A way of calculating local climate trends without the need for a government supercomputer

Changing climates? Forget temperature; watch the vegetation. If you do not want to use Koeppen, use the USDA growing regions map (plant and seed catalogs) and see if the plants in a higher numbered region are starting to grow naturally and thrive in your (lower numbered?) region. Crepe Myrtles grow well in zone 7-9, for instance. I live in Maryland and CAGW becomes real for me when palm trees grow naturally in my back yard, moving zone 9 vegetation up to the north end of zone 7. How long will that take do you think?

Interesting to read the responses here. Thanks for reading and commenting.
Some say the climate is much more than temperature, and I agree. A proper climate outlook would cover additional variables important to life, especially precipitation. A corollary principle: If you want to understand precipitation changes, study the changes, not the rainfall itself.
Preoccupation with surface temperatures comes from the global warming theory that posits temperatures are/will rise with rising CO2. I thought people should have a tool to look at the trends as they are.
It is said that a line is too simple a depiction of a complex phenomenon. True, but here’s the thing: The attempts to extract other signals from the noise are fraught with difficulty and statistical controversy. Just look at the long discussion at Bishop Hill (with some insightful comments from Nullis in Verba).
http://www.bishop-hill.net/blog/2014/7/3/where-there-is-harmony-let-us-create-discord.html#comments
It is common practice to start looking for the relation between two variables (here, time and temperature) by drawing a linear regression. That applies here, and it is rough, but useful. The deviations suggest that much more is going on and needs to be understood. But it’s a start to have a frame of reference.
I object to the BEST summary description of Kansas temperatures as rising 1.98 +/-0.14°C. Why? Because the number is partly fact and partly projection, a mixup of observed and not yet observed. It’s another indication of the malaise in climate science, where expectation and observation are repeatedly confused.
An example in the thread above are Nick Stoke’s comments. He basically is saying: These stations should not have readings so different from each other. There must be mistakes, and once we adjust for them, the records will be more in line. Well, yeah! BEST got the deviation down from 0.45 to 0.14. More about this later.
In keeping with what I said about BEST, I have to drop from my workbook the one station with an history less than 100 years. I didn’t like its shortness, but didn’t want to be accused of cherry picking (i.e. excluding available data from analysis). It happens to be only 64 years long with a century trend of 1.89°C, and removing it makes little difference to the results. Now the station ages range from 96 to 148 years old, so century observations are covered.
The point: Trustworthy people, including scientists, make it clear when they are reporting facts that have occurred, and when they are predicting future facts. Knowledge is proven ex post facto. That is why I said in the post, “if the next 100 years is anything like the last 100, then . . .” The conditional clause tells you that what follows depends on assuming the long term trend continues. If temperatures are much above or below trend, then we know something different is happening.

Bah. like should be link

Latitude, ferdberple
I concur with many issues you are raising. It is why I wanted data as close to the station sources as possible. At least with HADCRUT3, the raw data is distinguishable from their gridded product. As Greg Goodman points out, there is some nomenclature confusion. in the link below, the land station data is referred to as a HADCRUT3 “subset” without naming it specifically; ocean data being another “subset.”
The FAQs say that this raw data is cleaned observation, prior to any gridding, anomalies or averaging.
“The station data that we are providing are from the database used to produce the global temperature series. Some of these data are the original underlying observations and some are observations adjusted to account for non climatic influences, for example changes in observations methods or site location.
The database, therefore, consists of the ‘value added’ product that has been quality-controlled and adjusted to account for identified non-climatic influences. Adjustments were only applied to a subset of the stations, so in many cases the data provided are the underlying data minus any obviously erroneous values removed by quality control. The Met Office do not hold information as to adjustments that were applied and, so, cannot advise as to which stations are underlying data only and which contain adjustments.
Underlying data are held by the National Meteorological Services (NMSs) and other data providers. Such data have in certain cases been released for research purposes under specific licences that govern their usage and distribution.
It is important to distinguish between the data released by the NMSs and the truly raw data, e.g. the temperature readings noted by the observer. The data may have been adjusted to take account of non-climatic influences, for example changes in observing methods, and in some cases this adjustment may not have been recorded, so it may not be possible to recreate the original data as recorded by the observer.”
http://www.metoffice.gov.uk/research/climate/climate-monitoring/land-and-atmosphere/surface-station-records/faq
Interesting that the adjustments Nick wants to make have already been done by HADCRU, and possibly also by the NMSs. Too many cooks could spoil this broth.
Someone (our host, perhaps) said recently: “Raw data ain’t what it used to be.”
But I persist because I know that there will continue to be claims of rising temperatures.