Nov 27 2009
Colleague Of Mann, Jones, et al Knew They Were Faking AGW
I knew the AGW cult would crack open under serious scrutiny, but this is stunning even to me:
Nothing about the revelations surprises me. I have maintained email correspondence with most of these scientists for many years, and I know several personally. I long ago realized that they were faking the whole exercise.
When you enter into a debate with any of them, they always stop cold when you ask an awkward question. This applies even when you write to a government department or a member of Parliament. I and many of my friends have grown accustomed to our failure to publish and to lecture, and to the rejection of our comments submitted prior to every IPCC report.
But only recently did I realize that I had evidence of their fraud in my possession almost from the birth of my interest in the subject.
Expect a lot more evidence and revelations to come to light and rock Copenhagen to its foundations. This is just beginning. The Climategate Gang stepped on a lot of toes, bullied a lot of good scientists and made a lot of statistical mistakes. There will not be a huge wave running to their defense.
Perhaps “Hockey Team” more appropriate than “Climategate Gang”–the “-gate” label seems too over used ;o)
AJ: great work!
Here are a few gems I found in the programming files.
recon_mann.pro
Computes regressions on full, high and low pass MEAN timeseries of MXD anomalies against full NH temperatures.
THIS IS FOR THE Mann et al. reconstruction CALIBRATES IT AGAINST THE LAND-ONLY TEMPERATURES NORTH OF 20 N IN FACT, I NOW HAVE AN ANNUAL LAND-ONLY NORTH OF 20N VERSION OF MANN, SO I CAN CALIBRATE THIS TOO – WHICH MEANS I’m ONLY ALTERING THE SEASON
doland=1 0=use Mann NH 1=use Mann land north of 20N
Specify period over which to compute the regressions (stop in 1940 to avoid the decline
perst=1881.
peren=1960.
openw,1,’recon’+string(doland+2,format='(I1)’)+’_mann.out’
thalf=10.
recon_jones.pro
Computes regressions on full, high and low pass MEAN timeseries of MXD anomalies against full NH temperatures.
THIS IS FOR THE Jones NH10 reconstruction CALIBRATES IT AGAINST THE LAND-ONLY TEMPERATURES NORTH OF 20 N
Specify period over which to compute the regressions (stop in 1940 to avoid the decline
perst=1881.
peren=1960.
calibrate_correctmxd.pro
We have previously (calibrate_mxd.pro) calibrated the high-pass filtered MXD over 1911-1990, applied the calibration to unfiltered MXD data (which gives a zero mean over 1881-1960) after extending the calibration to boxes
without temperature data (pl_calibmxd1.pro). We have identified and artificially removed (i.e. corrected) the decline in this calibrated data set. We now recalibrate this corrected calibrated dataset against the unfiltered 1911-1990 temperature data, and apply the same calibration to the corrected and uncorrected calibrated MXD data.
mxd_pcr_localtemp.pro
Tries to reconstruct Apr-Sep temperatures, on a box-by-box basis, from the EOFs of the MXD data set. This is PCR, although PCs are used as predictors but not as predictands. This PCR-infilling must be done for a number of periods, with different EOFs for each period (due to different spatial
coverage). *BUT* don’t do special PCR for the modern period (post-1976), since they won’t be used due to the decline/correction problem. Certain boxes that appear to reconstruct well are “manually” removed because they are isolated and away from any trees.
obsj04_f7.pro
DOESN’T ACTUALLY SAVE ANY RESULTS, JUST MAKES THE PLOTS!!!!
Reads in the gridded Hugershoff MXD data, plus the regional age-banded and regional Hugershoff series and attempts to adapt the gridded Hugershoff data to have the same low-frequency variability as the ABD regions.
The procedure is as follows:
HUGREG=Hugershoff regions, ABDREG=age-banded regions, HUGGRID=Hugershoff grid The calibrated (uncorrected) versions of all these data sets are used. However, the same adjustment is then applied to the corrected version of the grid Hugershoff data, so that both uncorrected and corrected versions are available with the appropriate low frequency variability. There is some ambiguity during the modern period here, however, because the corrected version has already been artificially adjusted to reproduce the largest scales of observed temperature over recent decades – so a new adjustment would be unwelcome. Therefore, the adjustment term is scaled back towards zero when being applied to the corrected data set, so that it is linearly interpolated from its 1950 value to zero at 1970 and kept at zero thereafter.
(1) Compute regional means of HUGGRID to (hopefully) confirm that they give a reasonably good match to HUGREG. If so, then for the remainder of this routine, HUGREG is replaced by the regional means of HUGGRID.
(2) For each region, low-pass filter (30-yr) both HUGREG and ABDREG, and difference them. This is the additional low frequency information that the Hugershoff data set is missing.
(3) To each grid box in HUGGRID, add on a Gaussian-distance-weighted mean of nearby regional low frequency, assuming that the low frequency information obtained from (2) applies to a point central to each region.
(4) Compute regional means of the adjusted HUGGRID and confirm that they give a reasonable match to ABDREG.
For some regions (CAS, TIBP) the low frequency signal is set to zero because the gridded data gives a quite different time series than either of the regional-mean series. Also, for those series limited by the availability of age-banded results, I set all values from 1400 to 50 years prior to the first non-missing value to zero, and then linearly interpolate this 50 years
and any other gaps with missing values. Any missing values at the end of the series are filled in by repeating the final non-missing value.
SBD
Still wondering what the purpose of the “Cheat” variable is in:
cru-code/linux/mod/ghcnrefiter.f90
It appears to be a bias that is added to a calculation and replaces an array variable.
The code is a bloody nightmare. Thanks CP and SBD for looking at it. I will probably start collecting these gems into a post on reader observations (once I finished analyzing those CRU temp graphs for the world).
Just as long as there is a huge wave running to put these con men into prison.
Good work AJ.
Good work AJ……I told my friend at the park that a NASA guy was going through the e-mails, giving his findings on his blog. He wasn’t too impressed, because I didn’t know your area of expertise. I told him he should check you out he might learn something. I will be well armed for our next conversation. GOOD WORK! THANKS.
What is lost in the details of the hunt is that this person knew from the beginning that this was all a crock and now somehow seems to find the need after the fact to relay to us that insight.
The very fact that it was being used as a tool to change not just our country but the entire world was not enough of a threshold to make him speak out.
Sorry but this revelation does little to make me think better of him and in fact is pretty damning.
Paul Krugman (on ABC this morning) leaves you wondering if all economists are as equally corrupt as these “climate scientists†appear to be.