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.
Kind of like the sea level rise thing. Not a whole lot going on.
The South Pole is as Scott & Amundsen left it: a real bear.
Perhaps Jeff Id could publish this as a challenge to Steig et. al. and see how it stands scrutiny by the scientific community.
I hate straight lines…
They always will remind me of Homer Simpson buying Pumpkin futures… they were going up and up (just before halloween), and “if this trend continues, we’ll be rich in 2 years!”
Nature doesn’t make straight lines.
Sure “it” does, quite often actually. Oh, are humans not natural?
Has anyone ever drilled an ice core to bedrock in Greenland or Antarctica that could show us when the first layers of ice were deposited in those locations? Would that not tell us the last time those areas were ice free?
Continental drift tells us when they were ice free. Once they arrived at or near the poles, ice was just the natural consequence of living at that address.
You gotta love engineers. Where would we be without them? They are are underrated and probably in many cases, underpaid for their worth.
Another cut-to-the-chase presentation.
Anthony. Batting 1000.
For many years the NY Times has been publishing, “Dot Earth,” a daily blog
managed by its science editor, Andrew Revkin. Every conceivable argument
by deniers of anthropogenic global warming have been routinely published
in “Dot Earth” and responded to by others. After 57 years as a global
petroleum geologist, my observation is most oilpatch professionals are rigid in their denial positions. The question is, WHY ?
Why?
Maybe…because there is plenty of data, direct observations, and failed climate model extrapolations…I won’t mention any names…MANN…that support the “denial” that long-term, disastrous warming is occurring?
Jack Century as far as I know, the ONLY thing AGW proponents have going is 1998. Draw a line from any year during or after the late 70’s trough to 1998 and it scares the uninformed.
Justin Sane: The Greenland ice cores were drilled to the bottom of the ice. They brought up dirt with temperate zone vegetation remains. I don’t remember the date though.
Correction: “savethesharks” not “svaethesharks” as shown above…or just Chris
What is “TCO”?
REPLY: He’s an omnipresent troll in climate blogs. His MO is foul langauge, insulting ad homs, occasional (admitted) drunken rants, and refusal to answer any questions posed to him. He occasionally has some good moments, but he tends to tire everyone out. He’s been mostly banned here though on occasion when he has something relevant to say I let the comment through. Lucia put him in her troll box, so did Steve McIntyre. There are some other places where he’s banned also.
He has taken quite a dislike to me, and regularly posts things about how stupid he thinks I am. It’s quite amusing.
– Anthony
@ur momisugly mr.artday (20:12:24) :
Is this what you are talking about?
http://www.sciencedaily.com/releases/2004/08/040816090439.htm
I can’t seem to find any follow up on that plant matter though, anyone have any info?
Ben
Justin Sane (19:09:42): found this from 1993, “When scientists from the University of Alaska Fairbanks hit bedrock under Greenland’s ice cap for the first time in history this summer, the event macic newspaper headlines around the country. The drill cut through 10,015 feet of glacial ice to grab a sample of bedrock and to pull out a core of ice more than 250,000 years old.”
from http://www.gi.alaska.edu/services/machineshop/Picodrillarticle.html
Pamela Gray (19:37:36), supposedly without the obliquity of the ecliptic that we now have, ie. if the plane of the equator was close to the plane of the orbit, there would be no ice caps. The theory is that a long dark period is needed to grow enough ice to stick year round; not without regard to ocean currents and temps, as well as ambient local atmospheric temps and moisture, in my mind.
This may be a minor point. To get the temperature at the 5500 gird points from the 42 surface stations, you ought to interpolate between surface stations, not use the nearest neighbor. The temperature is more likely to vary smoothly from one station to another. If station 1 is 1 degree and station 2 is 2 degrees then the point in the middle is more likely to be 1.5 degrees than either 1 or 2 degrees.
I don’t know if this would be a signifigant difference in this reconstruction, but it could.
CodeTech (18:53:44) : “I hate straight lines…They always will remind me of Homer Simpson buying Pumpkin futures… they were going up and up (just before halloween), and ‘if this trend continues, we’ll be rich in 2 years!’ Nature doesn’t make straight lines.
If you ever took Freshman Chemistry, you’d know that is false. Or Geology 100. Or Botany 101.
i’m going to be quite specific in my attempted observations :
ANYTIME anyone post code, I would suggest the following :
At the top of all code segments, identify the source language, compiler and compiler version and hardware code is running on.
This is particularly important wrt what comes next :
with respect to ( wrt ) code that does math ( calculations on integers ? / reals ? )
identify how ALL variables are declared so observer can determine number ranges that can be stored without over/underflow.
next, with respect to division ( / ) , multiplication ( * ) and built in function usage ( min ) it is, I suspect in this case, quite important to insure that calculations are robust regarding minimizing the loss of data or migration of data OR errors into, when there is LOOPING going on.
last, what it any, provisions for error handling exist with regards to checking for math problems ( to simplify a rather complex issue ) while calulating in loops ?
let there be NO doubt, the code snippits shown are THE MEAT of this entire presentation – if the author can shed some light here, I can try to look further into their robustness.
Jeff nice work. but have a look at this
http://www.climahom.eu/software/docs/Prezentation_T_homogenization.pdf
Basically approaches to in-filling data. he has software you can download, but
the presentation is pretty good stand alone.
2nd to the last para, please make that ” what, IF any ” …. sorry .
very interesting article !
Thank you Jeff for this well done real “peer review.”
I have a few questions though.
1.Due to the uneven distribution of surface stations can interpolations by proximity bias the data upwards?
2. As an alternative system would it be more accurate to make interpolations by distance from the pole in a sort of “bulls eye” pattern?
3. Are terrain and weather patterns taken into account with the interpolations?
4. Have surface station changes in placement and instrumentation been accounted for?
5. If changing the start date and end date changes the direction of the trend, were the dates “cherry picked”?
I guess the bottom line is that it is hard to take as Gospel the original Steig paper when the result can be so easily manipulated.
Thank you again Jeff for your great work!
I wonder to myself ‘Self, why not measure deviations from high/low daily temps as well?” Weather is not irrelevant, so why only measure the deviation from some arbitrary average?
Jack Century (19:49:42) : “For many years the NY Times has been publishing, “Dot Earth,” a daily blog managed by its science editor, Andrew Revkin. Every conceivable argument by deniers of anthropogenic global warming have been routinely published in “Dot Earth” and responded to by others. After 57 years as a global petroleum geologist, my observation is most oilpatch professionals are rigid in their denial positions. The question is, WHY ?”
Possibly because they are much better educated than the average MSM propaganda victim. They are trained in Physics, Chemistry, Geology, and Mathematics. Consequently, it’s a lot harder to pull the wool over their eyes.
Jeff,
My first issue is with the term “reconstruction”, which I know you are not the one to have used first. Thus, this is a general comment and in no way meant to be a shot at what you have done. Steig and others have popularized this term. However, it seems to be this sort of activity takes a limited amount of data by location and fills in a great deal of missing information. Might it be better to call this “constructing” temperatures where there were none before? (I’m not fond of the term “proactive” either, even though it seems to be very popular.)
Without searching for the location data I’m not certain of the distribution of the 42 surface stations. I seem to remember a majority were along or near the coast with only a few at higher elevations in the interior. One source has the highest elevation there as 4,897 meters with an area of about 14.2 M sq. km. The contiguous 48 states of the USA has a high elevation of
about 4,420 m. (Mt. Whitney) and is about 8.08 M sq. km. It would be revealing to overlay an Antarctica map with station locations on a partial North American map to illustrate for the reader just how challenging this temperature “construction” is from a geographical perspective.
Also, on that map you might have actual temperature reports, perhaps average summer and winter both. If there is an actual temperature in your article I missed it; all seem to be reported as anomalies.
The above two things would help the less familiar with this topic gain perspective on the issue.
I like the tone of the article. The work can be understood with a little effort while some other similar attempts require a couple of advanced degrees.
Justin Sane,
Antarctica’s Eastern ice cap is provable stable going back to between 14-22 million years ago, when South America separated and the circumpolar currents were established that shut off Antarctica largely from the rest of the worlds climate. The West Antarctic Ice Sheet is less stable largely because much of it is welded to bedrock below sea level, there is significant vulcanism in the west, and the penninsula is a weak point in the circumpolar current system. WAIS makes up 10% of the ice in Antarctica vs the EAIS.
Naish’s ice core data said that changes in the tilt of Earth’s rotational axis has played a major role in ocean warming that has driven repeated cycles of growth and retreat of the WAIS for the period in Earth’s history between 3 million and 5 million years ago.
Since the end of the last ice age, the WAIS has retreated 1200 km from its peak. This is a rather significant amount of ice, and ice that was bound to subsea bedrock out to a very significant distance from shore and to a significant depth.
Additionally, currently the continental plate below WAIS is depressed between 0.5-1.0 km due to the weight of the ice on top of it. This is really where folks start keying their alarmism, because where the WAIS is thickest is where the bedrock is most depressed due to the more massive weight, so there is a reverse slope to the center of the WAIS. Alarmists argue that once sea water undercuts the WAIS at the bedrock due to warming enough to get over the ridges, water will quickly flow down in accelerating degrees to undermine and infill the depression. The problem of course is that this completely ignores the hydrostatic pressure of the ice on top of the bedrock and the depth within the bedrock that the iceline reaches….