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.
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.