A new book and the temperatures in the Mountains

One of the many significant salient points that Donna Laframboise makes in her new book on the IPCC lies in the predilection of the IPCC authors to rely on computer modeling over factual data. I will probably have more to say on this in my planned review of the book (which so far is fascinating to read and damning in the details) once I finish it, but it does suggest that posts such as these on the actual variations in US temperatures over the past century will languish in outer darkness – oh, well!!

To recap where we are, after looking at the temperatures of the individual contiguous states of the American Union, I have started to look at regional changes and to compare them. A significant drop of around four degrees Fahrenheit that occurred between 1950 and 1965 along the Eastern Seaboard, and which inter alia led to a southern migration of the black-capped chickadee, has since been reversed in the warming of that region post-1965. In contrast in the middle of the country there has been sensibly no warming trend since 1895 (which might explain why the Governor of Texas finds it harder to believe in global warming, since his state hasn’t seen any).

Yet on the West Coast the trends show a relatively consistent increase in temperature since 1895. And so the next place to look is to see what happened in those states that lie along the Rockies and provide the mountainous barrier between the West and the Middle. In the following post I am going to derive this graph, and comment along the way as I get there.

Average variation in time for four regions of the country, with the results adjusted as shown to separate the curves, and show them in order (bottom to top) from West to East.

For this exercise I am going to include Montana, Idaho, Wyoming, Nevada, Utah, Colorado, Arizona and New Mexico . I have previously used both the homogenized data from the USHCN and the Time of Observation corrected (TOBS) data, with a preference for the latter since, as I noted with the individual state evaluations, it has shown a consistently better correlation across the states with latitude and elevation than the data after manipulation.

Combining first the average temperatures for the states, using the homogenized data, one gets a relatively flat curve, but one with a decided kick over the last thirty years, the sign that many consider the marker for Anthropogenic Global Warming.

Average of the state temperatures for the Mountain Region, averaging the values for the different states in the region.

However, before there is much comment on this, it should be noted (when this is compared with the figure above it) that that trend is not as clear in the four regions as I ultimately graphed them. But before getting to that let me just put up a set of comparison graphs, using the USHCN homogenized data, to show that the temperatures of the eight states that I looked at appear to vary relatively consistently. By setting them one above the other it should be easier to cross-compare.




These are relatively consistent, though they appear to smooth a bit with movement south, but to get back to that kick in the end of the plots. As you may know, and I have commented in the individual state plots, the USHCN data is “homogenized” from the raw data. When one takes the average of this “manipulation” and subtracts the Time of Observation corrected values from it, then one gets this curve as the average change made by the climate scientists in reporting the values for the stations in the evaluation (all 233 of them).

Difference between the average USHCN homogenized temperatures and the raw temperature averages, as corrected for time of observation (the TOBS values).

Given that, the rest of the analysis will go back to using the TOBS values. Firstly this changes the average a little:

Average temperatures for the Mountain states, using the Time of Observation corrected raw data.

The change in the slope of the curve drops the rise in temperature per century from 1.7 deg F to 1.08 deg F.

However this curve was obtained by just averaging the average state temperatures, there are varying numbers of stations and varying areas for the different states. When one weights the value by the relative number of stations in the state (equivalent to averaging all the stations in the region), then one gets:

Average temperatures for the Mountain states, using the Time of Observation corrected raw data and averaging the 233 stations in the region.

In each state, the area that each station “covers” (i.e. the area of the state divided by the number of stations) varies from 8,500 sq miles in Nevada, to 2,123 sq miles in Utah. To try and account for this I have weighted the state values by the areas of the states, and this gives this plot:

Average temperatures for the Mountain states, using the Time of Observation corrected raw data and weighting the state averages by the area of the state.

With this plot the steadily increasing temperature suggested in the USHCN plot does not appear as evident, and the temperatures since about 1990 seem relatively steady.

So how do the regional values now compare?

Comparison of average temperatures for the different regions of the United States (as I have defined them)

Obviously the mountain temperatures are lower than those of the other regions given that there is a fall in temperature with elevation. For the combined region this looks like this:

Variation in state temperature as a function of average station elevation in the state.

The r-squared value is much lower for this than it is for the individual stations in the region, and so I will have to look at the effects of latitude, elevation and population separately.

But to conclude I wanted to see how the temperature patterns changed across the country, and the overlay of the regional temperatures made that a little difficult to see, so I “shifted” the curves by adding and subtracting temperatures from each set, so that the comparison of shapes could be made, and that is where we came in:

Average variation in time for four regions of the country, with the results adjusted as shown to separate the curves, and show them in order (bottom to top) from West to East.

The rising number of earthquakes in America, not Iceland

This is just a short post drawing attention to a couple of things that are starting to look a little odd. The first was the subject of a post over at Chiefio’s website pointing out that there has been a recent doubling in the number of earthquakes per day along the Western coast. This led him onto a piece that suggests that the recent activity might be a pre-cursor to a volcanic eruption near Hawthorne, Nevada – since there have been over 500 of these quakes in that area. And if one goes to the USGS site that maps their location and strength, the latest image shows that activity is still ongoing.

Recent earthquakes in the Hawthorne area (USGS )

The concentration of activity around a fixed point argues more for volcanic activity than it does a growing risk of a major earthquake. However if one looks at the region in general there is also a lot of activity along the major fault lines through California. However that tends not to be as focused, suggesting that the normal movement along the faults is continuing, though intensified just south of the border.

Recent Earthquakes on the west coast (USGS)

The two phenomena may well be separate. Generally I look for a lack of earthquake activity along a fault line as an indicator that the fault is not moving in that region, and thus stress is building up, and a larger quake will be required at some time in the future to relieve that greater stress. And in that regard it is the zone without the current quakes along the fault path that is more worrying to me than the zones where there is a lot of quaking, and thus movement.

In contrast it is the focusing of lots of earthquakes in a small area that suggests that the cause of the quakes might be more due to volcanic activity. Though one really also needs the relative vertical location of the epi-centers to determine whether magma is moving towards the surface, which is generally a warning of something in the offing.

The other thing that has me a little puzzled is the opposite situation. I have been monitoring the quakes in Iceland since the eruption last year, as reported by the Icelandic Met Office, and recording all those quakes that exceed magnitude 3. (At the bottom of this post. I note that after seeing about a hundred quakes in the past year, there hasn’t been one (greater than 3) since March 12th. Which is kinda odd.

The combination of the two events may or may not be related, we will have to see how things progress, but it is worth taking note of and keeping a closer watch to see what happens next.

Temperatures in Nevada, and Death Valley

Well trying to find the temperatures for the different states and compare the USHCN data with the GISS data is proving to be more interesting than I had thought. And it is taking a fair bit more time. So when I got to Nevada, as I moved West from Missouri, I thought that today’s state would be a faster run through. Turns out that, along the way there were a couple of other issues, and so even for a smaller sized population there are some problems. (I started writing this just after inputting the USHCN initial data into the table). Nevada has Death Valley, which although it has some of the higher temperatures in the Union did not make either the GISS or USHNC lists, since it has only been providing data since 1910.


Finding the temperature relationships started out easily. Checking with the USHCN stations first, there are only 13 stations listed, and so a quick modification to the generic file, and renaming it, made it easy to get and put up the basic temperature data. There was no data appearing until 1901 for Boulder City and there were seven years missing for Searchlight. So as I described earlier, I filled in estimates for each of these values by seeing that Boulder City (for e.g.) was, at 67.13 deg, 16.49 deg warmer than the state average of 50.64 deg, and that 1895 was 3.54 deg colder than that overall average. This suggests that the Boulder City temp was 63.59 deg that year. And so I filled that number in the space, and repeated the procedure to find an estimate of the rest of the missing numbers. And then, as I started to get the GISS data I started to run into trouble.


I looked at the Chiefio site to find the sites that GISS uses in Nevada. Not being sure which station was in each state, I went through the list and checked (by using the co-ordinates and Google Earth) to make sure which state each station was in. And in the process discovered that there were actually four GISS stations in Kansas and not just the three that I listed. So I will have to go back and redo that state, adding in the info from the GISS station in Goodland, KS. (But I will put that off for this evening).

The next problem that I ran into is that Chiefio cites two stations in Nevada as being GISS stations. These are in Las Vegas, and Ely. But when I open the Las Vegas data table the data only goes back to 1937. Odd, I thought that one of the criteria for selection was that there had to be a continuous record going back to 1895. So can I do the same correction to find the earlier data. Actually given that I am looking for a difference between the two sets of data, and that there are only two stations in the GISS record, I don’t think that I can do this. Wonder what the difference is? Well let me enter the data and then take a look. (Which is not the purely scientific way of doing this, but I am doing all this out of personal curiosity so press on . . . .) And it gets a bit more strange, since when I go to the Ely data there is only data since 1947. Now in Nevada there are some 35 stations listed by GISS (though I think the odd one or two are in other states), and a number of these have data going back to 1895 or earlier (see the USHCN list), so why pick two stations that only have partial data sets?

Have to think a bit about that one, but in the meantime how am I to handle the lack of complete sets of data to compare? Well, in the circumstances it is a little difficult to do a significant comparison, since Las Vegas is the station with the lowest elevation in the set I am looking at, and thus has the highest temperature, so it will have a significant influence, when it is brought into the averages. In fact the difference between the GISS data and the USHCN data consistently increases over the years that there is GISS data.


And the average difference over the time period where there are values for both GISS stations is 4.37 degrees. The impact of the added GISS stations on the overall average can be seen over the period from 1895, with the red showing the addition of the GISS data after 1945.


Looking at the influences on those temperatures, as previously, there is a strong correlation with latitude:


This is now becoming quite consistent over the states, as is the correlation with elevation:


But here in Nevada there is no significant correlation with longitude, nor is there much of a correlation with population, probably because there are not a lot of folk living near most of the stations. And there is not a significant trend looking at overall standard deviation of the data.

I am going to try normalizing the data to the center of the state, by just using latitude, (I believe that GISS uses distance but since the correlation shown above is relatively consistent with latitude, I will use that). The center of the state is given (by GISS) at 38.9N 116.4 W. So if I adjust for that using the equation on the latitude plot, then I get a figure of:


One can use the derived equation to determine the temperature profile for a station that was at the center of the state, and at the mean elevation for the state, which turns out to be 1,676 m. And that gives a plot:


Note that I have not used the GISS data in this series, because, had I done so, since the GISS data is hotter than the average, only including it in the latter parts of the curve would give a relatively cooler initial period and hotter latter half. So I left the GISS stations out of this plot.

And when we look at standard deviation, having adjusted to the center of the state and to the state mean elevation, then the plot shows a definite decrease in scatter as the years have worn on.


Which is interesting, but remember that this is a relatively small sample. And so on to correcting Kansas, and then to see what California adds to the picture. This is the state that Chiefio first got my attention by writing about, and it also brings us down to the ocean, which, until now we have been far from.

Today there were more questions about the data than about the hypotheses, hopefully we can get on to other things next time.

37. Pick Points

Half-a dozen or so stories of interest:

Since reconvening in Juneau last month, Alaskan lawmakers have been looking to the natural gas fields in the Brooks Range foothills to deliver gas to Alaskans by 2014. There has not been a lot of exploration for gas in the region to date, more for oil. The sort of country they are talking about is dramatically photographed. There are also plans for more wells north of Prudhoe Bay. Getting Alaska’s natural gas down south is something that will come up when President Obama goes to Canada this week. However there is some concern that the current glut of natural gas, from the shales around the lower 48, might make the project unwanted for a decade or more. Pipeline companies are therefore looking at a gas pipeline from the Rockies to Chicago, for example and there are plans for a new pipeline up into the region where the gas from the Marcellus shale is coming on line. Now as long as we can keep them running . . . .

The Nevada Governor is seeking to have bonds for power-line construction become tax-exempt. This is needed since new lines to areas where sun and wind are available are often not where folk are. At the end of last month the Public Utility Commission in Texas, without that incentive, gave 7 utilities pieces of a $5 billion package to bring Wind Energy from West Texas to Houston and North Texas. And as I noted last week, the “Green Power Express” is planned to bring wind power from the Dakotas to Chicago. With the right incentives it is claimed that the lines can be in within two years. Last Monday NV Power postponed plans to build a new 1,500 MW coal-fired power plant in Nevada, but still plans on putting in the transmission lines, though now for wind. At present a renewable energy line would be less expensive. However Gristmill would rather reduce costs by putting smaller power generators nearer users – the only snag being that you have to build the generator where the wind blows. And an environmental group in California has suggested that the power plant may not be needed, if there is sufficient improvement in energy efficiency, more renewable resources used, and more natural gas plants. The postponed coal plant may, in the interim, be replaced with a smaller gas-fired plant. It is a locally popular decision.

Cellulosic ethanol has a pilot plant running that is producing 20,000 gallons a year of ethanol from corn cobs. In defining this step forward it is noted that

With a few key technology improvements, the United States could do even better, creating up to 90 billion gallons of ethanol by 2030, enough to meet one-third of the nation’s transportation fuel needs,

GM is already on board with plans to boost production of cars that can use E85. There is some concern, however, that too much emphasis on biofuel crops could come at the expense of the rainforest. And the cellulosic plant that had been planned for Grand Junction, CO has been put on hold, due to the economy. (One of the partners is Suncor). I made a list of plants that were in planning or process earlier, but this one, which was announced in October, was not on that list. At present the economic floor price for ethanol, at the pump, is considered to be $1.50 a gallon, without taxes, and if gas is selling for less than $2.65 a gallon with tax, it will undercut the sales of ethanol. Last week the average price of gas was $1.93, while that for ethanol was $1.65. However, while some are working on making the fuel production more economical, there is also work going on to make ethanol engines better.

Hopes for increased oil production from Iraq have been the base for a number of studies that decry worries of oil decline. Yet all is not well in that region of the world. There are concerns in Parliament about the current state of the oil contracts. Yet the Government is proposing to further sweeten the deals with outside companies in order to boost output further. Certainly production is increasing and hopes to meet domestic demand this year, while exports rose to 1.81 mbd in December, the highest in 5 months, their target this year is 2 mbd of exports. Iraq has signed a deal with Iran whereby it will send crude to Abadan and receive refined products back. They will also jointly exploit some common fields.

OPEC, in general, now believe that they have roughly stabilized global oil prices with their latest cuts, although there will still be some instability because of the way in which stockpiles are being manipulated. There are currently 70 – 80 million barrels (one day’s global need) on tankers held offshore. With tanker numbers rising, as demand falls, there may be more floating storage coming on line, just when it is not needed. However, if oil prices don’t pick up soon, then OPEC may decide to cut more production at their March meeting. At 26.33 mbd in January, their current output is still 1.5 mbd above the target. (This excludes Iraq), although the OPEC Sec-General says that only a 600,000 bd cut is needed for balance. And this is the season where some refineries go into maintenance mode., which may last a little longer this year.

Gazprom announced Friday that its oil production last year was down 5.8%, that will likely be hidden this week, as the company will celebrate the opening of the LNG plant at Sakhalin Island. While the first shipment is publically expected in March (it was supposed to be tomorrow), local news suggests that it won’t be until April. Gazprom is also increasing their investment in refining, and hope to attract almost as much investment this year as last.

More stories can be found at The Energy Bulletin and Drumbeat at The Oil Drum.