling in the central Pacific and warming off the coast of western
26 North America [Miller et al., 1994]. The shift brought sweeping long-range changes in
27 the climate of northern hemisphere. Incidentally, after “the dust settled,” a new long era
2
of frequent El Niños superimposed on a sharp global temperature increase 28 has begun.
29 While several possible triggers for the shift have been suggested and investigated
30 [Graham, 1994; Miller et al., 1994; Graham et al., 1994], the actual physical mechanism
31 that led to the shift is not known. Understanding the dynamics of the above phenomena is
32 essential for our ability to make useful prediction of climate change. A major obstacle to
33 this understanding is the extreme complexity of the climate system, which makes it
34 difficult to disentangle causal connections leading to the observed climate behavior. Here
35 we present a novel approach, which reveals an important new mechanism in climate
dynamics and explains several aspects of the observed climate variability in the late 20th 36
37 century.
38
39 2. Methods and Results from Observations
40 First we construct a network from four major climate indices. The network approach to
41 complex systems is a rapidly developing methodology, which has proven to be useful in
42 analyzing such systems’ behavior [Albert and Barabasi, 2002; Strogatz, 2001]. In this
43 approach, a complex system is presented as a set of connected nodes. The collective
44 behavior of all the nodes and links (the topology of the network) describes the dynamics
45 of the system and offers new ways to investigate its properties. The indices represent the
46 Pacific Decadal Oscillation (PDO), the North Atlantic Oscillation (NAO), the El
47 Niño/Southern Oscillation (ENSO), and the North Pacific Oscillation (NPO) [Barnston
48 and Livezey, 1987; Hurell, 1995; Mantua et al., 1997; Trenberth and Hurrell, 1994].
49 These indices represent regional but dominant modes of climate variability, with time
50 scales ranging from months to decades. NAO and NPO are the leading modes of surface
3
pressure variability in northern Atlantic and Pacific Oceans, the PDO is 51 the leading mode
52 of SST variability in the northern Pacific and ENSO is a major signal in the tropics.
53 Together these four modes capture the essence of climate variability in the northern
54 hemisphere. Each of these modes involves different mechanisms over different
55 geographical regions. Thus, we treat them as nonlinear sub-systems of the grand climate
56 system exhibiting complex dynamics. Indeed, some of their dynamics have been
57 adequately explored and explained by simplified models, which represent subsets of the
58 complete climate system and which are governed by their own dynamics. For example,
59 ENSO has been modeled by a simplified delayed oscillator in which the slower
60 adjustment time-scales of the ocean supply the system with the memory essential to
61 oscillation [Elsner and Tsonis, 1993; Schneider et al., 2002; Marshall et al., 2001; Suarez
62 and Schopf, 1998]. Monthly-mean values in the interval 1900–2000 are available for all
63 indices.
64
65 In our approach, the four climate indices are assumed to form a network of interacting
66 nodes. A commonly used measure to describe variations in the network’s topology is the
67 mean distance d(t) [Onnela et al., 2005].


− Î
=
t t
ij d D
t
ij d
N N
d t
( 1)
2
( ) 68 (1)
69 Here t denotes the time in the middle of a sliding window of width Dt, N=4; i,j=1,…, N,
and 2(1 ) t
ij
t
ij d = − r , where
t
ij 70 r is the cross-correlation coefficient between nodes i
and j in the interval [t-Dt/2, t+Dt/2], and D t 71 is the NxN distance matrix. The sum is taken
4
over the upper triangular part (or the distinct elements of D t). The above 72 formula uses the
73 absolute value of the correlation coefficient because the choice of sign of indices is
74 arbitrary. The distance can be thought as the average correlation between all possible
75 pairs of nodes and is interpreted as a measure of the synchronization of the network’s
76 components. Synchronization between nonlinear (chaotic) oscillators occurs when their
77 corresponding signals converge to a common, albeit irregular, signal. In this case, the
78 signals are identical and their cross-correlation is maximized. Thus, a distance of zero
79 corresponds to a complete synchronization and a distance of 2 signifies a set of
80 uncorrelated nodes.
81
82 Figure 1a shows the distance as a function of time for a window length of
t = 11 years,
83 with tick marks corresponding to the year in the middle of the window. The correlations
84 (and thus distance values for each year) were computed based on the annual-mean indices
85 constructed by averaging the monthly indices over the period of November–March. The
86 dashed line parallel to the time axis in Figure 1a represents the 95% significance
87 level associated with the null hypothesis that the observed indices are sampled from a
88 population of a 4-dimensional AR-1 process driven by a spatially (cross-index) correlated
89 Gaussian noise; the parameters of the AR-1 model and the covariance matrix of the noise
90 are derived from the full time series of the observed indices. This test assumes that the
91 variations of the distance with time seen in Figure 1a are due to sampling associated with
92 a finite-length (11-yr) sliding window used to compute the local distance values.
93 Retaining overall cross-correlations in constructing the surrogates makes this test very
94 stringent. Nevertheless, we still find that five times (1910s, 1920s, 1930s, 1950s, and
5
1970s) when distance variations fall below the 95% significance level. 95 We therefore
96 conclude that these features are not likely to be due to sampling limitations but they
97 represent statistically significant synchronization events. Note that the window length
98 used in Figure 1a is a compromise between being long enough to estimate correlations
99 but not too long to “dilute” transitions. Nevertheless, the observed synchronizations are
100 insensitive to the window size in a wide range of 7 yr 
t  15 yr.
101
102 An important aspect in the theory of synchronization between coupled nonlinear
103 oscillators is coupling strength. It is vital to note that synchronization and coupling are
104 not interchangeable; for example, it is trivial to construct a pair of coupled simple
105 harmonic oscillators whose displacements are in quadrature (and hence perfectly
106 uncorrelated), but whose phases are strongly coupled [Vanassche et al., 2003]. As such,
107 coupling is best measured by how strongly the phases of different modes of variability
108 are linked. The theory of synchronized chaos predicts that in many cases when such
109 systems synchronize, an increase in coupling between the oscillators may destroy the
110 synchronous state and alter the system’s behavior [Heagy et al., 1995; Pecora et al.,
111 1997]. In view of the results above, the question thus arises as to how the synchronization
112 events in Figure 1a relate to coupling strength between the nodes. It should be noted that
113 in this study we are interested in the complete synchronization among the nodes, rather
114 than weaker types of synchronization, such as phase synchronization [Boccaletti et al.,
115 2002; Maraun and Kurths, 2005] or clustered synchronization [Zhou and Kurths, 2006],
116 which are also important in climate interactions.
117
6
For our purposes here, if future changes in the phase between pairs of 118 climate modes can
119 be readily predicted using only information about the current phase, those modes may be
120 considered strongly coupled [Smirnov and Bezruchko, 2003]. Unfortunately, in climate
121 data analysis we are limited by the fact that data are sparse and the phase might not be
122 well known. One standard way to circumvent these limits is to use symbolic dynamics.
123 For any given time series point, we can define a symbolic phase by examining the
124 relationship between that point and its nearest two neighbors in time. As shown in Figure
125 2, if the 3 points are sequentially increasing, we can assign to the middle point a phase of
126 0, while if they are sequentially decreasing, a phase of . Intermediate values then follow.
127 Notice that this procedure is totally non-parametric, as it does not compare the actual
128 values of the points aside from whether a point is larger or smaller than its neighbors. The
129 advantage of this approach is that it is blind to ultra-low frequency variability, i.e.,
130 decadal scale and longer. Use of symbolic dynamics is appropriate in this case, as we are
131 primarily interested in changes in the synchronicity and coupling of climate modes over
decadal time scales. The symbolic phase n 132 f may then constructed for each of the six
133 climate time series considered here, and is represented as the trigonometric pair
(cos ,sin ) n n n 134 Z = f f . Changes in this pair from year to year are represented as
(cos cos ,sin sin ) n,n 1 n 1 n n 1 n DZ = f − f f − f + + + 135 . It is straightforward to construct
a least squares estimator of , +1 D n n 136 Z of the type
D Z
n,n+1
est =MZ
n 137 (2)
138 where Zn denotes a vector of all six possible phase pair combinations between our climate
indices ,and where M = [DZn,n+1 Zn
T][ Zn
Zn
T]-1 139 is the least squares predictor matrix
7
calculated using all possible combinations for all years. A measure of the 140 coupling then is
simply
DZ
n,n+1
est − DZ
n,n+1
2
141 , where strong coupling is associated with small values of this
142 quantity, i.e., good prediction.
143
144 This quantity is plotted in Figure 1b. Figures 1c and 1d show the global temperature and
145 El Nino index in our period. The vertical broken lines in all panels correspond to the
146 times when the network went out of synchronization. Figure 1 tells a remarkable story.
147 First let’s consider the event in 1910s. The network synchronizes at about 1910. At that
148 time the coupling strength begins to increase. Eventually the network comes out of the
149 synchronous state sometime in late 1912 early 1913. The destruction of the synchronous
150 state coincides with the beginning of a sharp global temperature increase and a transition
151 from weak to strong El Nino events. The network enters a new synchronization state in
152 the early 1920s but this is not followed by an increase in coupling strength. In this case
153 no major shifts are observed in the behavior of global temperature and ENSO. Then the
154 system enters a new synchronization state in the early 1930. Initially this state was
155 followed by a decrease in strength coupling and again no major shifts are observed.
156 However, in the early 1940s the still present synchronous state is subjected to an increase
157 in coupling strength, which soon destroys it. As the synchronous state is destroyed, a new
158 shift in both temperature trend and ENSO variability is observed. The global temperature
159 enters a cooling regime and El Ninos become much less frequent and weaker. The
160 network synchronizes again in 1950. This state is followed by a decrease in coupling
161 strength and, as was the case in 1920 and in early 1930s, no major shifts occur. Finally,
162 the network synchronizes again in the mid 1970s. This state is followed by an increase in
8
coupling strength and incredibly, as in the cases of 1910 and 1940, 163 the climate shifts
164 again. The global temperature enters a warming regime and El Ninos become frequent
165 and strong. The fact that around 1910, 1940, and in the late 1970s climate shifted to a
166 completely new state indicates that synchronization followed by an increase in coupling
167 between the modes leads to the destruction of the synchronous state and the emergence of
168 a new state, in agreement with the theory.
169
170 3. Model Results
171 According to the theory of synchronized chaos such shifts in systems of nonlinear
172 coupled oscillators are caused by bifurcations as the coupling parameter changes. Thus,
173 the coupling strength acts as an external parameter modifying the system. In our case the
174 coupling strength is estimated from the data and thus it is not clear whether its variability
175 is dictated by some external forcing acting on the system or it is intrinsic. In order to
176 further investigate this issue we considered two simulations of a state-of-the-art coupled
177 ocean/atmosphere model. The particular model we examine here is the GFDL CM2.1
178 coupled ocean/atmosphere model [GFDL CM2.1 development team, 2006]. The first
179 simulation is an 1860 pre-industrial conditions 500-year control run and the second is the
180 SRESA1B, which is a “business as usual” scenario with CO2 levels stabilizing at 720
181 ppmv at the close of the 21st century [IPCC, 2001]. From these model outputs we
182 construct the same indices and their network. Figures 3 and 4 are similar to Figure 1 but
for the second century of the control run and the 21st 183 century simulations, respectively.
We only show results of the 2nd century of the control run. The 1st 184 century is not
considered to avoid the effect of transients. In the 3rd, 4th, and 5th 185 century it appears that
9
the internal variability of the model shuts significantly down, 186 which inhibits
synchronization. In Figure 4 the dominant trend of 2 0187 C/century caused by the radiative
188 forcing is removed to better delineate the shifts in temperature regimes, which are
189 superimposed onto it. The general mechanism observed in the actual data is observed in
190 both simulations. In the control run we observe three synchronization events around years
191 120-130, years 139-148, and years 180-188. Once in place, the first two events are
192 followed by an increase in coupling strength which eventually destroys the synchronous
193 states. This marks a shift in both the global temperature trend and ENSO variability. The
194 third event is not followed by a coupling strength increase and when it is destroyed there
195 are no noticeable shifts. There is a temperature (but not an ENSO variability) shift in the
196 mid 170s which is not associated with this mechanism. In the forced simulation we
197 basically observe two events. One in years 2027-2032 and another one in years 2065-
198 2072 (with an interruption in the middle). During both events the coupling strength
199 increases until the synchronous states are destroyed. Here again these events are
200 associated with marked temperature trend and ENSO variability shifts. We thus find this
201 mechanism present in observations and in model simulations. The fact that this
202 mechanism is present in the control run will indicate that the shifts are not caused by
203 some kind of bifurcation (which will require external influences) but rather it is an
204 intrinsic property of the climate system. The proposed mechanism seems to be rather
205 robust. For example, we still identify the mechanism in a larger network that includes
206 PNA, WP, and TNA possibly because of their regional ties to the four major modes used
207 here. Thus, larger networks may not offer additional information (however, if new nodes
208 do not represent significant modes of variability their addition may mask the
10
mechanism). In addition, we identify the mechanism in networks with three 209 nodes as long
210 as they represent all three major regions (tropics, north Pacific and north Atlantic; i.e.
211 ENSO, NAO and either PDO or NPO). It appears that the key to this mechanism is not
212 the inclusion of many nodes but the interplay of the (few) most dominant modes of
213 climate variability in the northern hemisphere.
214
215 4. Conclusions
216 The above observational and modeling results suggest the following intrinsic mechanism
217 of the climate system leading to major climate shifts. First, the major climate modes tend
218 to synchronize at some coupling strength. When this synchronous state is followed by an
219 increase in the coupling strength, the network’s synchronous state is destroyed and after
220 that climate emerges in a new state. The whole event marks a significant shift in climate.
221 It is interesting to speculate on the climate shift after the 1970s event. The standard
222 explanation for the post 1970s warming is that the radiative effect of greenhouse gases
223 overcame shortwave reflection effects due to aerosols [Mann and Emanuel, 2006].
However, comparison of the 2035 event in the 21st 224 century simulation and the 1910s
225 event in the observations with this event, suggests an alternative hypothesis, namely that
226 the climate shifted after the 1970s event to a different state of a warmer climate, which
227 may be superimposed on an anthropogenic warming trend.
228
229 Acknowledgements. We thank J.B. Elsner and three reviewers for their critical
230 comments and suggestions. AAT and KLS are supported by NSF grant ATM-0438612,
11
SK is supported by DOE grant DE-FG-03-01ER63260 and by 231 NASA grant NNG-06-
232 AG66G-1.
233
234 References
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236 Mod. Phys.74, 47-101.
237 Barnston, A.G., and R.E. Livezey (1987) Classification, seasonality, and persistence of
238 low-frequency atmospheric circulation patterns. Mon. Wea. Rev. 115, 1083-1126.
239 Boccaletti, S., J. Kurths, G. Osipov, D.J. Valladares, and C.S. Zhou (2002), The
240 synchronization of chaotic systems. Phys. Reports 366, 1-101.
241 Elsner, J.B., and A.A. Tsonis (1993), Nonlinear dynamics established in the ENSO.
242 Geophys. Res. Lett. 20, 213-216.
243 GFDL CM2.1 development team (2006), GFDL’s CM2 global coupled climate models,
244 Parts 1-4. J.Clim. 19, 643-740.
245 Graham, N.E. (1994), Decadal scale variability in the tropical and North Pacific during
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247 Graham, N.E., T.P. Barnett, R. Wilde, M. Ponater, and S. Schubert (1994), On the roles
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250 Heagy, J.F., L.M. Pecora, and T.L. Carroll (1995), Short wavelength bifurcations and
251 size instabilities in coupled oscillator systems. Phys. Rev. Lett. 74, 4185-4188.
252 Hurrell, J.W. (1995), Decadal trends in the North Atlantic oscillation regional
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IPCC: Climate change 2001- The scientific basis. Contribution of working 254 group I to the
255 third assessment report of the Intergovernmental Panel on Climate Change.
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262 Maraun, D., and J. Kurths (2005), Epochs of phase coherence between El Nino/Southern
263 Oscillation and Indian monsoon. Geophys. Res. Lett. 32, L15709,
264 doi:10.1029/2005GL023225
265 Marshall J., et al. (2001), North Atlantic climate variability: Phenomena, impacts and
266 mechanisms. Int. J. Climatol. 21, 1863-1898.
267 Miller, A.J., D.R. Cayan, T.P. Barnett, N.E. Craham, and J.M. Oberhuber (1994), The
268 1976-77 climate shift of the Pacific Ocean. Oceanography 7, 21-26.
269 Onnela, J.-P., J. Saramaki, J. Kertesz, and K. Kaski (2005), Intensity and coherence of
270 motifs in weighted complex networks. Phys. Rev. E71, 065103.
271 Pecora, L.M., T.L. Carroll, G.A. Johnson, and D.J. Mar (1997), Fundamentals of
272 synchronization in chaotic systems, concepts, and applications. Chaos 7, 520-543.
273 Schneider, N., A.J. Miller, and D.W. Pierce (2002), Anatomy of North Pacific Decadal
274 Variability. J. Clim. 15, 586-605.
275 Smirnov, D.A., and Bezruchko (2003), Estimation of interaction strength and direction
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Strogatz, S.H. Exploring complex networks (2001), Nature 277 410, 268-276.
278 Suarez, M.J., and P.S. Schopf (1998), A delayed action oscillator for ENSO. J. Atmos.
279 Sci. 45, 549-566.
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281 Pacific. Climate Dyn. 9, 303-319.
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283 (coupled) harmonic oscillators. IEEE Trans. Comp. Des. Int. Circ. 22,
284 1017-1027.
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14
287 Figure captions
288 Fig. 1: (a) The distance (see definition in text) of a network consisting of four observed
289 major climate modes as a function of time. This distance is an indication of
290 synchronization between the modes with smaller distance implying larger
291 synchronization. The parallel dashed line represents the 95% significance level associated
292 with a null hypothesis of spatially correlated red noise. (b) Coupling strength between the
293 four modes as a function of time. (c) The global temperature record. (d) Global-SST
294 ENSO index. The vertical lines indicate the time when the network goes out of
295 synchronization (see text for discussion).
296 Fig. 2: The six states for the symbolic phase construction. The points in each triplet
297 correspond to three consecutive points in a time series, and their relative vertical
298 positions to each other indicate their respective values.
299 Fig. 3: Same as Figure 1 but for a control run of GFDL CM2.1 model with 1860 pre300
industrial conditions. See text for discussion.
301 Fig. 4: Same as Figure 1 but for the GFDL CM2.1 SRESA1B simulation. See text for
302 discussion.

Note- if you can understand it (and its not directed at laypersons), it mentions nothing of the current theory of AGW being falsified. Rather they present a different hypothesis for the rapid upward shift in x global temps.

I hope you don't contruse and quote mine all the way through your book like this Ian.

[robk]

Iwi

Are you a science student?

[Ian]

Iwi is in fact schizophrenic, having posted here under a number of different identities as I've just discovered...
For that, and for repeatedly leaving text format tags on, he can take a breather for a day or so.

Having said that, iwis is confused. My post does not suggest AGW theory is falsified by Swanson and Tsonis, rather that they point out we've gone through a climate shift and we are now heading for a century of mostly cooling...which will make it harder, not easier, for greenhouse gases to cause runaway warming as claimed by muppets like the team at Hot Topic.

Far from quote mining, iwis, not only do I have the paper but also the interpretation that Discover magazine, a bastion of AGW belief, put on it, as I quote in Air Con at page 205:

"They estimate that all the warming due to carbon dioxide should have driven the temperature up 0.25 degrees C since then [2002]. The fact that it hasn't leads them to propose that the oceans and atmosphere have changed the way they handle heat. The oceans may have absorbed more heat due to a change in circulation, or the atmosphere may radiate more heat away by clouds..."

Iwis, go back to your sixth form science papers and learn what they mean, not just what you'd like them to mean.

[Shane Ponting]

Ian we can add code to prevent the format spillage - I'm just so darn tired at the moment my brain is failing to co-operate but I've seen it done dozens of times thus the simplicity with which the issue is now dealt with........

[Ian]

Shane, it's a Typepad blog so the formatting is out of my control.

[Ian]

Fixed

[Ian]

PS iwis...I've never before seen a science student get an "A" by citing the entire content of a journal paper in the body of their essay.

Tell me, did that technique work OK for you and would you recommend it to others here?

Don't bother answering, you're on rations for 24 hours. It would help if you could choose between one of your original aliases and stick to it.

[peter]

Iwi'sHart

We look forward to hearing more from you in a day or so. Keep it up!

[robk]

Which name will he / she choose? :-D

[George]

Ah the personal peace that a believer in the inerrancy of biblical scripture has. He reads God's promise to set the boundaries of the seas and never to flood the earth again, believes it and goes about living life. Eventually science catches up and observes it. In the interim the unbeliever gets all upset at this uncomplicated view of life and commences fretting and flapping like a shot duck. The irresponsibility of these simpletons! Don't they know we have to control the the planet or we'll all die? Then the chorus of the intellectual elite chimes in with Mastercard Marxists as a backing group -- tax us more and the planet will heal! Lunatics unite! Death to all those who deny Gaia!

Tiresome, boring, pointless, dumb; these climate tragics are merely frightened children and are to be pitied.

I have no patience to be sparring with idiots,who professing to be wise, have become fools. There are enough worries in the day to keep me occupied already.

[ropata]

George
Personally I prefer this sort of debate, before we sign on to a pregram of crippling the NZ economy.

[George]

Robbo, I take my hat off to your preferences. If you have ever argued with these head-tilters you will notice they are not open to being persuaded by any sort of evidence. Talk may be the food of chiefs but if you want to have an effect get a counter offensive signing program going. Otherwise the lemming effect is in play and we end up joining the luvvies at the bottom of the bluff.

[Sam Vilain]

Oh, come on Truffle, is this the best you can do?

Ian, you have to earn the right to have your words respected and fully rebutted. There have been enough faults already discovered in Air Con to place the whole work into question by default. That's what happens with literature, you make enough mistakes and the work loses all credibility. So it does not matter that Gareth did not read the entire thing. I mean, were you honestly thinking people would take seriously a work that accuses pro-AGW people of eating babies?

This comes back to that investigation thing that we've talked about before. First you investigate, then figure out what your point of view is. Not the other way around just to sell copy. Remember?

[Ian]

Utterly hopeless Sam, and an illustration of why the Left is ultimately doomed because followers rely too much on what the High Priests tell them to believe, instead of actually reading things themselves.

Errors in Air Con? Gareth hasn't landed a single significant blow against the book. The post above is further evidence that he continues to cite stuff out of context.

Eating babies? If you'd actually read Air Con instead of relying on Truffle's review, you'd have seen it was a sarcastic reference to calls and suggestions from a couple of prominent environmental/global warming believers that cannibalism might be a legitimate form of population control.

Don't whinge at me, take it up with the Greenies who said it, cited and referenced in Air Con.

Likewise, the Green who suggested cutting down trees was far more of a crime than selling a six year old child to a pedophile in an Asian brothel.

Face up to the loons you guys inadvertently support as fellow travellers on global warming. It ain't my problem.

Context is a wonderful thing, but unfortunately Truffle was going for cheap shots, twisted beyond all recognition.

He has skittered around all of the main points listed above...having being caught out in his alarmism.

The thing I'm loving about this debate is that every pro AGW critic like yourself has failed to actually read the book, yet turn up on blogsites spouting off about things that either aren't in the book or which they've read second hand from Hot Topic who got it wrong.

Meanwhile, more than 10,000 New Zealanders have now got copies of Air Con...and can see for themselves when critics have got it wrong...(such as the out of context quotemining about cannibalism which has become ubiquitous on lefty blogs)

[Sam Vilain]

Ian, so many words but so little content worth replying to.

[Sam Vilain]

Anyway, back to the main post.

You say that the graph you post "clearly shows" a slowdown in mass change. I see a small dip over a very short timescale near the end. Well, even rolling averages show dips like that, you have failed however to describe a trend. Hint: what is the correlation coefficient of your proposed trend line, and is it a significantly better fit than the overall trend line?

I see this a lot from deniers like yourself - looking at very small recent blips in figures and blithely suggesting that this negates an overall trend. It will never work.

btw, all that silly stuff about "truffles". Peer-reviewed science is the forest, and you are the pig snuffling around underneath for a truffle and keep thinking that maybe a big enough truffle will bring the tree down. Your insult is more accurate about yourself than about your adversaries.

[robk]

Sam

You said:
"I mean, were you honestly thinking people would take seriously a work that accuses pro-AGW people of eating babies?"

I thought Ian's reply was quite restrained.

What you said was pretty stupid when the actual context of the real statement is known. You get this context by reading the book...

So when you now say: "Ian, so many words but so little content worth replying to."

...it looks like you can't answer Ian's reply, so you are making smoke and running for it - hoping no-one will notice.

[AcidComments]

"To counter this, he quotes from an article in Science which discussed a paper at last year’s Fall Meeting of the American Geophysical Union, describing how glaciers in SE Greenland had slowed down after a period of “galloping” towards the sea. This, Wishart implies, means that the whole of Greenland has stopped melting."

Of interest.

This was from a few years ago.

The recent hype in Nature notwithstanding, Greenland has been cooling for the better part of two generations.

Greenland clearly hasn’t read its press. How many times have we heard that warming in Greenland is causing ice to melt, sea level to rise, ocean circulations to changes, and general climate calamity to proliferate? The Chylek et al. team reveals that from 1940 to 2000, annual temperatures in Godthab have cooled by 1.8°C, Angmagssalik has cooled by 1.6°C, and Egedesminde has cooled by 1.2°C from 1950–2000.

http://www.worldclimatereport.com/index.php/2004/03/15/greenlands-secret/

[Ian]

Sam, you wrote:

You say that the graph you post "clearly shows" a slowdown in mass change. I see a small dip over a very short timescale near the end. Well, even rolling averages show dips like that, you have failed however to describe a trend.

Probably because the graph has nothing to do with mass loss, and everything to do with sea level increase. Like I said, read things before opining on them.

If you can't read a 300 word blog post properly, what hope is there for you with a 100,000 word book? Which is probably why you wait to be spoon-fed by Hot Topic et al.

[Sam Vilain]

Ian, what a stupid little point to fix on.