Correlation between Temperature and Elevation

A mate of mine (David McL.) told me not so long ago that as a rule of thumb, all other things being equal, the temperature at different locations falls by 1 degree Celsius for every 100 metre increase in elevation. Thus a place that was 100 metres above sea level could be expected to be 8 degrees hotter than a place that was 900 metres above sea level.

I decided to put this concept to the test using real historical figures sourced from the Climate Online Data produced by the Bureau of Meteorology. The locations I selected are all on reasonably similar latitudes and are in or adjacent to the various local districts where (most of) the landholders live who are currently participating in a project I have underway in conjunction with the Lachlan Catchment Management Authority and Lachlan Landcare Network.

The approach I took was basically:
1. Source the climate data from the Bureau of Meteorology website for each location
2. Divide the elevation of each location by 100 to derive a temperature adjustment figure. Thus the adjustment figure for Ivanhoe at 85 metres above sea level is 0.85 (degrees C) and the figure for Frogmore given it is 500 metres above sea level is 5 (degrees C).
3. Add the respective adjustment figures to various temperatures (types) for each location to derive an ‘adjusted temperature’ figure. Adding the adjustment figure to the actual temperature in this way is in effect theoretically determining what the temperature would be at sea level – as a common denominator.
4. Analysing the results for various temperature types (such as maximum temperature, mean maximum temperature, mean minimum temperature, and lowest temperature) to test the hypothesis that the temperature falls by 1 degree C for every 100 metre increase in elevation.

My conclusion from the above analysis is that there is a very strong correlation supporting the hypothesis when using data for the mean maximum temperature. The correlation in the data was not nearly as good for the temperature types: maximum temperature, mean minimum temperature, and lowest temperature.

The accompanying graph shows the annual mean maximum temperatures (degrees C) for each of the locations I selected (line at the top of the blue shaded area) together with adjusted mean maximum temperatures (top line of the graph). The maroon shading represents the amount of the adjustment that was applied in degrees C. The vertical axis is temperature in degrees C and the horizontal axis shows each of the locations I selected. The numerical figure at the end of the name of each location is the elevation above sea level. As I’ve said previously the elevation figures were divided by 100 to derive the temperature adjustment figure. For graphing purposes I sorted the locations left to right in order of ascending elevation.

The key points from the graph are:
1. As the elevation increases the actual annual mean maximum temperatures decline (line above the blue shading)
2. The amount of the decline in temperature as the elevation increases is in fact roughly equal to 1 degree C for every 100 metres. This is graphically demonstrated by the fact that the top line figure in the graph is virtually straight and level from left to right – across all elevations.

POST SCRIPT: After completing this post I sent a link to another mate, John F. who happens to work at the Bureau of Meteorology. He subsequently sent me a link to an article that explains some of the science behind the temperature change impact. Here is a link: http://www.uwsp.edu/geo/faculty/ritter/geog101/textbook/atmospheric_moisture/lapse_rates_1.html