Jeff Id of the Air Vent has offered me this study he just completed for the consideration of WUWT readers. Given the wide audience we have here, I’m sure it will get a rigorous review and inspection. Let’s see how well it stands up. – Anthony
Closest Station Antarctic Reconstruction
In my last alternate reconstruction of Antarctic temperature I used the covariance of satellite information to weight surface stations. While the reconstruction is reasonable I found that it distributed the trends too far from the stations. This prompted me to think of a way to weight stations by area as best as I can. The algorithm I employed uses only surface station data laid on the 5509 grid cell locations of the Steig satellite reconstruction.
This new reconstruction was designed to provide as good a correlation vs distance as possible and the best possible area weighting of trend, it can’t make a good looking picture though but for the first time we can see the spatial limitations of the data. The idea was to manipulate the data as little as possible to make where the trend comes from as clear, simple and properly weighted as possible.
The algorithm I came up with works like this.
Calculate the distance from each of 42 surface stations to 5509 satellite points store them in a matrix 42 x 5509.
For each of 5509 points find the closest station and copy the data to that location. If there are missing values infill those from the next closest station looking farther and farther until all NA’s are infilled.
This is what the spatial distribution of trends looks like.
Figure 1
You can see how the trends are copied to the points of each polygon from each surface station. There’s quite a bit of noise in the graph but it seems that like temperatures are grouped reasonably well together.
The code looks for the above plot takes about 20 minutes to run.
#calc distance from surface stations to sat grid points
dist=array(0,dim=c(5509,42))
for(i in 1:42)
{
dist[,i]=circledist(lat1=Info$surface$lat[i],lon1=Info$surface$lon[i],lat2=sat_coord[,2],lon2=sat_coord[,1])
}
Circledist is Steve McIntyres’s great circle function with slight modifications.
circledist =function(lat1,lon1,lat2,lon2,R=6372.795)
{
pi180=pi/180;
y= abs(lon2 -lon1)
y[y>180]=360-y[y>180]
y[y<= -180]= 360+y[y<= -180]
delta= y *pi180
fromlat=lat1*pi180;
tolat=lat2*pi180;
tolong=lon2*pi180
theta= 2* asin( sqrt( sin( (tolat- fromlat)/2 )^2 + cos(tolat)*cos(fromlat)* (sin(delta/2))^2 ))
circledist=R*theta
circledist
}
Then I wrote a function to get the closest distance greater than a value ‘mindist’ I pass. The first call for the grid number ‘ ind’, mindist is set to zero and the closest station is returned. If the closest station has missing data, I infill what it does have and pass the distance from the closest station to mindist and get the second closest station returned. The process is repeated until all values are filled.
getnextclosestdistance = function(ind=0,mindist=0)
{
tdist=dist[ind,]
while(min(tdist)<=mindist)
{
mind=min(tdist)
if (mind<=mindist)
{
tdist=tdist[- (which(tdist == min(tdist), arr.ind = TRUE)[1])]
}
}
g= which(dist[ind,] == min(tdist), arr.ind = TRUE)[1]
g
}
This is the loop function that fills the array.
recon=array(NA,dim=c(600,5509))
recon=ts(recon,start=1957,deltat=1/12)
for (i in 1:5509)
{
lastdist=0
while(sum(is.na(recon[,i]))>0)
{
dd=getnextclosestdistance(i,mindist=lastdist)
lastdist=dist[i,dd]
mask = is.na(recon[,i])
recon[mask,i]=anomalies$surface[mask,dd]
print (paste(i,lastdist))
}
}
After that all that’s left is the plotting algorithms by RomanM SteveM and Jeff C which I’ve shown before.
The next graph is the trend calculated from all 5509 grid points.
Figure 2
The trend is again positive by 0.052 C/Decade, this time it is on the outer edge of the stated 95% confidence interval of Steig09 of 12 +/- 0.07C/Decade.
Like before I also looked at the trend from 1967 – 2007.
Figure 3
Figure 4
So from this reconstruction temperatures have dropped since 1967 at an average rate of 0.31 C/Decade. These results are similar to my previous reconstruction which looks like this.
The Antarctic, an engineers reconstruction.
Figure 5
Figure 6
And from 1967 – 2007
Figure 7
Figure 8
While I was initially happy with the engineers reconstruction, I found that station trends were not well localized by linear correlation weighting. (The correlation vs distance was not good) While peninsula station information stayed localized, the rest of the continent spread widely.
The trends shown match my last reconstruction reasonably well but in my opinion these are of superior quality.
Certainly the Antarctic temperatures have been flat or insignificantly cooling/warming in general for the last 40 years while 50 years ago there were lower temps recorded causing a very slight upslope in the 50 year trend. This is confirmed by the fact that sea ice has grown during the last 30 years among other observations.
The Steig 09 paper seems to be an artifact of the mathematics more than an actual trend. Amundsen Scott is the south pole data. The surface measurement is visually clean and has a downtrend for the full length of the data. This cooling is represented by the blue polygon in the center of the antarctic in this reconstruction.
TCO keeps asking me if I’ll post a trend higher than Steig. Every reconstruction I’ve done has reduced the trend from Steig 09. Every change no matter how small has resulted in a trend reduction from Steig 09, even the attempt to match Steig 09 has resulted in a slight trend reduction. I’ll say it now for the first time. In my opinion the paper is flawed and has an exaggerated warming trend due to bad mathematics. Temperature distributions on the continent are a result of artifacts in RegEM and not supported by the natural weather patterns as they were presented.
As an example which is pretty clear. Steig’s paper shows warming across the entire Antarctic. Here’s a plot of the ground data at the south pole.
Figure 9
A reconstruction cannot ignore a trend this strong. So TCO, it isn’t up to me. As Gavin likes to say, the data is the data. This data just cannot support Steig’s conclusions.
Sorry to feed the troll but:
“By 1904, Arrhenius became concerned with rapid increases in anthropogenic carbon emissions and recognized that “the slight percentage of carbonic acid in the atmosphere may, by the advances of industry, be changed to a noticeable degree in the course of a few centuries.” He eventually made the suggestion that an increase in atmospheric carbon dioxide due to the burning of fossil fuels could be beneficial, making the Earth’s climates “more equable,” stimulating plant growth, and providing more food for a larger population. This view differs radically from current concerns over the harmful effects of a global warming caused by industrial emissions and deforestation. ”
http://earthobservatory.nasa.gov/Features/Arrhenius/arrhenius_3.php
Jeff,
First – good work.
What I would like to know is which instrument has the greater accuracy and precision – the satellites or the stations? Given the number of data points a satellite can measure in a short time I would assume the satellite is better at covering a continent (5500+ data points) than a few stations (42). In addition, the satellite data doesn’t lose its accuracy with distance like the ground stations do. So while you CAN interpolate, the question is whether you should – doesn’t this just add noise to clean satellite data?
Here’s the point. Someone should check the satellite accuracy relative to the stations (I am assuming the satellite is more accurate over distance and time). If the satellite data for the station region maps well with the station data itself (I would assume either a bias at a station or bouncing due to less precision in the measurement) then you know the raw satellite data is the best you will ever get. This is a simple cross calibration test to make sure the satellite is performing well. Interpolating coarser station data and merging it with satellite data only reduces this very expensive accuracy.
And interpolation can lead to mathematical errors which always (and not surprisingly) lean towards global warming.
My view is don’t mix imprecise data with precise data unless you are filling holes in the precise data. Clearly this is not the case. This interpolation exercise is trying to fill holes in the imprecise data, which simply muddies the sat data.
More on my views here if interested:
http://strata-sphere.com/blog/index.php/archives/8677
Cheers, AJStrata
Great work (and website: I always learn a lot here). I agree with Holtquist and Wendt that an overlay of continental USA would help the general reader “get” the absurdity of trying to extract a meaningful picture of temperature, and trends in same, from such sparse datasets. Agree also that altitude adjustment could be huge. I used to live in Denver area. I could play golf in shirt sleeves, then drive an hour and ski. Should I have been extrapolating the temperature dataset of the golf course onto the ski slope? It was effectively another planet. Did Steig take that into account?
To Perry Debell. Re: “Thus Jack, in an incredibly short geologic time, the flawed works of both Svante Arhennius and Norman Newell will be consigned to the
‘ department of unusually stupid ideas,’ ” The Geological Society of America has published well balanced reasons why we’re now living in the Anthropocene Epoch. Since Arhennisu and Newell are both dead, are you claiming the world’s most prestigious geological society is also stupid ? ~snip~
Jack,
Maybe you could explain why C02 has been proven to not trap IR radiation in sufficient quantity to create a ‘green house’ effect – which is not a radiation driven process in the first place. Green House effects are trapped air which doesn’t allow convective removal of the heat.
Have your vaunted AWG scientists been able to show how CO2 stops air from transferring heat through convection? Maybe you should bone up on some science instead of PR. Try here
http://arxiv.org/pdf/0707.1161v4
and here
http://strata-sphere.com/blog/index.php/archives/8430
For starters
AJStrata
Antarctica did not acquire a permanent galcial environment until long after it had arrived in the Antarctic Circle. It’s climate upon arrival and long afterwards within the Antarctic Circle during the Mesozoic was typically cool temperate with prolific flora and fauna communities, including extensive rain forests. As recently as only 14 million years ago Antarctica was still warm enough to support the environment of a tundra. The present day glacial environment of the Antarctic began very recently in the paleogeographic timeline, and long long after continental drift had already positioned Antarctica in the Antarctic Circle at the South Pole.
Hooray for engineers. Unless you want your bridge to fall down, best to stick with just the facts … Why do all these alarmists dataset analysis have the same smell?
A story from the telegraph
“Arctic will be ice-free within a decade”
http://www.telegraph.co.uk/earth/earthnews/5116352/Arctic-will-be-ice-free-within-a-decade.html
Walt Meier, research scientist at the National Snow and Ice Data; “Most people would agree it is not a matter of if we lose the summer sea ice but when,”
Can’t wait for their excuses
There’s also a short message from Pen Haddow on the video
I’d like to see a more precise vocabulary used. Measurements are “data”. Interpolations are not “in-filled data” or “reconstructed data” or any sort of “data”; they remain interpolations.
Malcom, you’re right!
Scant data (Antarctica) or very coarse proxy data (tree rings) produce curves that have huge margins of uncertainity, and thus allow data manipulators and fudgers to draw the curves they want.
What we do know is that temperatures and sea levels have been going up for 18,000 years, and so that even the modestly ncreasing rates of today are nothing new.
Curves drawn with scant or rough data can neither be proven nor disputed.
The temperatures of the antarctica peninsula are explainable, apart of its northward projection, because the temperatures in the SH latitudes do not correspond to the temperatures at the same latitudes of the NH, because there is a wider ocean in front of SA coasts, then because the heat of the southern seas cool down there and having cooled down there go northwards, named as the Humboldt´s current along the coasts of SA up to the equator. When an el Nino appears, this appears as a counter current reaching more southern latitudes as the stronger it is.
It would be interesting to know if the higher temperature data of the peninsula it is or it is not concentrated around the 1997-1998 el Nino.
Unless of coarse historical observations show to the contrary (i.e. frozen English channels, farmers in Greenland, wine in England etc.).
Since Arhennisu and Newell are both dead, are you claiming the world’s most prestigious geological society is also stupid ?
Are you saying that is is impossible that they might be?
Justin Sane:
See http://en.wikipedia.org/wiki/Vostok,_Antarctica
Unedited data shows, not surprisingly, a macro cycle of warming/cooling. However, at the Industrial Age, the warming increases significantly. Again no surprisingly, religious naysayers conveniently lop off the far right section of the original Vostok data to make it appear as if history stopped about 200 years ago. That disingenuous chart is all over the internet.
Pamela Gray:
Continental drift does not answer everything. There is evidence to support violent shifting of the Earth’s orientation, whether by axis movement or crustal displacement. Per the latter, conventional geologists tend to dismiss Charles Hapgood out of hand, but I’m betting he’s closer to the truth than they are.
Matt Bennett (23:29:02) :
“which any sensible visitor from elsewhere in the galaxy would undoubtedly recommend”
When you next see them, would you please inquire about that fusion problem – we can’t seem to work it out quite yet and could use a little help.
“as mandatory for prolonged planetary survival”
Since our planet is apparently a living being, I’m curious if you could ask it just what it thinks of rap music. Oh, and see what you can do about those pesky volcanoes. Thanks!
Just a technical point that might make your task simpler:
You can choose a projection of the South Pole region that minimizes distance distortion and allows you to calculate distances with the simple Cartesian formula (i.e. Pythagoras). Thus, you could dispense with the great circle stuff.
This sort of analysis is routine within a lot of GIS (geographic information system) applications. You might find them an interesting addition to your toolbox.
Justin Sane (19:09:42)
and
Benjamin P. (20:39:20)
Check out this story:
http://news.bbc.co.uk/1/hi/sci/tech/6276576.stm
Is this surprising to some people? Why should Greenland or Antarctica have uniform weather over time?
Jeff Id
Complements on your graph. It very clearly shows the major variations and emphasizes how few stations there are actually providing data.
Shown this way, the warming trend in the northwest tip is clearly very different from the rest of West Antarctica.
I encourage you to write a letter to Nature highlighting the major differences that your found. That the central cooling over the north pole may be due to the ozone hole and/or changes in cosmic rays with the earth’s magnetic field impacting the clouds.
Did you notice how Mr. Century spoke of the correlation between human population and Co2 rise. Stopping at that point because the next logical extension would be a correlation between C02 rise and temperature rise. He stopped because he would then have to admit there is no correlation as temperature is not rising as per C02 theory. You have to admire his faith, though. It takes a lot of faith to deny all that science stuff.
Jeff
Have you investigated the literature on “Kriging”? This is a mining engineer’s/geologist’s infill method of estimating overall assay data from drill hole intersections of an ore body – particularly sheet-like veins (Krige was a South African mining engineer). The method uses a variogram approach rather than covariance. Here is a generalized development and application of it from a thesis.
http://www.nbb.cornell.edu/neurobio/land/OldStudentProjects/cs490-94to95/clang/kriging.html#intro
The “nugget effect” referred to is sporadic high grade intersections, which are probably not be an issue for your type of problem. The Kriging method has been well tested since you start with estimating the reserves, say, of gold and then you end up mining it and finding the real value. It might be interesting to try it first using only the ground stations – possibly overprinting a variation function grid based on latitude and topographic altitude which places Vostok as the coldest centre on those counts.
“Oh, and a seismic shift in energy policy to renewables (which any sensible visitor from elsewhere in the galaxy would undoubtedly recommend as mandatory for prolonged planetary survival)…”
The extragalacticals undoubtedly arrived on a cosmic ray powered sailing vessel. Hmmmm… I wonder how they do that whole escape velocity thing. Maybe they just stay in orbit and let a ladder down to the surface.
To David Harrington. RE: “Since Arhennius and Newell are both dead, are you
claiming the world’s most prestigious geological society is also stupid?”
And, to your question , David, “Are you saying that it is impossible that they (the GSA) might be?” My answer is definitely, no. For many good reasons, based on scientific observations and global wisdom, the Geological Society of America is absolutely right in publishing that we’re now living in the Anthropocene Epoch. But, by your asking that question suggests you are just geologically uninformed.
Check out the following source for climate history at the poles. The earliest ages are an unknown entity regarding the north pole area (no land there so no ice evidence). The south pole evidence of ice is missing but they may not be looking in the right place. By the time the land mass drifted from the southern hemisphere to the northern areas, it would have to cross the equator, leaving ice evidence in the dust, literally. And, the land that would have had ice evidence on it may now be molten core.
http://www.scotese.com/climate.htm
OT but I wonder if Hansen is involved in this as well?
More than 100 people have been arrested in Nottingham over a suspected plan to target a power station.
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Officers said they believed those arrested were planning to protest at nearby Ratcliffe-on-Soar power station.
A spokesman said “specialist equipment” had been found by officers who feared a threat to the safety of the site.
He said police thought there was a “serious threat” to the coal-fired power station, which is eight miles south-west of Nottingham.