A bit of a tiff developed over at Dr. Roger Pielke’s place over disagreements on the recent Texas heatwave being attributed to AGW or to ENSO. Bob Tisdale has something to say about that. Bob writes:
“In one email, Roger referred to my post about how poorly the new NCAR model hindcasts certain temperature indices, including ENSO, and Nelsen-Gammon’s decided to call my discussion about ENSO a red herring. Little does he know, I have observation-based data to back my claims.”
by Bob Tisdale
INTRODUCTION
I can see no basis for John Nielsen-Gammon’s attempt to attribute the record high temperatures in Texas to the hypothesis of Anthropogenic Global Warming. It appears that Nielsen-Gammon, like the Intergovernmental Panel on Climate Change (IPCC), relies on climate models to conclude that most of the rise in Surface Temperatures, globally and regionally, is caused by anthropogenic greenhouse gases. Unfortunately, their reliance on models to support that hypothesis is unfounded. The climate models show little to no skill at hindcasting past global and regional natural variations in Sea Surface Temperature, which, through coupled ocean-atmospheric processes, would have impacts on the temperature and drought in Texas. Since the climate models are incapable of replicating the natural modes of multiyear and multidecadal variability in Sea Surface Temperatures, the models are of little value as tools to determine if the warming could be attributed to manmade or natural causes, and they are of little value as tools to project future climate on global or regional bases.
And based on John Nielsen-Gammon’s comment about El Niño-Southern Oscillation (ENSO), it appears he has overlooked the significant contribution ENSO can make to the multiyear and multidecadal variations in Global Sea Surface Temperature anomalies, which are so obvious during the satellite-era of Sea Surface Temperature observations.
BACKGROUND
Roger Pielke Sr., has published at his blog a series of emails between he and John Nielsen-Gammon. Roger’s post is dated November 10, 2011 and is titled John Nielsen-Gammon and I Continue Our Discission. Pielke Sr.’s initial post on this topic, dated November 4, 2011, is titled NBC Nightly News Regarding The Recent October Snowstorm And A Quote From John Nielsen-Gammon. In it, Pielke Sr. refers to Nielsen-Gammon’s September 9, 2011 blog post at the Houston Chronicle website Chron.com titled Texas Drought and Global Warming. All three posts are worth a read and provide the fuel for this post.
In one of the emails reproduced in his recent post, Roger Pielke Sr. provided Nielsen-Gammon with a link to my November 4, 2011 post An Initial Look At The Hindcasts Of The NCAR CCSM4 Coupled Climate Model. (Please read this post also, if you haven’t done so already. It shows how poorly the recent version of the NCAR CCSM coupled climate model replicates the surface temperatures from 1900 to 2005.) And Nielsen-Gammon’s response to it included:
“When driven by observed oceanic variability, the models do a great job simulating the atmospheric response. With the present drought, it’s not a matter of predicting the oceans and atmosphere. We know the present ocean temperature patterns, so we can estimate their contribution very well from both observations and models. The models’ difficulty in simulating the statistics of ENSO itself is a red herring.”
First, I have no basis from which to dispute Nielsen-Gammon’s opening sentence of, “When driven by observed oceanic variability, the models do a great job simulating the atmospheric response”. I have not investigated how well the models actually perform this function. But that’s neither here nor there. Why? Well, if the hindcast and projected representations of sea surface temperatures created by the models are not realistic, then the atmospheric response to the modeled oceanic variability would also fail to be realistic.
Second, Nielsen-Gammon wrote, “We know the present ocean temperature patterns, so we can estimate their contribution very well from both observations and models.” Nielsen-Gammon’s sentence does not state that the models provide a reasonable representation of ocean variability. So the fact that Nielsen-Gammon can estimate the oceanic contributions from observations AND from models is immaterial. The models are so far from reality, they have little value as climate hindcasting, or projection, or attribution tools, as stated previously.
Also, if you’re new to the subject of climate change, always keep in mind, when you read a climate change post like John Nielsen-Gammon’s, where the author constantly refers to models and model-based studies (in an attempt to add credibility to the post?), that it may not be the same climate model being referred to. Models have strengths and weaknesses, and climate scientists use different models for different studies. Depending on the coupled ocean-atmosphere process being studied, even if one organization’s model is used, model parameters may be set differently, they may be initialized differently, they may use different forcings, etc. So, while two model-based climate studies may use the same model, the model runs used to study the atmospheric response to the Atlantic Multidecadal Oscillation, for example, may not incorporate the same forcings that are used to hindcast past climate and project future climate. In fact, there are model-based studies where observed Sea Surface Temperature data are used to force the climate models.
MORE EXAMPLES OF HOW POORLY CLIMATE MODELS DEPICT SEA SURFACE TEMPERATURE VARIATIONS
In addition to the post linked earlier in which I compared climate model outputs to observed data, I have also illustrated and discussed in detail the differences between the observed sea surface temperature anomalies and those hindcast/projected by climate models in the two posts titled:
Part 1 – Satellite-Era Sea Surface Temperature Versus IPCC Hindcast/Projections
AND:
Part 2 – Satellite-Era Sea Surface Temperature Versus IPCC Hindcast/Projections.
In those posts, I showed the very obvious differences between observed Sea Surface Temperature data and the model mean of the climate models used in the IPCC AR4 on global and ocean-basin bases, during the satellite-era of sea surface temperature measurement, 1982 to present. Here are a few examples:
Figure 1 is a time-series graph of the satellite-based observations of Global Sea Surface Temperatures versus the model mean of the hindcasts/projections made by the climate models used in the IPCC AR4. It shows how poorly the linear trend of the model mean compares to the trend for the measured Global Sea Surface Temperature anomalies. The models overestimate the warming by approximately 50%.
Figure 1
Figure 2 compares the linear trends for the observations and the model mean of the IPCC AR4 hindcasts/projections of Sea Surface Temperatures on a zonal mean basis. That is, it compares, for the period of January 1982 to February 2011, the modeled and observed linear trends, in 5-degree-latitude bands (80S-75S, then 75S-70S, etc., from pole to pole) from the Southern Ocean around Antarctica north through to the Arctic Ocean. It clearly shows that, in the models, the tropics warm faster than at higher latitudes, where in reality, that is clearly not the case. This implies that the models do an extremely poor job of simulating how the oceans distribute warm water from the tropics toward the poles. Extremely poor.
Figure 2
In those two posts, I not only illustrate the failings of the models on a Global basis, but I also illustrate them on an ocean-basin basis: North and South Pacific, East and West Pacific, North and South Atlantic and Indian Ocean. There are no subsets of the models that come close to the observations on a time-series basis and on a zonal-mean basis.
ON ATTRIBUTION
John Nielsen-Gammon notes in his article, after he changed attribution from “greenhouse gases” to “global warming”, that:
The IPCC has not estimated the total century-scale contribution to global warming from anthropogenic greenhouse gases, but has said that the warming since 1950 was probably mostly anthropogenic. So it seems reasonable to estimate that somewhere around two-thirds of the century-scale trend is due to anthropogenic greenhouse gas increases. That is to say, the summer temperatures would have been about
one or one and a half degrees coolerone half to one degree cooler without the increases in CO2 and other greenhouse gases. [John Nielsen-Gammon’s boldface and strikes.]
I cannot see how Nielsen-Gammon can make that claim when the IPCC’s model depictions of sea surface temperature variability over the past 30 years, which are coupled to global and regional variations in temperature and precipitation, differ so greatly from the observations. I truly cannot. The models are so different from observations that they have no value as an attribution tool. None whatsoever.
ON ENSO BEING A RED HERRING
The last sentence in the first quote from John Nielsen-Gammon above reads, “The models’ difficulty in simulating the statistics of ENSO itself is a red herring.” As a reference, Animation 1, is the El Niño-Southern Oscillation (ENSO)-related comparison from my post that Roger Pielke Sr. linked for Nielsen-Gammon (An Initial Look At The Hindcasts Of The NCAR CCSM4 Coupled Climate Model).It shows how poorly the models hindcast the frequency, magnitude, and trend of ENSO events. In that post, I explained why the failure of climate models to reproduce the frequency and magnitude of ENSO events was important. Yet John Nielsen-Gammon characterized my illustrations and discussion as a “red herring”.
Animation 1
Here’s what I wrote, in part, about Animation 1:
The first thing that’s obviously different is that the frequency and magnitude of El Niño and La Niña events of the individual ensemble members do not come close to matching those observed in the instrument temperature record. Should they? Yes. During a given time period, it is the frequency and magnitude of ENSO events that determines how often and how much heat is released by the tropical Pacific into the atmosphere during El Niño events, how much Downward Shortwave Radiation (visible sunlight) is made available to warm “and recharge” the tropical Pacific during La Niña events, and how much heat is transported poleward in the atmosphere and oceans, some of it for secondary release from the oceans during some La Niña events. If the models do not provide a reasonable facsimile of the strength and frequency of El Niño and La Niña events during given epochs, the modelers have no means of reproducing the true causes of the multiyear/multidecade rises and falls of the surface temperature anomalies. The frequency and magnitude of El Niño and La Niña events contribute to the long-term rises and falls in global surface temperature.
My illustrations and discussions of ENSO in that post are not intended to divert anyone’s attention from the actual cause of the rise in global temperatures, which is what I assume John Nielsen-Gammon intended with the “red herring” remark. The frequency and magnitude of ENSO events are the very obvious cause of the rise in Sea Surface Temperatures during the satellite era. And that isn’t a far-fetched hypothesis; that is precisely the tale told by the sea surface temperature data itself. One simply has to divide the data into logical subsets to illustrate it, and it is so obvious once you know it exists that it is hard to believe that it continues to be overlooked by some members of the climate science community.
Recently I started including two illustrations of ENSO’s effect on Sea Surface Temperatures in each of my monthly Sea Surface Temperature anomaly updates. (Example post: October 2011 Sea Surface Temperature (SST) Anomaly Update) Refer to the graphs of the “volcano-adjusted” East Pacific Sea Surface Temperature anomalies and of the Sea Surface Temperature anomalies for the Rest of the World. I’ve reposted them here as Figures 3 and 4, respectively.
Note Regarding Volcano Adjustment: I described the method used to determine the volcano adjustment in the post Sea Surface Temperature Anomalies – East Pacific Versus The Rest Of The World, where I first illustrated these two datasets. The description reads:
To determine the scaling factor for the volcanic aerosol proxy, I used a linear regression software tool (Analyse-it for Excel) with global SST anomalies as the dependent variable and GISS Stratospheric Aerosol Optical Thickness data (ASCII data) as the independent variable. The scaling factor determined was 1.431. This equals a global SST anomaly impact of approximately 0.2 deg C for the 1991 Mount Pinatubo eruption.
Back to the discussion of the volcano-adjusted East Pacific and Rest-of-the-World data: Let’s discuss the East Pacific data first. As you’ll quickly note in Figure 3, based on the linear trend produced by EXCEL, there has been no rise in the Sea Surface anomalies for the volcano-adjusted East Pacific Ocean Sea Surface Temperature anomaly data, pole to pole, or the coordinates of 90S-90N, 180-80W, for about the past 30 years. The El Niño events and La Niña events dominate the year-to-year variations, as one would expect, but the overall trend is slightly negative. The East Pacific Ocean dataset represents about 33% of the surface area of the global oceans, and there hasn’t been a rise in sea surface temperature anomalies there for three decades.
Figure 3
Since we’ve already established that Global Sea Surface Temperature observations have risen during that period (Refer back to the observation-based data in Figure 1), that means the Rest-of-the-World data is responsible for the rise in global Sea Surface Temperature anomalies. But as you’ll note in Figure 4, the volcano-adjusted Sea Surface Temperature anomalies for the Rest of the World (90S-90N, 80W-180) rise in very clear steps, and that those rises are in response to the significant 1986/87/88 and 1997/98 El Niño/La Niña events. (It also appears as though the Sea Surface Temperature anomalies of this dataset are making another upward shift in response to the 2009/10 El Niño and 2010/11 La Niña.) And between those steps, the Rest-of-the World Sea Surface Temperature anomalies remain relatively flat. How flat will be illustrated shortly.
Figure 4
Note: The periods used for the average Rest-Of-The-World Sea Surface Temperature anomalies between the significant El Niño events of 1982/83, 1986/87/88, 1997/98, and 2009/10 are determined as follows. Using the NOAA Oceanic Nino Index(ONI) for the official months of those El Niño events, I shifted (lagged) those El Niño periods by six months to accommodate the lag between NINO3.4 SST anomalies and the response of the Rest-Of-The-World Sea Surface Temperature anomalies, then deleted the Rest-Of-The-World data that corresponds to those significant El Niño events. I then averaged the Rest-Of-The-World SST anomalies between those El Niño-related gaps.
I have in numerous posts discussed, illustrated, and animated the variables associated with the coupled ocean-atmosphere process of El Niño-Southern Oscillation (ENSO) that cause these apparent upward shifts in the Rest-of-the-World Sea Surface Temperature anomalies. My first posts on this were in January 2009. The most recent ones are from the July 2011: ENSO Indices Do Not Represent The Process Of ENSO Or Its Impact On Global Temperature and Supplement To “ENSO Indices Do Not Represent The Process Of ENSO Or Its Impact On Global Temperature”.Those two posts were written at an introductory level for those who aren’t familiar with the process of the El Niño-Southern Oscillation (ENSO). In the initial post, I further illustrated the actual linear trends of the Rest-of-the-World data between the significant ENSO events, reproduced here as Figure 5. They are indeed flat.
Figure 5
And in the supplemental post, I further subdivided the Rest-of-the-World Sea Surface Temperature data into two more subsets. The first to be illustrated, Figure 6, covers the South Atlantic, Indian and West Pacific Oceans. As shown, Sea Surface Temperature anomalies decay between the significant ENSO events, just as one would expect.
Figure 6
And for the North Atlantic, Figure 7, which is impacted by another mode of natural variability called the Atlantic Multidecadal Oscillation (AMO), the linear trends between those significant ENSO events are slightly positive, also as one would expect. And the short-term ENSO-induced upward shifts are plainly visible in Figure 7 and are responsible for a significant portion of the rise in North Atlantic Sea Surface Temperature anomalies over the past 30 years.
Figure 7
CLOSING
This post clearly illustrates that John Nielsen-Gammon failed to consider that climate models prepared for the Intergovernmental Panel on Climate Change (IPCC) AR4 have little to no basis in reality. When one considers the significant differences between the observed Sea Surface Temperature anomaly variations and those hindcast/projected by climate models, the models provide no support for his conclusion that most of the rise in Surface Temperatures, globally and regionally, was caused by anthropogenic greenhouse gases.
This post also clearly illustrated that “The models’ difficulty in simulating the statistics of ENSO itself is”…NOT…“a red herring.” The process of the El Niño-Southern Oscillation was responsible for most of the rise in global sea surface temperature anomalies over the past thirty years.
SOURCES
For the sources of data presented in this post, refer to the linked posts from which the graphs were borrowed.
ABOUT: Bob Tisdale – Climate Observations
P. Solar says: “Your hand waving commentary about Ninos and Ninjas only explains the medium term ups and downs. What you wilfully ignore _in your own graph_ is a steady increase in ocean heat content.”
First, I have already written numerous posts about the increase in OHC, which is something Stephen is well aware of. Second, this post was not about OHC, but surface temperature and ENSO. Third, since Stephen shifted topics to OHC, in his typical discussion of the rise in OHC, he attempts to explain it with a decrease in cloud cover caused by solar, but he fails to provide data to support his conjecture, and when offered data that contradicts his conjecture, he shifts the timespan of the discussion. Fourth, the rise on OHC may appear to be a steady increase on a global basis, but it is not steady when divided into subsets. ENSO, shifts in Sea Level Pressure in the North Atlantic and Pacific basins, and AMO/AMOC are significant contributors to the rise in OHC since the 1970s. Fifth, if your comment about the steady rise pertains to the tropical Pacific OHC graph I linked for Stephen, in addition to the 1995/96 and 1998/99/00/01 La Nina events, one also has to consider the increase in sampling that took place in the 1990s. The TAO Project buoys are the primary source of temperature-at-depth readings in the tropical Pacific during that period, and there was a significant increase in coverage because the buoys were being installed. That would also need to be factored into any consideration of a long-term trend.
http://i52.tinypic.com/23k3zwx.jpg
The animation is from this post:
http://bobtisdale.wordpress.com/2010/12/22/toa-project-sea-air-and-sea-surface-temperature-data/
The Earth has a complex thermostat with inputs and outputs, the leads and lags due to its rather chaotic behaviour, give us pain and headaches as to trying to make sense of it.
The heat input to our little blue ball, in the music of the spheres dance that is our solar system is the sun, there is no other heat. However there is a lot of cold around us.
The sun and our distance from it does vary some what, as also the various output parameters of the sun vary, this tied to our dance around the galaxy gives us enough variables to cause all sorts of climate changes.
That our thermostat tends to keep us at 15C and a 1013 mb is a wonder, that a trace gas in the atmosphere can cause us to run into thermogedon on an oxygen, nitrogen, watery world is fantasy. Thank you Bob and Anthony and Willis and all other real thinking people on this site.
We owe you much for your hard work.
P. Solar: Let me expand on my earlier (November 13, 2011 at 1:29 am) comment. The topics of discussion of this post are John Nielsen-Gammon’s faith in climate models, his conjecture based on them, and his calling my discussion of ENSO in an earlier post a red herring. To counter this I presented how poorly climate models hindcast Sea Surface Temperature and presented the multiyear impacts of ENSO on Sea Surface Temperature. That’s my post in a nutshell. Stephen’s initial and subsequent comments, and the comments of those replying to him, have little to nothing to do with the subjects of this post. Stephen has effectively hijacked this thread. Scroll up through the comments and see how many of them are responses to his comments and not the post. Those who are new here, who want to learn more about the subjects being discussed in my post, are now being distracted, and possibly confused, by Stephen’s introduction of a totally different subject. This is commonplace for him. If I write about the satellite era of Sea Surface Temperatures, for example, he discusses paleoclimatology. Authors understand this will happen, but it doesn’t please us. So if you feel if my reply to him was rude, I was responding to his rudeness.
My “pet theories”, to use your description of my posts, unlike Stephen’s, are based on, and supported by, data of multiple variables. In my numerous posts about the process of ENSO, I have confirmed my understandings with data, including Cloud Amount anomalies, Downward Shortwave Radiation anomalies, Trade Wind strength anomalies, Sea Surface Temperature (Absolute and Anomalies), Sea Level anomalies, Depth-Averaged Temperature anomalies, Warm Water Volume anomalies, Ocean Heat Content anomalies, Precipitation anomalies, Lower Troposphere Temperature anomalies, Land Surface Temperature anomalies. I’ve provided animated maps of most of those, and I’ve animated maps of equatorial Pacific Ocean current strength and direction. I’ve taken the time to do this to support my posts and to help educate readers about the process of ENSO and its multiyear aftereffects
In the future, I will change my tack with Stephen. I will remind him of the topic(s) being discussed in the post, remind him that I do not appreciate his attempt to hijack the thread, and suggest he write a post on the conjecture he wishes to promote since it so interests him.
Regards
Oh dear. I didn’t mean to cause such a kerfuffle. To my mind the comments I made seemed germane to the thread.
There is no evidence that this summer in Texas was any “hotter” than other hot summers of the last century. Rather, the average temperatures were higher simply because the heatwave lasted longer.
Now if climate models could explain how and why these blocking weather patterns develop……?
http://notalotofpeopleknowthat.wordpress.com/2011/10/17/texas-summer-2011how-hot-was-it-really/
“Did you think of that all by yourself ? I’m impressed ;)”
Yup. Haven’t seen it anywhere else.
The relevance to this thread being that if the models don’t have the basic mechanics of the process right then as Bob rightly says they aren’t going to be able to allocate causation correctly for any climate observations that might be affected by ENSO.
Great post as usual Bob.
I am going to throw this information in just for kicks. Since it seems to link the sun to the ocean ossilations.
http://www.jpl.nasa.gov/news/features.cfm?feature=1319
WOW, climate scientists actually looking at REAL data in the written records and finding a posible solar/ocean oscillation connection…. I am amazed NASA allowed this to be published.
A second study:
http://tenaya.ucsd.edu/~dettinge/PACLIM/Yu02.pdf
Modeling again, sigh…
Another interesting tidbit is Frank Lansner, in his Rural Unadjusted Temperature Index (RUTI), noticed “the trend of the inland stations was markedly different from coastal stations and island stations….” This seems to fit what is indicated in the above paper.
http://joannenova.com.au/2011/10/messages-from-the-global-raw-rural-data-warnings-gotchas-and-tree-ring-divergence-explained/
As long as the CAGW crowd keep insisting that the total effect of the sun on the climate is TSI and not other factors and insist that TSI is essentially constant, they can continue to pretend that a 60ppm change in a minor greenhouse gas causes major changes.
The oceans are 70% of the earth’s surface and have orders of magnitude more heat capacity compared to air. That is the elephant in the room and that is why John Nielsen-Gammon is calling ENSO a “Red Herring” To divert attention away from the elephant. To divert research funds away from the study of what causes the ocean oscillations.
It shows how poorly the models hindcast the frequency, magnitude, and trend of ENSO events.
——–
I stared at those graphs for a while and could not see any obvious justification for this statement, I have concluded that just eyeballing these graphs is not an adequate way of analyzing whether the statement is true or not.
Not all of the climate models can produce ENSO-like behavior. So the statement is plausible. But on the other hand failure to reproduce ENSO-like behavior does not render a model ineffective at reproducing other kinds of coarser-grained behavior. So I am finding some of the logic dubious.
“Now if climate models could explain how and why these blocking weather patterns develop……?”
Part of the interest in posts such as this from Bob is that the basic point once accepted leads on to other issues so I hope that Bob doesn’t mind too much if I comment on the above. I think we can accept that the basic post is correct so unless we move on this thread will die.
I’m sure that warm SSTs affect the air pressure distribution above them. At the equator they clearly lead to a more energetic ITCZ as per Willis Eschenbach’s themostat hypothesis. What goes up must come down so the result is bigger and stronger high pressure cells either side of the ITCZ. That leads to more blocking in low latitudes.
At the same time more blocking may be caused in high latitudes by changes above the poles which cause polar high pressure cells to migrate equatorward as per Marcel Leroux’s mobile polar highs.
So, how to link it all to this post of Bob’s ?
Well Bob accurately describes all that goes on in the ENSO process and gets down to a lot of fine detail. It must be possible to get some idea as to how that blocking from oceanic events from below and that blocking from solar events above combine to affect the air flow changes associated with ENSO.
Personally I think it is the differential build of solar energy in the oceans either side of the equator that forces the basic ENSO phenomenon and the surface air flow follows the water whereas I think Bob believes that the changes in air flow drive ENSO.
However once that basic energy imbalance has accumlated sufficiently either side of the equator then the form and timing and intensity of the subsequent ENSO event (whether El Nino or La Nina) will be affected by the net combined influence of the bottom up oceanic influence and the top down solar influence.So to trhat extent the air flow will influence how the ENSO event plays out. The answer to the chicken and egg situation is therfore that although SSTs get the process started there is an influence from above as well (as per Bob’s contention).
THere are therefore three significant components namely that energy imbalance either side of the equator, the effect of that imbalance on the air flow above AND the influence at that time of solar effects at the poles which ultimately constrains how far the SSTs can drive the winds. On that basis we would both be right.
I don’t significantly disagree with any of Bob’s fine work but having satisfied myself that he is correct the most interesting path is to place it in a global context over long timescales. Admittedly the data we most need is currently lacking but there is no harm in setting up a hypothesis and comparing it with new data as it comes in.
I hope Bob will accept my approach as a compliment (and complement) to his established platform of ENSO data and not see it as a challenge to his domination of that arena.
wayne Job is right.
Bob, I have a question for you
Note that I have done a statistical analysis of the results from a number of weather stations all over the world.
In the choice of my sample of weather stations I have tried to maintain a balance according to latitude and the 70/30 water/land distribution. The results are attached for your information.
http://www.letterdash.com/HenryP/henrys-pool-table-on-global-warming
My latest results from Grootfontein in the Namib desert are not yet included in the displayed tables.
If you want details about how each of the black figures in the tables were arrived at,
I will gladly provide you with the file of each figure in the table with the details.
Although there does seem to be some variability here and there, due to a number of differing local factors,
the results of my sample so far show that maxima, means and minima have risen at a ratio 7.5 : 3 : 1 during the past 35 years. So, the increase in maxima far outstrips the rise in minima.
The implication is that mean temperatures have risen globally mainly due them being pushed by increasing maxima.
I think it is reasonable for me to assume that this rise in maxima caused some, if not most, of the rise in the minima as well.
It is my opinion that rising maxima can only be be caused by more (intense)sunshine and/or less clouds.
If it had been the other way around, i.e. rising minima pushing up the mean temperature, I would have to agree that the cause was trapped heat by an increasing level of greenhouse gases.
As it stands, the conclusion from my tables is simply that the increase in temperatures noted over the past 3 or 4 decades, was largely due to natural causes,
and not due to an increase in green house gases. Do you agree?
I am puzzled that most studies on the increase in the temperature on earth, including WUWT, only show the increase in average mean temperatures, or average anomalies (deltaT).
It seems to me there is a concerted effort by the “scientific” community to hide the truth about what is really causing the increase in temperature on earth.
I would like to hear from you what your thoughts are on this or whydo you think maxima and minima are ignored?.
The models treat ENSO as noise and therefore are incorrect if especially ERSSTv3b is true for NINO 3.4. Figure 4 posted by Bob http://i44.tinypic.com/r7jbdf.jpg does back up the possibility that ERSSTv3b is correct and the interpolated hadSST NINO3.4 that is often used instead, not the best representation of ENSO long term behaviour.
ERSSTv3b shows increasing temperatures over the NINO 3.4 region.
http://img94.imageshack.us/img94/963/nino34.png
HadSST shows no trend in temperatures over the NINO 3.4 region.
http://img221.imageshack.us/img221/2348/nino34had.png
La Nina’s are not only responsible for global cloud level decline, as the tropics is only responsible for about 50% of global albedo level trends. There was also a 50% decline in global cloud levels away from the tropics.
http://www.climate4you.com/images/HadCRUT3%20and%20TropicalCloudCoverHIGH-MEDIUM-LOW%20ISCCP.gif
Typo,
There was also a 50% decline in global cloud levels away from the tropics.
Should be ” There was also a 5% decline in global cloud levels away from the tropics.”
Please correct my previous post, this message can then be removed.
It appears that John Nielsen-Gammon does not understand the long term effects of ENSO. Because this is an area of climate science that has not been studied to any degree, it has the “moniker” of not being important, and therefore no cause-effect is established. Therefore, to him, a “Red Herring”.
There is ample literature, such as the above post, concerning precipitation patterns world wide. There is ample literature showing a sun/precipitation relationship. Do we know all the causes of this yet? No we don’t. Is the correlation so strong that this bears further study? Yes it is.
We still don’t know what causes gravity. Yet, there are laws written of the effects that gravity has on objects. That is a somewhat mature science. Climate science is a very infant science. Our ability to measure UV etc is only becoming somewhat certain. Our understanding of the forces that drive the sun, and the forces the sun provides to the earth are really about nill. Lots of hints, no clear cut answers.
The radical changes proposed by GAGW folks are based on conjecture, with very little science behind them. AS has been demonstrated over and over, the models fail. The solution proposed by GAGW folks is to take the mean of the models and project this as something useful. This is ludicrous, and non scientific. You do not take a bunch of outputs that are all wrong, meld them, and think that somehow the mean is right. If you tried this in a stats 101 class the teacher and fellow students would laugh you out of the room.
There should be no fear of the unknown, there should only be an intense desire to isolate the unknown and look for it.
Thankyou for yet another excellent post Bob.
I need your help to clear my head regards La Nina recharging ocean heat content.
As you show in your More Detail On The Multiyear posts, La Nina is accompanied by clear skies allowing more DSR (Downwelling Shortwave Radiation) to warm the water column.
In that post you also present Fig.3
Fig.3
This figure shows DSR anomalies in Wm2 which clearly indicate more DSR during La Nina and less DSR during El Nino.
But as we know, heat content is governed by not only energy in, but also energy out.
In the Fig.3 above, DSR anomalies range from +40 to -40 Wm2 but mostly around +20 to -20 Wm2.
What about energy out? The following link is to the BoM OLR (Outgoing Longwave radiation) values in the 7.5S-7.5N 170E-170W region.
OLR values
As can be seen, the OLR values range from about 270Wm2 during La Nina (no cloud cover) to as low as 170Wm2 during El Nino (cloud cover).
The range is in the order of about 100Wm2 as opposed to the DSR range of 40-80Wm2.
This is what’s causing the confusion in my head. Seems to be more energy out during La Nina
which contradicts the recharge hypothesis.
To add further to my confusion, during El Nino, the trade winds are suppressed. During La Nina trade winds strengthen. I presume these winds play an important part in the evaporation process at the sea surface. If they do, then during La Nina, more energy is transported up and away from the sea surface by these stronger winds, reducing any ‘recharging’ further.
I wish I had the skills to be able to compare DSR anomalies to OLR anomalies during ENSO.
Have I missed that comparison somewhere in your ENSO posts (which I’m going through slowly to improve my knowledge)?
Thank you once again for your invaluable voluntary work. Much appreciated and enjoyed.
Baa Humbug
I think you are making valid points but the answer lies in looking at the global scenario rather than the 7.5S-7.5N 170E-170W region alone. That region’s cloudiness seems to vary inversely with the global changes in cloudiness.
During the period of strong El Ninos in the late 20th century global cloudiness declined and now with a less active sun and less El Ninos relative to La Ninas global cloudiness is increasing again.
This thing is bigger than ENSO but ENSO is a major component as regards the variable supply of ocean heat content to the troposphere.
Ninderthana says:
November 13, 2011 at 12:32 am
“For God’ sake! When will people stop saying that there are no physical models to describe the ENSO phenomenon. There are dozens of possible models that have been proposed and you can read about (the preliminary musings of) mine here”
A computer model consists of code that can be solved for a simulation which is a set of numbers. The code has no cognitive content so it cannot describe anything. The set of numbers has to be interpreted by some researcher as values for the imagined world that the model simulates. The numbers have no cognitive content and are not about anything.
You need physical hypotheses to describe the world.
Matt G: In your comparison of HADISST and ERSST.v3b did you consider the methods used to infill missing data? I believe we’ve discussed this on other threads. As you may be aware, there’s lots of missing source SST data prior to the 1950s in the eastern equatorial Pacific. Did you determine which of the two datasets has the observational data reinserted after the infilling process? HADISST has the data reinserted after infilling, while ERSST.v3b does not. You’ll find this mentioned in papers as the reason the authors selected HADISST over ERSST.v3b.
Ninderthana says:
November 12, 2011 at 6:27 pm
This is very interesting speculation but it remains speculation. It contains no rigorously formulated physical hypotheses that have been reasonably well confirmed and that can be used to explain and predict the phenomena in question.
Baa Humbug, a question back: How would OLR reflect the ENSO discharge/recharge of Ocean Heat Content (0-700 meters), Warm Water Volume, or Depth-Averaged Temperature (the last two 0-300 meters)? All show the same basic discharge and recharge associated with ENSO? Downward Shortwave Radiation penetrates to depth of, what?, 100 meters, while Outgoing Longwave Radiation does not.
Stephen Wilde says:
November 13, 2011 at 4:31 am
“Oh dear. I didn’t mean to cause such a kerfuffle. To my mind the comments I made seemed germane to the thread.”
Mr. Tisdale strikes me as a conservative writer who rarely strays from the tried and true methods and measurements. I believe that if we respect that about him then we get more from his posts. I find his posts to be excellent.
Matt G: What’s the source of your ISCCP Cloud Amount data that appears more up-to-date that at KNMI? Gotta link?
Bob Tisdale says:
November 13, 2011 at 4:04 am
“Stephen has effectively hijacked this thread. Scroll up through the comments and see how many of them are responses to his comments and not the post. Those who are new here, who want to learn more about the subjects being discussed in my post, are now being distracted, and possibly confused, by Stephen’s introduction of a totally different subject. This is commonplace for him. If I write about the satellite era of Sea Surface Temperatures, for example, he discusses paleoclimatology. Authors understand this will happen, but it doesn’t please us. So if you feel if my reply to him was rude, I was responding to his rudeness.”
If Stephen attempts a subject change on your post then he should be banned from that thread. This is not a put down of Stephen. He makes valuable contributions elsewhere.
Hijacking a Bob Tisdale post causes unfathomable harm to those among us who follow Bob Tisdale’s work closely.
Matt G: To add to my earlier discussion of HADISST and ERSST.v3b. There is no peer-reviewed paper for ERSST.v3b. There was one for ERSST.v3, which mostly pertained to the inclusion of the satellite data to the post 1982 period and its influence on the data over its entire term. The satellite-based SST data served as the basis for the EOF and EOT analyses used for infilling. When they deleted the satellite data due to political pressure, it impacted the dataset over the entire term, not just the satellite era, and that has never been addressed in a paper. I’ll stick to HADISST.
Henry P: “I would like to hear from you what your thoughts are on this or whydo you think maxima and minima are ignored?”
Henry, monthly anomaly datasets are easier to work with in many ways. But when you’re dealing with annual maxima and minima, you’re restricted to annual data.
I also seem to remember a paper (or a webpage) a while back (5 maybe 10 years ago) by Hansen that gave the reasons why Global Land Surface Temperature was only presented as anomalies by GISS, but I wouldn’t have any idea which one it was. And I can’t remember anything else about the discussion (since I rarely look at land surface data).
Best of luck with that Pool Table.
Regards
Matt G says: “La Nina’s are not only responsible for global cloud level decline…”
Generally when people discuss cloud amount changes caused by ENSO, they’re discussing the equatorial or tropical Pacific.