Guest Post by Willis Eschenbach
I’ve been looking again into the satellite rainfall measurements from the Tropical Rainfall Measurement Mission (TRMM). I discussed my first look at this rainfall data in a post called Cooling and Warming, Clouds and Thunderstorms. There I showed that the cooling from thunderstorm-driven evaporation is a major heat-regulating mechanism in the tropics. This is another piece of evidence for my hypothesis that the global temperature is regulated by emergent phenomena, including tropical thunderstorms. This regulation keeps the temperature within a very narrow range (e.g. ± 0.3°C over the entire 20th century).
In that post, I looked at averages over the period of record. For this post, instead of averages over time I’ve looked at the changes in rainfall amounts over time. To begin the temporal investigation, Figure 1 shows the month-by-month variations in the average rainfall.
Figure 1. Movie loop of the monthly averages of the tropical rainfall, Dec 1997 – Mar 2015. The coverage of the mission only extends from 40°N to 40°S. Note that this covers about two-thirds of the surface of the planet. Units are mm/month.
Note how the rainfall amounts clearly delineate the Inter-Tropical Convergence Zone (ITCZ) that runs along and generally just above the Equator. As the name implies, the winds of both the northern and southern tropics converge near the equator. Where the winds meet there is intense rainfall, along with the deep thunderstorm convection that drives the global atmospheric circulation.
It is interesting to see the waves of precipitation wash over places like India. It’s like the earth breathing—in the summer when India gets hot, the hot air rises. When the air rises, it draws in the moist air from off of the Indian Ocean, which pours down as the monsoon rain.
Brazil, on the other hand, was a surprise in that I never knew that all of Brazil but the far north has a long dry period from July to January or so. And when it rains, the rain comes down from the north. Always more to learn.
Now, when I look at a timeseries record, I want to be able to separate out the regular seasonal changes from the rest of the data. Figure 2 shows the month-by-month rainfall averages for the area 40°N to 40°S, decomposed into the seasonal and residual components.
Figure 2. Decomposition of the monthly rainfall record (red line, top panel) into two components—a repeating seasonal component (blue line, middle panel) and a residual component (bottom panel) which is the data minus the seasonal component. The p-value is adjusted for autocorrelation by using the Hurst exponent to calculate the effective degrees of freedom. See here for details of the adjustment.
The main thing that stands out for me in this record are the two biggest El Nino/La Nina episodes, one in 1997-1998, and one in 2009-2010. We can see that during these episodes the tropical rainfall went up. There is also an overall trend, but it is not statistically significant.
Now, we can convert the rainfall data into evaporative cooling data. To do so, we utilize the rule that what comes down must go up. So if a half meter of rain falls in a month, a half meter of water must have been evaporated during the month.
And we know that it takes about 75 watt-years of energy to evaporate one cubic meter of seawater. This lets us convert the rainfall data to evaporative cooling data. Figure 3 shows that result. Of course it is identical in shape to the rainfall data, only the units are changed.
Figure 3. As in Figure 2, showing the decomposition of the monthly evaporative cooling record (red line, top panel) into two components—a repeating seasonal component (blue line, middle panel) and a residual component (bottom panel) which is the data minus the seasonal component.
As mentioned above, I’ve shown that as the temperature goes up, so does the thunderstorm-driven evaporative cooling. In other words, the variations in thunderstorm evaporative cooling are a response to the temperature variations.
Note the size of the variations in cooling, which can change by up to eight watts per square metre in a single month. This can be compared with the estimated changes in CO2 which are expected to be about four watts per square metre in a century …
This dependence of thunderstorm evaporative cooling on temperature be seen more clearly by looking at the deep tropics, what are sometimes called the “wet tropics”. The graph below shows the area from 10°N to 10°S. You can see in the bottom panel that the evaporative cooling was high during the 1997/8, the 2002/3, the 2006/7, and the 2009/10 El Nino/La Nina episodes, and decreased during the subsequent La Nina episodes
Figure 4. As in Figure 1, but for the deep tropics from 10°N to 10°S. This shows the decomposition of the monthly thunderstorm evaporative cooling record (red line, top panel) into two components—a repeating seasonal component (blue line, middle panel) and a residual component (bottom panel) which is the data minus the seasonal component.
The first thing that caught my eye is that at 120 watts per square metre, the evaporative cooling in the deep tropics is about 50% stronger than in the full TRMM 40°N/S dataset.
You can also see the El Nino/La Nina pump in operation. The “La Nina” portion of the El Nino/La Nina pump is much clearer in this deep tropical data. We can also see the smaller El Ninos of 2002/3 and 2007/8 along with the subsequent La Ninas.
Now, here is the interesting part. I wanted to compare the evaporation with the surface temperature. To start with, I used the HadCRUT4 surface temperature for the deep tropics. Figure 5 shows the two datasets, one of temperature, and the other of evaporative cooling.
Figure 5. Temperature and evaporation in the deep tropics 10°N to 10°S latitude. The upper panel shows the HadCRUT4 surface temperature data. The lower panel shows the evaporative cooling calculated from the TRMM rainfall data.
As you can see, the two datasets follow each other very closely. To demonstrate that, Figure 6 below shows the evaporation, along with the linear estimate of the evaporation based solely on the surface temperature:
Figure 6. Evaporation in the deep tropics 10°N to 10°S latitude (black), along with estimated evaporation based on temperature (red).
Note that this covers the entire deep tropics from 10°N to 10°S. This is not just the El Nino region in the Pacific, but also the other oceans and the land as well. And as you can see, in the deep tropics the temperature and the evaporative cooling are quite intimately related around the globe.
Now this correlation of temperature and evaporation should be no surprise. Common experience tells us that the warmer a wet object is, the quicker it dries by evaporation. So we’d expect evaporation to increase and decrease in parallel with temperature.
The surprising part of this analysis from my perspective was the size of the variation in evaporative cooling. We get a very large variation in evaporative cooling given a small change in temperature. Evaporative cooling rises by 27 W/m2 of increased cooling for each one degree C of surface warming.
I wasn’t all that convinced that big a number was correct, so I decided to check it against the CERES surface temperature data. It turns out that the CERES data gives us about the same answer. CERES data for the deep tropics says there’s an average of a 23 W/m2 increase in evaporative cooling per degree of surface warming for the deep tropics (10°N/S). Here’s the larger picture from the CERES data:
Figure 7. Trends in evaporative cooling per degree C of warming, for each 1°x1° gridcell from 40° North to 40° S.
As noted above, the TRMM data covers about two-thirds of the surface area of the Earth. From appearances, unlike in the tropics, the correlation of evaporation and temperature is negative in the unsurveyed areas of both the northern and southern extratropics. The grey line at about 30°N/S shows where the relationship goes negative. This is no surprise. In the extratropics, rain is associated with cold fronts instead of being associated with thermally driven tropical thunderstorms. As a result, although the overall average change in cooling shown in Fig. 6 is 11.7 W/m2 per degree of warming, I suspect this be largely offset once we have precipitation data for the currently unsurveyed areas.
Regardless of the unknown global average, however, in the tropics (and particularly the deep tropics) evaporative cooling generally goes up, and sometimes very rapidly, with increasing temperature. To take another look at it, Figure 8 shows deep tropical evaporation as a function of the CERES temperature data (note that the CERES data doesn’t cover the end of the 1997/8 El Nino-La Nina episode.
Figure 8. Evaporation in the deep tropics 10°N to 10°S latitude (black), along with estimated evaporation based on the CERES satellite-measured surface temperature (red).
So I got to thinking … if there were no thunderstorms, how large would we expect the change in evaporation to be for a one degree change in temperature? We expect the evaporation to go up with increasing temperature … but how fast?
To answer this, I turned to the literature. Evaporation can only be approximated, and there is more than one way to do it. I used the formula given here (Equation 5) for evaporation over the ocean, as well as the formula in the R package EcoHydRology. The two methods gave somewhat different answers for the change in evaporative cooling per degree of warming (see “Math Notes” below). One says that assuming tropical conditions gives us about 4 W/m2 per degree warming in the deep tropics. The other says about 6-7 W/m2 per degree. And no matter how I play with the variables of wind and temperature and relative humidity, I can’t fit the data with anything more than about 7-9 W/m2 increase in evaporative cooling per degree of surface warming.
On the other hand, the answer that we’ve gotten from a couple of sets of observations (HadCRUT4 and CERES) gives a value of around 25 W/m2 of increased evaporative cooling per degree of warming for the deep tropics. And the trends of individual gridcells in Figure 6 shows evaporative cooling of more than three times that per degree of warming.
To put the contrast starkly, at the average temperature of the deep tropics (~27°C), from theoretical considerations we’d expect a 1°C rise in temperature to increase evaporation by somewhat less than ten W/m2 depending on your assumptions … but the observed average increase is 23-27 W/m2, much more than the theoretical increase in evaporation from temperature alone. I hold that this is because of the thermally controlled nature of thunderstorms.
I think that the causative chain runs as follows:
Increased surface temperature ==> earlier and more daily thunderstorms ==> increased evaporation ==> increased cooling
However, I’m happy to entertain alternative hypotheses.
To recap: the unexpected finding is NOT that evaporation increases with temperature. We’d expect that. The unexpected part is that the evaporation increases by 27 W/m2 per degree C of warming, while the theoretical increase in evaporation per degree of warming is much less than that, under ten W/m2 per degree C.
How is this increase in evaporation accomplished? Well, therein lies the story of one of the under-appreciated abilities of the thunderstorm. A thunderstorm is a dual-fuel heat engine. It runs on either temperature or water vapor. And beyond that, it can create its own fuel as it runs.
Thunderstorms run off of low-density air. The low-density air rises, bearing water vapor upwards to the level where the water vapor condenses. The heat of condensation then powers the deep convection up the tower of the thunderstorm.
Now, there are two ways to get low-density air. One way is to heat the air, so it expands and rises. The other way is to increase the relative humidity of the air, because counterintuitively, water vapor is lighter than the air. So when evaporation increases, the air gets lighter and rises.
And here’s the beauty part. The thunderstorm doesn’t just depend on the existing evaporation. Instead, it generates its own increased evaporation (and thus increased evaporative cooling) in several ways.
First, once the thunderstorm forms it generates strong surface winds in front of and underneath the storm. Evaporation is a linear function of the wind speed, with a coefficient of about 0.7. So if wind speed increases from say 2 m/sec (4.4 mph) up to 10 m/sec (22 mph), you get about three and a half times the evaporation.
The next way that thunderstorms increase evaporation is that they are surrounded by dry descending air. Thunderstorms condense the water out of the air as it is lifted high into the troposphere. As a result, when the air exits from the top of the thunderstorm, it contains very little water. From there it descends, providing a constant source of dry air to the surface. If there is 120 W/m2 evaporative cooling in the deep tropics and the air dries from a relative humidity of 0.75 to 0.65, the evaporative cooling increases by about a third, to about 160 W/m2. So this provision of dry air is quite a large factor in the increased evaporation.
The final way that thunderstorms increase evaporation is by increasing the evaporating surface area of the water. Over the ocean, which is 83% of the deep tropics, wind-driven waves increase the oceanic surface area. Wind-driven short-period waves of say 1/2 metre height and 30 metre wavelength increase the ocean surface area by about 1%. But when those waves start to break, or when the storm winds blow the water off of the tree leaves and the grass, sending fine spray into the air, surface area increase from the spray droplets can be 5% or more.
So once the thunderstorm gets started, it manufactures low-density air that keeps it going by generating strong winds at the base, by lowering the relative humidity of the surrounding air, and by increasing the evaporating surface area. This lets the thunderstorm cool the surface to a temperature well below the thunderstorm initiation temperature.
I highlight this because it is a crucial and often overlooked fact, one than distinguishes thunderstorms from simple linear feedback. Once the thunderstorm is initiated, it operates in the exact same manner as manmade refrigerators. It uses evaporation to remove heat from the area to be cooled. And because it is generating its own fuel (low density moist air) it can continue to cool the surface to below the temperature at which it started. And this “overshoot” in turn means that it can keep a “steady state” temperature that only varies within a narrow range. When the temperature gets too high, it gets pushed down below the thunderstorm initiation temperature. Then the temperature starts to rise again, and when it does, a new thunderstorm forms, and it pushes the temperature down below initiation temperature. The cycle repeats endlessly, and the temperature of the system varies little.
And this is the reason for the large variation of evaporation with temperature. Tropical thunderstorms are a threshold-based emergent phenomena. This means that they emerge spontaneously once a certain threshold is surpassed. In the case of tropical thunderstorms, the threshold is mainly temperature-based. As a result, the evaporative cooling due to tropical thunderstorms is a function of the surface temperature.
In closing let me add this final movie. It shows the entire history of the TRMM tropical rainfall observations, month by month. To me, there’s nothing as fascinating as observational data.
My best wishes to you all,
w.
My Usual Request: If you disagree with me or anyone, please quote the exact words you disagree with. I can defend my own words. I cannot defend someone’s interpretation of my words.
My New Request: If you think that e.g. I’m using the wrong method on the wrong dataset, please educate me and others by demonstrating the proper use of the right method on the right dataset. Simply claiming I’m wrong doesn’t advance the discussion.
Math Notes: I’ve used the R package EcoHydRology to estimate the evaporative heat flows from a wet surface. Most (83%) of the deep tropics is ocean, and the rest is usually wet, so it is a reasonable approximation. The function I used is called “EvapHeat”. The package documentation says
EvapHeat : Evaporative heat exchange between a wet surface and the surrounding air
Description
Evaporative heat exchange between a surface and the surrounding air [ kJ m-2 d-1 ]. This function is only intended for wet surfaces, i.e., it assumes the vapor density at the surface is the saturation vapor density
Usage
EvapHeat(surftemp, airtemp, relativehumidity=NULL, Tn=NULL, wind=2)
Arguments
surftemp : surface temperature [C]
airtemp : average daily air temperature [C]
relativehumidity : relative humidity, 0-1 [-]
Tn : minimum dailiy air temperature, assumed to be dew point temperature if relativehumidity unknown [C]
wind : average daily windspeed [m/s]
This function gives the answer in curious units, kilojoules/m2 per day. So I convert it to watts continuous by multiplying by 1000 joules per kilojoule and dividing by 86,400 seconds per day. This is joules/second/m2, which is the same as watts/m2. I used this function with reasonable numbers for the variables in the deep tropics (surftemp ≈ 27°C, airtemp ≈ surftemp – 0.5°C, relative humidity ≈ 0.85, wind ≈ 2 m/sec.) The values for the surface and air temperatures are from the TAO buoy data.
The second way that I determined the increase in evaporation with temperature was using the formula shown here at the bottom of page 6. It gives smaller values for the increase in evaporation with a 1°C increase in surface temperature.
After much experimentation I found that regardless of the exact values chosen for the variables (surface temperature, etc.), the change in evaporative cooling per degree of surface warming is far below the ~ 25 W/m2 of evaporative cooling shown by the TRMM data. In all cases I investigated, any combination of values that gave a total evaporative cooling of ~ 120 W/m2 also gave a change in cooling of less than ten W/m2 of additional cooling for a 1° surface temperature change.
Love the movie representation. Would be interesting to see the wave function plotted so some study could reveal changes in amplitude and frequency. Even subtle central deviations from equator. This is important for the other two thirds of planet where the apparent consistency of the equatorial tropics causes extremes at the edges. This is most noticable when the wave-like slop hits me in Australia. Hits and misses may be mis-interpreted as climate change when nothing more than a random tropical slop event. ….. Not sure I have described this clearly, but I am keen on seeing the movie as a sort of maths sine wave. Changes in amplitude or periodicy could be weather predictors fot non equatorial regions…. Maybe?
Oops…..other third of planet.
This excellent analysis carries with it two second order effects that further explain low sensitivity to GHG forcings via the mechanism Willis demonstrates. First is Lindzen’s adaptive infrared iris. He focused on reduced cirrus as the diagnostic, from bigger/taller convection cells (Tstorms) producing more precipitation, leaving less moisture for detrainment into cirrus. But the idea can be broadend to include thermoregulation of upper troposphere specific humidity, which lessens the water vapor feedback. Second is the simple idea that tall thunderstorms carry the latent heat of evaporation released by condensation with temperature lapse rate higher into the troposphere, lessening the efficacy of the CO2 ‘GHG insulating blanket’. Depending on Tstorm and CO2 concentration, it is like ‘conceptually’ punching holes in the insulation through which the Tstorm concentrated heat more easily escapes to space.
Seperate onservation. Climate models cannot simulte Tstorms because of the latge size of their computationally constrained grid cells. Willis’ work suggests some of the ways the forced resulting parameterizations are wrong. For example, the models produce about half the tropical precipitation that is actually observed.
“punching holes in the insulation“. Nice description.
“Climate models cannot simulate Tstorms because of the large size of their computationally constrained grid cells.“. Keep saying it, it needs to be much more widely understood. [Typos fixed in the quote]
-or- “Punching Holes in the Greenhouse Ceiling” would make a good title for the paper.
“Can thunderstorms break through the (greenhouse) gas ceiling?”
+1
Really good T storms regularly dome into the stratosphere.
Yes, this is precisely the prediction from Dr. Bill Gray. The increased water vapor along with some low level warming enhances convection driving the water vapor higher in the atmosphere. This condenses out more water (and latent heat) which leaves less water vapor. This reduces the GHE where it has one of the strongest effects. Also, the air is cooled more which helps cool of the surface when it descends.
Interestingly this process is a brilliant design. As we increase CO2 we get a small amount of warming and a small increase in precipitation. These are the 3 ingredients for plant growth. All 3 rise in tandem.
Fantastic science article Willis. Well done WUWT more of this type of thing please!
Willis Enjoy your stories which are entertaining and well written, and you papers on science and logic are the same. Very understandable. The thought occurred to me that it might have something to do with being truthful. Someone that claims to have and answer and doesn’t puts fills there paper with unintelligible verbiage, full of might and maybe, and yes a Dr degree from somewhere. Your logic is actually believable.
We are blessed to have you posting your thoughts and your trips.
Thanks
The major disagreement is that the heat that is released during a thunderstorm or any storm because of the increased co2 retains that heat and continues in a never ending cycle. I’ve argued the same. It comes down to whether the heat is retained or released.
Most thunderstorms can reach much higher than 9800 feet. And it is fairly cold up there. I think that the heat is released at that point. There is something wrong with the calculations of the IPCC. Hence, the big o debate about the second law of thermodynamics and it’s application in this case.
The IPCC in support of the retained heat sernario, commissioned a study on the total incoming and outgoing heat on a planet wide bases. Since the first one, I have not seen or heard of a second. Over 15 years with the additional co2, those numbers have to be in favor of the retained heat if the math is correct. The amount of incoming has to have remained constant ( the suns output doesn’t change. IPCC), while the total released should have been reduced.
I think they already know. The suns output changes, and the heat released from earth is variable. Short term changes in the output of the sun keeps the temperature from falling or rising too fast. Long term changes in output, result in long term temperature changes. The current level, and for the foreseeable future, of co2 is too small to have much of an impact.
CO2 cant retain heat……maybe just poor choice of words.
The problem is convincing the CAGW crowd. I am only assuming that part of their analysis is correct for the sake of argument. It’s endless if I didn’t start somewhere. And they will argue, still are, the second law of thermodynamics.
My concern was to put this research in context of what the IPCC believes. Tropical thunderstorms or not, the heat is retained per the IPCC. (Not me) If the heat is released from more thunderstorm activity, CAGW doesn’t have much of a case. If the suns output varies, they also don’t have a case. More co2 or not.
“Short term changes in the output of the sun keeps the temperature from falling or rising too fast. ”
I agree with this completely rishrac. As a daily observer of global water vapor images as well as solar activity indices for several years, I’ve seen the oceans explode with evaporation during higher solar (TSI) days, and the opposite during low TSI solar periods. Getting all that into the form like Willis has is another story however.
Willis .Superb post!
See section 1.3.2 at
http://climatesense-norpag.blogspot.com/2014/07/climate-forecasting-methods-and-cooling.html
“The IPCC climate models are further incorrectly structured because they are based on three irrational and false assumptions. First, that CO2 is the main climate driver. Second, that in calculating climate sensitivity, the GHE due to water vapor should be added to that of CO2 as a positive feed back effect. Third, that the GHE of water vapor is always positive. As to the last point, the feedbacks cannot be always positive otherwise we wouldn’t be here to talk about it. For example, an important negative feed back related to Tropical Cyclones has recently been investigated by Trenberth, see:
http://www.cpc.ncep.noaa.gov/products/outreach/proceedings/cdw31_proceedings/S6_05_Kevin_Trenberth_NCAR.ppt”
He says in Fig 2.
http://3.bp.blogspot.com/-ZBGetxdt0Xw/U8QyoqRJsWI/AAAAAAAAASM/ewt1U0mXdfA/s1600/TrenPPT.pn
The evaporative peak at about 2003 in your Fig 8 is probably the important millennial RSS temperature peak. http://2.bp.blogspot.com/-zZLVnsvgYTw/Vj0GEDv2q7I/AAAAAAAAAag/eumhxpS9ciE/s1600/trend11615.png
Because of the thermal inertia of the oceans the corresponding peak in the solar driver is at about 1991
http://3.bp.blogspot.com/-QoRTLG14Siw/VdOUiiFaI5I/AAAAAAAAAYM/NxQVb2LMefk/s1600/oulu20158.gif
For further discussion see
http://climatesense-norpag.blogspot.com/2015/04/climate-and-co2-exchange-with-freeman.html
Willis, a nice article. However, I have my doubts of a quality of the EcoHydRology package.The description of a function EvapHeat rings an alarm bell for me. It uses an average temperature and an average wind speed, to compute something that is highly nonlinear in both a temperature and a wind speed. As a surface temperature of a tropical ocean does not vary much in one place, using an average temperature is probably OK. But when the wind starts blowing off tops of waves, the evaporation increases dramatically. In addition, the conversion of an evaporation rate to a heat looks rather simplistic – a latent heat of evaporation depends on temperature, and I wonder how good a result all constants hardcoded in the package yield at 30 degrees C.
During the August 29, 2015 storm that hit Washington State, I was in the Puget Sound area and observed 60 to 70 mph winds with gusts up in the 80s blow the tops off of white-capped waves. This airborne moisture quickly became atomized forming a humid haze in the atmosphere.
Curious George November 11, 2015 at 3:09 pm
Thanks, George. To quote myself:
If you know a better way, bring it on. I’ve looked at the literature, and what I find are all variations on what is called “Dalton’s formula”. It says that evaporation is some function of the wind times the difference in vapor pressure ocean to air. So far I’ve tried three different variants, and none of the three show anything like the observed 23-27 W/m2 change in evaporation per degree C of surface temperature change.
Regards,
w.
Willis, You are focusing too much on thunderstorms and not enough on evaporation^^ Not saying you are wrong, just saying.
You seem to be missing two things, one is that the top of the thunderstorms is cooler for a given altitude. If you look at the thermal images you can see that the top of the storms are colder. If the heat from condensation was being carried higher the IR images would be warmer.
Second the surface (skin temperature) is much more consistent than the measurements indicate and it is the surface which evaporates.
What controls the temperature is cloud coverage, less cloud coverage equals higher temps and higher cloud coverage equals lower temps.
http://www.climate4you.com/images/HadCRUT3%20and%20TropicalCloudCoverISCCP.gif
Are you suggesting that OLWR is only from the top of the storm cloud? How about the OLWR from a point well below the top of the storm passing through (upwards) from a point where the water vapor has been precipitated? Think about it before you reply. Then consider the OLWR being released to ‘space’ as the dry air descends outside the storm. Does it not emit to space at this point?
eyesonu, yes the OLWR is what is measured by the IR. And yes the energy gets transported poleward before becoming OLWR.
Radiation energy varies with the fourth power of temperature. Colder air, different spectrum, less intensity.
jinghis said:
***FINALLY*** someone who speaks he truth!! Yes, there is the ‘heat of condensation’ (latent heat release) *BUT* it only adds about 3 F of heating to the 5.5 F cooling process every 1000′ so the rising air is still cooling…just not as fast. The BIG thing missed is that when that air that has risen begins to sink to maintain hydrostatic balance, it will WARM @5.5F/1000′ (dry adiabatic) because most of the moisture has been ‘wrung out’. So, as the air returns to it’s original level, it is warmer than when it began & this is where the Trade Wind Inversion is created from & stabilizes the atmosphere suppressing convection.
Think about it…works every time!
Interesting. Playing this out, if I understand this correctly, back at the surface, some of the now warmer descending air locally–but more so in advance of the direction of movement of the thunderstorm–gets recycled into the thunderstorm. Since these winds are warmer, wouldn’t this would be a fourth way (adding to Willis’ first three) in which thunderstorms increase evaporation.
Doesn’t this “wrung out” air at altitude become the source of the Hadley cells? When most of this dry air descends, it is near 30 degrees north and south. Thus the high temps in the Sahara, etc.
I suggest these desert zones that circle the Earth form a second heat radiating mechanism. The low humidity allows heat to freely radiate to space at night.
SR
This is not quite correct.
When air rises in a thunderstorm, the latent heat release from condensing water warms the air within the thunderstorm compared to the air surrounding the thunderstorm so it is ‘warmer’ than for a given altitude. What you describe as being colder at the thunderstorm cloud tops is another process where by the white cloud tops reflect sunlight and radiate heat rapidly effectively giving a skin temperature colder than the surrounding air.which is picked up by satellites.
Outflow from thunderstorms and hurricanes for that matter at the cloud tops is caused by higher air pressure compared to its surrounding air. Why is that? Because the layer of air in the thunderstorm/hurricane core is warmer than its surroundings which expands that layer of air and thus raising the pressure height level at the top of the layer. High pressure air moves to the surrounding low pressure air and hence the outflow at the top of thunderstorms and hurricanes.
Yes the air will warm when lowering back down to the surface following the dry adiabat but this will only be warmer than the surrounding air because it was warmed from latent heat release in the first place withing the thunderstorm. You can not create energy from nothing there has to be a process involved to change air parcel heat and this case it is the latent heat release.
Having said all of that, then if thunderstorms act as a negative feedback and thermostat against GHG warming then increased thunderstorm activity should in theory result in more warm moisture laden air to rise in the atmosphere and warm the upper troposphere I would have thought unless something offsets this somehow. More cloud would mean less solar reaching the ground so perhaps this is the equilibrium process.
Why do you suppose tropical cloud cover shows no response to the 1997 nino? Hell, stratospheric water vapor and tropospheric precipitable show a very clear spikes.
jinghis November 11, 2015 at 3:11 pm
Thanks, jinghis. First, since you didn’t quote a word I said, it’s unclear what you are objecting to. I asked you to quote what you disagree with, and I did so for an important reason. Without it, I haven’t a clue what difference whatever you think I’m “missing” might make. How would what I’m “missing” change my conclusions, and which ones would it change?
Next, you seem to think that the thermal images show that the top of the thunderstorms is cooler than the surrounding air. Not true. What you are comparing in the thermal images is the temperature of the thunderstorm tops to the temperature of either the lower clouds or the temperature of the surface, depending on conditions. You are not comparing the thunderstorm top temperature to the surrounding air at “a given altitude” as you seem to think. We know this because if the thunderstorm tower top were actually colder than the surrounding air, it would sink … and since it doesn’t, we have to know that the top of the tower is at the same temperature as the surrounding air.
(Note that this description above is for a mature thunderstorm. When the tower is boiling skyward as the thunderstorm forms, the tower top is most definitely warmer than the surrounding air. The vertical tower development continues until the tower top is at the same temperature as the surrounding air, at which point it levels off and ceases vertical growth.)
I’m sorry, but this makes no sense. First, the temperature of the ocean skin is more variable than the underlying water temperature, not more consistent. It warms and cools with each gust of wind.
Second, I don’t understand what difference it makes.
You say:
While I would generally agree, there is no one single thing that controls temperature. Instead, the temperature is regulated by an interlocking system of clouds, thunderstorms, dust devils, El Nino/La Ninas, waterspouts, and other emergent phenomena.
I am interested in your graph, however. It says “climate4you graph” but when I went there I couldn’t find any cloud datasets at all. Do you have a link to the data, or at least to the graph?
And while I’m one the subject, PLEASE DON’T POST UN-CITED GRAPHS. Sorry for shouting, but this one angrifies my blood. I generally just glance at uncited graphs and then ignore them. Without context and a link to the DATA (not a link to the graph but a link to the data itself), they are worse than meaningless, as they can be actively misleading. I’m not accusing you of bad intent or trying to mislead, you understand. I’m just saying that graphs without data are not science, they’re just an advertisement.
Many thanks,
w.
Here is the part of EcoHydRology that gives me shivers:
EvapHeat <- function (surftemp, airtemp, relativehumidity=NULL, Tn=NULL, wind=2) {
## surftemp: Temperature of surface [degrees C]
## airtemp: Temperature of air [degrees C]
## relativehumidity: between 0 – 1 [-]
## Tn minimum dailiy air temperature, assumed to be the dewpoint temperature [C]
## surftemp: Temperature of surface [degrees C]
## wind average daily windspeed [m/s]
windfunction = 0 & relativehumidity <= 1) {
airvapordensity <- relativehumidity * SatVaporDensity(airtemp)
}
else {
airvapordensity <- SatVaporDensity(Tn)
}
surfacevapordensity <- SatVaporDensity(surftemp)
return(round(86400 * windfunction * (surfacevapordensity – airvapordensity)))
}
SatVaporDensity <- function(T_C){
# T_C = Temperature [C]
VP <- SatVaporPressure(T_C)
return(round(VP/(0.462 * (T_C+273.15)), 4))
}
SatVaporPressure <- function(T_C){
# saturated vapor pressure at a given temperature (kPa)
#T_C: temperature [C]
return(0.611 * exp((17.3*T_C)/(237.2+T_C)))
}
Large mountain ranges cause rain shadows and deserts behind them in a lot of areas like the Sahara/ Gobi, but I always wonder how fast some of these mountains happened, Driving through the Rockies I see some really amazing rock formations that just do not seem to have happened with slow speed of tectonic plates (5-10 cm/year). They appear to have been way more violent which may be why some of our glacial periods happened so quickly?
Thanks Willis, good work. For anyone who has been in the tropics for some time, or at different times of the year, this is almost intuitive, obvious. But you have to explain it to the Warmistas, almost all of who do not live in the tropics, but rather the temperate regions of the planet.
I get the idea many warmistas never go outside, and rarely even look out a window.
They are, in general, not the outdoorsy and observant type.
I think of Willis’ work as being the other end of the stick: A study of the negative feedback mechanism that keep the “global temperature” as stable. Others, such as Svenmark, are trying to understand what drives the changes, which is more difficult due to multiple factors, while the Warmistas deny anything other than CO2.
Superb Willis,
TRMM is a very nice dataset. Glad to see someone put it to good use.
A couple of notes.
1. It’s nice to see CERES and Hadcrut4 both agree.
2. nic Lewis comment gave me an idea
comparing to GCM would be cool
Except they don’t agree. CERES shows less warming. Could this be due to incorrect adjustments to the hadcrut4 data? It would be a nice exercise to see what the hadcrut4 data would look like if one adjusted it to show 23 w/m2. One could then compare that to the UAH or RSS satellite data to see if that removed the 21st century divergence.
IPCC AR5 admits in TS.6 they don’t understand the water cycle and in FAQ 8.1 IPCC dismisses water vapor because A) they can’t explain or model, B) it’s a natural force and violates IPCC’s mandate of man caused only.
BTW IPCC assigns clouds an RF of -20 W/m^2 (watt is power not energy) which is cooling and lots of it.
If you work the numbers on IPCC AR5 Figure 6.1 you will discover that anthro C is partitioned 57/43 between natural sequestration and atmospheric retention. (555 – 240 = 315 PgC & 240/555) IMO this arbitrary partition was “assumed” in order to “prove” (i.e. make the numbers work) that anthro C was solely/90% responsible for the 112 ppmv atmos CO2 increase between 1750 – 2011. C is not CO2.
PgC * 3.67 = PgCO2 * 0.1291 = ppmv atmospheric CO2
IPCC AR5 Figure 6.1
……………………………….PgC/y……ppmv/y
FF & Land Use Source…….8.9……….4.22
Ocean & Land Sink…………4.9……… 2.32
Net Source.……….………..4.0……….1.90
If the anthro 8.9 Pg C/y (4.2 ppmv CO2/y) suddenly vanishes the natural cycle that remains would be a constant sink of 2.3 ppmv CO2/y. Reverse extrapolation (GCMs & RCPs apply forward extrapolation) calculates that 121 years in the past (278 ppmv CO2/2.3 ppmv CO2) or the year 1629 (1750-121) atmos CO2 would have been 0, zero, nadda, zip, nowhere to be found.
Oh, what a tangled web we weave!
The 8.9 Pg/y of anthro C simply vanishes in earth’s 45,000 plus Pg C cauldron of stores and fluxes. Mankind’s egoistic, egocentric, conceit means less than nothing to the earth, the solar system and the universe.
Thunderstorms lead me to the question of the effect and causation of hurricanes. Essentially, as I understand it, they’re basically super thunderstorms (or tightly associated with them). Would more thunderstorms cause more or less hurricane formation? By that I mean that more thunderstorms spread out over a wider area would dissipate the energy the hurricanes would need to feed themselves. I seem to remember Dr. Curry wrote a paper predicting global warming would cause more intense hurricanes, though the opposite seems to be happening.
Hurricanes cannot form and sustain if wind shear exists.
It is not a simple matter of more thunderstorms or warmer water.
If you note what happened in 2004 and 2005, just prior to the sudden formation of hurricane after hurricane, wind shear dropped off over the formation zones.
Thunderstorms don’t spin.
If you take a weather reporting station on land, look at the daily time variation of temperature over many years then go mildly multivariate and include daily rainfall, you will commonly find that at least 30% of the temperature variability can be explained, statistically before mechanistically, by rainfall.
Put simply, rain cools.
What is more, rain cools without mention of carbon carbon dioxide, greenhouse gases ….
With the current search for record this and that, extreme climate and so on, remember that a high temperature might or might not be unprecedented simply because the rain fell mainly in another paddock nearby.
The fickle finger of fate makes global headlines come and go like thunderstorms ….
It is all so contrived by those more interested in headlines than data.
Willis,
In this and other pictorial representations, such as some covering El Nino events, the eye is drawn to a lot of activity around the Indonesian islands. At times they look like the start point for repeating processes but this is just a strong pictorial effect. In the world of real data and observation, have others theorised if Indo does have a key role and if so, why?
Could it be a focus on the ring of fire with a permanent (for now) high geothermal gradient seeding processes like you describe here?
Hi Geoff
More likely the Asian and Australasian land masses blocking ocean currents (and to a lesser extent winds) on the western side of a large ocean basin. Heat and moisture accumulate near Indonesia- more to the north of the equator because there is more ocean to the north- Australia and New Guinea are further to the East. Which is why the ENSO cycle is in phase with NH seasons- building up in NH summer/autumn when the larger north Pacific is more directly exposed to the sun, peaking in NH winter, and hard to predict in NH spring. What interests me is the way the rainfall appears to circulate anti clockwise about Jakarta as the monsoon ebbs and flows.
Please see my studies relating Northeast Brazil:
1. Climatic fluctuations and homogenization of Northeast Brazil using precipitation data, Pesq. Agropec. bras., Brasilia, 19:529-543, 1984 — homogeneous zones, I- above 4-5 deg. S. lat,; II – between 4-5 and 8-10 degress S. lat. and III – below 8-10 deg S. Lat. Fortaleza data has very long precipitation series. This showed 52 year cycle [similar to onset dates over Kerala Coat in India] with submultiples of 26, 13 & 6.5 years with stronger amplitudes in 26 &13 year cycles. — 2013 was dry year, soalso the case with Durban.
2. A simple method for the estimation of global solar radiation over northeast Brazil, Pesq. Agropec. bras., Brasilia, 19:391-405, 1984 — The input in to this model is precipitation [cube root of precipitation]
3. A method for the estimation of potential evapotranspiration and/or open pan evaporation over Brazil. Pesq. Agropec. bras., Brasilia, 19:247-267, 1984 — The input is precipitation [cube root of precipitation]
Dr. S. Jeevananda Reddy
The GIF movies that show the “earth breathing” are just spectacular.
Love this site and contributors!
There is also the fact that less than ten percent of water droplets in clouds make it down to ground level, the rest evaporates mid air, close to the cloud base. That’s how clouds stay afloat.
So there is a lot more evaporative cooling going on, than calculated from net precipitation. True, it is not cooling at the surface itself, but some way above it, still, it gives a large contribution to vertical heat transport to the upper troposphere, where absolute humidity gets so low, that water vapor no longer acts as a greenhouse gas, letting radiative cooling to space kick in.
Rain that evaporates before reaching the ground is called virga.
You can see it with the naked eye. Very common in deserts. As BP points out, it amounts to multiple rounds of evaporative cooling.
http://www.weather.gov.sg/climate-past-climate-trends/
These climate trends from the link above from Singapore which is 1 deg North of the equator and remains in a semi permanent tropical weather pattern all year round show some interesting results. Firstly that there has been an increase temps and precip from the mid 70s to mid 90s then it has leveled off very much like the global Satellite temperature records suggest. To me this implies a new equilibrium has been reached where perhaps temps rose and increased evaporation, but only to a point where increase precipitation now overrides the warmer signal from GHG warming. This would add weight to Willis’s theory I think.
Willis,
Very nice post. Clear and informative. The most interesting thing is the ‘self-sustaining’ nature of convective storms, where wind from the storm increases evaporation and so drives total cooling far beyond what you might expect. The persistence of convective cells is quite amazing over open water; you can watch them for hours.
Nature’s heat pipe. Huacane does the same thing. Moves a ton of heat with little delta T
Willis,
Buried tonight and long since down with the convective cooling thing, but the crazy thing about your animation is that the Indian ocean completely has its own program. The Atlantic and Pacific oceans follow the trade winds and the Hadley circulation. Why doesn’t the Indian ocean follow suit? Check out Bob Tisdale’s animation of the 1997 nino SST’s. That telegraphs across the Indian ocean and bounces off Africa very sensibly as one would expect the rainfall to do.
Nope. The rainfall in your graphic trends SW to NE and stacks up in the crook of Indonesia and the west side of the horn of India. Almost like the Hadley were displaced half a tropic to the south by the landmass of Eurasia.