Guest Post by Willis Eschenbach
I got to thinking about the effect of thunderstorms on the surface air temperature. So I figured I’d wander once more through the TAO buoy dataset. The data is available here. I swear, every time I perambulate through that data I get surprised, and I learn things, and this was no exception.
I decided to look at the relationship between sea surface temperature (SST), surface air temperature (SAT), and rainfall. Figure 1 is a graph showing all three of those variables from one of the TAO buoys.
Figure 1. Hourly data from the TAO buoy at 0°N, 156°E (in the Pacific warm pool north of the Solomon Islands). This shows both rainy and dry hours. Black line shows a 1:1 slope, where a 1° rise in SST is equalled by a 1° rise in SAT. Both color and size indicate rain amount. N = 9,067 observations
So … just what are we seeing here? And what might I learn from it?
I went into this to see how much thunderstorms affect surface air temperature and sea surface temperature. Now, I was surprised by the shape of this graph. The first thing I concluded is that we’re seeing two different regimes here. One is what is happening during the thunderstorms, and the other is what’s happening during the dry hours.
I also note the well-known SST limitation of just over 30°C. Only 0.4% of the sea surface temperature measurements in the total dataset are over 31°C (N = 62,507).
Next, it’s clear that thunderstorms are temperature limited. To investigate that, I looked at solely the hours which had measurable rain. Figure 2 shows just those records.
Figure 2. Rainy hours only of the hourly data from the TAO buoy at 0°N, 156°E (in the Pacific warm pool north of the Solomon Islands). Black line shows a 1:1 slope, where a 1° rise in SST is equalled by a 1° rise in SAT. Both the color and size indicate rain amount. N = 422 observations
As you can see, the thunderstorms have a clear minimum temperature. They are unable to persist with a temperature of much less than about 29.5°C. It’s also clear that the greater the rain, the greater the depression of the air temperature and the sea surface temperature. And as you’d expect, the depression in air temperature from the thunderstorm is larger than the depression in SST. Air temperatures drop up to maybe 3°C, from 28° or 29° down to 25° to 26°, whereas sea temperatures only drop up to about 1°C, from say 30.5° down to 29.5°C.
Finally, here are the records of only the dry times, the times without an active thunderstorm overhead. Figure 3 shows those hours when no rain is falling.
Figure 3. Dry hours only of the hourly data from the TAO buoy at 0°N, 156°E (in the Pacific warm pool north of the Solomon Islands). Black line shows a 1:1 slope, where a 1° rise in SST is equalled by a 1° rise in SAT. N = 8,645 observations
Note that both the SAT and the SST move in parallel much of the time (black line). I would say that the residual observations in the lower central area represent the colder air and colder ocean temperatures that remain after a thunderstorm when it has stopped raining.
CONCLUSIONS:
• Thunderstorms cause the coldest air temperatures in the record, well below the temperatures when there is no thunderstorm activity.
• Thunderstorms drive air temperatures down by up to 3°C or so, and sea surface temperatures down by up to 1°C or so.
• This ability to drive the surface temperature well below the normal temperature is the sign that the thunderstorms function as a governor, rather than as a feedback.
At least that’s how I interpret the graphs, YMMV of course. Dang TAO data … always turning up new stuff to puzzle my cranium …
My regards to you all,
w.
[snip . . OT . . mod]
Anyone who has spent a lot of time on the ocean, e.g. Windsurfing will tell you the same. You experience a sudden drop in air temperature with the onset of a storm. Sea temperature is more difficult to asses quantatively.
Thnx Willis.
Am I interpreting the last graph correctly, i.e. SSTs seem to be mostly about 1.5DegC warmer than SATs?
Willis: Some of the rain probably evaporates as it falls, perhaps cooling the air the 3 degC and the surface of the ocean (with a much greater heat capacity) much less. The air may remain cooler than the ocean for several/many hours after the rain ends, possibly accounting for the dry hours which lie well below the line in FIgure 3.
Didn’t know the buoys recorded precip. It does tend to back up your thermostat theory.
More interesting finds Willis. Nice digging.
“thunderstorms function as a governor, rather than as a feedback.”
You may or may not be right about this but in order to have any meaningful discussion or for that conclusion to mean anything and be useful you need to define what you mean by both terms.
As I pointed out in your last thread on this, a governor works by feedback (both +ve and -ve) . So when is a governor not a feedback?
You have quite a firm opinion on this and you’re bright fella so I’m inclined to think you may be right but with a clear definition I’m not sure what you may be right about.
I think your governor implies it must control the lower as well a putting an upper bound. I’m not sure I can see how that would happen or where the data demonstrates this.
Perhaps you could expand.
Thanks for the post.
“As you can see, the thunderstorms have a clear minimum temperature. They are unable to persist with a temperature of much less than about 29.5°C.”
Should it be 24,5 degrees C?
The sun heats the sea, and the air is warmed by convection (and conduction) from the sea water.
Thus, the water is in average warmer tha the air. A large portion of the energy from the sun is removed from the water as phase transformation -liquid water turns into water vapour – rises, condenses into clouds, releasing that energy some 1000 m height. The cool(er) water forms droplets and fall back as colder rain into the sea. The air is due to lower heat capacity more cooled than the sea water. And the next day, it all starts again, or seen from above, moves 15 degrees/hour westwards.
“As you can see, the thunderstorms have a clear minimum temperature. ”
Your claim is not supported by your graphs. There’s a huge orange blob in the area where most measurements are and it’s not clear what are relative volumes of events per unit of graph area. Make a histogram and then claim something like that.
“Thunderstorms cause the coldest air temperatures in the record, well below the temperatures when there is no thunderstorm activity.”
I don’t see any such thing on your graphs. Coldest non-storm air temperature on your graph is about 24C, coldest storm temperature is about 24C as well. If you are talking about average, then again get rid of that orange blob and make a histogram.
“Thunderstorms drive air temperatures down by up to 3°C or so, and sea surface temperatures down by up to 1°C or so.”
It’s clear that something like that happens, the underlying physical principle is called evaporation which depends on surface area which is clearly larger during thunderstorm when the sea surface is extended by wind and rain drops have enormous surface area just as they are.
However your numbers are again not substantiated by your graphs. My guess is no significant influence on water temperature and maybe about 2C on air.
“This ability to drive the surface temperature well below the normal temperature is the sign that the thunderstorms function as a governor, rather than as a feedback.”
I wonder where did this come from. I don’t see how any such claim can be derived from your data.
Sorry, a typo:
“Coldest non-storm air temperature on your graph is about 28C, coldest storm temperature is about 28C as well.” should have been 24C for both.
[Fixed. -w.]
Greg,
By no means would I pretend to speak for Willis, but in basic terms I suspect he is referring to a governor in the sense of an engine governor, i.e. a rev limiter. In this sense a governor is not a feedback, it is simply a threshold.
Put another way, when excess atmospheric heat builds in the tropics, thunderstorms are created, which remove the heat by evaporation and convection, etc. When it is cooler nothing happens. Governors in the sense I have for them do not have lower bounds.
It may be informative to redo the rainy hours plot and join the dots. Scatter plots can be useful but throwing away the time information in a time series often loses key information.
Trond A says:
March 28, 2013 at 2:17 am
It’s an SST, I’ve changed the text to clarify that.
Thanks,
w.
Kasuha says:
March 28, 2013 at 2:29 am
Huh? Take a look at Figure 2, where I’ve removed the “huge orange blob”. You want a histogram? Sure:
Guess what. It doesn’t show anything more than Figure 2 shows.
Well, since you needed a histogram to see what was obvious above, I suppose the same could be true now … but no, Kasuha, I’m not going to do that one. If you can’t see how much the storms are cooling the air by looking at the graphs above, you’ll never get it.
Thanks for your guess, Kasuha. However, since you’ve proven that you couldn’t read Figure 2 without an accompanying histogram, I fear that your guess is not of great interest to me.
However, you could consider it this way. Without thunderstorms, the air and sea temperatures generally run in parallel. When one goes up a degree, so does the other one. This is indicated by the black line.
Since during the thunderstorms the air temperatures are up to 3° below the black line, my claim is most assuredly substantiated by the graphs. Note that I was not indicating the AVERAGE as you appear to be doing. I was indicating the RANGE (up to 3°C), which the graph clearly shows.
The claim that thunderstorms act as a governor is derived from a whole host of data, and I have written about it often. This is merely one more piece of evidence for that claim.
Regarding the nature of the evidence, think about whether simple linear negative feedback, the only kind discussed by the IPCC, can push a system below its starting point.
w.
Thunderstorms are also extra shiny white on top and are very good at reflecting sunshine back to cosmos. They usually develop when moist are are warmed quickly by the Sun(IR from the surface).
I would argue that it’s(moist air over sea/equator) a positive feedback increasing temperature quickly and a negative feed when the temperature approaches 30 deg C.
A climate cruise control or thermostat?
Peter says: “Put another way, when excess atmospheric heat builds in the tropics, thunderstorms are created, which remove the heat by evaporation and convection, etc. When it is cooler nothing happens. ”
What you have just described is a feedback, which is why all this needs some clear definitions to be meaningful. Hopefully Willis can provide a clear definition of what he means by governor and feedback. This is about the third article he’s written on this without defining what he means by governor and what he means by “a feedback”.
Greg says:
March 28, 2013 at 2:10 am
Interesting point, thank, Greg. Yeah, I have a post half written on this question.
The IPCC only discusses simple linear feedback .One basic difference between a governor and simple linear feedback is the following:
With simple linear feedback, the size of the feedback is proportional to the size of the input.
With a governor, the size and the sign of the feedback is proportional to the difference between the current value of some system variable (temperature, rpm, etc.) and the desired value for that variable.
There is a second difference;
With simple linear negative feedback, a system can never be driven past its starting point. To do so, the feedback factor would have to be less than -1 … and that is unstable.
With a governor, the system can be driven past its starting point. For example, when thermostat turns the air conditioner on in a house, it stays on until the heat drops past the starting point. To control a lagged system like a house or the climate, where things take time to heat up or cool down, such “overshoot” is necessary.
Now, let’s consider the thunderstorms. They are not a function of the size of the input (forcing). Instead they are a function of the temperature. In addition, they can drive the temperatures down below the starting point. For both of these reasons, I say they are functioning as a governor (e.g. a thermostat), rather than a simple linear feedback.
I will edit the text in the head post to make it clear what kind of feedback I’m discussing.
All the best,
w.
it is all about Latent Heat. Only a difficult concept for climatologists.
Can you plot the hour just after the rain occurred? Doing so would confirm “that the residual observations in the lower central area represent the colder air and colder ocean temperatures that remain after a thunderstorm when it has stopped raining.” — John M Reynolds
All of the excellent articles on this website lead me to the inescapable conclusion that whilst we know a fair bit about the climate of our planet, we still know painfully little or at least enough to know that we can’t make definitive policy decisions on what we do know. The little we know is dangerous in the hands of those who would seek to exploit it. We are in the realm of a religion where interpretation is everything. Is this how science works?, Are you a heretic long before you become a visionary?. Someone needs to explain because I’m paying taxes that the mafia would be proud of.
Frank says:
March 28, 2013 at 12:41 am
That was my speculation. I figure I can quantify it. My schemo fantastico is to find a bunch of isolated hours of rain (no rain in the hours before or after).
Then I can compare the SSTs and the air temps before, during, and after the thunderstorm … all it takes is time. Well, plus then I have to actually do it …
w.
The other thing a thunderstorm cell does, is it scrubs humidity from the air around it, acting as a condenser to aggregate moisture and concentrate it. This changes the heat capacity of the local atmospheric environment in the vicintiy of the cells. This is not so apparent in large mesocale systems but is readily evident on land (at least) when individual cells and super cells go to work.
I was surpised to learn that we have Top-Of-Atmosphere buoys – then read it again ;(
I’ve always maintained (whether right or wrong) that the loss temperature is the mechanism for creating thunderstorms with heat energy converted into electrical energy (lightening) and that lightening is not due to the rather naïve “rubbing together of raindrops” etc.
For example lightening can also occur above volcanoes where the air is cooled as it rises without any rainfall. So this theory would seem at odds with Willis’s thunderstorm controlling mechanism if I have understood him correctly although lightening is a manifestation of dissipating the heat energy in my book.
Governors are simply controllers with a set point and negative feedback. So, if the claim is that this is a governor, perhaps someone will explain what the controlled set point is [u]and[/u] give a physical reason for it. Starting point is not a set point although it might be. I would strongly advise studying basic control theory and terminology, please.
Willis: “With a governor, the system can be driven past its starting point. For example, when thermostat turns the air conditioner on in a house, it stays on until the heat drops past the starting point. To control a lagged system like a house or the climate, where things take time to heat up or cool down, such “overshoot” is necessary.
Now, let’s consider the thunderstorms. They are not a function of the size of the input (forcing). Instead they are a function of the temperature. In addition, they can drive the temperatures down below the starting point. For both of these reasons, I say they are functioning as a governor (e.g. a thermostat), rather than a simple linear feedback.”
Thanks for clarifying. I think the air-con analogy a fairly good one and probably clearer to most people.
Control systems such as air-con and thermostats have hysteresis, ie they tend to lock into one state or the other within a small control range. This primarily done to prevent jitter where the system would constantly be flashing on and off when the control variable (temperature) was at or near the desired value.
Hysteresis is obtained by adding some +ve feedback. This must be bounded by a stronger negative feedback to ensure the system is overall stable. This corresponds to the self-maintaining actions of a storm. As you have explained in previous threads, once they start they reinforce themselves even if the initial conditions are not longer present. Thus they can drop local temperatures below the initial conditions.
For this kind of system to work there needs to be an energy input that works in the opposite direction to the active state of the governor: a simple air-con won’t to anything to make the house warming in winter. In this case it will fail to regulate.
Now obviously the sun is always “on” in tropics, though it is variable due to change in position through the year and there are other heat losses such as evaporation and direct radiation to the sky that are substantial. There is also massive heat loss with persistent ocean currents evacuating heat to higher latitudes.
Now the tropics never freeze even during glacial periods of a ice age. It would be interesting to see whether there is any data showing whether it is still above 29 degC. Were tropical SST still above 25.4 degrees in 1812-1815 ?
But the basic idea of storms as localised air-con seems a sound analogy.
Now as Willis points out the control variable is temperature, it has no response to what climate scientists like to call “forcings”. If there is an additional energy input (eg GHG) or a slight drop in insolation due to volcanoes, solar variation or whatever, the system should be perfectly stable and stay within the same control range. It will just pump more or less heat out of the region as required.
I think this is one of Willis’ key points too. A simple linear negative feedback would settle at a slightly higher value if there was more input and lower if less input energy.
So far I’ve had to use the term ‘locally’ twice but the basic idea holds the road. Tropical air-con governor seems good.
“Were tropical SST still above 29 degrees in 1812-1815 ?”
Oops, that SAT , for SST that would be 25.4 degC.
[Fixed. -w.]
Willis, I don’t see this supported by the graph(s)
It’s also clear that the greater the rain, the greater the depression of the air temperature and the sea surface temperature.
This would require a before and after measurement wouldn’t it?
Otherwise interesting, and thanks again. It looks like the water likes to be 4-5°C warmer than the air for the most rainfall, if water is >29.5°C, assuming I get the unlabeled volume/color scheme at all.
Next question is where does tropical air-con dump its variable heat output required to maintain stable surface temps?
Short answer, mid troposphere. From there it gets radiated into space and convected polewards.
Viewed from a global energy budget perspective such radiation to space is a negative feedback process. Less heat into tropics causes less heat out (other direction, ie negative) , more heat in more heat out to space.
That, I think is the sense in which IPCC regard it a negative feedback. This is what leads to the expectation of a tropical troposphere “hotspot”, the “fingerprint” of AGW.
Sadly, our main suspect was apparently wearing gloves and did not leave any fingerprints 😉
The second destination is higher latitudes / polar regions. There has been a considerable change in Arctic ice cover in the last 35 years (notably in excess of gains down south).
Now that is a whole other field of study and is probably the last bastion of the global warming hypothesis. I won’t open that can of worms here but the link to tropical air-con is interesting.
So in conclusion, I think Willis is correct with his tropical air-con governor as far as tropics are concerned.
On the face of it I don’t see this as being incompatible with that mechanism being a simpler negative feedback on a global scale.
FrankK says:
March 28, 2013 at 4:18 am
I’ve always maintained (whether right or wrong) that the loss temperature is the mechanism for creating thunderstorms with heat energy converted into electrical energy (lightening) and that lightening is not due to the rather naïve “rubbing together of raindrops” etc.
For example lightening can also occur above volcanoes where the air is cooled as it rises without any rainfall. So this theory would seem at odds with Willis’s thunderstorm controlling mechanism if I have understood him correctly although lightening is a manifestation of dissipating the heat energy in my book.
———————————————————————————————–
e.g.
http://www.tumblr.com/tagged/volcano%20lightning
Again, Willis finda a correlation and calls it a conclusion. What great science. This would never pass peer review.
Willis
“This ability to drive the surface temperature well below the normal temperature is the sign that the thunderstorms function as a governor, rather than as a feedback.”
Reads well, but I’ll be damned if I can parse it. The ability of thunderstorms to cool water below the temperature where evaporation triggers the storms indicates something? Quite possibly, but I’m pretty sure I don’t really understand its importance.
Question: My impression is that the Red Sea and Persian Gulf get distinctly warmer than 32C every Summer. Assuming that’s true, have you given any thought as to why thunderstorm moderated Sea Surface Temperature limitation doesn’t seem to work there?
1) Heat from the Sun evaporates the Sea surface.
2) Vapor is forced upward.
3) Vapor cools by giving up heat to space at 5 to 10 miles up.
4) Water falls.
This is a perfect “hot spot” governor!
As we enter a new era of a “quiet Sun”, we will need less of the “hot spot” effects. Could this lead to a overall reduction in rain? Could the “quiet Sun” lead to droughts in -> +-30 – 40 Lat. around the world. Colder doesn’t necessarily imply wetter: it implies higher relative humidity easier.
Willis
This all seems really interesting – loads of data. Just a couple of questions:
1) Would it be worth separating night time from day time temperatures. I knows it’s the tropics but would you not expect two different regimes to exist. Might explain why you get a larger variation in SAT over short SST interval in your last plot.
2) The other point, does your study assume that thunderstorms form “in-situ”?
Brad in fairness he does sign off with a caveat – you should read the full article.
“thunderstorms function as a governor, rather than as a feedback.”
and from Greg goodman”:
“Viewed from a global energy budget perspective such radiation to space is a negative feedback process. Less heat into tropics causes less heat out (other direction, ie negative) , more heat in more heat out to space. That, I think is the sense in which IPCC regard it a negative feedback. This is what leads to the expectation of a tropical troposphere “hotspot”, the “fingerprint” of AGW. Sadly, our main suspect was apparently wearing gloves and did not leave any fingerprints.”
Is it possible that the number of thunderstorms and area of the thunderstorm belt can change (to dump anothroprogenic warming). The so called hot spot does not need to exist(govenor controlled), Maybe the satellites pick up lightening activity and that could act as a marker for frequency and area. The data set in any case would need to go back to the 70s, which it doesn’t.
Again, excellent science Willis, you are a genius.
@Willis
Can you recolor figure 3 as a function of (time – time of last measurable rain) with orange being the high color and a rainbow for shorter times? That should make the comma tail stand out as depression due to rain.
Brad says:
March 28, 2013 at 5:44 am
Again, Willis finda a correlation and calls it a conclusion. What great science. This would never pass peer review.
________________________
Brad, Willis stated the obvious, but used a bit of data to illustrate his point. Many of your “peer reviewed” papers get nowhere near reality, yet are used by the greedy and powerful to shape (and rob) our world.
If you think what he says is wrong- here’s your chance- prove him wrong!
Willis
Insightful.
1) Time of Day
You previously showed a repetitive cloud cycle building up in the afternoon in the tropics.
Is there a corresponding time of day dependent variation in thunderstorms?
2) Daily vs cyclonic
Is there a distinction between daily thunderstorms (small) and
cyclonic thunderstorms (large)?
While preparing an EIS for Rabaul, I noticed that cyclones are rare within +/- 7 degrees and very rare +/- 4 degrees of the equator. (Solomon Islands appears to range from ~6.4 N to 10.5 S?)
Thus there may be a very strong latitudinal variation in strong thunderstorms from occasional cyclonic activity as a function of the distance from the equator due to the Hadley cells.
Happy hunting.
I often wonder about the fact that evaporating water is an endothermic process, which is unusual in nature, and how this affects the climate in general. Of course that is why we sweat, the process cools our bodies. If the atmosphere holds more water at higher temperatures, then how is it affected by the increased endothermic effect of evaporation? How is this factored in to climate models? And where do thunderstorms, which are endothermic, fit in?
‘Blood, sweat and tears’ in human endeavour could translate to ‘solar, sweat, and clouds’ in the ‘climate’.
Willis, perhaps you have found the signature of rain. I note the lower hook (Fig 3) persists in the non-rain hours. Based on your hypothesis, wouldn’t that suggest sometimes there is rain during those non-rain hours?
Willis Eschenbach says: “With simple linear negative feedback, a system can never be driven past its starting point. To do so, the feedback factor would have to be less than -1 … and that is unstable.”
Well it’s a negative feedback that ain’t ‘simple’! When you introduce a LAG in a negative feedback it can indeed drive past it’s starting point. Just the kinetics of the convection alone represent a lag in the feedback by intuitive examination – suddenly stop the heat and moisture differences that initiated the convection in the first place and it does not suddenly stop anymore than rain drops stop on their way down.
Brad says: “Again, Willis finda a correlation and calls it a conclusion. What great science. This would never pass peer review.”
No, Willis is making conclusions on his observations of the data. Such is the food of new theories but, in this case, REAL food from REALITY – not ‘junk food’ spewed from incomplete and maybe even intentionally biased climate computer models.
I’m not surprised at what you are observing. The rates of the processes of evaporation and condensation are controlling the rates of energy transfer between the ocean and the atmosphere. Also, I think these rates are controlling the global uniformity of atmospheric concentrations of CO2. CO2 is not controlling these rates.
Steve Keohane
This would require a before and after measurement wouldn’t it?
In truth you’d need wind spead as well, even if slight, it can reduce vapour pressure thus increase evaporation which in turn lowers atmospheric temperatures, furthermore, it reduces the insulating properties of warmer air at the surface all of which affects SST. But at some point you have to look at the data, and without all this additional analyses, you must draw what seem like reasonable conclusions.
The case for thunderstorms (if forming in-situ) occurring within a small SST range is borne out by the data – it’s not conclusive proof but it is suggested and seems a reasonable conclusion. The other points about the effects of thunderstorms are also there in the data. If you have other data or studies to contradict these then present them.
What you are asking for is a comprehensive study that would require a dedicated research team. Beyond the scope of what is being attempted here.
Willis:
The TS is acting as a “super radiator” putting a huge burst of IR out into space. We know the number of TS’s, we know relative size! Can we start making a estimate of energy dissipation away form good old Earth? Certainly the cold water in the oceans is part of that moderating effect…making the problem “difficult” as you have a bifurcated balance. I.e., one part that is VERY immediate, and one part that has a “lag time”. (Could be days, could be years).
Just some toughts.
Max
Brad:
Your post at March 28, 2013 at 5:44 am says in total
I strongly suggest that you try to read the article by Willis and his subsequent comments in this thread because the kindest understanding of your post is that you have not read what Willis wrote.
Willis has a hypothesis which he has repeatedly explained, and he continues to investigate available data to determine whether it falsifies his hypothesis. His above article is yet another of his investigations of available data. To date he has failed to find any data which falsifies his hypothesis and has determined that much data supports it. His above article reports yet more supporting information.
Please note that Willis does not merely throw out his studies but interacts with proper disputations. For example, in this thread he yet again repeatedly attempts to explain the difference between what he calls a ‘governor’ and simple linear feedback for those who fail to understand: i.e. linear feedback is a response to any change such as to reduce the change but a ‘governor’ actively opposes any change such as to overwhelm it.
It seems you fail to understand that WUWT is science blog and not some propaganda blog such SkS or RC. Were you able to cite information which refutes his hypothesis or if you were able to refute his interpretation(s) of the data then I am sure Willis would be grateful, but comments such as yours are only a waste of space in the thread.
I have bothered to write this response to your post in hope that this response will dissuade other anonymous troll from wasting space in the thread as you have.
Richard
Willis, there is another factor involved in the charts and the change in temperatures. Have you ever noticed when you boil water, there is what appears to be a first boil or bubbling before the water actually boils. These are the gasses dissolved in the water escaping. All gasses in water act as a liquid until their triple point is reached. You can demonstrate this by a simple experiment. Take a beaker of water, put a thermometer in it and place in the sunlight. As the temperature reaches approximately 29 C, bubbles will form on the sides of the beaker. They will continue to form until the temperature reaches approximately 30.5 C. Carbon dioxide is one of those gases, It’s triple point where it can no longer remain a liquid is 30.3 C. Your charts show this transition point. A chemistry lab test for carbon dioxide is to bubble it through a solution of calcium hydroxide. The solution will turn cloudy as calcium carbonate is formed. If you will check your chemistry book, you will find that this reaction is endothermic and removes a significant amount of heat from the water.
Willis,
It has been claimed that less ice coverage in the Arctic causes both colder temperatures (by blocking, shifting of the jetstream) and more snow (by increased humidty leading to more precipitation). I reviewed the Arctic sea cover data for each of the sub-regions and saw that the Greenland sea area did have an historical lower ice coverage during the main winter time period, though the rest did not (again, regional not global). The precipitation, though …
Perhaps you have the data, perhaps not. Your correlation here is interesting. I wonder:
what this data would say about the Arctic seas:
1) what is the correlation between SST, open water and air temperatures, and
2) what is the correlation between these three and precipitation, in particular snow?
Willis,
Good write-up and quite plausible. Also, it appears most of the complaints are primarily semantic. There is a huge instrumentation and control system industry. It has a long history of theory and practice with specific terminology. For instance, your term ‘governor’ is typically used to hold a machine near a fixed operating speed. A device that keeps a machine from over-speeding would typically be called a ‘limiter’. Both provide a negative feedback control of the machine but with somewhat different operating curves. The governor’s negative feedback is usually linear while the limiter would obviously be non-linear.
How should you deal with this minor semantic problem? Just make a small statement near the start of an article that you might be taking liberties with technical terminology.
What seems obvious is that the IPCC already knows about this concept, but in order to preserve their political agenda, prefers to ignore it. Worse yet, they rely on an unproven mechanism and harp on it ad nauseum.
Thanks, Willis, for these exceptionally thought-provoking posts regarding storms, and for helping to drive a stake into the egotistical and nefarious “science” the IPCC practices. Come to think of it, “science” based on subterfuge isn’t science at all-they’re simply masquerading as such.
cd says:March 28, 2013 at 7:03 am
Steve Keohane
[…]
What you are asking for is a comprehensive study that would require a dedicated research team. Beyond the scope of what is being attempted here.
No, I was just wondering how Willis came to the conclusion he did, based on what is presented. Where is the temperatureΔ vs. rain volumeΔ derived? Intuitively they are related, just don’t see the data.
It would be interesting to know what surface barometric pressure is while all this is going on. Low pressure cells reduce temperature without changing the energy balance – there is no net loss of energy to space when a pressure wave ripples through a region.
Willis’ post is a simplified version of Lindzen’s adaptive iris hypothesis concerning self regulation. And there is an aspect beyond simple radiative cooling of the latent heat released into the upper troposphere as OLR with the condensation of precipitation. Condensation lowers humidity, which is why UTrH is not constant as the IPCC and the GCMs say, but rather appears to decline with warming as shown both by reanalyzed radiosonde and now satellite data. Which explains why the prophesied tropical upper troposphere hot spot does not exist. Which means the water vapor feedback is too high, so the GCMs are oversensitivity. Which is now being shown by other means.
Goes back to the undeniable fact that GCMs don’t model clouds and precipitation well, because much of the phenomenon (Tstorms being a good example) exists solely inside a grid cell.
In the literature, superparameterizations for clouds increased precipitation, resulted in declining UTrH with warming from CO2 forcing, and lowered sensitivity to about 1.5
The complete narrative is there in observational data plus GCM experiments, yet is being steadfastly ignored by AR5SOD. The climate chapter in my book The Arts Of Truth covers some of this prior to the AR5 leak.
An interesting prediction of this world view is that even in extreme cases of climate variability, the average tropical SST should not vary by more than ~1-1.5C, i.e. the range of temperatures recorded for local thunderstorm onset. The prediction then would be that the contrast in SST for the tropics between now and the last glacial maximum should be a similar small value. I seem to recall that SST proxies suggest that the difference is ~2C, but I can’t immediately put my hands on such a study. This might be a useful direction for further research, no?
Brad says: March 28, 2013 at 5:44 am
“…Again, Willis finda a correlation and calls it a conclusion. What great science. This would never pass peer review….”
Here Brad, lemme fix that for ya:
“The supposed 97% of climate scientists” found a correlation and called it a conclusion. What great science. That should never have passed peer review.
Steve Keohane
I do see what you mean but you need to isolate each event for each individual time series. This would take quite a bit of time.
I still think night vs day would be a useful demarcation.
Steve Keohane says:
March 28, 2013 at 5:10 am
Steve, thanks for the question. Amount of rain is shown on the graph by the size of the bubble. Now, in Figure 2, are the big bubbles in general nearer to or further from the black line than the small bubbles?
Since the small ones are (by and large) up near the black line, and the large ones are (again by and large) lower down, this means that the greater the rain, the greater the depression of the air temperature.
w.
Brad says:
March 28, 2013 at 5:44 am
Jeez, Brad, get a grip. I look at things, and I draw conclusions. It’s called a “preliminary analysis”, and no, it wouldn’t pass peer review because IT’S NOT SUPPOSED TO. It’s supposed to be what it is, an interesting analysis of things that neither you nor I knew about yesterday. New research, in other words, not a finished, polished, ready-to-publish work.
I do notice, however, that you don’t find that any of my conclusions are incorrect. You just want to hassle me. As you say, that’s “great science”, Brad, no actual content at all to your post, just venom …
Let me invite you to be a jerkwagon somewhere else. Come back when you can either
1) actually find an error in my work, or
2) find something interesting to discuss in the topic.
(I give you this advice as a friend, because your standing on the sidelines and trying to urinate upwind onto the participants is just getting you wet, not us … and worse yet, you might not have realized it but doing that reveals the size of your johnson and people are starting to laugh.)
w.
Hoser says:
March 28, 2013 at 6:38 am
Hoser, I’ve investigated that further. It’s mostly from residual cooling from the thunderstorms, within a couple of hours of the rain.
w.
Thanks Willis I appreciate your efforts to describe what I’ve observed sailing the tropics for 15 years. What you have illustrated is quite notable in Atoll lagoons where the water temp is considerably higher than outside. Someone also asked about data during evening hours. Any passage maker knows that at 0 dark 30 the worst thunderstorms/squalls occur. I put it to radiative cooling in the upper atmosphere. The tops of the daily buildups cool, overturn, grow, and the result is a very nasty Cb. Another chap commented on Tropical Cyclones not occurring between 6.5 N and the equator, relating I’m sure to the decline in coriolis. The coordinates are not true. This year alone at least 2 tropical depressions occurred near 3.5N in the longitude area described. Yachties who think they are safe within 5 degrees are just lucky.
Many others stated this but you have the desire and ability to take available data and use it to explain things some of us see everyday; thanks for that.
As you noted in a previous post, not only are T-storms Gaia’s tower heat sinks convectionally speaking, they all convey cold down via actual cold air moving downward, to the surface.
The term “limiter” mentioned by GaryW is used in engineering. I agree. There are mechanisms that are designed to “limit” overspeed, overtemp, overpressure, overcurrent, etc.
“Governor” and “feedback” note a wider context. Also, the term “governor” is often used instead of the term “overspeed limiter” for the same reason that language is often less precise than for many people compared to professional engineers.
The “global heat engine” is a physical reality that a bright 10 year old can easily witness on a daily basis. Every morning the area of the Earth that is exposed to the Sun becomes rapidly overheated, with some thermal lag, about an hour. The same thing occurs when you switch on a “lavalamp” with a lag time of about a minute. It takes longer to reach “dynamic equilibrium” but the same physics occurs.
The Earth is constantly and continuously trying to reach as cold a temperature as possible, and biology is constantly evolving to sequester carbon for itself.
Willis is a talented observer, with the ability to sift out various confirmations of what has been known for many decades, and can be found in many old meteorology texts.
I think most people intuitively can see that the “warming physics” over decades can not possibly go “unbalanced” or “tip” into catastrophe. This is because we see hundreds of watts per square meter warming every single day, and the Earth compensates very rapidly.
The catastrophe promoters are also easily dismissed and I hope ignored, just like the UFO promoters, but we must remain ever vigilant to the political Stalinists and Lysenkoists.
Willis, you say “thunderstorm” but most everything else refers simply to “rain”. Is there a critical distinction here, or did you just use “thunderstorm” to mean “rain”? (As a landlubber, I don’t know much about the sea, so for all I know rain at sea is always a thunderstorm.)
I used to think that rain cooled where I live, but have since become convinced that this effect is often/usually because rain in these here parts is caused by a cold front moving through. It was the cooling air that caused the rain, not vice-versa. I can’t tell if your analysis distinguishes between cooling caused by evaporation (and higher clouds, for example thunderheads), cooling caused by the shade of cloud cover on a sunny day, and cooling due to precipitation.
Always enjoy your posts Willis.
That ‘zone’ at 30,29 (with or without thunderstorms) is pretty much why models are not doing too well. No limits in tha models ya know. 30,32,34,36 … it’s all there when you force the model. For everything else … there’s reality
You know Willis, by taking the climate elements bit by bit, you are turning up; beautiful stuff, stuff that sticks out at you and leaves little room for alternative explanation. The more of your analyses I read, the more I’ve come to believe a detailed and complete science of climate is knowable. Integrating it all into a whole one day, perhaps is the tough part. If it can ever be done, it will because of studies like yours. Great stuff. Isn’t there an institution out there that sees this and would honor themselves by granting you a PhD and professorship?
A personal observation about temperatures and thunderstorms in the tropics (Singapore).
There is often a perceptible drop in temperature about 30 seconds before it rains. This drop in temperature is a sure sign it will rain.
I believe the drop in temperature is due to the rain in a tropical storm being associated with a convective downdraft that brings cooler upper air to the surface.
Which makes me think, the ‘overshoot cooling’ is mostly just redistribution of troposphere air, and has little effect on the heat gain/loss of the climate (excepting, increased ocean evaporation from the cooler surface air and latent heat transport generally).
Otherwise, interesting as always.
Philip Bradley says: March 28, 2013 at 4:49 pm
“..A personal observation about temperatures and thunderstorms in the tropics (Singapore)…
Nicely summarized post on the Little Ice Age, Philip! Interesting.
http://aerosolsandclimate.wordpress.com/
.
Philip Bradley says: March 28, 2013 at 4:49 pm … re LIA posting: (sorry if OT)
Complete Miller etal LIA paper is here http://www.leif.org/EOS/2011GL050168.pdf
Fig 2 is an interesting illustration … interesting points … note the low and increase of Solar Irradiance (A) coincides with the peak and gradual exit from the LIA. … and note the 1st aerosol peak (B) precedes ‘the dying peak’ (C) while the second one follows ‘the dying peak’…?
markx, I started that blog in order to bridge the gap between the language used in scientific papers and the knowledge assumed, and what a general audience can understand. A particularly large gap IMO, with aerosols and climate. Unfortunately, I got distracted by other things, and didn’t keep it up.
Philip
It seems you got it one:
http://cimss.ssec.wisc.edu/wxwise/class/thndstr.html
I have to say I never noticed this in temperate zones – although I do generally know when it is about to happen. Funny, perhaps its imperceptible but there all the same. The build up to thunderstorms are amazing, the amazing skyscapes, the calm and darkness just before the storm.
Willis, you’ll see it all when you take small subsections over time and “connect the dots” through time in your charts. You will be able to see the dynamics much like Spencer did with his “squiggles” that provided the first true evidence of “negative feedback”, though I agree in his analysis and yours is the incorrect term. I haven’t seen the resolution in time, but I would like to take a look at it. Please provide a link or just email me the data.
I should be able to pull your data into a format with which I could write a thunderstorm detection algorithm, and then you could page through charts of these events and see what is truly interesting. I’m thinking we could set detection criteria, then analyze the attack, amplitude, decay, duration, and other important aspects of whatever data you have available, and relate those things to the variables that were present during onset. Then once we see that detection works, post these storm results against whatever initiation threshold triggers you see fit. I think it will show that the 1:1 ratio, while correct on average, has underlying features. I think these features will change during the day based on the conditions during onset, factors such as the level of overcast, humidity, temperature, or just W/m^2. When we see these events unfold over time with the dots connected, and play them like a movie, we will see what is filling in the area under the straight line, and how those slopes interplay with the conditions. We will laugh at how we were unprepared for how simple it was, how such events are absolutely outside the realm of classical comatology, and you will write another amazing article that advances the science.
I’ve recorded data at very high rates for many days at a time, (orders of magnitude higher than required by a storm) and pulled that into excel in small sections (50,000 lines at a time, for example, if you’re using ancient excel like me), run my waveform analysis subs on it and learned amazing things in a manufacturing environment – things we never dreamed were happening. But they were. I was able to write code to capture every event of interest, ignore all others and see how those events related to other factors. And write other subs that even highlighted those weird detected features on charts and added text describing events so others could see when significant events occurred, and why.
Recently I did an analysis in Excel that is so mind blowing even I can’t describe it in under 2 hours. One of the outputs is an AutoCAD script file that creates a drawing of an entire assembly of parts, showing the phenomena in question. You input a few factors about a few automatic transmission parts and their relative eccentricities, and it calculates how 12 different parts engaged, and outputs a 3D drawing. Then I did 300,000,000 iterations varying 2 other variables to determine frequency of an particular event of concern. Flagged all of the combinations that looked troublesome. Then we manually outputted the drawings for the ones that seemed problematic, and proposed redesigns things to avoid those events.
Working on something like this seems infinitely more important. YOU are on the verge of describing how these important climatic factors interact. I want to be part of this. Please email me. Thanks, Mike S.
Michael D Smith says:
March 28, 2013 at 9:15 pm
Mike, thanks for the comments. As I mentioned above, the data is here. I encourage you to do any type of analyses you wish with it.
My other posts on the TAO dataset are:
A Tropical Oddity
Cloud Radiation Forcing in the TAO Dataset
The Tao That Can Be Spoken
TAO/TRITON Take Two
The TAO of El Nino
w.
One should remember that while warm air rises in the center of a convection cell, cold air from the stratosphere is descending around the perimeter and this plays an important part in the
SAT cooling.
cd says:
March 28, 2013 at 5:53 pm
Philip
It seems you got it one:
http://cimss.ssec.wisc.edu/wxwise/class/thndstr.html
Thanks for the link. It helps explain how thunderstorms can persist after sunset when there is no solar heating. A continuos supply of moist air drives the thunderstorm process into the night time. As I have previously noted, close to the equator (within 100km – Singapore, Riau Islands), thunderstorms occur at all hours of the day and night with no noticeable afternoon peak.
It would appear that thunderstorms are driven primarily by humidity close to the equator and solar heating further away from the equator, eg in the region of the Solomon Islands.
I’d like to ask once again; have I interpreted these graphs correctly, i.e. SSTs are always warmer than SATs
Baa Humbug says:
March 29, 2013 at 1:12 am
“I’d like to ask once again; have I interpreted these graphs correctly, i.e. SSTs are always warmer than SATs”
That is definately true in the Western Pacific around Samoa. That is the driving force for the formation of thunder clouds. Evaporation makes the air lighter. The lighter air strives to maintain a wet adiabatic laps rate and rapidly rises in the center of the cloud like a flue. Think about the terminal velocity of golf ball size hail. That updraft air is constantly being replaced by cold downdrafts on the outsides of the thundercloud. As you move toward the poles where much less energy is being absord from the sun, SATs become warmer than SSTs and you don’t have thunderclouds. That should give you an idea of how this “temperature control” mechanism works.
Willis Eschenbach says:March 28, 2013 at 10:07 am
Steve Keohane says:March 28, 2013 at 5:10 am
Willis, I don’t see this supported by the graph(s)
It’s also clear that the greater the rain, the greater the depression of the air temperature and the sea surface temperature.
[…]
Since the small ones are (by and large) up near the black line, and the large ones are (again by and large) lower down, this means that the greater the rain, the greater the depression of the air temperature.
w.
Thanks for your response Willis. Sorry to be so pig-headed, but while I agree with everything you say, I can’t believe the graph shows the depression of air temperature. I could say it shows the average temperature. I could say it indicates the average air temperature is proportionately cooler during heavier rain. I don’t see how it supports a change in temperature from prior to and after it rained.
Brad says:
March 28, 2013 at 5:44 am
Again, Willis finda a correlation and calls it a conclusion. What great science. This would never pass peer review.
—————————
First, I read no conclusion ….. only theory with supporting data.
Honestly Brad, What does passing peer review have to do with anything? Since climategate I generally ignore it when someone says, “Here’s proof I’m correct cause it’s peer reviewed.”
Doesn’t passing peer review mean very little and depend entirely on the submitter and reviewer?
At least that’s what I read in the climategate emails, didn’t you?
This is real science. Here’s Willis’ data, his process and his reasoning in front of you. Try to get Mikey and the Team to do this even with a FOIA demand. Cold theory laid bare for you to push forward or destroy. Your choice.
Here’s your chance to review real science instead of just repeating talking points.
Now, prove Willis’ science wrong.
thanks w.
cn
I believe the non-rain part of the steeper part of your fork is “close to rain”. It is the hours when there are clouds before and after rain. The flatter part of fork are sunny hours. The only assumption needed is that air warms up faster than water?
I’d like to ask once again; have I interpreted these graphs correctly, i.e. SSTs are always warmer than SATs
The graphs do show that on average this is true throughout the day for this location. I wouldn’t expect this to be the case outside the afternoon thunderstorm/monsoon zone. Where I live in a mediteranean climate (no afternoon thunderstorms) summer afternoon air temperatures exceed SSTs by a large amount.
And globally, average SSTs are about 1.5C warmer than surface air temperatures. And as fhhaynie notes, this is an important characteristic of the Earth’s climate.
Hi Willis: Good stuff, both your scientific observations and your life essays. In your Figure 3 you attribute the goat-beard hanging from the 1:1 line as cooling after a rain. How about filtering the data to remove measurements 2, 5, 10 hours after a rain event. If it is rain induced cooling you might expect to see the goat-beard progressively trimmed with increasing time after a rain. If the goat-beard persists during intervals with no recent rain events it could be attributed to gust-fronts/downdrafts distal to the rain event. You might also expect SST not to lower as much. Cheers, Mark
Mark Beeunas says:
March 29, 2013 at 10:25 pm
I did that, Mark, and found exactly what you predicted. When I removed the data from one, two, and three hours after a rain, the “goat beard” got progressively shorter. So the beard is from the cooling after the rain. It was a pain to do it, it was late, and I didn’t snap screenshots, but that’s the outcome.
All the best,
w.
Steve Keohane says:
March 29, 2013 at 4:51 am
Not sure I can help with that, Steve. It is clear that most of the time, SST and air temperature run in parallel. However, when there is rain, the air temperature is much lower. You say this doesn’t show “the depression of air temperature”, so I’m totally at a loss about how you understand the whole system.
How do lower air temperatures not indicate a depression of air temperature?
And how does a depression of air temperature from rain not indicate that the succeeding temperatures will be cooler than if the rain had not occurred?
Perhaps you should get the TAO data and work through it yourself, Steve. I fear I can’t explain it much better or differently than I have.
All the best,
w.