by Greg Goodman
Pondering the recent downturn in Atlantic hurricane activity.
Introduction
Surface ocean temperature has been shown to be a key condition for development of tropical and cyclonic storms, though there are strongly conflicting opinions on its impact on long term trends. The present study looks at correlation of accumulated cyclone energy and surface sea temperature in the N. Atlantic basin and finds common periodicities linking the two. The similarity between the post-2005 drop in cyclone energy and a similar drop in the record from the 1930-1950 period is discussed.
https://climategrog.files.wordpress.com/2016/01/ace_amo_2015.png
Figure 1. Comparing North Altantic SST to Accumulated Cyclone Energy
A definition of accumulated cyclone energy is provided [here]:
“ACE” = Accumulated Cyclone Energy – An index that combines the numbers of systems, how long they existed and how intense they became. It is calculated by squaring the maximum sustained surface wind in the system every six hours that the cyclone is a Named Storm and summing it up for the season. It is expressed in 104 kt2.
The ACE metric is intended to provide better insight that simply counting the number of storms, since this has been strongly affected by improvements in detection and reporting and possible statistical variation in the proportions of storm intensity. Since storm energy originates in ocean heat energy (Gray 1968) [3] , total cyclone energy is a more appropriate metric than quantities such as storm count, when searching for possible a causal link between tropical cyclone activity and climate variability.
Data Sources:
Documentation of Atlantic Hurricane Database Re-analysis Project is provided [here]. The Atlantic hurricane database (or HURDAT) extends back to 1851. However, because tropical storms and hurricanes spend much of their lifetime over the open ocean – some never hitting land – many systems were “missed” during the late 19th and early 20th Centuries (Vecchi and Knutson 2008). Starting in 1944, systematic aircraft reconnaissance was commenced for monitoring both tropical cyclones and disturbances that had the potential to develop into tropical storms and hurricanes. This did provide much improved monitoring, but still about half of the Atlantic basin was not covered (Sheets 1990). Beginning in 1966, daily satellite imagery became available at the National Hurricane Center, and thus statistics from this time forward are most complete (McAdie et al. 2009).
The annual accumulated cyclone energy derived from HURDAT2 database is obtained [here]. Much research has been done recently to try to improve the earlier periods of the record. [1] [2] Many smaller storms are now reported that would not have been detected without modern surveying techniques [2].
Sea surface temperature data (SST) are taken from two processed data sources, both derived primarily from ICOADS source observations:
- HadSST3.1.1.0 is an “anomaly” dataset ie deviations from the local seasonal mean from an arbitrary reference period. Data recovered from KNMI [link] Data from 0 -70W, 0 – 60N were averaged.
- ERSSTv3 is a dataset of actual SST [link]. A single offset was subtracted from the N.Atlantic mean to align it with HadSST3. NOAA provide a detrended, N.Atlantic average they call AMO index. The data used here is NON detrended version, ie actual SST.
Data Processing:
Since ERSST has a strong annual variation, and HadSST3 has considerable high frequency noise and annual residuals, both were low-pass filtered using a 3-sigma gaussian filter with sigma = 12 mo. This removes most variability below about 2 years in period.
Considerable adjustments are made to SST for a number of reasons which are discussed on the Met. Office web site In particular, substantial adjustments are made to WWII period and subsequent years ( many of which are similarly adopted for both data sources used here ).
- ERI biases (North Atlantic): In the North Atlantic between 1970 and 1994, Engine Room Intake biases were generated from the means and standard errors from Kent and Kaplan 2006.
- Unknown measurements: AR(1) series with lag correlation 0.99 and range between 0 and 1 were used to assign a time varying fraction of unknown measurements to bucket. The remainder were set to be ERI measurements. The same value was used at all locations.
- ERI recorded as bucket: 30±10% of bucket observations were reassigned as Engine Room Intake measurements. One value per realisation was used and applied to all times and places after 1940.
- Canvas to rubber bucket: A linear switchover was assumed. The start point (all canvas) was chosen randomly between 1954 and 1957. The end point (all rubber) was chosen randomly between 1970 and 1980.
Most of the post-WWII cooling is the result of these somewhat speculative “bias corrections” in particular the phasing in of the “canvas to rubber bucket”” adjustment from 1954 to 1980. The adjustments made to HadSST3 were discussed in detail in the following article On the adjustments to the HadSST3 data set
The N.Atlantic annual cyclone season peaks in late summer. Annual ACE data were plotted at the mid-point of the year. Where ACE is shown low-pass filtered, a similar 3-sigma gaussian filter was used.
ACE data have also been affected by changes in shipping routes and usage during the WWII period, possibly leading to significant non-reporting of storms well away from land.
In general all three datasets should be regarded as unreliable during the WWII period.
Discussion
Similarities :
There is a strong similarity in the ACE and SST data, both at inter-decadal and inter-annual scales. The much discussed 60 year pseudo-cyclic variability is clearly seen in both SST and ACE. The inter-annual variability is particularly close in the more reliable post-1950 period but shows a strong similarity throughout the record. Since cyclones derive their energy from the heat of the ocean surface [3] this not particularly surprising but provides a means of comparing two fundamentally different measurements of climatic conditions.
Differences:
There are two very visible discrepancies in the two metrics. War-time ACE is very low and probably reflects some degree of under-sampling in that period. However, the low activity goes from 1934 to 1949, a far broader period that can be accounted for by WWII disruption to shipping. Also systematic airborne monitoring was started in 1944 (Klotzbach & Landsea 2015) [4] and there was no noticeable increase in ACE until 1950, suggesting the lower level of activity in the period, though less reliable, is real. A detailed account of uncertainty in the HURDAT data is provided by Landsea & Franklin (2013):[5]
There is a large peak in ACE 1893 that is opposed to the variation shown in the SST record. 1952 also shows a mismatch in the two records. With those two exceptions, the inter-annual variability in the two metrics follow each other quite closely throughout the record.
The post-2005 drop in ACE
Applying a low-pass filter to the annual ACE data allows a more direct comparison to SST.
https://climategrog.files.wordpress.com/2016/01/ace_amo_2015_gauss2.png
Figure 2.
An interesting feature becomes apparent: unlike SST, the end of the cyclone data has dropped sharply since its peak in 2004/2005. This looks very similar to the trough that started in the 1930s.
This drop is also reported by Klotzbach et al (2015) [5] which includes the most recent data.
Large, significant downward trends are present in accumulated cyclone energy in the Northern Hemisphere, the Southern Hemisphere, and globally.
It can also be noted that the inter-annual variations correlate much more closely during both the early and later 20th c. warming periods.
Other studies, such as Holland & Webster (2007)[6] , based on storm count rather than ACE seem to give a less clear picture of the SST linkage and, due to earlier publishing date, do not include the more recent decline.
https://climategrog.files.wordpress.com/2016/01/holland_2007_fig1.png
Figure 3. From Holland & Webster 2007, ( fig. 1 )
Common variability of ACE and SST can be examined by cross-correlation of the two time series. Common periodicities can be examined by spectral analysis of the cross-correlation function.
https://climategrog.files.wordpress.com/2016/01/ace_sst_spd.png
Figure 4. Cross power spectrum N.Atl. ACE vs SST
The two main common periods are close to 9 and 60 years, with a smaller peak around 5.6 years. The circa 9 y peak is centred on 9.07 years. It is noted that this is exactly the mean frequency corresponding to 8.85 y and 9.3 y, both of which are lunar cycles. The 8.85 y period corresponds to the precession of the lunar of apsides and 9.3 y is half the nodal precession period.
The 9.1 year periodicity appears to be the same periodicity reported as common to Atlantic and Pacific SST by Muller et al (2013) [8] and shown to be of lunar origin by N Scaffeta [9] by examining data from the NASA / JPL ephemeris.
Although tides are traditionally measured by the height of the water level, it should be remembered that tides are longitudinal waves and the principal movement of water is horizontal, not vertical. Long period tidal variations have to potential to move vast volumes of surface water and hence heat, thereby modifying ocean currents. This seems to have received little recognition or quantitative study.
https://climategrog.files.wordpress.com/2016/01/ace_amo_2015-detail.png?w=796
Figure 5. Detail of later 20th c. ACE and SST with major volcanoes marked.
While there is still too little data to confirm the length of the post 2005 reduction in activity, the dearth of land falling hurricanes in the U.S. has been widely reported, as has the failure of hurricane activity to match the “hottest year ever” claims made about SST.
If this lower level of activity contintues in the next few years, it will suggest that the stagnant temperatures of “the pause”, like those of the 30s and 40s, are not conducive to a high level of hurricane activity. This should then inform attempts to model cyclone formation and intensity.
While there is clearly a linkage between SST and cyclone energy, it is not a simple one-to-one relationship of warmer SST causing ‘more frequent and more extreme’ storms. A more detailed study of other factors such as wind shear and vorticity is covered in Emanuel 1995 [14]. A brief overview of more recent work is provided by Vecchi and Soden 2007[15]
Some studies of the correlation of SST and cyclone intensity and frequency [10] have, for reasons partly motivated by data quality issues, focused on the post-1960 period. However, it is clear that this will not give an accurate or representative assessment. Focussing on a limited period dominated by a rising section of the data runs a substantial risk of drawing false conclusions.
Emanuel (2005) [10]
… show that this index [potential destructiveness of hurricanes derived from the third power of wind speed] has increased markedly since the mid-1970s. This trend is due to both longer storm lifetimes and greater storm intensities. I find that the record of net hurricane power dissipation is highly correlated with tropical sea surface temperature, … My results suggest that future warming may lead to an upward trend in tropical cyclone destructive potential…
The accuracy of the claims and calculations made in Emanuel (2005) were questioned in a reply to the paper in Gray (2005)[11]:.
This paper’s conclusions are partially based on an analysis of poorly documented and biased tropical cyclone (TC) maximum wind (Vmax ) data from the Northwest (NW) Pacific. This study presents a sum of each tropical cyclone’s maximum winds – a very hard measurement to realistically obtain over a 3-5 decade period of changing maximum wind measurement techniques. The author then cubes these maximum wind speeds (Vmax3) of questionable accuracy. Such a cubing process greatly exaggerates any errors in the original Vmax estimate.
Almost any climate dataset will will show either an upward or downward trend. Suggesting evidence of causation from nothing more than sign of the long term trend has little justification. Extrapolating such a relationship outside the period of study, on nothing more than a baseless “if the current trend continues”, is more likely to be misleading than informative. There seems to be some unspoken assumptions that the most likely outcome is that a trend calculated over some arbitrary period will continue, while no logical or statistical basis for that assumption is ever put forward.
A rapid drop in hurricane energy is noted before the El Chichon and Mt Pinatubo eruptions (figure 5) and is already visible in the SST. In fact, both events were preceded by a higher level of cyclone activity that coincided with a peaks in the 9 y lunar cycle in SST and also coincided with peaks in solar activity. The temporal coincidence of all these factors raises the danger of false attribution.
Volcanoes play a significant role in attempts to model past climate. Generally, on a global scale, climate models produce little more than general GHG driven warming and a lot of internal noise. The cooling effect attributed to major stratospheric eruptions is important in putting a few bumps and dips in about the right place to give the visual impression that the model, at least roughly, resembles the recent climate history.
In multivariate regression studies or arbitrarily adjusting climate model parameters to reconcile model output with the climate record (Hansen et al 2002 [12] ), false attribution of subsequent cooling to volcanic forcing would lead to unduly high estimations of climate sensitivity to volcanic forcing. Consequently other radiative “forcings” (opposing warming) will also likely be over-estimated. A separate study of volcanic forcing is the tropics suggests a similar over-estimation of climate sensitivity [link].
Conclusion :
Secular trends underlying the 60 year pseudo-periodic variability in both SST and cyclone data may be determined more by sampling bias and the various adjustments and corrections applied to SST than they are by possible long term changes in the physical conditions. As such, caution should be applied before suggesting that they represent a real indication of a possible long term causal relationship.
The clear 60 y and 9 y periodicities draw attention to the need to investigate long period lunar tidal influences on ocean and atmospheric climate variables. This is needed in order to quantify and account for natural variability and also to avoid false attribution to other climate variables. In particular, large scale variations in surface transport of heat by ocean currents due to long period tides appears to be a much neglected factor [JC note: see this post about Charles Keeling, who was interested in the topic of tides and climate variability].
There is a stronger correlation between ACE and SST during the two major warming periods of the 20th century than in the plateaux or cooling periods. SST is not the single dominant factor determining cyclone energy. There is not a trivial linear relationship and it is probably not appropriate to project relationships derived from the study of data primarily from warming periods onto times of relatively stable SST conditions.
There is an indication that the drop in North Atlantic hurricane activity which apparently occurred during the pre-WWII warm period is repeating during the current temperature plateau.
Update: The following produces a beat pattern of about 59y that would match the periodicity found in the article. This may explain much of problem with
finding a consistent correlation to solar forcing in absence of the
recognition of a significant lunar periodicity.
p1=9.1;p2=10.8;
cos(2*pi*x/p1)+cos(2*pi*x/p2)
References [References]
JC comment: As with all guest posts, please keep your comments civil and relevant
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Since cyclones derive their energy from the heat of the ocean surface [3] this not particularly surprising but provides a means of comparing two fundamentally different measurements of climatic conditions.
Spatially, when a tropical cyclone of a given vertical profile passes over ocean with higher SSTs, there is intensification, logically from the increased Convection Available Potential Energy(CAPE).
But spatial and temporal changes in SST are not necessarily congruous.
Wind shear and SST may be correlated. ACE may be influenced by the correlate and not directly by SST.
And the Atlantic trend should be in the context of global ACE.
Does global ACE and global SST show correlation?
A more disinterested analysis would include winter and extratropical North Atlantic storms like the hurricane-force cyclone that raged south of Newfoundland last week.
North Atlantic Hurricanes have been studied because of their impact on the US.
They are discussed here because they are the only extreme weather that has shown the slightest correlation with Global average temperature. At least they did, up until the early 2000s.
Gregg: That 60 year thing. What odds would you place on the current UAH/RSS data as showing the first half of a 60 year cycle? Fits the data. So where between 1.0 (all 60 year cycle) and 0.0 (on 60 year cycle) would you place your choice?
A nice disprovable observation. Yes/no.
p.s. Thanks for the assistance last time.
What may be more relevant is why UAH/RSS shows cooling since 2005 and SST is flat . I recall that Josh Willis originally found ocean cooling between 2005 and 2006 until he got told to get with the program and had to delete any offending XTBs that showed cooling.
It should be remembered that satellites measure lower tropo air over land and sea and are not directly comparable to SST. Land air + SST “averages” are technically BS since you cannot average temperatures of different media. [ extensive / intensive peropeties etc. ].
Greg.
I recall that Josh Willis originally found ocean cooling between 2005 and 2006 until he got told to get with the program and had to delete any offending XTBs that showed cooling.
Do you have any proof of this?
http://earthobservatory.nasa.gov/Features/OceanCooling/
JC note: very informative link, thx
I am very familiar with that article. It has been linked to several times here at Climate Etc. I have also exchanged emails with Josh Willis. He was not told to get with a program.
What is interesting is the willingness to skew what happened there into conspiracy horsechit.
Yeah, that link to ocean cooling being pencil whipped into compliance with global warming was put here and at WUWT many times by yours truly over the years.
You’re welcome.
Josh Willis on the the art of pencil whipping (Reader’s Digest condensed version):
“In fact, everybody was telling me I was wrong.”
“First, I identified some new Argo floats that were giving bad data; they were too cool compared to other sources of data during the time period. It wasn’t a large number of floats, but the data were bad enough, so that when I tossed them, most of the cooling went away.”
http://earthobservatory.nasa.gov/Features/OceanCooling/
Easy peasy. When the data isn’t what you want then just declare it “bad” and delete it. No muss, no fuss. Welcome to global warming “science”.
Josh Willis on the the art of pencil whipping (Reader’s Digest condensed version):
“In fact, everybody was telling me I was wrong.”
“First, I identified some new Argo floats that were giving bad data; they were too cool compared to other sources of data during the time period. It wasn’t a large number of floats, but the data were bad enough, so that when I tossed them, most of the cooling went away.”
http://earthobservatory.nasa.gov/Features/OceanCooling/
Easy peasy. When the data isn’t what you want then just declare it “bad” and delete it. No muss, no fuss.
Welcome to global warming “science”. Guaranteed results every time. One way or another.
He found his mistake. Do you know what a mistake is? Oh, I forgot, you’re the smartest person in the world and you have never made a mistake.
Willis didn’t make the mistake. Read harder. Some undisclosed number of ARGO buoys made the mistake of reporting unexpectedly low temperatures. So he arbitrarily dropped them out of the record. Like a puppy that piddles on the floor: BAD BuOY!
It evidently didn’t occur to Willis that the “bad” buoys might have detected cold water upwelling from the depths that wasn’t showing up in the exceedingly sparse XBT data he used as yardsticks. No investigation into the problem. Just ditch the data that doesn’t agree with the warming hypothesis; a tried and true methodology in global warming
story tellingscience.“So the new Argo data were too cold, and the older XBT data were too warm, and together, they made it seem like the ocean had cooled,” says Willis. The February evening he discovered the mistake, he says, is “burned into my memory.” He was supposed to fly to Colorado that weekend to give a talk on “ocean cooling” to prominent climate researchers. Instead, he’d be talking about how it was all a mistake.
Write a paper on that upwelling theory. Surely there is a journal for the polumath.
http://judithcurry.com/2016/01/10/appraising-marvel-et-al-implications-of-forcing-efficacies-for-climate-sensitivity-estimates/#comment-757682
Anyone who thinks he made innocent mistakes is incredibly naive and gullible. Put him under oath with threat of perjury and watch him spill the beans. Bureaucracies have mysterious methods to achieve desired results.
Dumb. Just plain dumb. His mistake was to ignore other lines of evidence, perfectly valid lines of evidence, that indicated there was something wrong with his result. A year later it became perfectly clear.
“You folks with the high sea level rise estimates have some ‘splaining to do.”
Well ice melts and the ocean bottom at the Equator is apparently 60 years away, round trip. Not all energy is heat.
Regarding the Willis cooling controversy, the 2007 correction indicated that both Argo float and XBT probe data errors “contributed equally” to the (spurious) cooling.
Furthermore, the authors had already tested for potential bias due to the expanding Argo float coverage:
I would also note that the warming trend arising from the XBT probe profile corrections was acknowledged in the original Willis 2004 paper. So it would seem odd if it was not already accounted for in the Lyman 2006 update that found the surprising ocean cooling trend.
The cooling they had identified was not an obvious error since Levitus (2005) also found “a short period of rapid cooling (6 × 10^22 J of heat lost in the 0–700 m layer) from 1980 to 1983.” Nevertheless, I would not fault a researcher for taking conflicting data into account whenever warranted.
Perhaps someone with more experience in this field can provide more conclusive input.
Willis, 2004: http://www.geo.utexas.edu/courses/387h/PAPERS/willis_jgr_04.pdf
Lyman, 2006:
http://onlinelibrary.wiley.com/doi/10.1029/2006GL027033/full
Willis & Lyman 2007 correction:
http://onlinelibrary.wiley.com/doi/10.1029/2007GL030323/full
Oplusa – Willis was a co-author on the 2006 paper.
It is interesting that UAH TLT also shows a strong cooling at around that time.
http://www.drroyspencer.com/wp-content/uploads/UAH_LT_1979_thru_December_2015_v6-1.png
It should be noted that TLT is not the same thing as SST but the similarity in timing of this drop is interesting.
One of the problems with this “bias correction” program is that if it was a warming bias it would have been seen as “expected” warming and would not have raised any questions.
When 2014 was declared warmest year EVA, no one was spending all there spare time ploughing through XTB and AGRO data trying to find the “defective” data leading to the warming.
It is not bias correction but bias confirmation that is happening.
http://oceans.pmel.noaa.gov/sites/default/files/atoms/files/OHCA_curve_2015_2.pdf
You might like to take a look at the triad plots of UAH I have over there (moved to dropbox entry – near the bottom). That shows a lot more complexity in the system available in he available data IMHO. I would welcome you opinion if you have the time.
I think both observations are a little stretched. Some instruments were considered to be out of calibration. I am sure the reasoning for doing so was considered to be engineering required at the time. If that turns out to be not true then I don’t think guile will have been the root cause.
Greg: A Gaussian is a Gaussian as you and Vaughn observed. So the annual stands. The 15 year is just because that’s an inflexion point in the data. The 7 =4 years is a punt as you well observe. Just shows a ‘trend’ that is a bit better than OLS I think.
https://climatedatablog.wordpress.com/2015/12/21/moved-to-dropbox/
And published previously here
http://wattsupwiththat.com/2014/03/16/crowdsourcing-a-full-kernel-cascaded-triple-running-mean-low-pass-filter-no-seriously/
Hi Richard, I don’t know how I missed this at WUWT.
Looks pretty good, applying well-behaved filters. The obvious problem is using the single 75y RM. They are really aren’t worth a S*** . If you cant do a filter, you stop, you don’t apply a crap filter because it’s the only one with a short enough kernel.
As I have demonstrated in the article you reference, running mean “filters” can quite often produce a dip where there should be a peak. Since you will not know whether this is happening how can you believe the output.
Specifically is the inflection point in the middle real or not? Should it be a peak? One thing is for sure threre can not be a change from one slope to another if you have filtered out everything shorter than 75 years so this most certainly is a artefact of the defective filter. Also note the two short flat sections 1932-1940 and around 1915 : how can you have such short term features after applying a heavy low-pass filter. Again that can ONLY be artefacts of the defective filter.
Your treatment of SG filter is sensible, shame you include the crappy running mean. Most readers will not realise that inflection HAS TO BE an artefact and will accord it some value.
Sorry I did not see this earlier.
Just looked at the graph again. 1915 is slight peak 1940 is dip 1970 just shows the next peak. This is in anti-phase with the correctly filter triple running mean curce: typical RM artefacts !!
Re HadCRUFT4 [sic] I also get rather tired of pointing out that you can not meaningfully combine land and sea temperatures. Physically different media with very different head capacities, it’s physically meaningless.
A mathematical tool for temperature data
https://climatedatablog.wordpress.com/2014/02/19/first-post/
And I do kinda realise the position I am here. I took what I gathered from conversing with you and Vaughn and make a tool from it. I rather do, from our previous conversation and my experience as to its limits and advantages. The fact that I have placed an invite to him should not go unnoticed IMHO. I stand or fall by that scrutiny.
And as a last post before I let moderation catch up with me, I shall quietly observe that a google search of two words, climatedatablog richardlh gives a nearly perfect summation of two years of work with all the relevant papers, etc. in just 2-8 pages in the Internet. Not bad if I do say so myself.
And if you all think I am sitting here, saw in hand cutting away at that on which I stand, then consider this. A small addition to a quote that long predates me.
Art of War (sugested addendum)
https://en.wikipedia.org/wiki/Battle_of_Waterloo
https://en.wikipedia.org/wiki/The_Art_of_War
https://en.wikiquote.org/wiki/Sun_Tzu
Know your Friends well, your Enemies better {and your Allies at least as well}.
Without Blucher, Waterloo may have turned out very differently
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Figure 2 is quite compelling showing the correlations in long-term dips and rises. Imagine what could happen as the SST anomaly rises towards 1 C in the next few decades based on this history.
Perhaps you could try demonstrating that you read the article before commenting, not just looking at the pictures.
Yes, the article has a lot of idle speculation, so I added some more.
Do you do that often?
Yes, idly thinking what if the rise is not part of a 60-year cycle, but the expected one from climate forcing which just keeps going up. That whole line of thought was missed, so I just thought I would mention it.
Well if you see something that you thing is not correct, try saying so directly , with substantive arguments backing it up instead of playing your usual warmist clown act.
You do occasionally seem capable of coherent argument, so give it a try.
If your sole aim is to pollute 50% of comments with your usual garbage, I shall ignore any further posts and suggest others do likewise.
What’s missing is the known trend part of global SSTs. Basically it has been warming at an accelerating rate, and you have not considered that, nor its implications for the future. Analysis into repeating cycles doesn’t do this important component justice.
Jim, what is your assertion of “acceleration” based on? I’ve seen you claim this before. There was no acceleration in SST in 20th c. Atlantic or globally. What are you referring to?
I suspect you have fallen for the old cosine acceleration trick:
https://climategrog.files.wordpress.com/2013/04/warming-cosine.png
https://climategrog.files.wordpress.com/2014/07/amo_trends.png
https://climategrog.wordpress.com/amo_trends/
I’m not interested in projecting or predicting. Before attempting that you need to understand the system This article is about analysing the data we have and trying gain some understanding
There does appear to be a faire degree of correlation between ACE and SST but it is not y=k*x , that is what the article is saying if you got as far as reading it yet.
If you read it and disagree with any points made, please don’t hesitate to quote what you disagree with and state why.
Jim D: If I may.
There is no doubt that has and is changing. The apportionment to ‘blame’ is what I think this whole debate is about
The 30-year global trend at the end of the 20th century was double the average trend of the whole 20th century. This is an acceleration. The 30-year trend, when continued, gives us another 0.5 C in 30 years, hence my earlier comment. I think the 30-year trend will continue in the future, and that is just because of the way the forcing that steers it is changing. Cycles fade into the background when the forcing accelerates.
Jim D ;”The 30-year global trend at the end of the 20th century was double the average trend of the whole 20th century. This is an acceleration”
Did you read my last reply Jim? This is exactly what I said: you have been mislead by the cosine warming trick. Thanks at least for stating clearly what you were referring to.
You then go on with the usual “trend” fallacy. You fit a linear trend ( for no stated reason ) to an arbitrary period and then spuriously ASSUME that this “trend ” will continue. What is the loigic behind that? Is there some unwritten law that any and all “trends” will continue?
What is your reason for choosing that period to fit a trend and why do you assume that this trend will continue? There are no straight lines in climate on ANY time scale, this is purely a man-made idea.
“There are no straight lines in climate on ANY time scale,”
I think I did a blog post on that somewhere. Oh yes…
https://climatedatablog.wordpress.com/2015/12/22/are-straight-trend-lines-propaganda-or-science/
Cycles fade into the background when the forcing accelerates.
Forcing has decelerated since peaking in 1989:
http://www.columbia.edu/~mhs119/GHGs/dF_GHGs.gif
You may resume making things up.
TE, to state it more clearly, as the forcing accelerated in the late 20th century, the trend increased. Now the trend is steady because the forcing is still rising at a steady rate. That steady rate is 0.5 C per 30 years consistent with 2 C per doubling. These are the numbers we can use to suggest that the anomaly in 30 years will be 1 C on that SST anomaly graph, and why it is worth thinking about how this is affected by going to 1 C in a few decades. It is a scenario that is paced by both the forcing and temperature trends.
climategrog, as far as I can tell, you are the one who plotted linear trends. I made the distinct case that the trend has increased between the 20th century average, and that since 1980. This is nonlinear by definition. Also the increase in trend was expected by most of us, but took the CO2 skeptics by surprise, and they still try to fit cosines to it in hopes that the upward trend will reverse (chance being slim to none).
Jim D | January 11, 2016 at 9:24 pm |
TE, to state it more clearly, as the forcing accelerated in the late 20th century, the trend increased. Now the trend is steady because the forcing is still rising at a steady rate. That steady rate is 0.5 C per 30 years consistent with 2 C per doubling.
Huh? UCB actually measured the change in forcing from 2000 to 2011.
The 30 year rate, based on the UCB measured 0.2 W/m2 = 22 PPM , for the 346.04 (1985) to 400.83 (2015) transition, is 0.51 W/m2 – not °C – W/m2.
This also appears to be only a surface phenomenon. That means the BOA sensitivity of 5.5 W/m2 not the TOA sensitivity of 3.7 W/m2 should be used. That makes the 30 year forcing change 0.1°C.
PA, take a look at TE’s graph and do the mathematics yourself. The forcing trend is 0.03-0.04 W/m2 per year since 1980, and the global temperature trend is 0.017 C per year since 1980. These two give you 2 C per doubling. It’s right there in the graphs.
Jim D | January 11, 2016 at 11:03 pm |
PA, take a look at TE’s graph and do the mathematics yourself. The forcing trend is 0.03-0.04 W/m2 per year since 1980, and the global temperature trend is 0.017 C per year since 1980. These two give you 2 C per doubling. It’s right there in the graphs.
Perhaps you misunderstood. They actually measured the forcing from 2000 – 2010 and it was 0.2 W/m2 over an 11 year period. So the CO2 forcing on the graph is 50% too high. It was measured to be 0.02 not 0.03. The chart seems to be what you get using the IPCC formulation CO2 alone forcing. That isn’t the actual forcing it is just the IPCC estimated forcing from CO2 in isolation.
I’m plotting trends because you are making spurious claims about them without plotting them or referring us to where you get your hand waving summary of climate from. I’m providing you with DATA.
I am showing you that fitting a trend to the rising part of a cosine and comparing it to a longer “trend” produces exactly the “acceleration” you are claiming is happening in climate, yet as we all know a cosine has zero long term trend.
Thank you again for a clear statement. That is EXACTLYyour problem and that of a large part of AGW alarmists. You start out with a preconceived position and let bias confirmation run unchecked.
Even when I prove to you that the “acceleration” you have been claiming for months is totally a result selectively fitting straight lines to data with periodic repetition you totally ignore it and carry one with you spurious claims.
Why do you bother posting here? Do you really think that you are going to convince anybody of anything other than your own wilful ignorance? I gave it shot at explaining because a lot of sensible, honest people have been mislead by this cosine acceleration scam.
You have demonstrated that you are neither sensible nor intellectually honest. There is no point my wasting time on logic and science with you.
Thanks for a least taking the time to prove how baseless your claims are, the nonsense on which you think they are based and your lack of amenability logical argument. That should help everyone ignore you drivel in the future. I know I will.
“The forcing trend is 0.03-0.04 W/m2 per year since 1980”
…The estimated forcing trend is 0.03-0.04 W/m2 per year since 1980…and the estimated global temperature trend is 0.017 C per year since 1980,,.
How about since 1880, 1780, 1680? Lets not concentrate too much on recent history
From Loehle & Scafetta (2011)
More than one linear trend. There has been a consistent trend of 0.1C/decade from 1940 to 2000 not present prior to that time.
https://curryja.files.wordpress.com/2011/07/loehlescafettawuwtfigures01_page_2.jpg
The 1940-2000 linear trend happens to coincide with the modern solar maximum:
https://upload.wikimedia.org/wikipedia/commons/thumb/2/28/Sunspot_Numbers.png/500px-Sunspot_Numbers.png
I believe there’s a causal connection between the modern solar maximum and the 60 year linear trend identified by Loelhe and Scafetta. Henrik Svensmark explained how in his Cosmoclimatology hypothesis:
http://astrogeo.oxfordjournals.org/content/48/1/1.18.short
(con’t)
Given the 0.1C/decade trend ceased as soon as the sun went quiet beginning in 2005 it would be quite an extraordinary coincidence if the sun wasn’t the driver instead of CO2. Moreover note that the “global cooling scare” of the early 1970’s coincides with a single exceptionally low solar cycle.
https://www.eia.gov/todayinenergy/images/2013.03.28/sunspots.png
Moreover we can see other quiet solar cycles aligned with temperature dips. The correlation is far better with the sun than with CO2.
http://appinsys.com/globalwarming/GW_Part6_SolarEvidence_files/image013.jpg
“Why do you bother posting here? Do you really think that you are going to convince anybody of anything other than your own wilful ignorance?”
Please show some pity for our most prolific and annoying denizen, Greg. The little fella is not responsible for his actions. He’s a huffpo drone.
PA, you can take it up with TE, but that forcing is global top-of-atmosphere, and yours is for one or two point measurements at the surface. Global TOA is more relevant to climate change than two points at the surface.
climategrog, OK, you can look at the 30-year temperature with its trend at the end of it, and see what kind of cosine you want to fit to that. So far a case can be made that it has not passed its inflection point, so it is less than half way to its max. I think fitting a cosine to this with zero added trend will look ridiculous, but go ahead, and see what you get for a max, or whether it can be stretched more than half a cycle back into the history. It’s more than a cosine going on, and some people have not picked up on this important fact yet.
http://www.woodfortrees.org/plot/gistemp/mean:120/mean:240/plot/gistemp/from:1985/trend:40
Jim D | January 12, 2016 at 8:52 pm |
PA, you can take it up with TE, but that forcing is global top-of-atmosphere, and yours is for one or two point measurements at the surface. Global TOA is more relevant to climate change than two points at the surface.
Well, that’s fine – but the measurement should be the entire effect delivered to the surface – which is the only thing that anyone cares about.
Since the measurements are at the top and bottom of the temperate zone, the measurement is sort of a worst case. The higher humidity of the tropics should reduce the warming effect since the band spreading from the higher water vapor will saturate some of the CO2 bands.
Right now it looks like accurate measurement of CO2 forcing will doom CAGW as a problem. Accurately measuring CO2 forcing is the first thing that should have been done before they started crying CAGW.
It doesn’t make sense to cry wolf before you have seen or heard a wolf.
As Obama just said in his speech, yes, there are a few holdouts left, but the rest of the world has already moved on.
Here.
http://www.huffingtonpost.com/entry/obama-climate-change_5695b77ce4b086bc1cd5dc8c?utm_hp_ref=politics
Well as an acknowledged non-expert, I am not sure whether you know enough to tell whether there is a potential wolf there or not. It’s puzzling to me how some people can cavalierly and confidently dismiss most climate change research when they know so much less than the scientists who do the research.
Jim D | January 12, 2016 at 11:12 pm |
As Obama just said in his speech, yes, there are a few holdouts left, but the rest of the world has already moved on.
“Post Turtle” Obama couldn’t find his posterior with both manipulatory appendages and a flashlight.
You need to start citing competent sources, not failed community organizers..
PA, and it is not just Obama who thinks that way but, as he noted, “our military, most of America’s business leaders, the majority of the American people, almost the entire scientific community, and 200 nations around the world”, so it is either all of them or you who have it all wrong.
yimmy, yimmy
The reality is that the World’s leaders came together at the lavish Le Gran Soirre d’ Paree and decided to do next to nothing.
“so it is either all of them or you who have it all wrong.”
Jim that is a common logical fallacy. Ad Populum I believe it’s called. Everyone thought that the earth was flat or that the continents didn’t move at one stage. Science isn’t democratic. You don’t get to vote on the truth, and someone saying at everyone agrees doesn’t make it so.
Furthermore, I don’t believe that to be the case. Skepticism on AGW but particularly CAGW is much more widespread than you seem to think and even at governmental levels. Even governments who pay lip service to the issue are subtly or not so subtly changing their energy policies in light of the changing “realities” – both from the fact the problem is clearly far less serous than was previously supposed, and the very real need politically and socially to keep energy costs down.
“97% of climate scientists believe…” is demonstrably bollocks. You know this. Nearly every single skeptical commentator you tangle with here would constitute part of the “97%” as it was initially framed, so it is essentially meaningless.
Joseph | January 12, 2016 at 11:27 pm |
It doesn’t make sense to cry wolf before you have seen or heard a wolf.
Well as an acknowledged non-expert, I am not sure whether you know enough to tell whether there is a potential wolf there or not. It’s puzzling to me how some people can cavalierly and confidently dismiss most climate change research when they know so much less than the scientists who do the research.
Huh?
I quote the only piece of real science research, the February UCB study all the time. It indicates a near-TSR value of 0.64°C. I will wait for the study in about 7 years or so which produce a TSR measurement but go with what we know for now.
The trend to the data is pretty consistent so if we measured at dozens of places for the next 6 years we could get a unassailable well bounded TSR measurement.
And there is no point in doing anything on global warming until we have a good empirical measurement of the TSR.
The peak CO2 measurements from responsible professionals in the fossil fuel field is 460 PPM peak CO2. The current CO2 trend combined with a pre-mid-century peak in fossil fuel consumption supports that analysis.
ESRL reported a 3.17 PPM increase in 2015, despite the mid-year difference being 2.2. PPM due to a quixotic last month increase peaking at the end of December.
Week beginning on January 3, 2016: 402.10 ppm
Weekly value from 1 year ago: 399.87 ppm
Weekly value from 10 years ago: 381.18 ppm
The value they will have to report for 2016 will be ugly. Right now it looks like it will have to be below 1.5
PPM.http://www.mercurynewsdaily.com/global-fossil-fuel-emissions-may-decline-in-2015-7518/
Emissions look flat and in the near term will stay flat (there are some predictions emissions declined 0.6% In 2015).
Continue to dance your dance. We have plenty of time to collect data before we even think about taking actions that appear to be unnecessary.
PA, with flat emissions and high concentrations in 2015, people will be shrieking that sinks are saturated and we are all doomed.
No accounting for late northern hemisphere spring and el nino. No look back at the 97/98/99 concentration fluctuations and emissions rates.
aaron | January 13, 2016 at 11:19 am |
PA, with flat emissions and high concentrations in 2015, people will be shrieking that sinks are saturated and we are all doomed.
No accounting for late northern hemisphere spring and el nino. No look back at the 97/98/99 concentration fluctuations and emissions rates.
Environmental absorption was 7.01 GT in 2014 according to CDIAC.
Either 2016 or 2017 will exceed that record significantly.
The claim the sinks will saturate is absurd. The ocean is absorbing the CO2 in the Arctic and it will be gone for centuries (and with 38000 GT already in the ocean is a drop in the bucket). This ignores the fact that growth in the ocean should also be spurred. The warmers are schizophrenic on this they claim red tides are increasing due to CO2 but general ocean plant life is decreasing.
The land absorption is in plants, porous rock, and weathering and that won’t saturate either. CO2 has to get over 1000 PPM before plant growth starts leveling off.
But we will see. The rate of CO2 rise may be 2 PPM or less in 2020. If we don’t see the 3+ PPM/y predicted by the IPCC the CAGW party is over.
Cyclones can only respond to absolute SST, but I get your point. However, the distribution of any increase in SST would seem as important as the global anomaly trend itself. Consider that the current Pacific El Nino (probably) disrupted North Atlantic storms in 2015.
The headline graph includes ERSSTv3 which is actual SST. Both SST and ACE are arbitrarily scaled and shifted . Nowhere do I present global anomalies nor do I discuss “trends” other than to disparage the idea or when quoting others that subscribe to the trend obsession .
IMO climatology would get along a lot better is the word “trend” was banned from the discussion.
“IMO climatology would get along a lot better is the word “trend” was banned from the discussion.”
No, it would not. The trend is your friend… until it stabs you in the back.
Warmists and satellite data trend:
http://lowres.cartoonstock.com/office-workload-overwork-overworked-backstabbing-backstabbers-jnan3106_low.jpg
Idle thought: I wonder whether the correlations would change noticeably if the physical size of storms was also a component of the ACE (ACE-plus?) calculation? The idea would be to more completely account for the total energy in a given cyclone.
Of course, such estimates would largely be limited to satellite-era estimates. Like I said, idle thought.
If you have read the link that explains how ACE is calculated and think that you can seen some obvious errors in that I suggest you send your thoughts to Chris Landsea to that he can correct the years of work that has gone into calculating the data.
I’m wasn’t trying to criticize you or ACE. I was contemplating a possible method to improve a pretty good metric. Thanks for posting an interesting analysis.
I was not taking it as a criticism but I don’t see that your suggestion would do anything that is not already being done. If you think that current ACE is not an good estimation of cylone energy maybe you could explain why. Usually “idle” comments are not that helpful.
ACE is not a perfect measure of total cyclone energy, although it is a reasonable estimate. The true “total” amount of energy would have to include the mass being moved — which is a function of the size (essentially, diameter) of the storm. As far as I know, and according to the definition of ACE you provided, the size of the storm is not included in the ACE metric.
And if that was insufficiently clear, the definition from above:
Good point. Wind radius is hard to determine and poorly recorded historically. Many of the earlier periods are infilled by historical research of newspaper reports etc. The way it is done is probably the most consistent over the full record.
Check out refs [2] and [5] for more detail.
Do the slopes of some of these graphs coincide with changes in arctic sea ice by chance?
https://climategrog.files.wordpress.com/2015/12/ct_ice_area_short_anom_nh_2015_final.png?w=584
https://climategrog.wordpress.com/2013/09/16/on-identifying-inter-decadal-variation-in-nh-sea-ice/
Bear in mind that ice volume ( for which ice area is a defective proxy ) would be linked to the integral of temperature. Don’t expect the two to be in synch.
Yes. Mass is more important. Changes in extent may be indicative of ocean circulation changes though. Judith had some posts over the past few years which show various historical estimates of arctic ice. I’m interested in the whole mid-19th century to present, not just the satellite.
http://judithcurry.com/2013/09/08/arctic-sea-ice-minimum/
As an Engineer I would have thought the water/ice surface area governed the energy transfer rate much more. Lots of energy flows, though no temperature change, in those few mms.
Richard, if you want to measure energy, you need to deal with ice volume and latent heat of fusion. To find the causes and feedbacks ice area is more important.
Humanity is witnessing a catastrophic drop in Atlantic hurricane activity and it’s a travesty!
Indeed, if the current “trend” continues by 2100 there well be no hurricanes at all. WE must act now !
wind tax?
dewindifacation?
uh … wait… we would need more wind
wind tax credit
at last, tax policy working for moi
In fact with further extrapolation the Atlantic may experience negative hurricanes by 2150.
Let EU act now!!
China will continue pumping out NOx SOx mercury and carbon dioxide until Alabama, Florida and Clemson collapse in hurricane disasters and the Pac 12 can rise in the college football ranks.
Scott
Yep, an unexpected change in the “tide” when it turned Red (Crimson) from a short dribble and then started to flow again like tsunamis down the shore lines. Look out for those end runs in whatever “sport” (isn’t all this “climate stuff” sport?) you wish to participate in! Covering the bulk in the middle is NOT sufficient!
Interesting analysis. Logical hypothesis. And there does seem to be a 60-70 year ocean cycle, since it is also qualitatively evident in Arctic sea ice.
My main uncertainty problem is not early ACE because of unreported storms. It is the greater uncertainty in regionally important SST prior to ARGO. Was mostly shipping route observations. The area of the tropical eastern/central Atlantic where NH hurricanes incubate has been greatly undersampled since the opening of the Suez canal. And probably even before then, looking at shipping between Europe and South America on great circle routes. Too far west, then too far south.
Good points. You will notice that my main point is that the underlying secular variation is more determined by sampling error and atempts to “correct” SST than anything else and can not be relied upon.
However, also note that this is SST is taken 0-60N 0-80W. Some studies have tried to focus on the region where a lot of storms form or just the peak months etc. and don’t get better results. ACE is determined by the whole path , not just in the birth canal.
Even taking this broad brush approach, there is a clear correlation. That somewhat avoids lack of sampling in specific regions.
BTW , various SST records and different taper functions on the spectral analysis all gave a peak between 58-60 years.
Rud,
Interesting correlation? (JCH states there’s no merit, or more accurately there is no 60 year cycle. Wonder if Joseph would have as much issue with JCH as ‘some blog poster’ being not on the same level as a ‘climate scientist’ denying this science.): http://onlinelibrary.wiley.com/doi/10.1029/2012GL052885/full
Build a bonfire, buy some hotdogs and some beer, and party until the AMO goes negative… the negative AMO watch.
the negative AMO watch party
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‘While there is clearly a linkage between SST and
cyclone energy, it is not a simple one-to-one
relationship of warmer SST causing ‘more frequent
and more extreme storms.’
You’ve got the sun
in the morning and
the moon at night,
tides ‘n currents,
wind shear ‘n buckets,
weather system with all
therein, behavin’ more
like clouds than clocks.
The moon is still there in the day time. That’s why there are two high tides per day. Sometimes storm clouds are behavin’ more like clocks.
Silly serf. (
Did I miss it or are the correlations with the entire seasonal SST anomaly for the entire region from 0 to 60N?
It would seem to me that a more meaningful, though more difficult, comparison would be the path differentiated absolute temperature and path differentiated CE.
The Atlantic might be anomalously warm, but the hurricanes form only over the anomalously cool areas.
Also, how do we distinguish hurricanes that form in anomalously cool July waters versus anomalously warm Novembers?
This article is not aiming ot provide a means of modelling cyclones, there is a lot of work already published on that. The references are in a pdf at the end of the text several cover that.
If you think you can get better correlation from a more selective are go ahead. I did not find any clear indication of that.
Hurricanes don’t know what the temperature anomalies are.
They do know what the actual temperatures are.
It has been found that a minimum of about 26.5C SST is needed to create a tropical storm. So any relationship is likely to be to the excess over that trigger point. That makes it an anomaly.
Whether you subtract of 26C or 299K , it does not make any difference.
If I plot SST in kelvin , it is a flat straight line with no resemblance to ACE.
Both variables were arbitrarily scaled and an offset added to align them. You could use real SST and an ACE ‘anomaly’ if you prefer.
Say it ain’t so… despite a penchant among AGW experts to find any alarming association between seemingly natural disasters and humanity’s CO2, so matter how spurious, are you telling us that there is no way we can massage, mangle, and manipulate the data to hide a drop in cyclone energy?
The take home message, if you want one, is that despite some quite clear positive correlation, the two hottest periods in the SST data both show a marked drop cyclone energy.
Warmists always want simplistic linear relationships between climate variables that can be summarised by arbitrary linear “trends” that can be spuriously extrapolated way outside fitting period.
This article shows that it does not apply to SST leading to “more frequent and violent storms”.
Powerful replacement in works for climate-modeling computer
http://www.msn.com/en-us/weather/topstories/powerful-replacement-in-works-for-climate-modeling-computer/ar-CCoIG3?ocid=spartanntp
GIGO, only faster. Wow!
Sorting out GIGO from DIGO can be a long task. Sorting out blame even longer. Been there, done that.
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Any heat engine operates between two reservoirs at different temperatures, and the amount of energy that is converted is proportional to the temperature difference.
Physically, ACE can not be a function of just the SST. If it correlates with SST that is because SST is one of the two relevant temperatures. My question is, what is the other one? What is the temperature *difference* that drives storms? Is it the difference between the sea surface and the air immediately above (I suspect not) or perhaps between the sea surface and the upper troposphere?
Unless this is understood I don’t see that plotting ACE vs SST is of much value. Plot ACE vs delta-T.
It also follows that increasing SST can not by itself increase ACE, or the severity or frequency of storms. That can only happen of the other (lower) temperature is increasing by a smaller amount.
Pretty sure it is the delta between SST and upper troposphere. Hurricanes start out as bands of thunderstorms known as tropical depressions. Coriolis force on the travelling convection cells causes counterclockwise self organization in the NH. Factors for intensification are less well understood. The basics are well illustrated at the National Hurrican Center website.
Thanks ristvan. Upper troposphere temperatures are not constant are they? Has anyone tried plotting ACE (or hurricane frequency) against (SST – UTT) ?
That’s very good point Gareth but I was not aiming to create a climate model for hurricanes here. Mid to upper tropo temperature is probably the other end of the heat engine. There’s more on the existing theory in the refs.
You may find them easier to use on my original version on climategrog, something got lost in the move to C. Etc and the links no longer work.
https://climategrog.wordpress.com/2016/01/10/on-the-relationship-of-ace-and-sst/
I agree SST is only part of the story. That was one of the points of the article to point out the simplistic “more frequent and more violent storms” narrative just does not fit the facts.
Temperature at the “other end” is very likely a factor as is wind shear and knock on effects of Pacific wind patterns. I don’t see any discussion of the war-time dip as a real event and the similarity to the current situation does not seem to have been noticed.
Chris Landsea agrees that there may be grounds for the mid century dip being at least partially a real climatic event rather than just under sampling, though it will have suffered under sampling.
Thanks for the link, Greg. The other heat engine we need to think about, that drives global weather, is that between the tropics and the poles. As everyone seems to agree, as the earth warms, the poles warm more than the tropics, so that temperature difference decreases, and we would expect less strong jet streams, etc. (I see wikipedia agrees with me on this:
https://en.wikipedia.org/wiki/Jet_stream#Longer-term_climatic_changes )
which again seems to contradict the general “more extreme weather as a consequence of AGW” narrative.
Which ‘everyone’ is that? Do you see the Antarctic warming apart from in crap like Steig et al ? You see how incidious this propaganda is? They just call it “polar amplification” and less discerning readers assume that it refers to both poles. The should call it Arctic amplification. They do not even have any explanation for the observation that it is warming quicker, but they are sure it’s due to CO2.
Proof is not longer needed: it obvious !!
I would not cite WonkyPedia as a authority on anything, I certainly would not even look at it for anything climate related.
When I see a signal being stronger in one pole and zero at the other my first inclination would be search for the cause where it is strongest. Also note that annual CO2 swing is greater in the Arctic that at mid-latitudes there the CO2 is produced. How does that happen? Polar amplification?
Once we start to study variation in ocean currents we may start to have some understanding of what causes polar see-saw ( opposing trends at the poles ) and the so called polar amplification. For the moment, I’m not aware ANY climate models that even include a lunar component.
Aparently tides only happen twice a day and it all averages out.
Tides at the poles are not twice a day are they? That’s further on down the globe surely.
Have a look at these for some concept of what the oceans are doing with/to the polar regions.
Image at upper left is from LANL: http://www.lanl.gov/newsroom/picture-of-the-week/pic-week-2.php
http://pages.swcp.com/~jmw-mcw/Curry_Ocean_Flows.jpg
http://oceanservice.noaa.gov/education/kits/tides/media/supp_tide03.html
For the driving forces that result in the patterns we see here on Earth
And this for the force vector pattern.
https://en.wikipedia.org/wiki/Tidal_force#/media/File:Field_tidal.svg
The area I think that may be of interest is where the vector becomes tangential to the surface. High Latitudes are important for both water and air IMHO.
Annotated and with air circulations added
https://climatedatablog.wordpress.com/2016/01/12/tidal-and-other-forces/
P.S. Please note this is an unopposed force, unlike the tides we all know because it is tangential, not vertical.
Richard,
my fig was for earthly water flows, wind and cosmic influences (which I have often commented to be MAJOR factors) were nor the intent. Also, there is likely to be much “eddy mixing” with depth of the seas as they store energy to be deposited on the land and polar regions during the next glaciation (soon? few hundred years? Not likely thousands!!) when the “pots” of energy get transfer via winds and clouds from warm seas to colder regions.
Anyone wonder what will happen if and when the tip of SA and the Antarctic continents join and restrict flow around the Antarctic (see my fig above; lower right)? How much sea level drop (e.g.) to make this important in altering the pattern of the southern Pacific?
I think the ocean cill from Greenland through Iceland to Scandinavia is a more likely choke point. A move of only a few meters up or down will change Climate in very unpredictable ways I suspect.
Wondering what JCH would say when Antarctica has grown to touch SA.
At some point, the oceans begin their long slow decent to 100 meters and that water goes to land and poles. When do you suspect the ocean’s energy will be sufficient (stored deep) to be the tipping point to the next massive glacier or has it already begun, JCH?
Any heat engine operates between two reservoirs at different temperatures, and the amount of energy that is converted is proportional to the temperature difference.
That is true for reservoirs that are co-located.
Given the distance between the reservoirs the lapse rate (what drives the convection) may have more effect than a minor temperature change.
If the TOA (255 K) moves up so the lapse rate is the same that would seem to me to have less effect than if the lapse rate increases with the TOA (255 K) height unchanged.
Yep, need a slope against which to work. Elsewise a static system results.
Is that graph of accumulated cyclone energy correct? This one by Dr Ryan Maue has the accumulated energy DECREASING from 1994 onwards. Nothing like the graph shown here.
http://policlimate.com/tropical/global_running_ace.png
Read the title of that graph , you’re looking at NH and global , not N. Atl. Though the drop off is similar , west Pacific storms make the timing of the peak different.
You’re comparing apple to a basket of mixed fruit ;)
>>you’re looking at NH and global , not N. Atl.
Where does it say that? It says: “N Atlantic SST vs ACE. The graph I depicted here is ACE. ie: tropical cyclone, not simply Atlantic hurricane data.
R
Ralfellis,
The subtitle of his post is “Pondering the recent downturn in Atlantic hurricane activity” and it’s also mentioned in the text, but you’re right – his graph doesn’t say it.
However, I read the graph title as N Atlantic SST vs (N Atlantic) ACE, otherwise it would have to say vs global ACE.
http://berkeleyearth.org/wp-content/uploads/2016/01/2015-Hottest-Year-BE-Press-Release-v1.0.pdf
Sorry, didn’t mean to knock this recent posts.
huh?
huh?
Oh right, so the “Earth’s temperature” ( which is NOT an average and I’m too dumb to understand the unstated difference ) is warmer the “1850-1900 average” , which is an average ?!
Looks like you PR missed the memo too.
Now instead of you typical hit an run one liners, can you say how you combing temperature data two physically different media into one figure in a physically meaningful way without hiding behind the complexity of the processing?
ie actually try addressing the criticism rather than avoiding it.
Sorry, That wasn’t meant for you it was for Mosher and it was just a joke. BTW I haven’t the foggiest!
2015 set the record with 99.996% confidence
…
This year exceeded the previous warmest year, 2014, by 0.14 C. As this amount greatly exceeds the margin of error by over 5 standard deviations, giving 2015 an unambiguous claim as the warmest year.
…
2015 was approximately 0.1 degree C hotter than 2014,
…
Relative to the early industrial period of 1850-1900, Earth’s surface
temperature has risen 1.14 C +/- 0.08 C as of 2015. The Earth has warmed at an average rate of 0.08 C/decade since 1900, and 0.17 C/decade since 1970. On top of this, weather variations such as El Niño lead to fluctuations of +/- 0.1 C in typical years and +/- 0.2 C in unusual years.
Well, the announcement is a pretty bold statement.
Just more politicised garbage based on non physical “averages” of land and sea surface temps.
Sorry guys you cannot add/subtract/average temperatures of different physical media. Land , sea and air have massively different heat capacities. It is as meaningless as averaging fahrenheit and celcius temperature readings.
BEST project was of potential interest when it was conceived as taking a fresh attempt at deriving a land temperature record.
Since then the whole presentation has become completely alarmist. The original objective of the project to encompass both warmist and sceptical viewpoints to reach an objective record that everyone would accept has long been dropped.
Sorry we don’t average. You don’t understand the math. Give it up.
Hi Mosh’
Oh right, so the “Earth’s temperature” ( which is NOT an average and I’m too dumb to understand the unstated difference ) is warmer than the “1850-1900 average” , which is an average ?!
Looks like your PR girl missed the memo too.
Now instead of your typical hit an run one liners, can you say how you combing temperature data of two physically different media into one figure in a physically meaningful way without hiding behind the complexity of the processing?
ie actually try addressing the criticism rather than avoiding it.
If you want to average any set of numbers and, in order not to have GIGO, they do need to be of the same ‘types’ and any ‘centre’ of the set has to have some meaning to be useful. Standard set theory, statistics and mathematics
Steven Mosher:
If your criticism has any validity, BE should at least correct the press release when it says:
No fair “dumbing down” your own public statements and then calling everyone else dumb for relying on them.
Steve:
your penchant for equivocation is simply boundless.
Nothing is ever boundless. Some things do get very big or small, that’s all.
yes: his appetite for equivocation is nearly boundless.
What’s the point of this comment?
Next time maybe tweet or email to Judith for week in review.
Politics and policy edition ;)
Don’t see where it’s listed as a ‘projection’ as opposed to an actual observation. Press releases have value.
Possible dumb question:
The post discusses both SST and ACE trends and levels, but I’m unclear which he believes is the relationship. The above quote assume the trend in temperature affects the level of ACE. How would that work?
This discusses material I’m not familiar with. But wouldn’t trends affect trends, and levels affect levels?
Thanks Larry,
Firstly please quote where I discuss “trends” other that to disparage the idea. AFAIAC “trends” are meaningless crap and we’d to a lot better to ban the word from the whole climate discussion.
The correlation analysis is “levels” if you want it in those terms.
The quote does not assume anything. What you are seeing, like the idea I was discussing “trends”, is what you are reading into it. The quote says IF the lower levels of activity continue. It does not even discuss the downward “trend” neither does it say, suggest or imply that the lower activity is “expected” to stay low , get lower still or bounce back up. Since there is total break from the noted correlation in this period I don’t know how you arrive at the idea I “assumed” some linkage here.
Try quoting what I actually wrote, instead of assuming what I assumed based on your own assumptions.
What you are reading into what was actually written is a reflection of how the whole field of climatology has become so polluted with the idea of “trends” over arbitrary periods and the totally spurious assumption that the most likely outcome is that such a trend will continue. Even if I don’t say that you manage to read it into what I actually wrote.
It’s about the third time I’ve had to make the point in comments: the article is not proposing a model for predicting hurricanes ( look into the refs if you want more on that ). What it does show is the there is some strong correlation but the two warmest periods of relatively stable temps ( plateaux ) in the record show a strong drop in ACE.
This is at odds with the simplistic claims that are one of the cornerstone of alarmism that global warming will produce “more frequent and more violent storms”.
Greg.
Emanuel’s study casts doubt on what had been the consensus view of most climate scientists — that in most ocean basins, tropical cyclones are likely to become less frequent as the world warms, but that the storms that do occur are likely to contain stronger winds and heavier rains.
Greg,
Wow. You are quite excited, too much for me. I’ll drop the question.
“Trends and levels” are jargon in my business. I meant, and should have said, “levels and changes”.
JCH,
Thanks for the link to that story. I had forgotten about Emanuel’s paper. He makes a clear and bold prediction. Will be interesting to see follow-up research on this.
Here’s the link to it: http://www.pnas.org/content/110/30/12219.full?sid=8ed88613-d754-4af8-b7dc-590b0b09c40c
Sorry I lost you there Larry. I just prefer that when someone tells me I’m assuming something, that it is me that is assuming it and not them.
I agree that climatology does seen to have inherited a lot of this “trends” and running means baloney from econometrics, where it does not work either. They seem to have failed to notice how badly that field does in prediction of catastrophic change before adopting all their techniques.
The thing is, it is not just “jargon”. There seems to be some crazy mindset that believes a “trend” in a random walk actually means something and that the most likely thing to happen next is for the trend to continue. In fact, in AR1 it is the change that is the random element.
Isn’t it high time we bring this backward science into the 21st century beginning with continuously measuring wind forces using official electronic wind gauges, set up in official grid patterns, as determined by expert ACEologists with supercomputers that run sophisticated programs, using properly applied parameters to adjusted data to correctly interpret the results?
Wagathon,
Is it “high time” to do that? The weather monitoring satellites are aging. The funding for quality control on the surface land atmosphere network is minimal, the number of stations has shrunk.
I suspect if outside experts looked at the GCMs they’d see spaghetti code.
It would be interesting to have an assessment made to determine what funding would be necessary to upgrade the US and global weather monitoring systems (both instrumentation and personnel) to an adequate level. More than they’re going to get, I suspect.
More interesting would be an assessment to determine the funding necessary to prepare America for repeat of likely weather during the next 50 years — no climate change, just likely repeat of past weather by the “100 year” standards. More than we’re likely to spend, I suspect.
But at least these two lists would show us our level of current preparations. They we could dream about upgrades like you suggest for monitoring wind — and the many other upgraded sensors that would tell us much.
We can’t even put money aside to maintain the roadways without government stealing it and hiring more bureaucrats to justify its existence.
“A rapid drop in hurricane energy is noted before the El Chichon and Mt Pinatubo eruptions (figure 5) and is already visible in the SST. In fact, both events were preceded by a higher level of cyclone activity that coincided with a peaks in the 9 y lunar cycle in SST and also coincided with peaks in solar activity. The temporal coincidence of all these factors raises the danger of false attribution.”
The greater danger there is in getting the solar-ACE relationship reversed, and hence also the solar-AMO relationship reversed. Both of those ACE peaks coincide with episodes of weaker solar wind, and an increase in negative North Atlantic Oscillation. Look at the ACE index in the Gleissberg Minimum where the bulk of the negative NAO is through 1885-1895, that’s during the lowest solar. The trough from the 1930’s in ACE coincides with an increase in positive NAO (Hurrell), evidently not strong or long enough positive NAO to cool the AMO well though.
If this solar minimum follows the pattern of the last few, from roughly a year past SC24 sunspot maximum, should see generally much weaker solar wind states, and a sharp increase in negative NAO. That will push ACE back up again as in Gleissberg.
Space age solar wind. Note the very strong conditions in the 1970’s (+NAO cold AMO), and the general decline from the mid 1990’s (-NAO and warm AMO)
http://snag.gy/fjGhc.jpg
Hi Ulric.
I’ve looked at so many wiggly lines like that and know that you can see whatever you want in them. Hand waving arguments about this and that period are equally unconvincing.
I was a little confused about claiming both negative and positive NAO cause the same thing.
I’m not saying there’s nothing in what you are saying but I think you need to do some kind of maths and extract or correlation or something that proves the point.
Greg
greg, you just gave the graph the hand wave in an unconvincing manner. The idea is not to see what you want in it, but to carefully inspect the correlations at the noise level. Try zoom?
In case you had not noticed, the primary error by the author was in assuming that around sunspot maxima is higher solar. When in fact many sunspot cycles have a major low in the solar wind at sunspot maximum.
Greg: “I was a little confused about claiming both negative and positive NAO cause the same thing.”
I did not.
I’m not brushing off what you are proposing. What I suggested you did was to “carefully inspect the correlations at the noise level.” and produce something more convincing than verbal commentary.
Then it was unclear to me what you were suggesting. Another reason we invented maths to describe science. If you have a clear effect at least plot it in a way that makes it obvious.
BTW Ulric, I owe a debt of gratitude. IIRC it was you, commenting on my thread at Talkshop years ago, that identified the period that I had found in SST as the lunar apside.
I got banned from TS by Tattershall before we could finish discussing the article. So a belated thanks for the tip. That has been an amazingly useful piece of information.
“Then it was unclear to me what you were suggesting. Another reason we invented maths to describe science.”
Take your time to understand properly what I write before making comment then. The only maths there is positive and negative NAO.
“What I suggested you did was to “carefully inspect the correlations at the noise level.” and produce something more convincing than verbal commentary.”
I am thoroughly convinced that there was a considerable weakening of the solar wind late 1979 and well into 1980. Take a good look at the graph, if you can manage to see what the wiggly lines are actually doing.
Lunar tidal forcing of SST’s does not make sense to me. Because the dominant ocean modes of ENSO and the AMO are driven primarily by atmospheric circulation variability.
RichardLH | January 12, 2016 at 2:57 pm |
https://climatedatablog.wordpress.com/2016/01/12/tidal-and-other-forces/
Yes, you cannot “lift” the ocean surface much by gravitational force but vast quantities of water can be made to move horizontally.
It should be remembered that this idea of “tidal bulges” is not the way it happens on a planet with large continents but this image of the tide raising forces is illustrative as a starting point. The actual tides form complex patterns as they resonate and reflect around the ocean basins. The phase of the tide at any geographic position in relation to the position of the moon can only determined by observation. It can literally be anything.
The major period that resonates with the surface density and depth of the oceans is the semi-diurnal and diurnal tides. If you compare the density change at the thermocouple you will find the resonant period will be of the order of a year or two. How this resonates will depend upon the form and depth of the ocean basin.
I think that much of what is called El Nino is caused by similarly complex tidal patterns on the thermocline, which, with a much lesser density difference, responds most strongly to periods about 1000 times slower than the density change at the surface.
I have been saying for several years that it is essential to identify the lunar effect before trying to detect solar and other “forcings”
https://climategrog.wordpress.com/2013/03/01/61/
The presence of the 9.1y cycles found in this article and also reported in Muller and Curry in Atlantic and Pacific SST and by Scafetta globally make serious study of the lunar effects and their cause essential to any improvement in understanding climate and its “forcings”.
My take on this is to do with trying to look at this all in a different hemisphere ‘slice’ for the data.
A Pacific + Antarctica hemisphere versa the rest. Ties up the two poles nicely with one heat sink each. Splits ocean into 50% versa 20% + 90%+ land. And the energy transfers NS mostly lie within those two views.
Just another viewpoint that may, or may not, provide information from data.
I suppose that what I am saying is that the data is what it is. Looking more and more closely at the historic values which are not going to change isn’t likely to help much.
How about other, different, viewpoints to ‘look’ at the same data. That has always worked well in other disciplines in the past.
What do you mean : “historic values which are not going to change” ?
You really have not been following climatology recently , have you ? ;)
The data itself does not change. Our methodology to ‘see’ into it does.
New data is added every day. I just wish we could do the same at the other end :-)
“I have been saying for several years that it is essential to identify the lunar effect ”
Well good luck with that on anything other than daily data IMHO. The sample rate of month is too close to lunar for fine resolution IMHO.
Well if it was just monthly, yes it would be mostly filtered out by the cruddy “monthly” averaging. But the whole point is that there is more to lumar variation than twice daily or twice montly tides.
9.1 years seen here is a lunar cycle. Until that is explained it will continue to get falsely attributed to solar and volcanic forcing.
I don’t doubt that there are long term cycles in the data. The Moon is a very strange neighbour.
I would be trying to see what, if ant, there is below as well as above that in frequency.
Well, below I have found what looks like an amplitude modulated 4.5y in trade wind data, but it’s a tentative interpretation
https://climategrog.wordpress.com/wpac850_sqr_chirp/
This has also been reported in papers about tropical atl. and pacific.
The typical figure of QBO is circa 28mo = 9.3y / 4
Longer than about 20y gets difficult to detect because of the length of any reliable data but is suspect that the famous 60y cycle is partly lunar and partly solar.
The following produces beat pattern of about 59y that would match the periodicity found in the article above:
p1=9.1;p2=10.8;
cos(2*pi*x/p1)+cos(2*pi*x/p2)
This explains why naive attempts at fitting simply solar alone have found it works in certain periods then falls apart. This usually leads to unjustifiable cherry-picking of the periods where it seems to work by proponents and equally naive rejection of the whole idea of a solar forcing because it does not show a constant, simplistic correlation.
This was the principal conclusion of my article on spectral analysis of SST.
https://climategrog.wordpress.com/2013/03/01/61/
On Zen and the Art of Climate Analysis
Given all the evidence it would be surprising if there wasn’t a 60 year cycle in the data. Other periodic functions must be there as well. Even Newton decided that the Moon was very complex. Did you know that he observed that Jupiter had an effect on its path?
http://www.sciencedirect.com/science/article/pii/0083665676900179
I am also surprised that I an find nowhere in the literature (refs if not true please) a Gravity Anomaly at Earth’s surface of the combined Sun/Moon field, laterally and vertically. A plot of exactly where the lines between the various centres cross the Earth’s surface, etc. A time series in 4D.
That is the input Power signal after all. Then it might be possible to get some information out of the data.
Global warming alarmism is nothing more than new age high tech pandering.
It isn’t that high tech. The GCMs are just expensive curve tracers. You can draw the same curves by hand with a pen or pencil for 1/10**12 (1 trillionth) the money.
http://www.climatedepot.com/2016/01/13/claim-global-warming-could-cause-humans-to-develop-webbed-feet-cats-eyes-and-gills/
http://i.dailymail.co.uk/i/pix/2016/01/13/00/3012D07E00000578-3396624-image-a-27_1452646761328.jpg
FYI about margin of error on SST perhaps relevant to this discussion
Today I posted a useful note about the margin of error for measurements of SST by NOAA’s Anthony Barnston. It is a comment to their “December El Niño update“. Bold emphasis added.
Wow, that is amazing progress: finally some realistic assessment of uncertainty. And +/-0.3C would cover almost all the variability since the beginning of the 20th c.
Climate grog,
If NOAA can today measure the SST of the Nino3.4 region to 0.3C, their measurement uncertainty of the change during 1950-2010 of the upper 2000m of the global ocean must be substantially larger (larger area, 3 dimensions instead of 2, older technology, sparser coverage).
From memory I recall the estimated temperature gain of the upper 2000m 1950-2010 to be 0.09C — an order of magnitude smaller than uncertainty for current SST in Nino3.4.
Agreed, OHC before 2003 is mugs game. They are quite simply making time series from data that never existed.
Re Fig 1, with such high interannual variability, and given that the ACE database is very much a work in progress, I’m highly skeptical about any attempt to detect trends and patterns in the data.
All climate records are “work in progress”. That is why the past gets colder every year ! “The future is certain, only the past changes.” ;)
I don’t detect or claim to detect trends and I specifically make the point that the long term secular variation is more due to sampling error and speculative adjustments than anything else.
As for patterns, are you saying that the common 60 and 9.1y periodicities that have long been noted in the the surface temp records are coincidentally present in ACE too?
BTW climategrog is Greg Goodman. Since Judy was forced to make everyone login to comment, I come up with my WP account name instead of my name.
Just when you think things are all settled.
http://thames.me.uk/s01680.htm#top
Bottom Ice in the Freshwater Thames!
One of the great scientific facts of my childhood was the understanding that whilst most liquids become denser as they get colder this only applies to water down to a point, and that point is at about 4ºc. Water is at its densest at this temperature and then as it cools further it actually gets less dense.
This strange quirk of nature is probably responsible for the survival of life on earth and certainly for life on land. Together with the fact that ice is less dense than water and therefore floats – it means that even relatively small bodies of water never freeze through to the bottom – and therefore life could survive.
The convection currents caused by water cooling at the surface, becoming denser and falling, cease at 4ºc and even reverse (colder water being forced to the surface where it freezes and insulates the rest).
I write this because I have recently discovered the following:
It is in “Oxfordshire of One Hundred Years Ago” by Eleanor Chance. W E Sherwood writes –
There is another thing which I suspect the Conservancy, by their dredging, may have stopped, but I am not certain, as it is so long since we have had a severe winter, and that is the formation of ‘ground ice’, ice that is that forms on the bottom of the river.
When I spoke to my science master about it he talked about the maximum density of water, and told me that the thing was impossible, but I took him down to the river, and showed him, opposite the barges [ie the College Barges along the left bank at Christchurch Meadow], the bottom all covered in ice.
I think he was annoyed, but at the river for behaving so unaccountably – indecently even, he seemed to think – and not at me. He was so far right that in a lake or in a river of uniform depth the ice cannot so form, but in the Thames in those days there were deep reaches followed by banks of gravel over which the water was shallow.
In times of frost the heavier warmer [ie 4ºc] water sank and remained in the deep parts, and what flowed on was the lighter water at or close to freezing point, and when the crystals formed in this they attached themselves, as forming crystals will, to any solid they could find; in this case to the gravel at the bottom.
This ice rose from time to time in spongy masses, bringing with it some of the gravel, and floated on until it reached the lock. Here it packed, and if the frost continued, formed a thick mass of rough ice which, as more came down extended further and further up stream; and it was on this ice, far more than surface ice, that on three occasions I remember a coach and four was driven from Folly Bridge to Iffley.
I sometimes wonder if people’s blind use of statistics is because it allows them to stop thinking about what this data is and the steps required to get to it so far.
I’ve updated my blog post with where I get the assertion that improving local drainage can significantly effect local temperatures. Dredging = No more Bottom Ice?
And the dates?
And the historic references to Binsey/Thornbury which go back to pagan times or close thereto.
All at the same Thames river height for the last 2000 years or so!
You would think that that change would show up in http://www.gtc.ox.ac.uk/about-gtc/history-and-architecture/the-radcliffe-observatory.html as it is less than a mile away!
So it is my assertion that UHI http://www.smithsonianmag.com/science-nature/city-hotter-countryside-urban-heat-island-science-180951985/?no-ist started back as far as 600AD or so in Oxford!
Two bites.
One when the river was diverted.
And another when it was dredged.
And a whole class, reference, thermometer just yards away!
https://en.wikipedia.org/wiki/Urban_climate
Rural areas have more wet surfaces (in towns, rivers are often covered and water runs off into drains). Evaporation from these wet surfaces produces cooling because heat is absorbed by the process of evaporation. Buildings are heated, and vehicles and air conditioning systems generate heat.
http://www.metoffice.gov.uk/services/climate-services/case-studies/urban-heat-islands
Heat islands exist because the land surface in towns and cities, which is made of materials like Tarmac and stone, absorbs and stores heat. That, coupled with concentrated energy use and less ventilation than in rural areas, creates a heating effect.
Evaporative cooling and evapotranspiration
Though it is termed ‘evaporative cooling’ it is not cooling as such, rather ‘warming less’ (Gill, 2006). Through evaporation, incoming energy is used to convert water into water vapour. Energy is being used to drive the evaporation process rather than being transferred to the sensible heat that we feel, thus air temperatures are lower (Oke, 1987). Where the water is within a plant, on its surfaces or in the soil, the process is termed evapotranspiration. Vegetation is sparser in cities than in the countryside, reducing cooling through evapotranspiration and much of the surface is sealed, reducing cooling through evaporation. This is a primary contributor to the UHI.
http://www.forestry.gov.uk/pdf/FCRN012.pdf/$FILE/FCRN012.pdf
I would also have though that the weir at Wytham or close to would provide a very good sampling point for the land area to the West, almost to the Severn, for both rainfall and water temperature. This before it gets polluted by urban heat later on down the river
I wonder if this area might be a possible area of interest to
http://onlinelibrary.wiley.com/doi/10.1002/wcc.144/abstract
as a potential case study?
As the actual area itself goes back to medieval days or before almost untouched except for farming. It sits just slightly below the city to its East so UHI will have a draft effect rather than heating for most wind directions.
Its local climate is driven almost totally by evaporation requirements. It floods every year. And has done so down recorded history.
““the quiet little hamlet of Woolvercot; the only living creatures visible being some white geese on the green,” wrote William Black of it as he knew it. It was here, according to Holinshed, that King Memphric, who about a thousand years before Christ originally founded Oxford, calling it Caer Memphric, was seized and devoured by wolves in a solitary dingle; hence the name.””
http://thames.me.uk/0TST/t00040.htm
I suppose that this other 3000 year old site may be able to provide as much insight into aspects of Climate on the other side on England.
http://www.peterboroughtoday.co.uk/news/latest-news/bronze-age-dig-in-whittlesey-uncovers-very-rare-3-000-year-glimpse-into-the-past-1-7155145
That makes two 3000 year old sites in the UK!
The Binsey site for the West of England, the Radcliffe and CET.
The Whittlesey site for habitation, food, diet, estimated sea level, etc.
That’s not bad for a small island at the edge of the North East Atlantic.
As a reference to the boundary layer problems with temperature sampling and local drainage and humidity, turbulence.
http://www.met.tamu.edu/class/metr452/models/2001/PBLproject.html
“The lowest layer of the atmosphere is called the troposphere. The troposphere can be divided into two parts: a planetary boundary layer, PBL, extending upward from the surface to a height that ranges anywhere from 100 to 3000 m, and above it, the free atmosphere. The boundary layer is directly influenced by the presence of the Earth’s surface, responding to such forcings as frictional drag, solar heating, and evapotranspiration. Each of these forcings generates turbulence of various-sized eddies, which can be as deep as the boundary layer itself, lying on top of each other. Consider the case of solar heating: solar heating of the ground on a sunny day creates thermals of warmer air that rise over colder air causing vertical mixing and turbulence. Therefore, in any weather prediction model, the PBL must be parameterized as a mechanism for turbulence (Stull, 1988).
A good surface forecast is often critically dependent on accurate estimates of surface fluxes, and in turn, on reasonably accurate soil moisture and temperature estimates.”
https://upload.wikimedia.org/wikipedia/commons/e/eb/The_air_over_Los_Angeles.ogg
“This movie is a combined visualization of the PBL and wind dynamics over the LA basin for a one-month period. Vertical motion of the PBL is represented by the gray “blanket”. The height of the PBL is largely driven by convection associated with the changing surface temperature of the Earth (for example, rising during the day and sinking at night). The colored arrows represent the strength and direction of winds at different altitudes”
““Physical laws and equations of motions, which govern the planetary boundary layer dynamics and microphysics, are strongly non-linear and considerably influenced by properties of the Earth’s surface and evolution of the processes in the free atmosphere. To deal with this complicity, the whole array of turbulence modelling has been proposed. However, they are often not accurate enough to meet practical requests. Significant improvements are expected from application of a large eddy simulation technique to problems related to the PBL.
Perhaps the most important processes, which are critically dependent on the correct representation of the PBL in the atmospheric models (Atmospheric Model Intercomparison Project), are turbulent transport of moisture (evapotranspiration) and pollutants (air pollutants). Clouds in the boundary layer influence trade winds, the hydrological cycle, and energy exchange.”
I seem to remember the Roman’s had fountains to provide a similar, local, cooling effect. Perhaps Port Meadow has kept Oxford cool? Natural air conditioning.
And in defence of my assertion that the two instrument sets, thermometer and satellite see different views. They do. One lives in the PBL an ties to measure that. The other probably sees the layers above 3000m better.
And if I may quietly observe, in the days before radio and satellites, our weather predictions were pretty poor. Am I being asked to believe that we do any better with Global Temperature? The two temperature series need to be bought into cross-calibration to do what the other can’t IMHO.
Richard Linsley Hood @RichardLinsleyH · 4 mins4 minutes ago
http://bit.ly/1U28QHX http://bit.ly/1RrLOwi http://bit.ly/1Omc9rV Climate in Oxford 600-2016
Another factoid, the night wind/
http://bit.ly/1nq1P9z
I am sure that others who have been in hot countries with mountains will know this. The night wind.
On still nights after a hot day things tend to cool off fast. But in my experience in a very strange, though obvious, way.
A river of cold air, less than a meter thick, flows down over the landscape like a broad river flowing onwards. This air can be very cold. The air above can still be quite pleasant even. But the feet! No more sandals. Boots at night.
And that reference thermometer sitting at 2 meters close by?
Well I’m not sure what it sees.
P.S. Boom After Festival 2012.
How should we measure tMin?
Warm air rises. Cold air falls. I think everybody will are with that.
tMax therefore makes sense as a sampling at 2 meters in a shaded place that will closely measure the likely maximum air temperature for the day.
But tMin? Should that also be sampled at 2 meters?
Well the temperature profile is considerable different at night to the day. Cold air falls.
Would it not, therefore, if we are trying to re-purpose the ground instruments into a volume air temperature measuring device, be reasonable to place the tMin sensor closer to the ground? To accurately measure the air volumes above.
https://climatedatablog.wordpress.com/2016/01/17/a-suggested-transit-line-for-uhi/
Measuring the amount of UHI there is in the environment is tricky.
The above transit in Oxford, UK may supply a site to determine is range and outcomes.
Sites A and C are slightly below the town itself in elevation, which sits on a ridge of land running down from the North. They are situated close to the edge of typical winter flooding but otherwise their local climate is driven almost entirely by evaporation requirements.
Site B is in University Parks which, although it is at the same level to the main town, itself is a green and open area. As it is at the same level as the town it should be able to sample the bulk air temperature of that elevation in non-built areas.
The world renowned Radcliffe Observatory with its long and detailed temperature and rainfall records is just below the transit line as shown in green.
It would therefore be able to provide a second, built environment, place to obtain temperature and other readings to provide a second in town sample point, D.
This is, I would have thought, an ideal place to examine experimentally to see what detailed, and potentially back-castable, temperature series in Oxford as any UHI estimated discovered can then be removed from the Climate figures.
Some historic maps of The Thames/Isis river complex around Oxford
https://climatedatablog.wordpress.com/2016/01/17/the-answer-for-the-perch-thames-question/
Prof. Curry…
Are we going to get a post on Hurricane Alex? This seems to be the first time since 1938 an Atlantic hurricane has formed in January. 1938 AMO seems similar, I haven’t been able to find out about the Atlantic Equatorial mode, although that seems to be primarily summer.
https://upload.wikimedia.org/wikipedia/commons/thumb/1/1b/Amo_timeseries_1856-present.svg/672px-Amo_timeseries_1856-present.svg.png
I’m following this on twitter and the tropical listserv. I’ll see if anything materializes that is worth a post.
Alex appears to have formed in very cool waters:
http://icons.wxug.com/data/images/sst_basin/gl_sst_mm.gif
(S)he ( can we get an all androgynous name list? ) appears to have taken advantage of a narrow slot of low shear:
http://tropic.ssec.wisc.edu/real-time/atlantic/winds/wg8midshr.GIF
Also of note, GFS and UKMET have Alex’ remains headed to Greenland and then Eastern Canada. I’m curious as to what amount of snowfall ensues.
AK:
The only SST info I have seen for that region of the Atlantic does not suggest tropical conditions. Have you been able to find up-to-date SST for the area of formation?
Oops. I didn’t type fast enough. Thanks TE.
http://www.ssd.noaa.gov/PS/TROP/DATA/RT/SST/ATL/20.jpg
From NOAA Hurricane ALEX Forecast Discussion
So it appears the proximate cause is not unusual warmth for SST but unusual cold for the upper troposphere? Fascinating!
Yes. I wonder how much ENSO has to do with it, although AFAICT 1938 was a La Niña year. I also wonder about the Atlantic Equatorial mode. And it could just be a very low probability event involving a cold upper air mass.
Here’s the transition ( if this appears ):
http://realearth.ssec.wisc.edu/api/image?products=globalir.50&width=715&height=436&background=terrain&map=¢er=32.698963857891265,-40.74999999999999&zoom=3&timerange=2016-01-10%2018:00:00,2016-01-14%2018:00:00×tep=21600s&animate=true&type=file.gif
Clearly ‘cold core’ to start – part of a trough with cold air cumulus visible behind the surface cold front.
IMO we should look at the relative phase of the 9.1y lunar cycle and SSN cycle.
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That’s a very revealing chart, AK. A fairly steep decline from about 1950 to 1975 which culminated in the cooling scare of the mid-1970’s. Then we launched globe spanning temperature measuring satellites just in time to hit a 25 year upswing ending around 2005. Now we have 10+ years hiatus in the bank and the steep decline begins.
Note the temperatures on the warm side aren’t significantly higher than past peaks.
I suppose it won’t be long until the data underlying this chart is tortured into global warming submission like all the other data.
Of course they’re not, AMO is a detrended series !
Is getting goosed upwards for another 85 years torture?
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Hello wordpress?? Am I logged in yet or are you going to dump my post again?
Looking at fig 2 in the article, it can be noted that 1938 was the low point in the earlier slump ACE that also occurred during a plateau of warm SST.
Normal cyclones don’t like static SST. Maybe cold water ones do.
That is to say, the general correlation of SST and ACE seems to break down during warm ‘hiatus’ periods.
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Please lets use scientifically CORRECT units for ACE. It is stated that ACE is expressed as 10^4 kt^2. Since one is integrating something in TIME, the units for ACE HAS to be kt^2-HOURS. Sometime in the future, scientists will upgrade the 6-hourly reporting to hourly, and future scientists will be confused about comparing their sums with sums done in the 2010s. If one sums kt^2 over 6-hr reporting periods, the correct way to report these results should be sum kt^2 * 6 hours, and the units should be reported as kt^2-hours. My take on this is that for the ACE numbers presented here should be reported as 10^4/6 or 1667 kt^2-hr
ACE should be 60000 kt^2-hours, not 1667. Accidentally divided rather than multiplied by 6
Dear Dr. Curry,
This might have some influence over weather:
Graphs and data of Solar Radio Flux and Sunspot Number through May 2016
Note that the smoothed graphs show that the current Solar Cycle 24 is about 60% less than Solar Cycle 23.
NOAA/SWPC via VE3EN: “SolarHam.com – Monthly Solar Flux and Sunspot Averages + Trend Charts.” Scientific. SolarHam, March 2016. http://www.solarham.net/averages.htm.
Best regards!