Again, water is wet, which doesn't support evolution. But your original claim before your goalpost moving was that there are some facts which support the creationist position. You can either find an example that isn't ridiculously wrong, retract your absurd claim, or pull a "Jane" by doing neither. Surprise us.

Now that you've moved the goalpost to a fact that just doesn't refute the creationists' arguments, here's one: water is wet.

No, isochron dating only relies on nuclear decay rates being constant, which has been confirmed by SN1987a, etc. Try again.

What facts support the creationist position?

... this is why others caused an uproar when "original data" went missing from EAU and CRU right around the time of "climategate". ... there was simply no way to evaluate the quality of CRU's work. access to the RAW DATA was NOT available. Only data that has already been "massaged" (to an unknown degree) was available before the "official" release, and that release was prompted by complaints about this very (and very valid) issue. ... access to original data is vital to verifying and reproducing results. ... CRU could have avoided the FOIA requests if they'd simply handled things in a professional, reasonable manner, as opposed to one that was blatantly arrogant and dismissive. They needlessly pissed a lot of people off. When you do that, you should not expect them to not piss you off in return. ... I'm not trying to say data was actually "missing", but it is true that some of it was not available. And CRU's documented attitude regarding requests about it contributed to an atmosphere of distrust. ...

Jane Q. Public, please use your feminine voice to tell Lonny Eachus that when he finds himself deep in a hole, he should use his masculine strength to... stop digging.

Again: "Any independent researcher may freely obtain the primary station data. It is impossible for a third party to withhold access to the data. Regarding data availability, there is no basis for the allegations that CRU prevented access to raw data. It was impossible for them to have done so."

Your continued attempts to smear CRU while refusing to retract your latest misinformation are noted. Since you and Lonny Eachus keep spreading misinformation which threatens the future of our civilization, I have no choice but to keep debunking you and Lonny Eachus. Stay tuned.

access to the RAW DATA was NOT available

Previously, you could have used your ignorance as an excuse. Now you're just lying. And apparently neither you or Lonny Eachus have enough intellectual integrity to retract your latest steaming pile of civilization-paralyzing misinformation. This flood of misinformation isn't just staining "Jane Q. Public's" sock puppet legacy. It's also staining Lonny Eachus's real human legacy. Please stop.

it was uncovered that most of the original data could (later) be obtained from the original sources

I didn't notice this comment before I wrote mine, otherwise I'd have been forced to correct this incorrect claim too. Again, the majority of data in CRU's dataset "are derived from the same freely-available raw data sets used by NOAA and NASA." Most of the data was already in the public domain, which is why the FOIA blizzard against CRU was so hysterically pointless.

Years ago, I explained in excruciating detail that this played absolutely no role in evaluating the quality of CRU's work because the majority of data in CRU's dataset "are derived from the same freely-available raw data sets used by NOAA and NASA." The Muir Russell review reproduced the necessary code in two days without any help from CRU.

And, of course, this isn't CRU's fault because “the authority for releasing unpublished raw data to third parties should stay with those who collected it.” Oddly, many people seem to ignore this point and blame CRU.

By the way, I debunked the misinformation that you and Lonny Eachus were spreading about Cowtan and Way 2013. Feel free to retract your misinformation (or double down on it) here. Lonny Eachus is welcome to do the same, but for some reason he never replied.

That's why it was "impossible" for CRU to have withheld access to the raw data. Because they didn't collect it in the first place. Anyone who was actually interested in the data could always have gotten them from the same sources that CRU did.

"Any independent researcher may freely obtain the primary station data. It is impossible for a third party to withhold access to the data. Regarding data availability, there is no basis for the allegations that CRU prevented access to raw data. It was impossible for them to have done so." [Muir Russell Review, p48,53]

The cosmic microwave background radiation is slightly closer to an ideal blackbody spectrum than that of an incandescent bulb, but people can't see it. So physicists don't nitpick continuous spectra like you keep doing, because nobody should be surprised that incandescent bulbs are made of atoms.

Pardon me for nitpicking a bit, but incandescents are not "continuous spectrum". Generally speaking, they are more continuous than fluorescents and LEDs, but continuous they are not.

MIT society of physics students: "one can observe a continuous spectrum by looking at an incandescent light bulb."

Doing even the most cursory of searches on gallium and reading through the Wikipedia entry (http://en.wikipedia.org/wiki/Gallium) would suggest that gallium is not chemically intert, may not be non-toxic to humans, and given that extremities can easily get cold enough to drop below the freezing point of gallium, I'd have to say that it might rather well leave a residue, forget about the stickiness others have reported.

Yea, that'd be great: inject liquid metal, have it thicken and solidify in your feet and fingertips because you step outside on a brisk day, giving you the equivalent of massive frostbite. No thank you.

There are growing numbers of Chinese researchers in my field (neuroscience) and their results always need to be taken with an extra-large grain of salt. It looks like the same is true here.

Cowtan and Way 2013 compensated for missing HadCRUT4 surface temperature measurements in places like the Arctic and Africa by using the spatial pattern of satellite data to produce a hybrid satellite/surface dataset. Jane and Lonny ponder the differences between Cowtan and Way's hybrid dataset and HadCRUT4:

I keep asking: what's wrong with my basic premise: that if your measurements are shown to be off by 100%, there's something wrong with your science? That was my point. [Jane Q. Public]

... They are saying that it is not the 0.05 degrees C per decade that the AR5 report gives for the last 15 years, but that it is, instead, 0.12 degrees C. Which is actually a difference of not 100% but 140%, for the most recent 15 years. [Jane Q. Public]

@ScienceChannel @jimmygle PLEASE tell the Anthropogenic Global Warmists! Yet another report surfaced saying their "science" was off by 140% [Lonny Eachus]

Jane and Lonny's basic premise wrongly ignores the large error bars on these noisy, short-term trends. The SkS trend calculator can calculate the trends and error bars from 1997 through (including) 2012 for both HadCrut4 and Cowtan and Way's hybrid dataset:

1997-2013 HadCRUT4 Trend: 0.049 0.126 C/decade
1997-2013 HadCRUT4 hybrid Trend: 0.119 0.150 C/decade

The hybrid dataset's central estimate is inside the error bars of the original HadCRUT4 estimate.

... they haven't been right yet... They admit that they have no explanation why their models, which projected continued if not increased warming, do not explain why it has dropped by more than half (0.12 to 0.05 deg. C / decade) over the last 15 years. Or, for that matter, why their margin of error (-0.05 to +0.15 deg. C) for the last decade and a half is 4 times the size of their actual estimated warming. Nope... it's pretty damned clear. Something is wrong with their science. [Jane Q. Public]

I calculated error bars on UAH trends. The black line on the second page shows the UAH trend ending in 2012, for different starting years. The error bars are shown in red; they're 95% confidence uncertainty bounds. Note that error bars on longer trends are smaller than the large error bars on shorter trends.

Anyone can reproduce my results by downloading the free "R" programming language used by professional statisticians. Then save this code as "significance.r":

# run using R CMD BATCH significance.r
# outputs to Rplots.pdf and significance.r.Rout
# load custom functions

# for generalised least squares
library(nlme)

# options
xunits="year"
textsize=1.4
titlesize=1.8
colfit="red"
pch1=20#points

# read basin data
indata = read.table("greenland2013/GIS_climate.nasa.txt",header=T)
title="Greenland mass"
yunits="gigatons"
tlims=c(-350,-190)
alims=c(-60,0)
#indata = indata[which(indata$x>2002.0),]

# remove mean
indata$y = indata$y - mean(indata$y)

n = length(indata$x)
n

midpoint=(indata$x[n]-indata$x[1])/2.0+indata$x[1]

# fit model
fit=gls(y~x,data=indata,corr=corARMA(p=1,q=1))
#fit=gls(y~x+sin(2*pi*x)+cos(2*pi*x),data=indata,corr=corARMA(p=1,q=1))
#fit=gls(y~x+I(x^2)+sin(2*pi*x)+cos(2*pi*x),data=indata,corr=corARMA(p=1,q=1))
fitsummmary=summary(fit)
slope = fitsummmary$tTable[2,1]
slopeerror = 2*fitsummmary$tTable[2,2]#2 sigma
plot(indata$x,indata$y,type="o",pch=pch1,lwd=2,cex.main=titlesize,cex.axis=textsize,cex.lab=textsize,xlab=xunits,ylab=yunits,main=title)
points(indata$x,fit$fit,type="l",lwd=2,lty=2,col=colfit)
lowerbound=fit$fit-slopeerror*indata$x
lowerbound=lowerbound - mean(lowerbound) + mean(fit$fit)
points(indata$x,lowerbound,type="l",lwd=3,lty=1,col=colfit)
upperbound=fit$fit+slopeerror*indata$x
upperbound=upperbound - mean(upperbound) + mean(fit$fit)
points(indata$x,upperbound,type="l",lwd=3,lty=1,col=colfit)
confint(fit,digits=6)
midpoint=(indata$x[n]-indata$x[1])/2.0+indata$x[1]
top=(indata$y[which.max(indata$y)]-indata$y[which.min(indata$y)])*0.99+indata$y[which.min(indata$y)]
text(midpoint,top,sprintf("%+.3f+-%.3f %s/%s",slope,slopeerror,yunits,xunits),cex=2,col=colfit)

Just download temperature data (from WoodForTrees, Skeptical Science, Cowtan and Way, or any other climate data source). Then redirect the read.table command to that file, and save the data in this format:

x y
2003.04 1184.10
2003.12 1006.97

Then run it using the command "R CMD BATCH significance.r"

Notes: My code comments (using "#") a command to select different starting years using the "#" prefix. The second page of my results were calculated using similar code in a for-loop to cycle through different starting years. Here's another R script that automatically downloads the latest HadCRUT4 annual data.

Funny but Kevin Cowtan and Robert Way were just able to employ satellites in a "study" that ends up with even better, more positive warming trends than those from the airports themselves! ;-) Never underestimate the alarmists' creativity in fabricating evidence. [Lubos Motl]

Lesser scientists would feel obliged to point out some of the "creativity" in Cowtan and Way's open source code and data before implying that they fabricated evidence. Motl has apparently transcended that obligation, but others should at least ponder the validations Cowtan and Way explain in this 4 minute video.