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Saturday, August 21, 2010

Info Post
Back in March I looked at the temperature record for Nevada, not, at the time being aware that there were various forms of the data available. Now that the Time of Observation corrected raw data has become available, I am continuing the review of the initial sets of posts by creating a second file looking at what difference using the TOBS data makes. The first thing that is of interest is that there continue to be lots of months in which there is no data in the TOBS set, which produces a blank for that year of the record for a number of sites. While I want to get more information before going much further it is clear from the data examined to date that there is a correlation between the temperature at a given point and both its latitude and its elevation (see below). Whether those factors are built into the averages that are calculated in generating the homogenized data that was originally tabulated at the USHCN site is something I am going to look at in more detail at another time. It is interesting to note, however, that at Climate Audit, Hu McCulloch has been looking at different ways of finding global temperatures from station data, as have Zeke Hausfather and Steven Mosher at Watts Up With That? There has also been the recent critical review of Michael Mann's statistics in generating the hockey stick curve by McShane and Wyner , which is written to be readily understandable by less expert statisticians. (I have read it). But, as I said, those are topics for another day.

Today I went to the USHCN page, typed Nevada in the “state box”, clicked on the “Map Sites” button and downloaded the TOBS mean temperatures for the 13 stations that are available in Nevada. There are a significant number of years with no data, but looking back at the original post, there is a problem in comparing the GISS station data with the USHCN in that the GISS station data doesn’t start until 1937 in one case, and 1947 in the other. So any comparisons before then are not possible.

Looking at the difference between the GISS stations and the average TOBS temperature there is still a growing difference over the period of observation. This was obvious in the original, and remains so in going back closer to the original data.


With the homogenized data the increase is growing at 0.02 deg F per year, whereas the original data shows a growing difference of 0.03 deg F per year.

Because of the limited data, and so that the overall change can be seen in relative terms, the average temperature for Nevada is plotted slightly differently than usual. It still, however shows a steady increase in temperatures over the years.


The increase is actually greater in the TOBS data than in the homogenized data (0.018 deg/year as opposed to 0.03 deg per year).
Looking at the stage geographic information as it affects the temperature, the effect of latitude continues to be significantly important:



And while there is a slight sensitivity to longitude, again this is dominated by the changing elevation as one moves West.



This becomes more evident when looking at the effect of elevation itself, where there is a strong (actually stronger since the homogenized R^2 value is o.6) inverse relationship to elevation.


Given the shorter and more limited number of data series for the different stations in the state in different years, the examination of standard deviation values over time is relatively meaningless, though it is included purely for completeness.


As with the other states with relatively large percentages of the population living in smaller communities, as reflected in the populations near the stations, there is a significant logarithmic relationship to population.


I guess I missed posting that in the first review of the state. The correlation was slightly better (R^2 of 0.15) but there was less than a 10% change in the coefficients.

Well the next state to look at is California, and we start seeing the effect of the oceans. The interaction between Sea Surface Temperatures (SST) and local land temperatures is one of the factors that is built into some of the models of global temperature, but rather than look at other work, we’ll see what the data shows first.

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