Will the Real Hockey Stick Please Stand Up?

This is another re-post from old days.  Just because I’m thinking of how Doctor Michael Mann earned his stellar reputation.

---

I won’ t abuse you with my venting today. Mostly pictures. Pretty interesting ones I think.

I used the CPS method today with actual proxies from M08. Instead of the infilled data with the fake hockey stick glued on the end I used the original original 1357 series before processing. I also chopped off the 95 Luterbacher series which aren’t really proxies, they are temperature. It didn’t make any big difference to the shape of graphs in my results but I don’t like em.

The Hockey Stick Data Hoax – reposted

From back in the day where we learned the types of GAMES Mann was playing with data.  You wonder why people say mean things to a scientist of his stature?  I don’t.

---

I said it again.  Hoax!  The more I learn about hockey stick graphs, the worse it is.

The graph below is from a very important group of data in the M08 latest hockey stick.   This represents an average of 105 of the 1209 data sets used in  M08 or 8.6%.  But wait, the “CALIBRATION” process eliminates bad correlation data series so only 484 of the 1209 were kept in the final calculation.  Of the 484 series which were kept 95 of them were from this very same set of proxies. Mann08 used 95 of these series in the final 484 or 20% of his data.

Proxies are not known to be temperature.  The process of calibration is used to determine if proxies are temperature by pattern matching to measured temperature in the last 100 years.  Well I like trees but they are lousy thermometers. There is a buzzword in the field called DIVERGENCE, everything in climatology is so politicized they can’t call a turd a turd.  Divergence means “doesn’t really match temperature”.  Well guess what 20% of the data right off the top doesn’t match temperature very well so our brilliant scientists who are saving us from CO2 plant food, did the honorable thing and CHOPPED THE DATA THEY DIDN’T LIKE RIGHT OFF THE END!

The last 38 inconvenient years of data for these series were truncated, chopped, amputated, excised and cut from the data.

This is not the end.  Mann08 feeling pretty cocky after pushing the other magic papers through the IPCC is emboldened in the face of the publicity they actually PASTED FAKE DATA ON THE END OF THE SERIES.

The new fake data has a nice smooth and not noisy temperature rise, they then compare the fake data to the temperature value and with great fanfare determined that over 90% of the measurement of tree hardwood series are actually TEMPERATURE.

Evidence of Sea Contamination In Antarctic Sat Data

Know your data!

It’s the first rule of any engineering project you undertake. Mistakes often happen at the base level of data collection, errors in the early stages propagate through a project once the data is accepted, the effects of which are often misunderstood or unquantified. Nobody is immune to this of course, it’s just a point I want to make. From an engineering standpoint, it means heavy verification, often multiple times until you’re sure that your answer is reasonable. In my world if I’m wrong, things don’t work and big money is flushed down the toilet. In climatology if they are wrong and it is pointed out, there is little recourse or concession of the mistake. It would just be another messed up science if the politicians and polyscienticians weren’t forcing ridiculous policies down our throats, but that’s another story.

Jeff C found a site on the NSIDC where they provide AVHRR satellite data from 1982 to 2004. This data is monthly data which means daily cloud masking and error correction have already occurred. The masking is different than Steig used in his Antarctic paper and it may have had a substantial impact but at least we have a point of reference. There are several questions to answer, are 3 pc’s enough to represent the data, are the trends similar to the presented trends, are there other problems in the data.

Honestly, I’ve spent many hours now looking at the data and while I don’t have the answers to all these questions, there will be some interesting things over the next week or two. I really need to send Christmas cards to the team for all the entertainment they provide.

Jeff C deserves enormous credit for accessing and processing the data, we did work on it together but there were big hours spent in analysis and verification. Anyway, instead of getting too far ahead of myself and into some of the incomplete but still interesting finds I’ve decided to catch my readers up.

Below is a movie of the skin surface temperature of the Antarctic. Watch the video a couple of times and you may see some interesting features.

Antarctic Temperature RegEm Forensics

Thanks to Molan Labe who was quite helpful in identifying what I believe is the correct coefficient into regparm for the purposes of recreating the RegEm calculations. After some considerable time I am still not able to recreate the results of Steig’s paper perfectly, but as you can see below, I am fairly close.

First let’s look at the mean trend of the reconstructed AWS station data by Steig. All data used was from the Climate Audit directory (thanks to Steve McIntyre) so the updated reconstructions and data are not involved.

Surface Station Data

Surface stations were used in the Antarctic with RegEm to infill satellite and AWS data for the establishment of the warming trend.  This is the data used in the final reconstruction.  It is much more complete than the AWS data so I plotted all of the trends to see what they look like.  I had to calculate my own anomaly this time so I used a monthly mean method and subtracted it from the temp data to create the black curves below.  These plots are typical to the data and represent the set  pretty well as far as completeness.

Arctic Sea Ice Increases at Record Rate

Something I’ve been interested in for the last several months is sea ice data. What makes it interesting is that as I understand it, models demonstrate the poles should be most sensitive to global warming leading the planet temp, especially in the Arctic. Recently I have been able to process the monthly and daily gridded arctic data as provided by NSIDC. The daily values allow a better analysis of trend than can be provided by the monthly data.

If you’re like me you recall the claims of fastest melt rate ever were made about 2007 , I fully believed them, because the graphs showed a much more negative value than in the previous 30 years as shown in Figure 1 below.

Satellite Temp. Homoginization Using GISS

RSS and UAH have differing 30 year trends which lie outside my calculated measurement error for the data. Subtraction of the two measures leaves a step located at about 1992. Since they both use the same dataset, the question becomes. Which series is right?

After reading several papers and some short emails to some smart people, I have come to understand the bulk of the trend difference to this single step point in the data which corresponds to the time when satellite NOAA-12 began adding data into the trend.

Below is a graph of the RSS-UAH data where the step is quite visible. The flatness of the slope on either side fo the step is a good indicator that most of the data is in good agreement between the satellite processing algorithms.

The graph below is a plot of the raw data and a filtered difference and the overall trends of the data. You can see the trends are crossed and divergent.

NSIDC Issues Corrections to Webpage

Based on The Air Vent post carried by Watts Up With That, the National Snow Ice Data Center has issued several corrections to the documentation of their sea ice area time series.

Most will remember my earlier post which plotted global sea ice trends. After initially concluding that the global ice level wasn’t decreasing measurably Tamino pointed out a problem in my analysis. After issuing my corrections, thanks and apologies to Tamino and the um…..thousands of readers of Watts Up With That, I went back to work investigating what was really happening to the ice area time series.

It was actually quite lucky that Tamino mentioned the step in the data and criticized me for not reading carefully (something which was mentioned in several comments on the various threads). When I first learned of it, I found the criticism was based on an entirely different set of ice area data with different source documentation. Still, I checked closely and found the tiny step in the time series and was convinced that I had missed something. I had spent a huge amount of time learning the data before I made my post so it was frustrating to say the least. Understand, I used several resources to check my work; not the least of which was the National Snow Ice Data Center (NSIDC) anomaly graph which has the same shape as the one I generated.

Here Comes the Snow

Yeah, you can tell from the title I live on the topside of the world. A bit egocentric for sure but the winter is setting in here and it’s looking cold. Anthony Watts did a post on PDO (Pacific Decadal Oscillation) which has recently shifted colder. A lesser known form of la nina the PDO is yet another regular oscillation in the weather system. One which doesn’t get the press it deserves simply due to its longer timescale.

Click on the picture to link to watts up.

The blue wedge region surrounded by the green is apparently the typical signature of the PDO cold cycle. What didn’t get enough attention IMO is the trend. By the trend we should have been expecting this event for some time. Fortunately for us, digital diatribes (link on right) kept up with the trend and laid it out several days before the main stream media and Watts Up picked it up. Take a close look at this graph.

Left Turn Clyde

What three things do these three people have in common?

1 – They all have extremist left wing global warming backgrounds.

2 – They all support hard CO2 caps.

3 – They all have been recently nominated to top positions in Obama’s administration.

Click on the pictures for some bio information.

Satellites Quantify Rainfall/Temp – 5 Times More than IPCC predicions.

NASA: Global warming to increase severe storms, rainfall

PASADENA, Calif. (AP) — The frequency of extremely high clouds in Earth’s tropics — the type associated with severe storms and rainfall — is increasing as a result of global warming, according to a study by scientists at NASA’s Jet Propulsion Laboratory, Pasadena, Calif.

In a presentation today to the fall meeting of the American Geophysical Union in San Francisco, JPL Senior Research Scientist Hartmut Aumann outlined the results of a study based on five years of data from the Atmospheric Infrared Sounder (AIRS) instrument on NASA’s Aqua spacecraft.

For every 1.8-degree (F) increase in average ocean surface temperature, the team observed a 45-percent increase in the frequency of the very high clouds. At the present rate of global warming of 0.23 degrees per decade, the team inferred the frequency of these storms can be expected to increase by six percent per decade.

Everything was going fine until this last paragraph. Point two three, you sure big guy. Who says point two three, even GISS data only says 0.18/decade. The last decade showed little or no warming whatsoever. A flat line.

Blogging is Great!

I’ve thoroughly enjoyed this experience so far. What amazing entertainment, brilliant commentators and excellent drama. It was actually the Digital Diatribes of a Random Idiot which got me to start blogging. Joe’s site, with unique comments and truthful analysis encouraged my start.

I started blogging about energy and ice cores in August. I looked at how different forms of alternative energy have so many problems as related to oil, coal, natural gas and nuclear. After a short time Climate Audit posts led me to dig in to Mann 08 where I discovered deeply (and simplistically) flawed statistics.

Let’s look at some of the bigger events which have happened to the Id.

– Discovery that biofuels, wind power and solar are not technologically ready to replace existing energy sources.

– Uncovering multiple flaws in Mann08. A huge adventure for sure, after all this guy created Albert Gore’s hockey stick graph.

– I found that Mann 08 infilled data, pasting on a hockey stick on the end of 90% of the proxies.

The All Important Blade of the Stick Uses Less Than 5% of the Data

– I learned that Mann 08 used a correlation to temperature to sort proxies and throw out the data which didn’t fit his assumptions. Since this time I learned that this has been proven statistically incorrect by many authors.

Simple Statistical Evidence Why Hockey Stick Temp Graphs are Bent!!

Looking back there are some problems with my statements in this post but the math result was completely accurate.

—-

A Bit of Backlash to AP Propaganda

These guys must read the air vent too.

Scientists Call AP Report on Global Warming ‘Hysteria’

Scientists skeptical of the assertion that climate change is the result of man’s activites are criticizing a recent Associated Press report on global warming, calling it “irrational hysteria,” “horrifically bad” and “incredibly biased.”

They say the report, which was published on Monday, contained sweeping scientific errors and was a one-sided portrayal of a complicated issue.

This mirrors my post earlier.

AP Drinkin’ the Global Warming Coolaid

Listen to some of these quotes from this article.

How Do These Things Happen

I took some flack on how I missed such an obvious problem in the data. Well, things are rarely as clear as they first seem. Let’s look at the facts, below is a plot of the uncorrected bootstrap data.

See the offset at 1987, no how about the same graph zoomed in.

There it is, that little scribble after 1987.5. That’s the entire difference between my first and second posts. But it’s worse than just this, here is some text from the actual pages.

Sea Ice Decreases Despite the Air Vent

Well tonight I get the great pleasure of redoing a post in the face of an inconvenient truth. To add insult to injury the error in my ways was pointed out by none other than my favorite liberal – Tamino who pointed out this section of the NSIDC data center. How I missed it in the hours I spent reading the site is beyond me. He did owe me one, at least we know he’s reading.

Note that unlike ice extent, the Arctic values for ice area do not include the area near the pole not imaged by the sensor (the “pole hole”). This area is 1.19 million square kilometers for SMMR (from the beginning of the series through June 1987) and 0.31 million square kilometers for SSM/I (from July 1987 to present). Therefore, there is a discontinuity in the “area” data values in this file at the June/July 1987 boundary.

This means that the sea ice area prior to 1987 was actually 0.88 million kilometers higher than the dataset indicated (if we assume 100% filled). Why it isn’t corrected in the data is due to the fact that the actual fill level is less than 100%. This results in an exaggerated downslope. Anyway here’s the new graphs (with a somewhat exaggerated downslope).

Here’s an image from the IUIC cryosphere page first which shows global trend.

Here’s the link check it out yourself. This isn’t that different from my original post but there is some down slope.

———————–Results from my exaggerated correction are below. ——————————–

Raw data looks like this after adding 880000 km^2 to the raw data before 1987.