http://comics.com/reality_check/2009-05-25/

http://saf.met.no/p/ice/nh/conc/conc.shtml

or not?

http://nsidc.org/data/seaice_index/daily.html

Looks like we satellite problems again. There are also other missing swaths…

Mike

Steve’s comment on the ClimateAudit post is here:
http://www.climateaudit.org/?p=6038#comment-342160

Yes and Yes. Where is the complete set of manipulating algorithms published including data and code as required in all other branches of science?

Is the raw data still available or are we left with processed data which reflects the desired conclusions?

Can we get a copy of this “study” and have a thread where we give it a good peer review?

“And I still would like to see error bars or something that gives an idea of the spread of data ”

For GISTEMP, look here. Had you ever looked for this kind of information? It has been there all along and very easy to find.

The graph at your link has 3 green error bars with no explanation of what they mean. Each data point should have error bars and we need to know what the error bars mean. And how would we know how much error is due to the baseline data and how much is due to the ongoing monthly measurements? Graphs that show averages without defined error bars do not allow an assessment of the meaning of the data.

I looked up Hansen’s Global Temperature Change paper that appears to be the source of the graph you linked to. Here is his explanation of error bars:

Estimated 2 sigma error (95% confidence) in
comparing nearby years of global temperature (Fig. 1 A), such as
1998 and 2005, decreases from 0.1°C at the beginning of the 20th
century to 0.05°C in recent decades (4). Error sources include
incomplete station coverage, quantified by sampling a model-
generated data set with realistic variability at actual station loca-
tions (7), and partly subjective estimates of data quality problems
(8).

I particularly like the last part about subjective estimates. Boy, that sounds precise and repeatable. So I guess his error bars are of the same quality as his data, which is not surprising. I would just like to see plus or minus 2 sigma based on the measurements that were averaged so we could see the spread of the data.

For GISTEMP, look here. Had you ever looked for this kind of information? It has been there all along and very easy to find.

he point is not valid either way. Monthly anomalies are temperature departures relative to the mean temperature for that month during a given ‘base period’. GISS use the 1951-1980 period. So, if the 1951-1980 mean temperature for May is 14 deg and the temperature for May 2009 is 14.5 then the May anomaly will be 0.5.

Thanks for clearing that up. Every time I have seen an explanation of the baseline, it is always something like “the average global temperature from 1951-1980″ which is very different from what you are describing. However, I still maintain that the term “anomaly” is poorly chosen for the reasons I previously mentioned. And I still would like to see error bars or something that gives an idea of the spread of data used to calculate the “baseline”. How are we to know if a 0.2° difference is significant. If the standard deviation of the data used to calculate the baseline was 0.2, for example, then it would not be significant. Without this information, we have no way of knowing whether we are looking at real differences or just noise (even if the data itself were not suspect).

Naw I didnt read the mail. I’m ears deep in alligators. 20 hour days is killer.
Stuck in Asia with a bad connection. I’ll check later tonight, when I finish
work. I’m grumpy.

If all temperature readings were taken in one hemisphere then that point would be valid – but they are not. Whether the readings in each hemisphere are equally weighted is another matter.

The point is not valid either way. Monthly anomalies are temperature departures relative to the mean temperature for that month during a given ‘base period’. GISS use the 1951-1980 period. So, if the 1951-1980 mean temperature for May is 14 deg and the temperature for May 2009 is 14.5 then the May anomaly will be 0.5. The base period is irrelevant. If you don’t like the GISS base period then use one of your own. Use the satellite base period (1979-1998) if you prefer. This gives a GISS April anomaly of ~0.2 deg, i.e. similar to the RSS anomaly.

If you have the GISS data, converting from one base period to another is trivial. But you don’t even need to do that because GISS will do to for you . Click here ->

http://data.giss.nasa.gov/gistemp/maps/

Then select Hadl/Reyn_v2 in the Ocean drop down menu. Enter your preferred base period (e. Begin: 1979 End: 1998) then click on Make Map . You should end up with this ->

http://data.giss.nasa.gov/cgi-bin/gistemp/do_nmap.py?year_last=2009&month_last=04&sat=4&sst=1&type=anoms&mean_gen=04&year1=2009&year2=2009&base1=1979&base2=1998&radius=1200&pol=reg

which if it’s worked will show a global anomaly map. In the top RH corner you will find the monthly “anomaly” relative to the chosen base period. In this example it is 0.19 deg.

“People see the “zero” point as the “normal” point. So the choice of zero is important to see if we’re rising from normal, or returning to normal.”

There is no meaningful definition of ‘normal’ in this context and hence no non-arbitrary choice of reference period.

“This echos previous replies, in that the choice of zero is used to create as large a positive (above zero) change as possible. The more above zero we get, the scarier the news sounds.”

If a difference of 0.1°C makes you scared, you’re a bit more timid than most people! I find the suggestion that the baseline was chosen in the way you suggest to be obviously absurd. Given that the GISTEMP record was first produced in the early 1980s, using the previous three decades as the base period seems rather obvious. If the desire was to produce larger positive figures, why didn’t they use 1880-1910 as the reference period?

chriscafe:

“Surely the major problem is that NOAA and GISS manipulate the raw data using unpublished algorithims”

Have you ever looked at any of the papers mentioned here or here? What definition of ‘unpublished’ are you using?

evanmjones:

“Well, believe it or not, it’s like this: NCDC takes its data and adjusts it (much controversy there). GISS takes the fully adjusted NCDC data and “unadjusts it” via some strange algorithm and then applies its own adjustments to the mangled results.”

That’s pure fiction. Have you ever read GISS’s own description of the actual procedure?

I would have thought there is only the need for one group to monitor the worlds surface stations ?? I`m sure there’s a good reason ?

Well, believe it or not, it’s like this: NCDC takes its data and adjusts it (much controversy there). GISS takes the fully adjusted NCDC data and “unadjusts it” via some strange algorithm and then applies its own adjustments to the mangled results. Why they do not simply start off with NCDC raw data is a mystery for the ages.

HadCRUT, as I understand it, starts off with NCDC raw data, but does not reach all over the north pole by extrapolating from the “Siberian Thought Criminal” stations, so it generally clocks in a bit cooler than NCDC or GISS.

Satellites measure lower troposphere using microwave reflection proxies, and are not surface temps. They should (acc. to AGW theory) be warming faster than surface, yet they don’t. The sats are in pole-to-pole orbit and their cameras stick out the sides, so they can’t look directly down at the poles (I also think there is a problem measuring reflections off the ice). So the N/S polar temps are a lot less certain than they otherwise might be.