Gentle Cough - The Post Dispatch and Cherry-picking data

It has been a little while since I wrote anything about the Global Warming situation. Not that there is not an ongoing series of messages about how we are going to be drowned by increased glacial melting, or that extreme events might become more prevalent, and that we need to take precautions in case they do. Of course there is not a lot of evidence that the rate of extreme event occurrences has been increasing, but the alarmists feel that there is some need to drive home the message that the world has to be concerned about Global Warming, even when the globe isn’t warming. And so this post, which first notes why I wrote the last sentence, and then comments on how the media message is changing so that, by cherry picking data, alarm can still be spread.

So first let us look at the Global Warming situation. It has received very little coverage in the United States, and barely rated a mention in the UK, but the recent release of a new plot of global temperatures by the Climate Research Unit (CRU) at the University of East Anglia (UEA) is worth putting up, purely as a matter of record.

Figure 1. Global average temperatures over the past 15 years (British Daily Mail ).

This Met Office release (on a Friday) has largely been ignored by a scientific community that only exists in its current form as long as the reality that this graph presents remains ignored.

There was an immediate controversy in the UK (but not here, where it remains largely unknown) and there was a follow up report the following Sunday. But, even while ignored, the lack of increase in global temperature over the past fifteen years is surely some indication that the models widely used to predict an exponentially increasing global temperature, are falsified.

So what can a good alarmist do? Well consider the headline in the St. Louis Post Dispatch on November 26th. “2012 so far the warmest year on record in parts of Missouri.” So let me talk about this for a minute.

Notice that this does not say that the entire state is at its warmest. Rather it reports that Jayson Gosselin of the National Weather Service has noted that this was the warmest year on record for St. Louis and Columbia.

The average temperature in St. Louis so far this year is 63.4 degrees, a full degree higher than the 62.4-degree average seen in the previous warmest year, 1921. In Columbia, the previous warmest year as of Nov. 24 was in 1938, when the average was 61 degrees. This year, the average is 61.7 degrees. In Kansas City, Mo., it has been the fourth warmest year on record so far, with an average temperature of 61.3 degrees, Gosselin said.

He goes on to be more specific about when the heat wave occurred (in case we missed it!)

Gosselin, who works in the Weather Service's office near St. Louis, said the "meteorological spring" _ March through May _ was far and away the warmest ever in St. Louis with an average temperature of 61.1 degrees. Second warmest was 1910, when the average was 57.5 for the spring months. Summer also was unusually warm. Average temperatures in March, May and July all set records in St. Louis, he said.

For those who forget, I took a look at the Missouri State Temperatures first back in February 2010, when I first became curious as to whether our state was showing the global warming that everyone was talking about.

I found the location of all the US Historical Climate Network sites for Missouri and determined their location (latitude and longitude) elevation and population. Now as it turns out that there are 26 stations in Missouri, and so I took the average temperature for each station each year (this was the “homogenized” temperature in that initial post) and was able to plot the average state temperature over time.


Figure 2. Average “USHCN homogenized” temperatures for the state of Missouri (USHCN)

And if you look at that plot the state temperature has barely risen (less than half a degree Fahrenheit in 115 years) since official temperatures have been recorded, and the hottest years were in the 1930’s in the dust bowl years.

But there was something missing from the data table and it turns out that three of the largest cities in the state, Columbia, Springfield, and St. Louis were not tabulated in this network, but are, instead, part of the Goddard Institute for Space Studies (GISS) network that Dr. James Hansen used for his work.

And, being further curious, I then combined the two sets of data and obtained a plot for temperature as a function of population.


Figure 3. Temperature as a function of population size around the station. This conclusion, that there is a log relationship is not new. To quote from that post:

Oke (1973) * found that the urban heat-island (in °C) increases according to the formula –

➢ Urban heat-island warming = 0.317 ln P, where P = population.

Thus a village with a population of 10 has a warm bias of 0.73°C. A village with 100 has a warm bias of 1.46°C and a town with a population of 1000 people has a warm bias of 2.2°C. A large city with a million people has a warm bias of 4.4°C.

It is interesting to note that his coefficient is 0.317 and the one I found is 0.396.

( * Oke, T.R. 1973. City size and the urban heat island. Atmospheric Environment 7: 769-779.)

But then I revisited the state later in time, after the USHCN started also providing the raw and Time of Observation Corrected data (TOBS). And I found a few more interesting facts.

Firstly I compared the difference between the GISS data for the three large cities with the state average temperatures for both the raw data, and the “homogenized” data.


Figure 4. Difference between the average temperature in the large cities, and that of the average temperature in the State. The blue line is for the homogenized data, the red is for the raw.

I then went on to compare the TOBS average to that of the largest cities and this is what I got:


Figure 5. Difference between the average temperature in the large cities of the state, and that of the average temperature in the state using the TOBS data.

A slight upward trend, but not that significant. As for the temperatures in Missouri, over the past 100 years, with the correction – really there is no trend, it has been relatively stable:


Figure 6. Average TOBS temperature for the state of Missouri over the recorded interval.

I did note that the highest temperatures were some decades ago.

Oh and the correlation with population held up with the TOBS data, the coefficient was 0.327, and the r^2 value was 0.14.

Now I finished the entire contiguous United States some time ago, and that temperature relationship to population held up quite well, as the individual state reports listed on the rhs side of the blog show.

So what do we learn from this? That alarmist rhetoric is continuing with an embarrassing lack (for those of us who are scientists) of balance in the reporting. Data now has to be carefully cherry-picked to still be able to convey the message that the world is warming. One wonders how long they will be able to get away with this before they are called out by more prominent folk?

The Met Office, NASA GISS and is there a Thermometergate?

Because there are very obvious current differences between the weather in the United Kingdom and the forecasts of the Met Office, the BBC are reporting that the some at the Office are considering stopping the practice of making long-term forecasts. One of the problems has been identified:

The Met Office has now admitted to BBC News that its annual global mean forecast predicted temperatures higher than actual temperatures for nine years out of the last 10.

The bias is very small overall, about 0.05 degrees C, but the fact that it is a persistent warming bias should, perhaps, be of concern, relative to the accuracy of the models using it. Of course there are those, such as Professor Mobbs at Leeds, who would argue differently:

"All models have biases and these are very small. It may be, as the Met Office suggests, that the observations are wrong, not the model."

Must be all that illusion of snow that must be confusing folk in the UK after the model promised a greater chance of a warm winter.

Thermometergate, the concern over the quiet, and at the time un-noticed switch whereby the NASA Goddard Institute for Space Studies (GISS) changed number of stations used in assessing global temperature, is slowly getting more visibility. There was an hour long special (visible in five parts) on KUSI in which (during part 4) John Coleman introduced and talked with E. Michael Smith, who runs the site that has reported on this, and which has reviewed the GISS code and discovered that they now rely on a much smaller number of data acquisition sites than they have previously.

One final note: There has been A Great Dying lately for thermometers. Since about 1990, there has been a reduction in thermometer counts globally. In the USA, the number has dropped from 1850 at peak (in the year 1968) to 136 now (in the year 2009). As you might guess, this has presented some “issues” for our thermal quilt. But do not fear, GIStemp will fill in what it needs, guessing as needed, stretching and fabricating until it has a result.

Going through the list of stations that survive and looking for those in Missouri, there are apparently three:
(the first and second sets of numbers after the station name give the latitude and longitude of the stations)

42572434000 ST.LOUIS/LAMB 38.75 -90.37

42572445000 COLUMBIA/REGI 38.82 -92.22

42572440000 SPRINGFIELD/M 37.23 -93.38 .

Going to the actual GISS site to see how the values check out, GISS does recognize the drop in the number of station records that are used:

Number of stations used to generate the GISS temperature record

The full list of Missouri stations (there are 35 of them) are also given. The relevant plots given are:

Lambert St Louis temperatures

Columbia MO temperatures

Springfield Mo temperatures

The consistent part of which plots seem to be the lack of current evidence of warming and the higher temperatures during the dust bowl era. I also looked at the University site in about the middle of the state (at Rolla) and got this:

Temperatures at Missouri University of Science & Technology (until recently UMR)

One thing that did strike me about that record was that it did not look the same as the plot that I got from the USHCN data base, and which I had used once before. So I went and got that plot for Rolla:

Plot of the Mean Rolla Temperatures from the United States Historical Climate Network (USHCN) data base.

The impression of a rising trend evident in the GISS plot is not as evident in this one, and the highest temperature is barely, rather than clearly, 2006.

What is, however, odd, is that the USHCN data base for Missouri does not carry the station data for the three sites chosen by GISS.

I am going to continue to monitor the Rolla site, since (apropos Anthony Watts project on the validity of station data there has been an new technical addition near the measuring station and it will be interesting to see what, if any, effect the wind turbine has on the data generated from the weather station.

Current status of the station at Missouri University of Science and Technology (note the wind turbine on the right, and the weather station on the left).

The debate over the impact of the reduction in the number of sites that are being used to generate global temperature averages will no doubt continue, though it is interesting to note the specifics of what Dr. Hansen has said in his response to the KUSI report.

“NASA has not been involved in any manipulation of climate data used in the annual GISS global temperature analysis. The analysis utilizes three independent data sources provided by other agencies. Quality control checks are regularly performed on that data. The analysis methodology as well as updates to the analysis are publicly available on our website. The agency is confident of the quality of this data and stands by previous scientifically based conclusions regarding global temperatures.”

Now NASA (GISS) recognized that there has been a reduction in the number of monitoring stations (it is after all their graph that I used above) what it does not do is comment on the impact that changing the data base has on the overall result.

We will see how long it takes to getting around to addressing that issue.