DTR, Cloud, and Rainfall

In my last brief post I showed how Diurnal Temperature Range is related to rainfall in Northern and Southern Australia in Northern and Southern wet seasons (which correspond roughly to summer and winter).

In this post I show the relationship between DTR and daytime cloud, and between rainfall and daytime cloud, and something very peculiar about South-Western Australia.

All data are taken straight from the Bureau’s Climate Change Time Series page.

DTR is affected by rainfall through Tmax being cooled by cloud albedo, evaporation and transpiration, and Tmin warmed by night cloud and humidity.  There must be a relationship between clouds and rain, although it is (rarely) possible to have rain falling from a clear sky with no visible cloud.  Rain is easily measured in standard rain gauges.  Cloud is calculated by trained observers, and we only have data for 9 a.m., 3 p.m., and daytime cloud.  The data give no indication of cloud type, thickness, or altitude, just amount of sky covered (in oktas, or eighths).

Here I show scatterplots for Australia as a whole annually, and for Northern, South-Eastern, and South-Western Australia in summer and winter.  I calculate both rainfall and cloud as percentage differences from their means.

Fig. 1:  DTR vs Rain for Australia annually:


Fig. 2:  DTR vs Cloud for Australia annually:


Notice much better correlation between DTR and Cloud.

Now let’s look at the relationship between rainfall and daytime cloud.

Fig. 3:  Percentage difference in Rainfall vs percentage difference in Cloud for Australia annually:


Note a 10% increase in cloud cover could be expected to be associated with a 25% increase in rainfall.

Fig. 4: Percentage difference in Rainfall vs percentage difference in Cloud North Australian summers:


Fig. 5: Percentage difference in Rainfall vs percentage difference in Cloud North Australian winters:

Note how rainfall in the North Australian dry season varies proportionally more, but has a slightly lower correlation (>0.8 vs 0.9).

Fig. 6: Percentage difference in Rainfall vs percentage difference in Cloud South-East Australian summers:


Note the much greater effect of cloud on rainfall in the southern dry season.

Fig. 7: Percentage difference in Rainfall vs percentage difference in Cloud South-East Australian winters:


Now, get ready for a surprise.

Fig. 8: Percentage difference in Rainfall vs percentage difference in Cloud South-West Australian summers:


Fig. 9: Percentage difference in Rainfall vs percentage difference in Cloud South-West Australian winters:


What’s going on in the south-west?

Here’s how DTR compares:

Fig. 10:  DTR vs percentage difference in rainfall: South-west Australia


Similar relationship to everywhere else.

Fig. 11:  DTR vs percentage difference in cloud cover: South-west Australia


And this graph clearly shows the relationship between rain and cloud is closer in the wet seasons, but also clearly shows that South-west Australia is an extreme outlier.

Fig. 12:  R-squared comparison between rain and cloud in wet and dry seasons


Why the huge difference?  There is no relationship between cloud and rain in south-west Australia, unlike everywhere else.  The South-West has seen a marked decline in rainfall since the late 1960s, but an increase in cloud cover.  It seems counter intuitive, but there you go.

Any suggestions are welcome.

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5 Responses to “DTR, Cloud, and Rainfall”

  1. MikeR Says:


    Yet again, very thought provoking stuff.

    I suspect the issue with the South West many have something (I am not sure exactly what) to do with the use of DTR anomalies (i.e. DTR -average DTR for that month) compared to just using DTR calculated directly from Tmax – Tmin.

    I have downloaded the monthly cloud data and Acorn Tmax and Tmin data and rain data for Perth Airport from 1955 until 2015.

    Firstly for the rain data, if you correlate this with the DTR anomalies, the value for R2 is only 0.114. However if you correlate rain directly with DTR the R2 improves greatly to 0.706.

    For the cloud data correlated with DTR anomalies the value of R2 =0.227. For the cloud data and DTR, the correlation improves to R2= 0.731.

    Rain versus cloud gives R2 =0.547.

    It seems, if we had the actual DTR values rather the anomalies for S.W Australia, we might get a much better correlation than was found above.

    Ken, I know you have a large collection of temperature data both raw and homogenized for all the Acorn sites. Maybe you could look at some other sites in the south west, that have cloud data, to see if this pattern is common to these sites.

    Like you I am puzzled why S.W Australia exhibits this outlier behaviour when compared to the rest of Australia.

    I have links to plots of the data here – http://s20.postimg.org/9xmp8c44d/DTR_Cloud_and_Rain4.jpg and http://s20.postimg.org/pt6xxw5b1/Rain_versus_Cloud.jpg .

    Ken, I hope this provides food for thought for you, or someone else reading this blog. All very interesting.

  2. MikeR Says:

    Hi Ken,

    I got hold of the cloud data from the BOM ‘site networks’ under climate change, see- http://www.bom.gov.au/climate/change/index.shtml#tabs=Tracker&tracker=site-networks .

    You will find the sites that have cloud data in Australia or a particular region by selecting the Daytime Cloud (or 9 am, 3pm) option.

    It would be interesting to see if DTR derived from the Raw data gives better or worse correlations than DTR derived from the homogenized Acorn data. I might have a go at that for the Perth data if I can find the time.

  3. MikeR Says:

    Ken, That’s OK. The B.O.M. did not make it easy to find and you have to go elsewhere on their site to download the appropriate rainfall data.

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