Guest Post by Willis Eschenbach
A while back in the US there was an ad for a hamburger chain. It featured an old lady who bought a competitor’s hamburger with a great big hamburger bun. But when she opened it up she asked …
I got to thinking about this in the context of whether there is any real danger in a degree or two of average temperature rise, or whether it’s a big bun with no beef. In my previous post, “Lies, Damned Lies, Statistics … and Graphs”, I closed by saying:
My conclusion? Move along, folks, nothing to see here …
A commenter took exception to this, saying
When talking about global average temperatures, tenths of a degree really do matter.
Now, if tenths of a degree changes over a century “matter” for the globe, they certainly must matter for parts of the globe.
So here’s your pop quiz for the day: Which US State warmed the most, which cooled the most, and by how much?
To answer this, I used the USHCN State Temperature Database. Here are my findings:
Figure 1. Temperature trends by state, USHCN data. Seven states cooled, and forty-one warmed.
The state that warmed the most was North Dakota (top center), which warmed 1.4°C per century. The state that cooled the most was Alabama (middle of three dark blue states, lower right). It cooled by 0.3°C/century.
To compare with my previous post, here’s a similar graph, of the decadal changes in North Dakota by month.
Figure 2. North Dakota decadal average temperatures by month, 1900-2009. Red line is the average for the decade 2000-2009. Photo is an old North Dakota farmhouse.
As with the US, for much of the year there is little change, and the warming is in November to February. Note that unlike the US, during that four months, the temperature of North Dakota is below freezing (32°F) …
Now, if tenths of a degree “matter”, if they are as important as the commenter claimed, we should have seen some problems in North Dakota. After all, it has warmed by 1.6°C since 1895. That’s almost three times the global average warming.
But somehow, I must have missed all of the headlines about the temperature calamities that have befallen the poor residents of the benighted state of North Dakota. I haven’t seen stories about them being “climate refugees”. I didn’t catch the newspaper articles about how it has been so hard on the farmers and the frogs. I am unaware of folks moving in droves to Alabama, which has cooled by -0.4° since 1895, and thus should be the natural refuge of those fleeing the thermal holocaust striking North Dakota.
In fact, I don’t remember seeing anything that would support the commenter’s claims that tenths of a degree are so important. North Dakota has warmed near the low end of the range forecast by the IPCC for the coming century, and there have been no problems at all that I can find. So I have to say, as I said before,
My conclusion? Move along, folks, nothing to see here … where’s the beef?
APPENDIX: R Code for the US Map
(I think this is turnkey. Sometimes WordPress puts in extra line breaks. If so, it is also available as a Word document here.)
The code requires that you download the USHCN Temperature Data cited above and save it as a “Comma Separated Values” (CSV) file. I downloaded it, opened it in Excel. I split it using “Text to Columns …” into the following columns, as detailed in the USHCN ReadMe file:
FILE FORMAT:
STATE-CODE 1-3 STATE-CODE as indicated in State Code Table above. Range of values is 001-110.
DIVISION-NUMBER 4 DIVISION NUMBER. Value is 0 which indicates an area-averaged element.
ELEMENT-CODE 5-6
02 = Temperature (adjusted for time of observation bias)
YEAR 7-10 This is the year of record. Range is 1895 to current
year processed.
JAN-VALUE 11-17 Monthly Temperature format: Range of values -50.00 to 140.00 degrees Fahrenheit. Decimals retain a position in the 7-character field. Missing values in the latest year are indicated by -99.90.
FEB-VALUE 18-24
MAR-VALUE 25-31
APR-VALUE 32-38
MAY-VALUE 39-45
JUNE-VALUE 46-52
JULY-VALUE 53-59
AUG-VALUE 60-66
SEPT-VALUE 67-73
OCT-VALUE 74-80
NOV-VALUE 81-87
DEC-VALUE 88-94
If that is too complex, the CSV file is here.
Here’s the R code:
# The code requires that you download
# the USHCN Temperature Data
# and save it as a "Comma Separated Values" (CSV) file.
# I downloaded it, opened it in Excel, and used
# "Save As ..." to save
# it as "USHCN temp.csv"
#Libraries needed
library("mapdata")
library("mapproj")
library("maps")
# Functions
regm =function(x) {lm(x~c(1:length(x)))[[1]][[2]]}
#Read in data
tempmat=read.csv('USHCN temp.csv')
# Replace no data code -99.9 with NA
tempmat[tempmat==-99.9]=NA
# split off actual temps
temps=tempmat[,5:16]
# calculate row averages
tempavg=apply(temps,1,FUN=mean)
# calculate trends in °C by state
temptrends=round(tapply(tempavg,as.factor(tempmat[,1]),regm)*100*5/9,2)
# split off states from regional and national
statetrends=temptrends[1:48]
#calculate ranges for colors
statemax=max(statetrends)
statemin=min(statetrends)
statefract=(statetrends-statemin)/staterange
#set color ramp
myramp=colorRamp(c("blue","white","yellow","orange","darkorange","red"))
# assign state colors
mycol=myramp(statefract)
# names of the states (north michigan is missing for ease of programming)
myregions=c("alabama", "arizona", "arkansas", "california", "colorado", "connecticut", "delaware",
"florida", "georgia", "idaho", "illinois", "indiana", "iowa", "kansas", "kentucky", "louisiana", "maine",
"maryland", "massachusetts:main", "michigan:south", "minnesota", "mississippi", "missouri", "montana", "nebraska",
"nevada", "new hampshire", "new jersey", "new mexico", "new york:main", "north carolina:main", "north dakota",
"ohio", "oklahoma", "oregon", "pennsylvania", "rhode island", "south carolina", "south dakota", "tennessee", "texas",
"utah", "vermont", "virginia:main", "washington:main", "west virginia", "wisconsin", "wyoming")
# draw map
par(mar=c(6.01,2.01,4.01,2.01))
return=map('state',regions=myregions, exact=T,projection='mercator',fill=T,
mar=c(5.01,8.01,4.01,2.01),col=rgb(mycol,maxColorValue=255),ylim=c(10,60))
# set up legend boxes
xlref=-.48
yb=.37
ht=.05
wd=.08
textoff=.025
# assign legend labels
mylabels=round(seq(from=statemin,by=staterange/12,length.out=13),2)
#draw legend
myindex=0
for (i in seq(from=xlref,by=wd,length.out=12)){
xl=i
xr=xl+wd
yt=yb+ht
rectcolor=myramp(myindex/11)
rect(xl,yb,xr,yt,col=rgb(rectcolor,maxColorValue=255))
text(xl,yb-textoff,mylabels[myindex+1],cex=.65)
myindex=myindex+1
}
text(xl+wd,yb-textoff,mylabels[myindex+1],cex=.65)
# add annotations
text(0,1.08,"US Temperature Trends (°C/century)")
text(0,1.03,"USHCN Dataset, 1895-2009",cex=.8)
Willis,
It’s hotter’n hell down here in Atlanta during the summer, and we are not supposed to have winter, according to the chamber of commerce. So, don’t confuse us with facts. Our minds are made up.
The hysteria caused by AGW promoters over temperatures is not really any different fromthe hysteria caused by eugenics promoters over perceived racial impurity issues.
GaryW (07:36:23) :
“Now picture that sailor on the deck of a rolling square masted sailing ship pulling a thermometer out of canvas bucket of sea water to take a reading by the light of a swinging oil lantern. That is what we are using as our base for a one degree F temperature rise per century.”
This is an excellent point, given NOAA’s famous criticism of the surface stations project:
“…as many different individuals participated in the site evaluations, with varying levels of expertise, the degree of standardization and producibility of this process is unknown.”
I’m sure all of those early 20th century ships, on which the sea surface temperature database is based, were just teeming with “qualified” climate observers…
OT, I guess, but this belongs in the synchronicity or “spooky coincidence” file (if you have one):
When I was writing a comment to your last post suggesting that the background image of your “scary” graph might be Homer Simpson reenacting Edvard Munch’s painting “The Scream”, I wondered whether to also point out the enviro-climatic significance of the painting – i.e., that many think the nightmarishly red sky that Munch actually witnessed in 1883 and that inspired the painting with its screaming figure representing nature in torment was probably caused by the cataclysmic eruption of the Krakatoa volcano. I decided against because its relevance to the topic was marginal and those who would likely find it interesting would probably already know about it.
Then, by some fortuitous coincidence, the volcano Eyjafjallajokull erupts in Iceland causing mayhem to air traffic and bloody red sunsets in parts of Europe. And the Daily Mail publishes this radar picture of the volcano to reveal a spooky similarity of its three craters with the screaming face in Munch’s picture:
http://i.dailymail.co.uk/i/pix/2010/04/16/article-1266403-0928E978000005DC-548_964x571.jpg
The full background story is here:
http://www.dailymail.co.uk/sciencetech/article-1266403/Iceland-volcano-space-The-dramatic-ash-plume-engulfing-Britain-seen-above.html
GaryW,
The problem with your logic concerning the accuracy of old thermometers is that we are talking about an average of thousands and thousands of readings. The accuracy of the individual measurements is of far less importance when you are talking about an average.
For example, imagine that you are taking a census and averaging the age of a population. You will probably only ask people their age in years, not years and months, so there is a +/- margin of error of 11 months, or almost one year, for any individual. But when you compute the average age for a population of thousands of people, you will wind up with the exact same answer that you would have gotten if you had asked people for their age to the nearest month. The only reason why this would not happen would be due to disproportionate things like more people having been born in the winter months.
In the case of temperature readings, there is no reason whatsoever to believe that any set of readings would be consistently misread in one particular direction at any time.
And the fact that you got an average age of, say, 23.4 years for one population versus 25.6 for another is not incorrect simply because it appears that you are extending the average age to a degree of accuracy that exceeds your original, individual measurements. Quite to the contrary, using decimals is very appropriate, and the margin of error involved depends not on the accuracy of the individual measurements, but rather the size of the population that you used to compute your average.
Merrick,
“I think you need to rethink your hypothesis or your source. . . Since the surface of the earth in the northern hemisphere is decidedly colder during the nothern hemisphere winter than it is in the northern hemisphere summer your statement above is an absolute non-starter. ”
Well then, perhaps you can explain why the models all predict the main effect of GHG’s to be less cold winters, not hotter summers?
actually fargo nd has been having record spring floods for about a decade now, but i don’t trust the temperature map anyway. what happened to michigan there? are texas and kentucky off the radar scope or light blue? i liked the premise and agree with the sentiment…
Alan D McIntire (07:31:18) :
If most of the warming was due to increased use of energy in urban areas, a majority of the warming over the last century would be at night and during the winter.
Energy use is a small part of UHI, by my rough estimates probably 10% – pavement and structures are the biggest part. They collect energy better than natural surfaces, express it back into the atmosphere only through radiation and conduction (temperature) where natural surfaces release most through transpiration and evaporation (humidity), and have much higher thermal capacity (especially pavement).
Part of that extra warming in the western states would be due to increased irrigation. I suspect the hottest temperatures have gone down thanks to the latent heat of evaporation, and nighttime temperatures have gone up more than daytime temperatures have gone down- thanks to condensation of water vapor at night.
I believe there was a paper by Christy and Spencer (I found it referenced in one of Pielke’s papers), that described irrigation in California as resulting in lower daytime temps but higher nighttime temps than an equivalent, un-irrigated environment close by. I believe there was another paper by someone else that found the same results in New Mexico.
Scott (07:32:17) :
I think this posting makes me think more about thermal energy and its importance. Most of the heating in North Dakota was in the winter – when it’s very cold. When it’s that cold, the absolute humidity is much lower and much of the surface water is frozen.
Lower humidity and frozen water have one notable thing in common – they both LOWER the heat capacity of the system. Thus, it takes a much smaller energy change for ND to warm up 1 C in the winter than it does for AL to cool 1 C in the summer (or anytime during the year I’d imagine).
Temperature, by itself, tells us little about atmospheric energy – it’s just a proxy. There was a good conversation on this topic after the Meier post here: http://wattsupwiththat.com/2010/04/08/nsidcs-walt-meier-responds-to-willis/
Now obviously more stuff is present in the system than just water (and its vapor), but I’d guess that rock/asphalt/etc has a fairly constant heat capacity with respect to temperature compared to water.
When looking at a surface in respect to the atmosphere (climate) it can get very complex, but when I look at anthropogenic forcings of the climate… surface changes have not received their proper due. What’s important to consider is what was there before and what replaced it.
If, for example, you replace a field with a parking lot there are some important differences in place other than thermal capacity:
One is surface area – 1m2 topographic is not 1m2 surface area from an atmosphere standpoint when you’re talking about leaves or grass – they’re more like radiator fins. Mainstream climate science seems to say the only change of significance to their current analysis is albedo, which means that replacing a field of 10% albedo with concrete at 20+% would have a cooling effect. Evaporative effect is a big deal too. The one really interesting thing that not many people think about – pointed out by Anna V recently – is that like any living thing, plants work to maintain an optimal internal temperature to perform photosynthesis – they do this passively by clustering leaves in cold environments to hold heat in better, and actively through controlled transpiration.
To make a long story short, we all know what it feels like to walk on an asphalt road during the summer… and how roads are the last surfaces to hold snow and the first to melt during the winter. In the US we have paved 61,000 square miles – which is roughly the state of Wisconsin… and that’s only accounting for roads and parking lots.
Has anyone given any thinking to what temperature delta between the building and the MMTS does? How much would it throw stuff off to a MMTS that is 10′ from a building if the temp difference is, say 20C vs a temp difference of, say, 40C?
I say that looking at those Jan/Feb numbers for ND. I assure you most sincerely that the temp differences between the buildings and the MMTS location are much larger in Jan and Feb in ND than they are the entire rest of the year.
So I guess what I’m asking is does MMTS micro-siting bias get worse the larger the temp delta is between the “polluting building” and what the environment temp of the MMTS would have been if the building wasn’t there?
Willis;
You’re certainly in good company with this post…….Richard lindzen has
been saying the same thing for quite awhile now…….of course since he’s
an academic type, it takes him a lot longer to say it.
Richard Graves (06:31:13) :
urederra (04:05:36) :
This from The Guardian….
Global warming monitoring needs to find ‘missing heat’, say scientists
Kevin Trenberth and John Fasullo, climate scientists at the National Centre for Atmospheric Research in Boulder, Colorado, say that only about half of the heat believed to have built up in the Earth in recent years can be accounted for. New instruments are needed to locate and monitor this missing heat, they say, which could be storing up trouble for the future.
Give them funding quick!
———————
That is the controversial “dark heat” Al Gore and the climatologists have discovered, sort of: they can plot its effects, but it’s hiding in nature and can’t be measured directly 🙂 “Blessed are they who haven’t seen and yet believe.”
Looking at my question again it looks pretty obvious. But I’m talking about monthly changes in temp deltas. So in January maybe the average difference is 40C, but in July the average difference is only 15C. The first has got to pollute a too-close MMTS more than the second, right? And then you get a graph that looks just like the one Willis is showing.
Montgomery AL is so hot that my mother claims it was built over the gates of Hell. It could use whatever cooling it got.
David S (06:41:21)- When it’s -38 degrees anything, the last thing you want to do is waste alcohol on measuring temperature. Incidentally, does Scotch work in thermometers? I bet if I marketed a clear flask, with a standard Centigrade scale on the side, Global Warming would be history.
Merrick, Vincent, urederra:
I had a good post in response to urederra’s comment on GHG effects, but for some reason it never made it (deleted? marked as spam? Internet gobbler got it?).
But to repeat myself, the problem with urederra’s original statement, and Merrick’s interpretation, is that CO2 does not get it’s “heat” from the sun. CO2 is primarily transparent to the wavelengths of electromagnetic radiation received by the earth from the sun. This energy heats the surface.
The surface then emits infrared radiation, which is absorbed by greenhouse gases like CO2 and H2O. It is quickly re-emitted in all directions. What goes down warms the ground. What goes sideways warms the air. What goes up warms the air above, or eventually makes it back into space.
The temperature that you feel during the daytime is certainly very dependent on the amount of sunlight received, which is affected by the angle of incidence of the sun (lower in winter), length of the day (shorter in winter), and other factors like cloud cover.
But when night falls, the amount of heat retained by the earth and atmosphere, as opposed to quickly escaping back into space, depends on greenhouse gases. For this reason, the effects of GHGs are more strongly felt in winter, and at night.
To use a familiar analogy, most deserts (which by definition are arid and so have little moisture in the air) get very hot during the day, but cool dramatically at night. In contrast, places like the southeast United States are very humid. Georgia is at the same latitude as the Sahara desert, and so gets the same insolation year round, but nights there are hot and humid. People sit on the porch after dark fanning themselves, because the GHG effect of the water vapor in the atmosphere keeps the air warm long after the sun sets.
This is still true in the winter, even though there is less water vapor in the atmosphere, and as Vincent pointed out, the effects of CO2 become even more relevant in cases where humidity is low (arid regions, winter, etc.).
“But somehow, I must have missed all of the headlines about the temperature calamities that have befallen the poor residents of the benighted state of North Dakota.”
Yeah, Willis, you missed the record floods of recent years.
“Where’s the heat?” — Maybe Minnesotans for Global Warming could produce a spoof commercial of a LOL (Little Old Lady) going into Al Gore’s Restaurant and asking that question.
Maybe they could work in the line, “Fried with that?”
geo (08:56:27) :
…I’m talking about monthly changes in temp deltas. So in January maybe the average difference is 40C, but in July the average difference is only 15C. The first has got to pollute a too-close MMTS more than the second, right? And then you get a graph that looks just like the one Willis is showing.
I’m not sure if microclimate corruption can really explain all of it – due to wind and convection trying to understand the spatial effects – even for putting asphalt down under a station – are not an easy equation. If you get a hold of Pielke’s work he spends a lot of time analyzing boundary layer conditions in the atmosphere and how they interact with stations – it’s really friggin complex.
I think, in this case, coming at the problem from the other direction is probably best, as Spencer did here: http://wattsupwiththat.com/2010/03/16/spencer-direct-evidence-that-most-u-s-warming-since-1973-could-be-spurious/
urederra (04:05:36) :
This from The Guardian….
Global warming monitoring needs to find ‘missing heat’, say scientists
Kevin Trenberth apparently can’t account for 50% of the Earths heat buildup. I would bet he thinks “it’s a shame that he can’t”.
Strange, according to Willis, Colorado has been heating up!
sphaerica (09:37:52) :
But when night falls, the amount of heat retained by the earth and atmosphere, as opposed to quickly escaping back into space, depends on greenhouse gases. For this reason, the effects of GHGs are more strongly felt in winter, and at night.
Overall nice post – just a minor nit… but are you implying that all of the winter and Tmin trends are due to GHGs?
If so, don’t you think that maybe 61,000 square miles of pavement in the US and documented effects of irrigation on Tmin might have a *little* to do with it too?
Is it possible to chart the highs and lows separately?
I know, it’s possible — does the data exist to chart the highs and lows separately? How charting at different times of day? Is there data there for that?
I wonder how these temp changes would compare with population changes. Just looking, I can see it wouldn’t have an r sq. near .9, but I suspect it would show some relationship.
I have not read all of the posts, but want to add that:
Warming is essentially less cooling in the winter. The hot parts of summer have not gotten hotter.
So there would be no warming refugees, just fewer corpsicles to locate in the Spring. That’s a good thing.
Russ Blake (09:54:38) :
Kevin Trenberth apparently can’t account for 50% of the Earths heat buildup.
If these guys had ever taken a macroeconomics course from a good professor they’d know what their problem is – it’s really not difficult.
They’re missing a REALLY big variable (more likely variables) from their equation. While not exactly like this we could, more or less, recreate their work as follows: Take the temperature trend from 1980-2000, assume that CO2/GHGs have a direct causal relationship with temperature, assume water vapor content is driven by temperature which is driven by CO2/GHGs, and assume that CO2/GHGs are really the only variable changing (everything else changes in reaction to it – the system, after all, was in balance before we came along right?). From this you work out the power of the mechanisms and feedback (sensitivity) – a relatively simple calculation described here: http://brneurosci.org/co2.html
Since CO2/GHGs continue to increase after 2000, the derived sensitivity implies there has to be more warming than observed – and now that OHC has stopped increasing they can’t say it’s going into the ocean. Make no mistake – this indicates a very serious issue with their theoretical model.
In respone to NickB.
You’re right, some of that UHI warming will be due to less evaporation from streets, buildings, and sidewalks than from grassy land. A better measure of temperatures should include humidity- I think Pielke Sr addressed this issue.
Back to temperatures, the world’s population has quadrupled,
from about 1.6 billion to about
6.5 billion in the last century. , and urban populations have more
than quadrupled. The world’s energy use has gone up by a factor of
10 over the last century, again most of that increase being in
urban areas. I get a rough estimate of 0.26 watts per square meter
heat energy produced. Assuming that 3% of the land surface is
Urban, and 30% of the earth’s surface is land, I get
29 watts per square meter assuming most of that heat is produced in
urban areas. And that has
gone up by a factor of 10 since 1900- implying an increase from 2.9 to 29 watts. Since most of our temperature measurement is in populated areas, i think that 26 watt increase would have a significant effect on temperature measurements.