Guest post by Mike Crow
Figure 1 Night time temperature profile of a clear sky night in NE Ohio. 8:28pm Sunset/6:16am Sunrise
Climate science is all about surface temperature trends. The problem with this is that the CAGW is a rate of cooling problem, not a static temperature problem. Is Co2 changing the rate of cooling, thereby altering the expected surface temperature, are the hypothesized positive feedbacks actually there, are there any actual measurements of these parameters. I think there is. Every night the Sun sets on every location on Earth, and the surface starts to cool by radiating heat into the cold black of space. What can weather station data tell us about this?
Figure 2 Count of NCDC Daily station records by year (2011 is partial year)
The temperature record has daily min and max temperatures. When the Sun comes up in the morning, on most days it warms the surface from the minimum temp of the day peaking late in the afternoon. Then the Sun sets and temperatures start to plummet. I live at 41 N Lat, and on a clear night the temperature will drop 20-30 F (Figure 1), over a degree F per hour. If there’s a CO2 effect in the temperature record, it should show up in night time cooling. The question is, does this loss of cooling actually show up in the data?
I went in search of an answer, I started with NCDC’s global summary of day’s data set which contains over 120 million station records, and starts late 1929. The first thing to notice is how few samples there are each year prior to 1973 (Figure 2).
What I wanted to look at is how much the temperature went up “today”, and how much does it drop “tonight”. Today’s Rising temp is today’s T-max –today’s T-min. Falling temp is today’s T-max – tomorrows T-min, the drop in temp over night. Difference is Rising – Falling.
To do this, you have to have good records for both today and tomorrow, so as part of my data import process, I validate that the temperature records are good. NCDC provides placeholder values for temp, even when the data isn’t available, I trap these and remove them. This leaves me with a set of data as it is from NCDC, augmented with Rise, Fall, and Diff (Figure 3). The NCDC data also contains some station information, Latitude, Longitude, Altitude, Country, and State where appropriate. This allows me to aggregate temperature records by station location, as well as create a google map of the station in a aggregate set. When annual averages are generated, I average the daily values for a particular station, then average the annual values of the collections of stations in the area being examined.
This is where the temperature data would be homogenized. I feel that since temperatures are not linear spatially and the sample size changes so much over time, homogenizing temperature data is basically making up data that doesn’t exist. I understand some might say not doing this creates a bias where the data is over sampled, I feel making up data is worse than bias.
Figure 3 Annual average Min, Max, Rise, Fall and Diff Temperature for all Global Stations Google Map of Locations
After the preprocessing step there are some 109 million daily samples from 1940 to early 2011. A couple of things to note:
· Rise and Fall are almost identical to each other, and they are approximately 18F for the entire period.
· You can see the “AGW” warming signal in the Min/Max temperature records, yet Rise/Fall does not increase at the same pace.
· Diff is very small, and to make it more than a flat line, it is multiplied by a constant (in this case 365).
· Values are erratic for the earlier years that are under sampled.
· One would expect a positive trend in diff if there was a general loss of nightly cooling and there isn’t one.
The data divided up by Latitude (Figures 4-8):
Figure 4 Average temps for Stations > 66.5 Lat
Figure 5 Average temps for Stations >23 and <66.5 Lat: Google Maps for Eastern Stations, Western Stations
Figure 6 Average temps for Stations <23 and >-23 Lat
Figure 7 Average temps for Stations < -23 and > -66.5 Lat
Figure 8 Average temps for Stations < -66.5 Lat
Lastly I ran a report on the Continental US since it has a large number of stations, the graph is just of diff without a multiplier (Figure 9).
Figure 9 Diff for Continental US
I can also generate daily average reports, Here’s the daily average for stations North of 23 Lat 1950 to 2010 Diff * 100 (Figure 10).
Figure 10 Daily diff * 100 1950-2010 for > 23 Lat
When the ratio of Day to night increases, Diff is positive. When the ratio decreases Diff is negative. This is really a graph of temperature response to a change in incoming solar energy. I’ve read comments that said: “Boy it’d be nice to turn the Sun off for a while to measure the response”, will this is the next best thing to doing exactly that. The question I had from this graph, is what’s the slope of changing Diff as the day gets longer (Figure 11), and as the day get shorter (Figure 12)? So I created the following:
Figure 11 May to September cooling rate: Summer slope
Figure 12 November to March warming rate: Winter slope
If you plot out the slope of the daily temperature change for spring to fall and fall to spring you get this (Figure 13).
Figure 13 Slope of Spring to Fall and Fall to Spring temperature response as the length of day changes for >23 Lat
Unfortunately, there isn’t enough data to see if it truly is a ~60-70 year cycle, but it clearly shows that the slope for both the cooling and warming decreased, where the winter warming slope is both larger and changed more than the summer cooling slope. I would expect a Co2 signal to decrease the cooling slope, which we have, I wouldn’t expect it to decrease the warming slope as well.
What would affect both? A change in Orbit or tilt comes to mind, as does a change in Sea Surface Temps, but would SST’s change both? A change in cloud cover might change both.
What will be interesting to see is as we collect more data, does slope continue to go back up, detecting a natural cycle affecting cooling rates.
In any rate, the data shows Rise and Fall being very consistent over the entire data set, where diff seems to be negatively correlated to temperature increases, when it warms up, it cools a little more overnight. Which makes some sense, and if the heat that’s radiated into space is air warmed over warm ocean waters, which then moves over land, it makes even more sense.
Conclusion:
The world wide surface station measured average daily rising temp and falling temp is 17.465460F/17.465673F for the period of 1950 to 2010, not only is the falling temperatures slightly larger than rising temperatures, 17.4F is only 50%-70% of a typical clear sky temperature swing of 25F to 30F, which can be as large as +40F depending on location and humidity.
This shows conclusively that the average night time cooling is not limited by GHG because low humidity clear skies cool far more than the global average. Since recorded Min Max temperatures show no sign of a loss of cooling on a daily basis since at least 1950, even if CO2 has increased the amount of DLR, something else(most likely variablity of clouds) is controlling temperatures. This would seem to eliminate CO2 as the main cause of late 20th century warming.
MiCro says:
May 17, 2013 at 7:36 am
About dew point. Radiation from a surface is at the skin surface temperature. When dew is formed on the surface, the surface will be at that temperature. As moisture is taken out of the air, the dew point will be lowered. At the Southpole, the surface is ice and the reported skin surface temperature closely matches the reported frost point temperature. The air temperature measured above the surface is slightly higher. I noticed in your Fig. 1 that around 4:00 am the temperature leveled off. What was the reported dew point at that time?
Changes needed:
Roger Knights says:
May 17, 2013 at 9:02 am
Since I can’t edit the page, If a mod can make these changes, I’d be fine with it.
“the hypothesized positive feedbacks”
“The question I had from this graph, is what’s the slope of changing Diff as the day gets longer (Figure 11), and as the day gets shorter (Figure 12)?”
[Done. -willis]
Question from an uneducated layman; if a parcel of air warms at the surface, it expands, rises, and cools. Where did the absorbed heat energy go? I say it was shared with the cooler air above, not lost at all. I read that nitrogen, oxygen and argon do not radiate at temperatures encountered in the atmosphere. So how does 99.9% of the atmosphere cool down once it has been warmed?
fhhaynie says:
May 17, 2013 at 8:55 am
Dew point ranged from about 48F to 43F through the night, and at 6:00am was about 9F below the temp(43F).
Greg Goodman says:
May 17, 2013 at 7:53 am
MiCro says:
@John West,
Incoming solar is mostly in the .5-1u range, the nearest Co2 band is a little over 4u and a small absorption at about 3.5u. Solar IR should pass through Co2 untouched…..
>>>>>>>>>>>>>>>>>>>>>>>>>>>
The problem is the IPCC and it’s definitions of ‘forcings’
If you look at the IPCC causes of warming/climate change you will notice that WATER is conspicuous by it’s absence. See Table In AR5 from WUWT link
A physical chemist, Rich, explains why water, one of the most important forces in the climate, is not considered a ‘forcing’ and instead is considered a ‘ feedback’
Therefore if you look at temperature changes caused by anthropogenic emission of carbon dioxide then you have to lump the effects of water into the mix.
NOTE: I consider CO2 the feedback since oceans occupy 70% of the earth’s surface. Solar energy has the greatest effect on the ocean (link 1, link 2)and Henry’s Law means a change in the temperature of the ocean from a change in solar energy (NASA link) will change the amount of CO2 uptake or outgassing. link
I have a suggestion (really, a plea to you and all other authors) which is relevant to the presentation, but not to its scientific content. Please do not use bitmaps in jpeg format for presenting charts and graphs! The figures are (a) difficult to read and (b) ugly as sin. Please use a lossless bitmap format: I strongly recommend png. Line drawings will look much, much better.
You can use jpeg if you wish, but if you do, use a lossless compression version of jpeg.
paqyfelyc-638
I appreciate this comment, though I’m not sure there still isn’t value to this. When you look at the overall average of all of the temperature records(Rise/Fall), it’s still slightly negative. So IMO either the records are accurate enough to be used to show a temperature trend, and therefore Diff is slightly negative, or it isn’t good for either purpose.
Also I process the data on the paired days (today’s min/max and tomorrows min) on each station, then aggregate multiple stations together. So while the reading are recorded in tenths of a degrees, each record has to be larger by at least a tenth of a degree to show any difference. Now you might argue that tenths of a degree still isn’t accurate enough, but as I said above the data is either good for both, or it’s not.
This agrees with the only attempt I know to measure DWIR.
http://journals.ametsoc.org/doi/abs/10.1175/2011JCLI4210.1?journalCode=clim
” The AERI data record demonstrates that the downwelling infrared radiance is decreasing over this 14-yr period in the winter, summer, and autumn seasons but it is increasing in the spring; these trends are statistically significant and are primarily due to long-term change in the cloudiness above the site. ”
Also, is there information on cloudiness in the data (I just skimmed the article). Seems like it would be better to eliminate cloudy nights to get better data.
Mathematicians have a sense of ‘beautiful’ work. Elegant, concise, persuasive.
What you have done is beautiful. And very important. Amazing that it has not previously been done.
A suggestion for a companion analysis concerning the magnitude of the positive water vapor feedback. If specific humidity (calculable from relative humidity, temperature, and barometric pressure) can be estimated for a large sample of stations where it fundamentally is different (e.g. Arizona, Florida) then the same rise/ fall/ diff analysis across varying atmospheric water vapor over time would shed light on the magnitude of the feedback. Would only be partial, since UTH is the most import factor and this analysis would only be for surface levels. Worth a though.
Richard M says:
May 17, 2013 at 10:04 am
The NCDC doesn’t indicate level of cloud cover. I originally wanted to mine the data for this, but decided it would reduce the validity of the answer I get, we don’t like it when the team picks out the data they like. Now, it’s not to say that as an addition to this work, mining subsets wouldn’t have additional value.
Rud Istvan says:
May 17, 2013 at 10:10 am
Thanks You!
I did recently look at the data to see if there was insight to be found, and it’s maybe, humidity is recorded only once per day.
For Christmas, like what Keith Gordon has, I asked for a simple weather station, in part so I could get a better understanding of how temp and humidity vary related to fixed time measurements that lack physical insight (no one is looking at what the weather is vs what the data that’s being recorded says).
Is there any evidence for “catastrophic” global warming other than climate models? When actual observations are analyzed, there is nothing to be alarmed about. Time will tell us whether recent warming was just another natural event (like the 30s) or actual mild warming due to CO2. In the meantime, Mike, keep up the honest questioning. If alarmists can’t come up with good answers to counter your research, they will try to Cook your goose by claiming 97% disagree with you. But eventually, they will just end up eating “Crow.”
@Louis, lol
There’s basically 2 arguments,
The data isn’t detailed enough to detect the change and/or there bias due to not homogenizing spacial locations.
As a data specialist (I do this for a living), homogenizing non-linear temps over a linear area is just making up data (and can be shown to be wrong by looking at temp data across a few different local stations, Try Cleveland and the surrounding area), especially when sampling changes over time, and that’s exactly what happened with the temperature record. It’s also why I did the Diff report on the US, as it’s arguably the most sampled area on the planet, to help reduce the bias from not homogenizing the data.
Another thing, if you haven’t looked at any of the google maps (link by most of the area graphs), I think the North Pole/Arctic is worth the effort, note that none of the stations are actually in the middle of the ice, almost all of them are on the coasts, though I’m not sure how they adjust them as the ice melts and regrows over the year.
Thanks Mike.
You should check out the Hourly data. It might hold some revealing facts.
ftp://ftp.ncdc.noaa.gov/pub/data/noaa/
Eric Barnes says:
May 17, 2013 at 11:16 am
That was what I originally went to get, but the hourly data I found wasn’t free. After thinking about it, decided that using Min/Max could work.
I went and took a look at some of the data, this could be a decent place to start for a next step.
And then there’s the diurnal near surface co2 cycle:
http://meteo.lcd.lu/papers/co2_patterns/CO2_Windspeed_Solar_08to110706.png
Brilliant!
I cannot understand why the average of the daily temperature increases compared to the average of the daily temperature decreases is of much significance. It seems to me that if you add up all of the daily temperature changes (both increases and decreases), you have to get the difference between the starting temperature and the ending temperature. Does this mean that you can find the difference between the averages by merely dividing the difference between the starting and ending temperatures by the number of days without bothering to even consider what the temperatures were in between? If so, why bother?
Donald Mitchell says:
May 17, 2013 at 1:17 pm
It’s today’s increase minus tonight’s decrease. Since tomorrow morning will not be the same temperature as this morning there’s a difference.
But I think it’s important to actually calculate how much it cools over night, this is the period that Co2 has to affect if it’s changing the planet. Average temp is a lousy proxy for the “Co2” effect.
“It doesn’t set at the poles in summer.” Nor throughout the spring.
John West says:
May 17, 2013 at 5:55 am
Considering a large portion of the Sun’s output is IR, CO2 acting as an insulator (by virtue of indiscriminant re-emission of IR effecting net transfer) there’s no reason it shouldn’t work both ways. Slowing Earth’s cooling as well as slowing the Sun’s warming of the Earth. In other words, any possible enhancement of the Greenhouse Effect could be a wash, making it a little warmer at night and a little cooler during the day.”
It DOES work both ways, but once there’s enough CO2 in the atmosphere already to absorb the 5% on so of the sun’s radiation in the CO2 range, adding additional CO2 will only increase the greenhouse effect, not augment the zero greenhouse effect .
For an atmosphere that absorbs all radiation from both the earth and the sun,
with a 1 layer atmosphere,, the sun sends X watts per square unit to the atmosphere
The atmosphere absorbs 2X units , X from the sun and X from the earth’s surface,
and radiates 2X units, X units back to space, X units back to the earth’s surface
The earth absorbs X units from the atmosphere, radiates X units back to the atmosphere.
So the net effect of the surface warming from an infrared absorbing atmosphere is the same as the effect of NO atmosphere.
Adding another absorbing layer to the atmosphere will still have no effect, so adding CO2 to the atmosphere will have a zero effect on surface radiation from the sun- that fraction can be ignored- only the fraction absorbed by the atmosphere from earth’s surface need be considered.
To be thorough, there’s also an “anti-greenhouse” effect. See
http://en.wikipedia.org/wiki/Anti-greenhouse_effect
The atmosphere of Titan is transluctant to some wavelengths, and translucent to part of the surface radiation.
Suppose Titan receives X watts per square unit from the sun, all absorbed by the atmosphere
the atmosphere absorbs X units from the sun, radiates 1/2X to space, 1/2 X to Titan’s surface.
Titan’s surface receives zero units from the sun and 1/2 X from the atmosphere, and radiates 1/2 X back to space ( with the atmosphere transparent to surface radiation).
This results in a surface cooler than a surface with NO atmosphere
You did okay until the last sentence; please explain how the two would behave oppositely WHEN the operative LWIR wavelengths are not that far apart for CO2 and H2O.
.
On a ‘micro’ scale –
A. Eventual transport of the ‘parcel’ (with sensible heat expressed as a temperature adjusted for the ‘thinner’ of air existing at a higher altitude) to another locale where it might be forced to descend, or form clouds at existing altitude perhaps even creating a Nimbus (rain) cloud or it might be forced to ascend further (due to real meteorological forcing or orographic lift) where it might form clouds etc.
B. Subsequent mixing with ‘other air’ where the heat energy then becomes ‘shared’ with the mixed-in air, and then onto A. above.
On a really ‘macro’ scale – Given the general circulation of a Hadley (Mid-level etc) cells, eventually all air parcels arrive in more northern (toward the poles) latitudes where the majority of the heat energy gets ‘dumped’ above say about 55 deg (or so) latitude where there is (on average) a net-loss of radiative energy into space, so it becomes important for Hadley, Mid-level and Polar cell circulations to physically transport in ‘warmer’ air masses (parcels) from equatorial and mid-level regions.
A little brush-up on Hadley cells et al: http://en.wikipedia.org/wiki/Hadley_cell
.
If you want to see real surface cooling going on, don’t go to Ohio.
Try the mid afternoon in one of the North African or Arabian deserts, for cooling that will grab you.
With surface Temperatures of maybe +60 deg. C (140 deg. F), the radiative cooling rate is about 1.8 times what it is in Ohio nights, and because the desert air is so dry, there isn’t much H2O in the atmosphere, to capture a lot of outgoing LWIR radiation.
Also at those Temperatures, the spectral peak wavelength is more like 8.8 microns, than 10.1 microns, so the 15 micron CO2 absorption band is driven even further away from the peak of the energy spectrum.
Well it may even be less that th 9.6 micron Ozone band which also blocks outgoing LWIR radiation.
The “atmospheric window”, is wide open in those hot daytime desert Temperatures.