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?

Flaring and the Siberian temperature profiles

After I had drafted the following post I initially put it on the shelf, since the idea that the gas flares would have an impact over such a large area began to seem a bit of a stretch. But then, in the last week a new paper has been published in Nature and been commented on by both Roger Pielke Snr and Watts Up With That. Simplistically it finds that the actions of the wind turbines in Texas have caused a temperature change of 0.72 degC per decade due to the way in which the turbines modify atmospheric behavior. Wikipedia notes that Texas has an installed capacity of 10,377 MW, nameplate, and generated 6.9% of the electricity in that state in 2011.

 Russia has been flaring up to 50 billion cubic meters of natural gas a year. If a cubic meter of natural gas contains 37 Megajoules of energy and Russia is burning 50,000,000,000/365/24/3600 = 1,585 cu m/sec this is equal to 58,600 MW – six times the size of the nameplate Texas wind farms, recognizing that flaring goes on 24-7 while the wind turbines are much more intermittent. So it seems the topic has more validity than I might have thought, but is there an effect? If one looks at the global temperature maps that are issued by the Goddard Institute for Space Science (GISS) there is a consistent trend in those, which indicates the much higher temperatures that are found in Northern Russia and Siberia. These high temperatures are a significant contributor to the overall analysis that the average global temperature has been rising for the past 40-odd years.

Figure 1. GISS reported temperature anomalies for Feb 2012.

 Being as I am a curious person, I looked at the temperature record that GISS reports for Khanty-Mansiysk, (K-M) which became a city some 40-years ago, with the growth of the oil industry in the neighboring Samotlor oil field. The city is found at 61 deg N 69 deg E, with an elevation of 190 ft. (According to Google Earth). GISS has the town named as Hanty-Mansijs and gives the temperature history as:

Figure 2. Temperatures for Khanty-Mansiysk as reported by GISS.

 I will forego for now the adjustments that are made by GISS to the original data. In these regions this was recently covered by Paul Homewood at WUWT and I have written similarly on the adjustments that GISS consistently makes to individual state temperatures in those posts listed to the right hand side of this page. However this got me a little curious, given that the rise in temperature shown occurs in a region where there has been a considerable amount of gas flared, as I have commented earlier. The amount is in the range of 24 billion cubic meters a year in the region of Khanty-Mansiysk alone (half the Russian total), and I have used this illustration from the world bank of the thermal plumes that they generate.

  Figure 3. Thermal plumes from gas flares in Siberia

In more recent times there are new fields being developed in Eastern Siberia and up in the Yamal, many of whom cannot as yet pipe their natural gas away. As a result it is still being flared, and I have become curious if we could correlate any of the increase in Siberian temperatures with the increase in Russian flaring of natural gas. So, in a way reminiscent of the work I did on US state temperatures, I have downloaded the data from GISS on the 32 stations that lie within a thousand kilometers of Kanty-Mansiysk to see what they show, Some stations have incomplete data, and so I don’t know what I will find as this post starts to look into the data set. First, just out of curiosity I took the average value for the stations over the years, and plotted it against time.

Figure 4. Overall average temperature for the GISS reported stations within a thousand km of Kanty-Mansiysk 

 While there is a relatively constant range until about 1960 it seems (just by eyeball) that the temperature starts to pick up thereafter. Which is where it is important to note that this was about the time that oil production in the region began to pick up. To re-iterate that plot from the discussion of Western Siberian production.

Figure 5. The oil and gas fields of Western Siberia (after Grace – Russian Oil Supply) 

 Thus, just about the time that the temperatures in the region began to pick up, so the wells were being sunk, and the gas flared, from the production. So there is a little bit of a coincidental timing here. But that does not necessarily mean that there is any interaction other than co-incidence at this point in the story. But what it allows me to do, for the moment, is to truncate the data sets that I am looking at and confine them to post-1970. And, just for curiosity, I am going to use a 2nd order polynomial for the trend line for the overall data – to see what it might be doing other than just increasing.

Figure 6. Average Western Siberian temperature – post 1970 

 Now what is interesting about this is that there is a little bit of a fall-off as suggested by the trendline. This could very well be because of the sun output changing, or a variation in GHG levels – though those have continued to increase. Alternately it could also be because of the campaign by the World Bank and the Russian Government, which is causing the Russian oil companies to increasingly capture the gas and either re-inject it or pipe it to a commercial source, rather than just flaring it. (And though the number of wells is increasing as the supply diminishes the effect on gas flared is not absolutely defined). 

 So how do we proceed from here? Well if the cause is the flaring, then it should be more of an impact down-wind of the fields rather than up-wind (as the GISS plot would suggest it is). So for each of the stations I am going to (as a simplified test) put a linear trend line through the post-1970 data and determine the slope. Then I am going to plot the slopes as a function of latitude, and longitude, with the location of Khanty-Mansiysk marked on the plots. For example, here is the data for K-M:

Figure 7. Average post-1970 temperatures for KM as reported by GISS 

 The slope of the temperature curve is 3.42 degC per century, so let me get all the data and see what it says:

Figure 8. Average station temperatures (blue over the full record, red post 1970) as a function of Longitude with K-M located at the blue line. 

 Not sure that this tells a whole lot, so let’s look at the average temperature rate of increase for those stations, post 1970:

Figure 9. Average rate of temperature change as a function of longitude – post 1970 and with K-M marked at the blue line. 

 Well apart from two stations there does not appear to have been much change as a function of longitude. How about latitude?

Figure 10. Average station temperatures (blue over the full record, red post 1970) as a function of Latitude with K-M located at the blue line. 

 Interesting in that the average temperatures seem higher at lower latitudes than higher - which would seem to argue against the GISS graph at the start of this piece, and there is the thought that the values that I am using are post-adjustment by GISS so they may have corrected for something I have missed.

 But then there is the plot of rate of temperature increase as a function of latitude:

Figure 11. Average rate of temperature change as a function of Latitude – post 1970 and with K-M marked at the blue line. 

 Hmm! Apart from the increase in the station almost immediately north of K-M and the slight increase in slope as one moves further North past K-M, which may or may not be significant, there is not a lot of immediately obvious answers in the data. Ah, well not every conjecture works out, though I would still like to compare the raw data instead of the modified. And there is still that very dark red plume down-wind of K-M to explain . . . . .

New Jersey combined temperatures

Crossing from Delaware into New Jersey as I come toward the end of the data acquisition part of the project I started last year looking at state temperatures over the past one hundred and fifteen years, I find that New Jersey has a dozen USHCN stations.

Location of the USHCN stations in New Jersey (CDIAC ).

According to the list, the only GISS station in the state is in Atlantic City. There have been 3 stations there, one that ran from 1895 to 2008, down at the Marina. This clearly shows the drop in temperature in the 1948 – 1965 period that I have been mentioning in the last few posts on the subject.

Longer term temperature profile reported for the GISS station in Atlantic City (GISS ).

However, as has become evident in many states that I have reviewed, the one that is being used by GISS has a much more recent history, only having been in operation since 1951.

That record also clearly shows the temperature drop, though with the start in 1951, it is not as clear that this is an anomaly from the overall rising trend.

Reported temperatures for the GISS station currently being used in Atlantic City (GISS ).

Given the steady rise in temperature of the station at the Marina, I was curious to see how far from the sea the new station is. It turns out to be at the airport, which is 9 miles from the sea, and 23 m above sea level.

Location for the current GISS station in Atlantic City, New Jersey.(Google Earth)

And then as I start to import the data for the USHCN stations, I find that the first one is still at the Atlantic City Marina:

Location of the USHCN station in Atlantic City, at the Marina (Google Earth)

New Jersey is 150 miles long and 70 miles wide, running from 73.9 deg W to 75.58 deg W, and 38.9 deg N to 41.3 deg W. The mean latitude is 40.1 deg , that if the USHCN stations is 40.3 deg N, and the GISS station is at 39.45 deg N. The elevation of the state runs from sea level to 549 m, with a mean elevation of 76.2 m. The mean USHCN station is at 53.9 m, while the GISS station is at 23 m.

Because of the short interval for which information from the current GISS station has been presented, the difference between it and the USHCN average is relatively short.

Difference between the data presented for the GISS station in New Jersey and the average of the USHCN stations

For the state itself, turning to the Time of Observation corrected (TOBS) raw data, and seeing how the temperature in the state has changed over the years:

Change in the TOBS temperatures, on average, for the USHCN stations in New Jersey.

It can be seen that there has been, with the exception of the time from about 1950 to 1965, a steady increase in temperature. As I had noted in an earlier post on Rhode Island the sea surface temperatures (SST) have risen by about 1.8 deg F per century. This is relatively close to the value shown in the above graph. (Note that the homogenized data plot shows a temperature rise of 2.45 deg F per century.)

Turning to the geographical factors, starting with latitude:

Effect of station latitude on temperature in New Jersey

Remember from previous observation that longitude is really a proxy in many cases for changes in elevation, and New Jersey is, in the main, relatively flat:

Effect of station longitude on temperature in New Jersey

There is really no significant effect of longitude, whereas when one looks at elevation:

Effect of station elevation on temperature in New Jersey

It is clear that the broadly consistent finding from other states on the role of elevation is valid also here, even with relatively smaller elevation changes.

When looking for populations, Charlotteburg has only one farm by it at the moment, but there are two sets of sub-divisions being developed in the neighborhood, which may have a significant impact on recorded temperatures in the future, though the reservoir may have a stabilizing effect.

Location of the USHCN station at Charlotteburg, NJ (Google Earth)

Indian Mills also did not come up with a citi-data site, so a check with Google Earth showed that it was close to Medford Lakes and that the station was surrounded by houses (with large lots). So I used the Medford Lakes population. Moorestown is on the edge of Philadelphia, but has a separate population,

Looking therefore at the effect of population, considering the average of the last 5 years temperatures against the local population:

Effect of local population on TOBS temperature for the USHCN stations in New Jersey.

Interestingly the homogenization of the data for the USHCN reported temperatures also creates a higher R^2 for this state.

Effect of local population on homogenized temperature for the USHCN stations in New Jersey.

Which suggests there might be some difference between the two sets of data, as there would appear to be. The recent drop is a little less than common to many earlier states.

Delaware combined temperatures

The last post in this series looked at the temperatures for Maryland and so, moving up along the coast, the next stop is Delaware.

Delaware USHCN stations (CDIAC)

Given the small size of the state, I thought it might also be interesting to compare the results with those for the GISS station in Washington D.C., since the latter would otherwise be left out. They are at about the same latitude, and of somewhat similar elevation, differing only in the size of their populations.

Temperatures as reported for the GISS station in Washington D.C. (GISS )

Given the built-up nature of the area around Wilmington there could be some debate as to the relative population sizes about the various stations, but for the moment I will accept the values from the citi-data sites that I have used to date. (The question is raised particularly regarding the Newark University Farm, which GISS considers to lie within metropolitan Wilmington).

It turns out that Washington is, on average, about 2.76 deg F hotter than the average for Delaware, though the difference has changed, with a steady increase until around 1980, and a fall thereafter.

Difference between the temperature reported for the GISS station at Washington DC and the USHCN average homogenized temperature for Delaware.

Looking at the overall change in temperature over time for Delaware alone, there is still that drop in temperature that occurs between around 1948 and 1965:

Average temperature for the USHCN stations in Delaware after homogenization.


Before homogenization, however, looking at the Time of Observation adjusted raw data, the trend is not as significant:

Average temperature for the USHCN stations in Delaware raw data after correction for time of observation (TOBS).

The temperature drop from around 1950 to 1965 is still present, but the overall temperature increase has fallen from 1.9 deg F per century down to 0.5 deg F per century.

Delaware is the second smallest state (after Rhode Island) and is only 100 miles long, while 30 miles wide. It stretches roughly from 75 deg W to 75.75 deg W, and from 38.5 deg N, to 39.8 deg N. The mean latitude is sensibly 39 deg N, the average of the USHCN stations is 39.3 deg N (D.C. is at 38.85). The state elevation runs from sea-level to 137 m with the mean at 18.3 m. The average of the USHCN stations is at 28.6 m.

The small number of stations makes the correlation coefficients of little real value, but they are included for consistency. It will be interesting to see how these numbers fit in when I compile the overall statistics.

Change in average station temperature in Delaware as a function of latitude.

Change in average station temperature in Delaware as a function of longitude.

Because of the relatively small change in elevation for the different stations, the correlation with elevation is not as evident here.

Change in average station temperature in Delaware as a function of elevation.

When I looked at the TOBS data available there is insufficient recent information to provide a realistic plot of temperature against local population unfortunately, but I’ll include the plot for consistency.

Change in average station temperature in Delaware as a function of population around the station.

It is clear in Delaware, as elsewhere, that the homogenization of temperature data, has led to an increase in reported temperatures with time.

Increase in temperature from the TOBS data to the reported homogenized temperatures for the stations in Delaware.

Virginia combined temperatures

This is a continuation of the series where I look at the temperatures recorded for an individual state, over the past 115 years, and see what that data tells us. Moving on from West Virginia which I covered last, to Virginia returns me to the Atlantic coast, and a certain curiosity as to whether the significant drop in temperatures between 1948 and 1965, found in other states further South along the coast, also occurred here. (For the impatient, it does). Virginia has 19 USHCN stations from Blacksburg to Woodstock, and has two GISS stations on the list, at Richmond and Roanoke.

Location of the stations in Virginia (CDIAC )

Unfortunately the CDIAC site still has the problems that I noted last week, when writing about West Virginia and it doesn’t appear possible at the moment to get the data directly from the site, which is an irritant. There are five Richmond sites as supplying data to GISS, though only one, Richmond Byrd, with the correct location, and it has data from 1911. Richmond is relatively close to the coast, and shows the temperature drop I referred to above, reaching a high in 1949, then dropping to a low in 1966.

UPDATE: Browsing Climate Audit, I came to Martin A's suggestion that we should consider the first difference trend for temperatures. I hadn't thought to do that, but since the data is easy to hand, I ran the plot and have added it to the end of the post. As Hu McCulloch noted, it doesn't seem to add much to the information on the state temperatures, having just about averaged out over the century. So, with respect, I don't think I'll add it to the repertoire.

Annual temperatures as reported for the GISS station at Richmond, VA.

Roanoke is one of the westernmost stations in the set, and it only has data from 1948, so that although there is a fall in temperatures from the beginning, which bottoms out in 1982, information on the temperatures in the 30’s is missing.

Annual temperatures as reported for the GISS station at Roanoke, VA.

When I combine the temperatures for the state from the USHCN network, and compare this with the average for the two GISS stations, then I get a graph that shows the change in range of the two stations, but that, recognizing that impact, shows that the GISS stations have always shown a higher temperature (by about 2.8 deg F).

Difference between GISS station average temperature and that of the USHCN average temperature per year.

In terms of the overall change in temperatures of the state over the century of data acquisition:

Change in average station temperature with time, for Virginia

There is still that drop in temperature from around 1950 to about 1968, with a consequent pick-up in temperature. Obviously we are no longer in that group of states that lost temperature over the century.

Virginia is 430 miles long and 200 miles wide. It runs from 75.22 deg W to 83.62 deg W, and from 36.52 deg N to 39.62 deg N. The central latitude is 37.49 deg N, that of the USHCN average is 37.7 deg N, and that of the GISS stations is 37.41 deg N.

The elevation in the state runs from sea-level to 1,742 m, with a mean elevation of 290 m. The average elevation of the USHCN stations is 281 m, and for the GISS stations 172 m.

It was a little more difficult to get the information on population for Virginia, since the site names did not easily fit with the source sites that I use. Bremo Bluff did not have a citi-data site, so I used the Zip-code site to find that it was 795. Burkes Garden was a little more of a challenge, with a population of 260 coming after a greater search, though it is 7 miles from Tazewell which has a population of 4,282. Dale Enterprise turns out to be on the outskirts of Harrisonburg (I had to use Google Earth to find that one) Hot Springs is (via Google Earth) actually now in Clifton Forge. Lincoln is near Purcellville, using the same approach; Piemont is in Orange, VA (via Google Earth) And so, ultimately it was possible to get some information on population sizes for all the stations around the state.

Looking therefore at the effects of geography and people on station data for Virginia.

Average station temperature for Virginia as it compares with station latitude.

The correlation is not as good as it normally is, and that may be because of the large variations in elevation within the state. That elevation also influences the apparent correlation with longitude, but remember that this regression line went up on the other side of the mountains in West Virginia.

Average station temperature for Virginia as it compares with station longitude.

The regression coefficient is also much greater with elevation.

Average station temperature for Virginia as it compares with station elevation

Correlating temperature over the past five years with recent population, gives:

Average station temperature for Virginia as it compares with population near the station.

If one were to take out the temperatures pre 1915, the homogenized and TOBS data would have been relatively equivalent until just after 1980 when there is an increase in the homogenized average.



UPDATE: Here is the finite difference plot, i.e. I have plotted the temperature change each year, by subtracting fromt hat annual average the temperature of the previous year, as a function of time. It is for the average of the USHCN TOBS data for the year, and it appears to suggest that, overall, the changes average out - which would suggest there hasn't been that much change in overall temperature, though the plots at the start of the post would suggest a rise of some 1.6 deg F per century.

Change in average Virginia temperature from the previous year, as a function of time.