Many are puzzled by the difference between surface temperature, measured in Stevenson screens, and atmospheric temperature, as measured by satellites. Some sceptics suspect surface temperatures cannot be trusted; some global warming enthusiasts claim satellite data are not accurate. The truth is both are accurate enough to be useful for their own purposes. But why the difference?
I have used data from the Bureau’s Climate Change Time Series site for monthly rainfall and surface temperatures for Australia, and from University of Alabama-Huntsville (UAH) for Temperature of the Lower Troposphere (TLT) anomalies for Australia, from December 1978 to October 2015. I converted rainfall and surface temperatures to anomalies from monthly means 1981 – 2010, the same as UAH. Throughout I use 12 month running means.
Firstly, surface temperatures are supposed to be different from atmospheric temperatures. Both are useful, both have limitations. The TLT is a metric of the temperature of the bulk of the atmosphere from the surface to several kilometres above the whole continent, in the realm of the greenhouse gases- useful for analysing any greenhouse signals and regional and global climate change. Surface temperature is a metric of temperature 1.5 metres above the ground at 104 ACORN-SAT locations around Australia, area averaged across the continent- useful for describing and predicting weather conditions as they relate to such things as human comfort, crop and stock needs, and bushfire behaviour.
This map shows the location of the Acorn surface temperature observing sites.
Fig.1: ACORN-SAT sites
Note the scale at bottom left, and that they are concentrated in the wetter, more closely settled areas. As with rainfall observing sites:
Fig.2: Rainfall observation sites
Fig.3: mean annual rainfall:
The scale is in millimetres: divide by about 25 to get inches. Consequently a very large area of Australia is desert, and another large area is grassland with few or scattered trees. Very little of Australia is green for more than a few months of the year. More on this later.
Here are 12 month running means of the Bureau’s Acorn maxima and minima since December 1978.
Fig. 4: 12 month running means of monthly maxima and minima anomalies (from 1981-2010 means) for Australia
Note that minima frequently lags several months behind maxima- which is why mean temperature doesn’t give us very much useful information.
Now compare surface temperature with the lower troposphere:
Fig. 5: Minima vs TLT anomalies
Fig. 6: Maxima vs TLT anomalies
TLT approximately tracks surface temperature, but with smaller variation. So what causes the difference between surface and atmospheric temperatures?
The culprit is that wicked greenhouse gas, H2O.
In the following graphs 12 month mean rainfall is scaled down by a factor of 25, and inverted: dry is at the top and wet is at the bottom of these plots.
Fig. 7: Maxima vs Inverted Rain
It is plainly obvious that very wet periods mostly coincide with low maxima, and dry periods with high maxima.
Fig. 8: Minima vs Inverted Rain
Again, minima has no immediate relation with rainfall (although cloudy nights are warmer), lagging many months behind.
Next I calculate the difference in anomalies- surface temperature minus TLT- to analyse the difference between surface and satellite data. As minima lags many months behind rainfall a close relationship is not expected.
Fig.9: Acorn minima anomalies minus TLT anomalies compared with rainfall anomalies
However, Acorn maxima minus UAH matches rainfall remarkably well.
Fig.10: Acorn maxima anomalies minus TLT anomalies compared with rainfall anomalies
It is not an exact match of course. The next graph plots the surface maxima- TLT anomaly difference against 12 month mean rainfall anomaly sorted from smallest to largest, with the horizontal axis showing monthly percentile rank by rainfall:
Fig.11: Comparison of maxima-TLT anomaly difference with ranked rainfall anomalies
Note that the surface- atmosphere difference tracks rainfall quite closely (+/- about 0.5C), with the largest positive and negative differences at the rainfall extremes, and also that the 12 month period where the rainfall anomaly crosses from negative to positive is at the 59th percentile: there are more dry months than wet months.
Another way of showing the relationship is with a scatterplot:
Fig.12: Surface maxima- TLT difference compared with rainfall
Note the R squared value: 0.76! At least three quarters of the difference can be explained by rainfall variation alone- not bad across a whole continent with a northern wet summer / dry winter and a southern wet winter / dry summer pattern.
An over simplified explanation of a complex process:
In wetter than normal weather, more and thicker clouds reflect sunlight and shade the surface, keeping it cooler than normal. Moisture from the surface (and vegetation) is evaporated, also cooling the surface. Deep convective overturning occurs during the day and evaporated moisture ascends in the atmosphere, where it condenses, releasing heat. The troposphere anomaly is thus relatively warmer than the surface anomaly in moist conditions such as during wet weather.
In a drought, fewer clouds allows more sunlight to heat the surface. The ground is dry; surface water is scarce; vegetation is thinner, drier, and shades less of the ground. Therefore the surface is hotter than normal. Less evaporated moisture means less condensation releasing heat in the troposphere, and therefore the troposphere anomaly will be relatively cooler than the surface anomaly. As well, as the Bureau explains, ” the rate at which temperatures cool with increasing altitude (known as the lapse rate) is greater in dry air than it is in moist air.” Thus in dry weather, ignoring convection, the atmosphere will be cooler than normal.
So how does this explain why the October 2015 surface maximum anomaly was a record +3.08C above the 1981-2010 mean, while the UAH anomaly was a mere +0.71C, and the rainfall anomaly was only -12.75mm, nowhere near the lowest?
This map shows the Normalised Difference Vegetation Index for October. The Bureau explains the index as a measure of “the fractional cover of the ground by vegetation, the vegetation density and the vegetation greenness”.
Fig.13: Normalised Difference Vegetation Index (NDVI) October 2015
What do the dark brown areas look like on the ground? Here’s a photo I took recently around about the area circled red:
Fig.14: Droughted country, Western Queensland, September 2015
Bare, dry dirt with scattered tussocks of dead grass- scattered prickly acacia in the distance.
A large area of Australia is relatively bare and bone dry, therefore hotter. Over wide areas, much less moisture is convected into the atmosphere, which will thus be relatively cooler than surface anomalies. North winds blowing from the interior towards the south will bring hot dry air even to green areas, causing much hotter surface temperatures there as well. Much of the moisture evaporated from these wetter areas is blown out to sea (outside the UAH Australian grids) so the TLT over even these green areas is relatively cooler than expected.
Atmospheric temperature anomalies are necessarily different from surface anomalies. Usually, atmospheric anomalies are less than surface maxima in hot periods and higher than surface anomalies in cool periods.
There is no conspiracy: over three quarters of the difference between surface and atmospheric temperature anomalies is due to rainfall variation alone.