New energy-budget-derived estimates of climate sensitivity and transient response in Nature Geoscience
Guest post by Nic Lewis
Readers may recall that last December I published an informal climate sensitivity study at WUWT, here. The study adopted a heat-balance (energy budget) approach and used recent data, including satellite-observation-derived aerosol forcing estimates. I would like now to draw attention to a new peer-reviewed climate sensitivity study published as a Letter in Nature Geoscience, “Energy budget constraints on climate response”, here. This study uses the same approach as mine, based on changes in global mean temperature, forcing and heat uptake over 100+ year periods, with aerosol forcing adjusted to reflect satellite observations. Headline best estimates of 2.0°C for equilibrium climate sensitivity (ECS) and 1.3°C for the – arguably more policy-relevant – transient climate response (TCR) are obtained, based on changes to the decade 2000–09, which provide the best constrained, and probably most reliable, estimates.
The 5–95% uncertainty ranges are 1.2–3.9°C for ECS and 0.9–2.0°C for TCR. I should declare an interest in this study: you will find my name included in the extensive list of authors: Alexander Otto, Friederike E. L. Otto, Olivier Boucher, John Church, Gabi Hegerl, Piers M. Forster, Nathan P. Gillett, Jonathan Gregory, Gregory C. Johnson, Reto Knutti, Nicholas Lewis, Ulrike Lohmann, Jochem Marotzke, Gunnar Myhre, Drew Shindell, Bjorn Stevens, and Myles R. Allen. I am writing this article in my personal capacity, not as a representative of the author team.
The Nature Geoscience paper, although short, is in my view significant for two particular reasons.
First, using what is probably the most robust method available, it establishes a well-constrained best estimate for TCR that is nearly 30% below the CMIP5 multimodel mean TCR of 1.8°C (per Forster et al. (2013), here). The 95% confidence bound for the Nature Geoscience paper’s 1.3°C TCR best estimate indicates some of the highest-response general circulation models (GCMs) have TCRs that are inconsistent with recent observed changes. Some two-thirds of the CMIP5 models analysed in Forster et. al (2013) have TCRs that lie above the top of the ‘likely’ range for that best estimate, and all the CMIP5 models analysed have an ECS that exceeds the Nature Geoscience paper’s 2.0°C best estimate of ECS. The CMIP5 GCM with the highest TCR, per the Forster et. al (2013) analysis, is the UK Met. Office’s flagship HadGEM2-ES model. It has a TCR of 2.5°C, nearly double the Nature Geoscience paper’s best estimate of 1.3°C and 0.5°C beyond the top of the 5–95% uncertainty range. The paper obtains similar, albeit less well constrained, best estimates using data for earlier periods than 2000–09.
Secondly, the authors include fourteen climate scientists, well known in their fields, who are lead or coordinating lead authors of IPCC AR5 WG1 chapters that are relevant to estimating climate sensitivity. Two of them, professors Myles Allen and Gabi Hegerl, are lead authors for Chapter 10, which deals with estimates of ECS and TCR constrained by observational evidence. The study was principally carried out by a researcher, Alex Otto, who works in Myles Allen’s group.
Very helpfully, Nature’s editors have agreed to make the paper’s main text freely available for a limited period. I would encourage people to read the paper, which is quite short. The details given in the supplementary information (SI) enable the study to be fully understood, and its results replicated. The method used is essentially the same as that employed in my December study, being a more sophisticated version of that used in the Gregory et al. (2002) heat-balance-based climate sensitivity study, here. The approach is to draw sets of samples from the estimated probability distributions applicable to the radiative forcing produced by a doubling of CO2-equivalent greenhouse gas atmospheric concentrations (F2×) and those applicable to the changes in mean global temperature, radiative forcing and Earth system heat uptake (ΔT, ΔF and ΔQ), taking into account that ΔF is closely correlated with F2×. Gaussian (normal) error and internal climate variability distributions are assumed. ECS and TCR values are computed from each set of samples using the equations:
(1) ECS = F2× ΔT / (ΔF − ΔQ) and (2) TCR = F2× ΔT / ΔF .
With sufficient sets of samples, probability density functions (PDFs) for ECS and TCR can then be obtained from narrow-bin histograms, by counting the number of times the computed ECS and TCR values fall in each bin. Care is needed in dealing with samples where any of the factors in the equations are negative, to ensure that each is correctly included at the low or high end when calculating confidence intervals (CIs). Negative factors occur in a modest, but significant, proportion of samples when estimating ECS using data from the 1970s or the 1980s.
Estimates are made for ECS and TCR using ΔT, ΔF and ΔQ derived from data for the 1970s, 1980s, 1990s, 2000s and 1970–2009, relative to that for 1860–79. The estimates from the 2000s data are probably the most reliable, since that decade had the strongest forcing and, unlike the 1990s, was not affected by any major volcanic eruptions. However, although the method used makes allowance for internal climate system variability, the extent to which confidence should be placed in the results from a single decade depends on how well they are corroborated by results from a longer period. It is therefore reassuring that, although somewhat less well constrained, the best estimates of ECS and TCR using data for 1970–2009 are closely in line with those using data for the 2000s. Note that the validity of the TCR estimate depends on the historical evolution of forcing approximating the 70-year linear ramp that the TCR definition involves. Since from the mid-twentieth century onwards greenhouse gas levels rose much faster than previously, that appears to be a reasonable approximation, particularly for changes to the 2000s.
I have modified the R-code I used for my December study so that it computes and plots PDFs for each of the five periods used in the Nature Geoscience study for estimating ECS and TCR. The resulting ECS and TCR graphs, below, are not as elegant as the confidence region graphs in the Nature Geoscience paper, but are in a more familiar form. For presentation purposes, the PDFs (but not the accompanying box-and-whisker plots) have been truncated at zero and the upper limit of the graph and then normalised to unit total probability. Obviously, these charts do not come from the Nature Geoscience paper and are not to be regarded as associated with it. Any errors in them are entirely my own.
The box-and-whisker plots near the bottom of the charts are perhaps more important than the PDF curves. The vertical whisker-end bars and box-ends show (providing they are within the plot boundaries) respectively 5–95% and 17–83% CIs – ‘very likely’ and ‘likely’ uncertainty ranges in IPCC terminology – whilst the vertical bars inside the boxes show the median (50% probability point). For ECS and TCR, whose PDFs are skewed, the median is arguably in general a better central estimate than the mode of the PDF (the location of its peak), which varies according to how skewed and badly-constrained the PDF is. The TCR PDFs (note the halved x-axis scaling), which are unaffected by ΔQ and uncertainty therein, are all better constrained than the ECS PDFs.
The Nature Geoscience ECS estimate based on the most recent data (best estimate 2.0°C, with a 5–95% CI of 1.2–3.9°C) is a little different from that per my very similar December study (best estimate 1.6°C, with a 5–95% CI of 1.0–2.9°C, rounding outwards). The (unstated) TCR estimate implicit in my study, using Equation (2), was 1.3°C, with a 5–95% range of 0.9–2.0°C, precisely in line with the Nature Geoscience paper. In the light of these comparisons, I should perhaps explain the main differences in the data and methodology used in the two studies:
1) The main difference of principle is that the Nature Geoscience study uses GCM-derived estimates of ΔF and F2×. Multimodel means from CMIP5 runs per Forster et al. (2013) can thus be used as a peer-reviewed source of forcings data. ΔF is accordingly based on simulations reflecting the modelled effects of RCP 4.5 scenario greenhouse gas concentrations, aerosol abundances, etc. My study instead used the RCP 4.5 forcings dataset and the F2× figure of 3.71°C reflected in that dataset; I adjusted the projected post-2006 solar and volcanic forcings to conform them with estimated actuals. Use of CMIP5-based forcing data results in modestly lower estimates for both ΔF and F2× (3.44°C for F2×). Since CO2 is the dominant forcing agent, and its concentration is accurately known, the value of ΔF is closely related to the value of F2×. The overall effect of the difference in F2× on the estimates of ECS and TCR is therefore small. As set out in the SI, an adjustment of +0.3 Wm−2 to 2010 forcing was made in the Nature Geoscience study in the light of recent satellite-observation constrained estimates of aerosol forcing. On the face of it, the resulting aerosol forcing is slightly more negative than that used in my December study.
2) The Nature Geoscience study derives ΔQ using the change in estimated 0–2000 m ocean heat content (OHC) – which accounts for most of the Earth system heat uptake – from the start to the end of the relevant decade (or 1970–2009), whereas I computed a linear regression slope estimate using data for all years in the period I took (2002–11). Whilst I used the NODC/NOAA OHC data, which corresponds to Levitus et al. (2012), here, for the entire 0–2000 m ocean layer, the Nature Geoscience study splits that layer between 0–700 m and 700–2000 m. It retains the NODC/NOAA Levitus OHC data for the 700–2000 m layer but uses a different dataset for 0–700 m OHC – an update from Domingues et al. (2008), here.
3) The periods used for the headline results differ slightly. I used changes from 1871–80 to 2002–11, whilst the Nature Geoscience study uses changes from 1860–79 to 2000–09. The effects are very small if the CMIP5 GCM-derived forcing estimates are used, but when employing the RCP 4.5 forcings, switching to using changes from 1860–79 to 2000–09 increases the ECS and TCR estimates by around 0.05°C.
Since the Nature Geoscience study and my December study give identical estimates of TCR, which are unaffected by ΔQ, the difference in their estimates of ECS must come primarily from use of different ΔQ figures. The difference between the ECS uncertainty ranges of the two studies likewise almost entirely reflects the different central estimates for ΔQ they use. The ECS central estimate and 5–95% uncertainty range per my December heat-balance/energy budget study were closely in line with the preferred main results estimate for ECS, allowing for additional forcing etc. uncertainties, per my recent Journal of Climate paper, of 1.6°C with a 5–95% uncertainty range of 1.0–3.0°C. That paper used a more complex method which, although less robust, avoided reliance on external estimates of aerosol forcing.
The take-home message from this study, like several other recent ones, is that the ‘very likely’ 5–95% ranges for ECS and TCR in Chapter 12 of the leaked IPCC AR5 second draft scientific report, of 1.5–6/7°C for ECS and 1–3°C for TCR, and the most likely values of near 3°C for ECS and near 1.8°C for TCR, are out of line with instrumental-period observational evidence.
===============================================================
Here’s a figure of interest from from the SI file – Anthony
Fig. S3| Sensitivity of 95th percentile of TCR to the best estimate and standard error of the change in forcing from the 2000s to the 1860-1879 reference period. The shaded contours show the 95th percentile boundary of the TCR confidence interval, the triangles show cases (black and blue) from the sensitivity Table S2, and a smaller adjustment to aerosol forcing for comparison (red).
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Mosher
Svalgaard
Matthew R Marler
Joseph Murphy
……..
I am encouraged by your affirmation of the ocean’s role in this climate change thing.
Pictorial preview of “Sinking in the North Atlantic” not to be confused with “Sinking of the Titanic” is available here:
http://www.vukcevic.talktalk.net/NaturalVariability.htm
lgl says, May 20, 2013 at 12:34 pm:
“Kristian
“This is ENSO (bottom graphs)”
No it isn’t.”
I’m afraid it is.
Here is HadCRUt4gl (global land+sea surface) and HadSST3gl (global sea surface) vs. Tropical Pacific/East Indian (24N-24S, 80E-80W) SSTa area weighted against and summed with North Atlantic (70N-0, 80W-0) SSTa, BTW:
http://i1172.photobucket.com/albums/r565/Keyell/ENSOAMOvsHadCRUT4ampHadSST3gl_zps866a1ff3.png
Not much of a mystery what drives global temperatures …
Vuk
Elsewhere the subject of co2 and it causing ocean warming came up.
I was at the Met office today looking for more data with which to extend CET and came across this book, with contributions from all the scientific great and the good of the era;
“Co2 warming in the ocean is confined mostly to the upper portion especially in the surface layer near 60N and 50S. Through increases in precipitation, weakened westerly wind stress and reduced overturning salinity, amounts decrease at high latitudes of each hemisphere. Salinity also increases in the subtropics. The resultant warming and refreshing of the high latitude ocean surface layer stabilizes the ocean and cause a weaker thermohaline circulation”
From ; Developments in atmospheric Science 19 “Greenhouse gas induced climate change 1991. This was as a result of a 1989 workshop in the US.
It suggests to me that at one time many of the scientific elite supported the idea that co2 caused ocean warming which, judging from the other conversation is now considered wrong. I wonder if their previous stance is reflected in AR1 or AR2? If so it demonstrates that -quite rightly- scientists can not only change their opinion but that they can be wrong.
tonyb
Bottom line:
This result is about in the middle between previous IPCC and leading sceptics’ estimates (good work 3% 😉 ).
There is further downward potential IMHO,
due to the implausible massive ocean heat content step function, while switching to ARGO,
no attribution to solar effects beyond TSI,
lower results in this study during negative PDO period, while the study covers mainly a positive PDO period,
slightly lower results of other recent observational data based studies.
jeremyshiers says:
May 20, 2013 at 8:29 am
Just because you define something like climate sensitivity does not mean it really exists.
The implication of climate sensitivity is rising CO2 levels cause rising global temperatures.
But for the last 15 years at least CO2 levels have been rising and temperature not.
This is an existential problem for climate sensitivity. In other words trying to measure it is just a waste of time.
http://www.woodfortrees.org/plot/esrl-co2/isolate:60/mean:12/scale:0.25/plot/hadcrut3vgl/isolate:60/mean:12/from:1958
is my current favorite graph
it clearly shows temperature changes lead co2 changes hence co2 can not be causing temperatures to rise.
Thanks Jeremy, you put it out clearly and the graph is really an eye opener!
climatereason says: May 20, 2013 at 1:15 pm
…………..
Hi Tony
It is a pleasure to hear from you again, and even greater to read some of your excellent narrative, all backed-up by historic ‘no nonsense’ records.
Ocean currents are the great distributor of the energy, with ability to change the climate to extent shown by the MWP, LIA and the modern warming.
TSI may change, but is it enough, cosmic rays may be variable but can they move clouds, planets revolve, but is their gravity pull up to it?
Dr.Svalgaard will say ‘NO’.
Ocean currents in the far North Atlantic are in the class of their own, here is a preview:
http://www.vukcevic.talktalk.net/NaturalVariability.htm
Matt Ridley,
Your link http://www.thetimes.co.uk/tto/opinion/columnists/article3769210.ece
Yields this, no matter what I try:
Oh Dear Lord- It looks like a nuclear explosion right now in southern Oklahoma City, in the path of yet another giant monster tornado which just now ripped through the suburb of Moore and south Oklahoma City.
News helicopters now flying around the destroyed areas- oh Lord, they’ve just shown two schools severely damaged and one of them is just so totally destroyed- people just now reaching the scene for search and rescue…
The tornado was on the ground for an hour and they are comparing the size to the May 3, 1999 tornado, when the world’s highest wind speeds were recorded.
I don’t know how the weather man can stand to report what we are seeing- total destruction path maybe a mile wide… emergency vehicles can not enter the areas due to massive destruction- tears are streaming down my face, I’m sorry…
In reply again to:
lsvalgaard says:
May 20, 2013 at 11:15 am
William Astley says:
May 20, 2013 at 10:44 am
1) Why did the ‘Dansgaard-Oeschger’ cyclic warming and cooling occur in the past? Michael Mann is focusing on removing the cyclic warming to help with the message.
There is no such precise ‘cycle’. http://www.leif.org/EOS/Obrochta2012.pdf by very respected authors.
William: Please, what is your point? A Dansgaard-Oeschger cycle is cyclic warming and cooling in the same regions that warmed in the 20th century. The past D-O cycles correlate with solar magnetic cycle changes. The joke paper you quote states the D-O cycle periodicity is variable.
The D-O cycle’s periodicity is variable as the solar magnetic cycle’s periodicity which is the cause of the D-O cycle is variable. No surprise there. It does not following however from the fact that solar magnetic cycles are variable that the solar magnetic variability is not the cause of the D-O cycles. The question is not if so magnetic cycle changes cause planetary temperature changes, but rather how and how much. The past D-O cycles were certainly not caused by changes to atmospheric CO2 levels. In fact atmospheric CO2 gradually increased as the planet cold. There is a lack of correlation.
2) Is the 20th century warming the warming phase of a Dansgaard-Oeschger cycle?
lsvalgaard says:
Therefore 2) is moot.
William:
You appear to have forgotten to include a logic statement, observational data, or analysis to support your assertion ‘therefore 2) is moot’. I accept the assertion the D-O cycle is variable.
The logical assertion that the D-O cycle is variable with a pseudo periodicity of 950, 1450, and 1950 years (that also matches known solar magnetic cycle periodicities which you have neglected to mention) however does not support the assertion that the D-O cycle did not happen or that the 20th century warming has not a D-O cycle.
You and the authors of the joke paper appear to have not looked at the Greenland Ice sheet temperature vs time, last 11,000 years determined from ice core analysis, Richard Alley’s paper.
I ask again.
Is the joke paper trying to convince us that the nine (9) D-O cycles did not occur? The joke paper specifically notes that there are cosmogenic isotope changes – Be10 and C14 – that correlate with each and every D-O cycle. The cosmogenic isotopes changes are caused by solar magnetic cycle changes.
http://www.climate4you.com/images/GISP2%20TemperatureSince10700%20BP%20with%20CO2%20from%20EPICA%20DomeC.gif
http://www.essc.psu.edu/essc_web/seminars/spring2006/Mar1/Bond%20et%20al%202001.pdf
Persistent Solar Influence on North Atlantic Climate During the Holocene (William: Holocene is the name for this interglacial period)
William: It is a fact that the 20th century warming occurred during a period of high solar magnetic cycle activity (the period of high solar magnetic cycle activity does not have to be the highest solar magnetic cycle activity to cause warming it only needs to be sufficient high to cause warming for the duration of the warming period).
It is also a fact that the regions of the planet that warmed in the 20th century, high latitude northern hemisphere are the same regions that warmed during the nine (9) past D-O cycles.
1. It is also a fact that the IPCC general circulation models predicted that the majority of the greenhouse gas warming would be in the tropics where there is the most amount of long wave radiation emitted off into space and where there is ample water to amplify the greenhouse gas warming. (Tropics did not significantly warm as predicted.)
2. There is almost no tropics warming observed and there is no tropical tropospheric warming at roughly 8 km above the surface of the planet observed. The tropical tropospheric warming is predicted to occur due to increased water vapor in the atmosphere which will amplify the greenhouse gas warming. That is not observed. (Tropical tropospheric warming did not occur.)
3. Lindzen and Choi’s analysis (2009 and 2011) showed that tropical region cloud cover increases or decrease to resists forcing changes (negative feedback) as opposed to the IPCC general circulation model positive feedback. Analysis finding 3 explains observation 2. (There is negative feedback in the tropics, rather than the IPCC general circulation model’s assumed positive feedback).
If there was not a ‘climate war’ going the above fundamental observations would have been acknowledgement and the science would be settled that the 20th century warming has a D-O cycle.
3) As the solar magnetic cycle has abruptly and anomalously changed will this change result in planetary cooling?
lsvalgaard says:
Actually, it is very likely that it will have the opposite effect: without dark spots to lower TSI, we may get even more irradiance during a Maunder-like minimum.
William:
Are you daft or trying to be humorous? TSI does not increase during a Maunder minimum. Are you asserting the planet did not cool during the Maunder minimum? Could you please provide a paper reference that TSI is reduce during a Maunder minimum? The following is a paper reference that notes TSI is reduced during a Maunder minimum.
Are you asserting cycle 25 will not be a Maunder like minimum?
UV and TSI increases when the solar magnetic cycle is more active and decrease when it less active. Changes to TSI and UV are one of the mechanisms by which the solar magnetic cycle changes causes changes in climate.
The following is a list of the current known mechanisms by which solar magnetic cycle changes module planetary climate:
1) Changes to the extent, composition, and orientation of the solar heliosphere
2) Changes to the cycle timing, magnitude, frequency, density, and composition of solar wind bursts and to the solar wind
3) Changes to the total solar irradiation (TSI)
4) Changes to the amount of UV in the solar radiation
Why did the planet cool during the Maunder minimum? Why did it warm and then cool during nine (9) past D-O cycles.
I am making a testable prediction. The high northern regions of the planet will cool due to the sudden change to the solar magnetic cycle.
This is not a prediction, but just an assertion.
William: You must have missed the paper I linked to above and provide an excerpt from that stated the high regions of the Northern hemisphere will now cool due to the solar cycle 24 change.
http://onlinelibrary.wiley.com/doi/10.1029/2011GL048529/abstract
Are the most recent estimates for Maunder Minimum solar irradiance in agreement with temperature reconstructions?
1] Estimates for the total solar irradiance (TSI) during the 17th-century Maunder Minimum published in the last few years have pointed towards a TSI difference of 0.2–0.7 W m−2 as compared to the 2008/2009 solar minimum. Two recent studies, however, give anomalies which differ from this emerging consensus. The first study indicates an even smaller TSI difference, placing the Maunder Minimum TSI on the same level as the 2008/2009 minimum. The second study on the other hand suggests a very large TSI difference of 5.8 W m−2. Here I use coupled climate simulations to assess the implications of these two estimates on Northern-hemisphere surface air temperatures over the past millennium. Using a solar forcing corresponding to the estimate of the first study, simulated Northern-hemisphere temperatures over the past millennium are consistent with reconstructed surface air temperatures. The large TSI differences between times of high and low solar activity as suggested by the second study, however, yield temperatures during all past grand solar minima that are too low, an excessive variance in Northern-hemisphere temperature on timescales of 50–100 years as compared to reconstructions, and temperatures during the first half of the 20th century which are too low and inconsistent with the instrumental temperature record. In summary this suggests a more moderate TSI difference of less than 1 W m−2 and possibly as low as 0–0.3 W m−2.
http://arxiv.org/abs/1112.3256
Solar activity and Svalbard temperatures
The long temperature series at Svalbard (Longyearbyen) show large variations, and a positive trend since its start in 1912. During this period solar activity has increased, as indicated by shorter solar cycles.
The temperature at Svalbard is negatively correlated with the length of the solar cycle. The strongest negative correlation is found with lags 10 to 12 years. These models show that 60 per cent of the annual and winter temperature variations are explained by solar activity. For the spring, summer and fall temperatures autocorrelations in the residuals exists, and additional variables may contribute to the variations. These models can be applied as forecasting models.
We predict an annual mean temperature decrease for Svalbard of 3.5 ±2C from solar cycle 23 to solar cycle 24 (2009 to 2020) and a decrease in the winter temperature of ≈6 C. … ….A systematic study by Solheim, Stordahl and Humlum [15] (called SSH11 in the following) of the correlation between SCL and temperature lags in 11 years intervals, for 16 data sets (William: solar cycles), revealed that the strongest correlation took place 10 to 12 years after the mid-time of a solar cycle, for most of the locations included. In this study the temperature series from Svalbard (Longyearbyen) was included, and a relation between the previous sunspot cycle length (PSCL) and the temperature in the following cycle was determined. This relation was used to predict that the yearly average temperature, which was -4.2 C in sunspot cycle (SC) 23, was estimated to decrease to -7.8 C in SC24, with a 95% confidence interval of -6.0 to -9.6C [15]. SSH11[15] found that stations in the North Atlantic (Torshavn, Akureyri and Svalbard), had the highest correlations.
William: Latitude and longitude of Svalbard (Longyearbyen)
78.2167° N, 15.6333° E Svalbard Longyearbyen, Coordinates
http://www.pnas.org/content/early/2010/11/08/1000113107.abstract
Synchronized Northern Hemisphere climate change and solar magnetic cycles during the Maunder Minimum
The Maunder Minimum (A.D. 1645–1715) is a useful period to investigate possible sun–climate linkages as sunspots became exceedingly rare and the characteristics of solar cycles were different from those of today. Here, we report annual variations in the oxygen isotopic composition (δ18O) of tree-ring cellulose in central Japan during the Maunder Minimum. We were able to explore possible sun–climate connections through high-temporal resolution solar activity (radiocarbon contents; Δ14C) and climate (δ18O) isotope records derived from annual tree rings. The tree-ring δ18O record in Japan shows distinct negative δ18O spikes (wetter rainy seasons) coinciding with rapid cooling in Greenland and with decreases in Northern Hemisphere mean temperature at around minima of decadal solar cycles. We have determined that the climate signals in all three records strongly correlate with changes in the polarity of solar dipole magnetic field, suggesting a causal link to galactic cosmic rays (GCRs). These findings are further supported by a comparison between the interannual patterns of tree-ring δ18O record and the GCR flux reconstructed by an ice-core 10Be record. Therefore, the variation of GCR flux associated with the multidecadal cycles of solar magnetic field seem to be causally related to the significant and widespread climate changes at least during the Maunder Minimum.
Kristian
Those are all temperatures, results, not drivers. You have no basis for claiming ENSO increased during last century.
There is much more damage from this storm than the may 3rd tornado which destroyed 8400+ homes and 1000+ apartments, but they are reporting much more massive damage path and now- three tracks they are following for other tornadoes around town… total chaos… we had trwo R4/F5 tornadoes skirt through/around the metropolitan area yesterday, but this monster made a direct hit- very close to the track of the May 3rd storm, but worse- more in town- at least three schools destroyed.
There will be many deaths from this storm, even with advanced warnings- anyone in the storm track who tryed to shelter above ground, has very slim chance to have survived this monster.
“For ECS and TCR, whose PDFs are skewed, the median is arguably in general a better central estimate than the mode of the PDF”
OK, but if one were to place bets based on the PDF- isnt the best place the bets; the mode?
i.e isnt this the most likley estimate?
William Astley says:
May 20, 2013 at 2:02 pm
William: Please, what is your point? A Dansgaard-Oeschger cycle is cyclic warming and cooling in the same regions that warmed in the 20th century. The past D-O cycles correlate with solar magnetic cycle changes. The joke paper you quote states the D-O cycle periodicity is variable.
Point is that it is not a ‘cycle’. In one of your earlier comments you quoted Rahmdorff using the precise period as an argument for its reality. Good that you now see that that is not the case.
The D-O cycle’s periodicity is variable as the solar magnetic cycle’s periodicity which is the cause of the D-O cycle is variable.
They both have longer-term millennial variations, the point is that they don’t match up. sometimes they do, sometimes they don’t. So no causality there.
You appear to have forgotten to include a logic statement, observational data, or analysis to support your assertion
I have included several in past comments, but they just sail past you, so you have had ample opportunity to read them.
The cosmogenic isotopes changes are caused by solar magnetic cycle changes.
First, the solar and climate cycles don’t match up. Second, more than half of the cosmic proxy variations are caused by variation in climate.
It is a fact that the 20th century warming occurred during a period of high solar magnetic cycle activity (the period of high solar magnetic cycle activity does not have to be the highest solar magnetic cycle activity to cause warming it only needs to be sufficient high to cause warming for the duration of the warming period).
Good to see that you have given up on the ‘highest ever’ idea. So we are making some progress. Now activity in the last half of the 18th century was higher than in the 20th, where was the warming?
“Actually, it is very likely that it will have the opposite effect: without dark spots to lower TSI, we may get even more irradiance during a Maunder-like minimum.”
Are you daft or trying to be humorous?
Not at all. Ponder this: TSI has two parts: one that increases it because of magnetic fields and one that decreases it because of the dark sunspots. Without the second part [during a Maunder Minimum] TSI will therefore increase. Now, perhaps there were no magnetic field to cause the first part to increase. But, we know that the cosmic rays were modulated during Maunder and Spoerer Minima, even more than today, so the magnetic field and changes to the heliosphere were certainly there.
Are you asserting cycle 25 will not be a Maunder like minimum?
The paper [by Livingston, Penn, & Svalgaard] I referred you to suggests that a Maunder Minimum is consistent with the data. We are halfway through a very weak cycle 24, yet TSI [measured by SORCE/TIM since 2003] is the highest ever, the CME rate is as high as at the maximum of cycle 23. So, even though the number of visible spots is decreasing it seems that some of the other solar indices are not following the sunspot number down.
The following is a list of the current known mechanisms
These are not known to be effective, merely asserted by some people to be so.
high regions of the Northern hemisphere will now cool due to the solar cycle 24 change.
I predict the NH will cool too, but you are not just predicting cooling, but also making the assumption that it is due to solar cycle 24 change; that last bit is not justified.
lgl says, May 20, 2013 at 2:03 pm:
“Those are all temperatures, results, not drivers. You have no basis for claiming ENSO increased during last century.”
That’s how it works, lgl. What comes first? Global SST drives global land temperatures (looking past the high level of noise), just like global surface temperatures drive global tropospheric temperatures, which finally drive OLR at ToA. That’s how the solar heat travels through the Earth system.
So then all we need to find is what part of the global ocean drives global SSTs. Clearly it’s the ENSO region (tropical-subtropical Pacific), sectors of which are all directly oceanically linked. SSTs here swing several months before the rest of the world. That’s no mystery, lgl. It’s pretty well understood. A few months later they tug the Indian and Atlantic oceans along through atmospheric teleconnections. There are great ENSO signals in the tropical/subtropical Indian Ocean, especially the eastern part, and in the North Atlantic (–> AMO), being additionally fed with warm water across the equator from the South Atlantic.
Now you document how the atmospheric content of CO2 affects the ENSO phenomenon. And how the Sun doesn’t.
William Astley says:
May 20, 2013 at 2:02 pm
http://www.pnas.org/content/early/2010/11/08/1000113107.abstract
Synchronized Northern Hemisphere climate change and solar magnetic cycles during the Maunder Minimum
It seems that when it suits your agenda a paper can be supporting evidence, and if not it is a ‘joke’. You may note that some of the authors of the above paper are also authors of the http://www.leif.org/EOS/Obrochta2012.pdf paper that you called a joke….
@ur momisugly William Astley
you quoted “abrupt climate events appear to be paced by a 1,470-year cycle with a period that is probably stable to within a few percent; with 95% confidence the period is maintained to better than 12% over at least 23 cycles
I clicked on the link but didn’t manage to find out when the next beginning or end of the quoted 1,470 year cycle was, with it’s 12% or 176 year margin. Thought it would be interesting to know.
All I can say is that my prayers are with you. Stay safe Luther.
Tornadoes will pick up as we move into cooling phase , keep you head down fella. Good luck.
Many families in Moore, OK will be dealing with broken hearts. Many children have been killed as elementary schools were in direct path of the tornado.
[off-topic -not interested – mod]
…send me an e-mail then.
If being a stupid piece of %&*# was a crime, Sen. Sheldon Whitehouse (D.-Rhode Island) would never get outta jail.
http://dailycaller.com/2013/05/20/democratic-senator-goes-on-anti-gop-rant-over-climate-change-as-tornadoes-hit-oklahoma/?utm_source=twitterfeed&utm_medium=twitter
Luther Wu says:
May 20, 2013 at 6:25 pm
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Hang in there Luther. I was relatively unscathed by the 1989 earthquake here, but severely scathed by the 1991 firestorm, so know what it’s like.
Re. the fake, lying diatribe from the regressive, I’ll leave you with two quotes, attributed to Edmund Burke, ca. 1770:
“It is a general popular error to suppose the loudest complainers for the publick to be the most anxious for its welfare.”
(The commenters there do not seem to be in error)
and:
All that is necessary for the triumph of evil is that good men do nothing.
(Continue, like many here, to be a good man)
Very saddened to hear about the tornado. My heartfelt wishes go out to all those affected by it.
Just to state the obvious, the longer the present temperature stasis continues, the lower the figure for climate sensitivity will become (assuming that manmade CO2 emissions remain unabatted).
it will be interesting to revisit this topic say in 5 years time if temperature anomalies have not begin to rise. Even more interesting, should temperature anomalies begin to show a decline. Expect to see re-assessments with climate sensitivity at 1.5C and then even less.