A slight rise in global average for February to 0.89C .
The reason for the slight rise seems to be because La Nina has finally faded away!
Triangulation of temperature measurements. This shows areas of above and below normal values (1961-1990 average)
All results can be downloaded
The last post showed that there was little change in the timing of, or the seasonal maximum of temperatures in Australia. Here I look at the long term trends in 3 different locations Yongala in SA, Alice Springs in central Australia and Townsville near the coast in Queensland.
Maximum daily temperatures and the Diurnal range in temperatures for Yongala, SA Click for large version.
The top signal is the daily maximum temperature recorded for over a 73 year period (73 summers). There are some very hot days but overall the signal is remarkably stable with no evident warming trend. The bottom trace shows the daily range in temperatures between night and day. There is a clear tendency for higher daily temperature swings in winter but there is no long term trend evident.
Alice Springs located in central Australia shows a much stronger seasonal change in maximum temperatures
Daily Maximum and Diurnal temperature range for Alice Springs. Note how there appears to be no change in Maximum temperatures.
Townsville is located in Northern Queensland next to the sea and the Great Barrier reef . It has a semi tropical climate and shows a much smaller seasonal cycle, with a smaller diurnal temperature range, inversely proportional to the seasons. Presumably this is because the ocean is cooler in winter reducing overnight temperatures.
Townsville daily maximum temperatures and diurnal temperature range.
None of these stations show any significant warming signal in this data. So why does ACORN show a warming trend ? The main reason is that they all use a selected set of “anomalies” based on the monthly differences to their 30 year temperature average. These values are called station “normals”. However before all this another bit of black magic called “homogenisation” is applied. Finally just 112 stations are selected for this warming trend analysis
Homogenisation is based on the assumption that nearby stations all follow the same warming trend, So there is an inbuilt tendency to correct or even reject any negative trends. Systematic differences can indeed be due to a site relocation, inducing a positive trend. When I looked at this earlier I found that this increased the average temperature anomaly trend by about 0.3C
Difference between the homogenised result (ACORN-SAT) and Raw measurements (1805 stations). Note the linear increase of about 0.3C with time.
One more problem is that anomalies don’t tell you whether it is maximum temperatures that are rising or instead minimum temperatures that are rising.
I found previously that in Australia it is nights (Tmin) that are warming rather than days (Tmax) !
Average maximum land temperatures in Australia compared to minimum temperatures
The global temperature data on land that is used to measure climate change is based on daily measurements across thousands of weather stations, some some of which date back to the 1700’s. These stations record the average temperature for each day based on the minimum (night-time) and maximum (day-time) temperatures. Originally these were measured by physical Min-Max thermometers, whereas today they are mostly automated digital recordings. The daily average temperature at each station therefore is just simply
Tav = (Tmin + Tmax) / 2
The monthly average <Tav> is calculated for the 12 months of the year for each station. These temperatures depend on the altitude and location of the station. Therefore in order to compare and combine them together us Temperature “anomalies” instead. For a given station the “anomaly” is the deviation from a 30 year climatology derived for that station by averaging <Tav> over a baseline 30 year period. These values are called “normals” and the 30 year period is a “baseline”. CRU uses a 1961-1990 baseline and NASA uses a 1951 – 1980 baseline. Finally all the monthly temperatures values recorded at each station are subtracted from their monthly “normals” to yield so-called monthly temperature “anomalies”. Once combined with sea surface temperature anomaly data and averaged over the earth’s surface we then measure a Global temperature anomaly. This has “temperature” has risen by ~1.2C since pre-industrial times. The rest of the story we know well.
However we can also define other “global” parameters such as “temperature range” which can be defined as follows:
Trange (Daily Diurnal Range) = (Tmax – Tmin)
We can then follow exactly the same procedure used for temperature anomalies to define Trange “anomalies”, and then compare these with more traditional temperature anomalies. For this comparison I use the GHCN daily temperature of Berkeley Earth because it is based on daily measurements.
Tav and Trange anomalies (Berkeley Earth)
We clearly see that as global land temperature anomalies “rise” so the global diurnal temperature “range” on land “falls”.
This effect can also seen in the Australia as calculated using the daily raw temperature measurements (ACORN), (curtesy Ron Graf).
Average Temperature Range compared to temperature anomaly (ACORN)
So the absolute temperature range is also reducing as the temperature “anomalies” rise.
Could the timing of seasons be changing due to human development? I chose to look at Alice Springs Airport because it is based in central Australia, far from coastal effects yet susceptible to urban development and of course rising CO2 levels.
Comparison of recorded temperatures in Alice Springs from 1950s with those in 2010s
There is no statistically significant effect whatsoever! The climate in Alice Springs seems to be remarkably stable.
