Have a look at this and see the observer strike through the reported TMIN and substitute the

Temp at the time of observation for tmin

Day 18. 68F is written as Tmin. 62F as the Temp at Time of Observation. (8AM)

then the ‘8’ is crossed out and a little 2 is written.

It would be interesting to see how the person digitizing the data entered this.

Its florida 2000 all over again.

PS. I selected Orland because we’ve looked at it. This is the 0ne month

I selected to look at. and is the only one I looked at. Kinda funny that I found a

TOBs thing

A real-world example of exactly why the concept of the Laboratory Notebook was developed. One of the cornerstones of the requirement for *independent* Verification of data for quality control purposes. Early in our educational process these are typically called Lab Reports.

As additional information is uncovered, more and more it seems that NASA GISS are not familiar with any of the concepts of data quality. And their feeble attempts to belittle and dismiss those who know the benefits of these concepts, and apply them to important analyses, are beginning to paint a very ugly picture of NASA GISS and its ‘science’.

]]>Instead of gridding an area with regular sized rectangles or triangles, why not do the following.

1. Imagine the stations are the vertices of an irregular polyhedron with triangular sides. i.e. draw lines between the stations until the area is split up into triangles, each triangle having one station for each of its three corners.

2. Now compute the temperature for each triangle by taking the average of the three temperatures for the stations at the three corners.

3. Divide the temperature by the area of the triangle (remembering that the triangle is on the surface of a sphere when computing the area).

3. Sum the weighted temperatures and multiply by the total area to get an average temperature.

The polyhedron can be created computationally by starting at an arbitrary station, finding the closest two stations to form the first triangle, then expanding out recursively from each of the three edges of this triangle adding a point to make a new triangle.

]]>Just looking at a few random months for Marysville in the last decade I’m struck at how many data gaps there are.

]]>Go to:

http://www.ncdc.noaa.gov/oa/mpp/freedata.html

Scroll down to the first category that says Individual station original that will take you to:

http://www7.ncdc.noaa.gov/IPS/getcoopstates.html

Then click on the state, then find the month and year and it gives you a link, click on the link and there you have it, the original hand written report.

I started with your and Steves favorite and the first one on John Vs CRN 5 list: Univ. of Tucson #1. John Vs data goes up to March 2006 so thats where I started (it was off by 3 tenths). Then I went back a year to March 2005, Johns spreadsheet was blank for that month but the report is there, no days missing (same with Wickenburg, AZ in Jan 1999). Then I went back another year to March 2004, it was off by 5 tenths.

I also did Gardiner, Maine for March in 2006 and 2005. It was off by 1 tenth for each.

I also checked blanks at Chico Univ. Farm, CA on John Vs spreadsheet for March 2006 and Nov. 1999; the NCDC reports were there but missing 9 and 10 days.

These were all March so try July or August and I get the feeling that the differences will be larger for the CRN 5 stations.

Get ready for some boring math because some of them didnt do their sums so I had to.

A Fahrenheit to Celsius converter can be found here:

http://www.wbuf.noaa.gov/tempfc.htm

I knew there was something wrong with all of this; Ive had my hand up to some of those AC units. And this is not John Vs fault, like I said, if it comes from NASA GISS or NCDC it is junk until you see it with your own two eyes.

]]>Ive compared several months from the original hand written station reports against the values in your station.csv file and none are matching. All of them are off from between 1 and 5 tenths. I have also found a couple of stations that have reports with less than 9 missing days but they are blank in your spreadsheet. All of the station reports that have 9 or more missing days are blank in your spreadsheet. I think the raw GHCN data is much less raw than they claim.

]]>Lots of interesting ideas in your posts, but I’m out of time and energy for tonight. I will try to respond tomorrow. ]]>

Create a file of all stations all 1221. ( ask if you dont know how)

Run them through JohnVs program.

Create a file of all stations EXCEPT those that Anthony says are Class 5. ( about 1160 stations)

Create a file of all stations EXCEPT those that Anthony says are Class1&2. (about 1160 stations)

Now, I know that about 700 of the stations in the sample are Unsurveyed. Lets call those CRNu.

What do you expect for ALL-CRNu1234

What do you expect for ALL-CRNu345.

That is, in one sample I take out those sites I know to be bad. In another I take out those I know

to be good.

If I take out the bad sites I lower the Anomaly consistently By .05C. More specifically,

Anthony has surveyed 33% of the sites and counted 50-60 CRN5.

IF you calculate the US anomaly graph for all 1221 stations ( 1950-1981) and then

IF you calculate the same graph, deleting those 50-60 stations, you will see a

Consistent difference in anomaly from 1880 to present. That difference is on the order of

.05-.07C. Namely, Remove the 50-60 stations That are class 5 and you will cut the Century

anomaly by roughly 5-10%.

When you take out the Good sites ( CRNu345) you get a difference from the whole that wanders

around the zero line, negative here positive there.

Have a look.

]]>