Posts Tagged ‘UAH’

Rainfall and Temperatures Part 2

November 29, 2015

In my last post I showed how in Australia more than three quarters of the difference between surface maxima and tropospheric anomalies can be explained by variation in rainfall alone. Figure 12 from that post showed that clearly:

Fig. 1: 12 month rainfall vs surface maxima – TLT difference: Australia

max diff v rain scatterplot

In this post I am looking at the different contributions made by the north and the south of Australia. This map shows the regions used for climate analysis by the Bureau.

Fig. 2: Climate regions

Climate regions
Northern Australia and Southern Australia have vastly different climates, as shown by the following graphs of mean monthly rainfall:

Fig. 3: Mean Monthly Rainfall: Northern Australia

Nthn rain av

Fig. 4: Mean Monthly Rainfall: Southern Australia

Sthn rain av

The sheer volume of wet season rain in the north dominates, and distorts, the national means, therefore it is sensible to analyse northern and southern influences separately.

Northern Australia, north of 26 degrees South, has less than 3 degrees outside the Tropics, so may be considered the tropical northern half of Australia. Do not think of this as a lush tropical paradise. Far from it. There are a couple of very small areas of wet tropics, and some softer country in the far south-east, but the rest is either monsoonal wet/dry (very wet summers, almost completely dry for the rest of the year), or desert. The rainfall graph for Northern Australia is for the whole region- most of which is desert. If the monsoon is weak or fails altogether we get drought.

Southern Australia is largely influenced by the Southern Annular Mode. Each winter the southern high pressure systems move north, and cold fronts sweep across the south bringing winter rains. If these systems don’t move far enough north, the rain systems dodge the bottom of the continent, resulting in drought conditions. The far north-east of Southern Australia (southern Queensland and northern New South Wales) gets a wet summer/ dry winter pattern, and Tasmania and coastal New South Wales get rain in all seasons.

Comparing the influences of northern and southern rainfall on the national surface- TLT differences:

Fig. 5: Northern rain vs national maxima- TLT difference

Nthn rain v nat max diff

More than two thirds of the national maxima-TLT difference can be explained by variation in the northern rainfall alone.

Southern rainfall has a much weaker correlation with national maxima- TLT difference:

Fig. 6: Southern rain vs national maxima- TLT difference

Sthn rain v nat max diff

Now let’s plot Northern rain vs northern maxima- TLT (for the whole of Australia) difference, firstly for each month:

Fig. 7: Northern rain vs northern maxima- national TLT difference: monthly

Nth rain v nth diff monthly

Nearly two thirds of the monthly difference can be explained by monthly rainfall alone.

Fig. 8: Northern rain vs northern maxima- national TLT difference: 3 monthly

Nth rain v nth diff 3m

Three quarters of the 3 month mean surface maxima minus national TLT difference can be explained by rainfall.

Fig. 9: Northern rain vs northern maxima- national TLT difference: 12 monthly

Nth rain v nth diff 12m

R squared value of 0.8348 corresponds to a correlation of -0.91! But wait- there’s more! The 24 month means give an even better fit!

Fig. 10: Northern rain vs northern maxima- national TLT difference: 24 monthly

Nth rain v nth diff 24m

And 120 month means show an extremely close fit:

Fig. 11: Northern rain vs northern maxima- national TLT difference: decadal

Nth rain v nth diff 120m

97% of decadal northern surface maxima- national TLT difference is explained by decadal northern rainfall variation.

Fig. 12: Southern rain vs southern maxima- TLT difference: monthly

Sth rain v Sth diff monthly

Fig. 13: Southern rain vs southern maxima- TLT difference: 3 monthly

Sth rain v Sth diff 3m

Fig. 14: Southern rain vs southern maxima- TLT difference: 12 monthly

Sth rain v Sth diff 12m

More than half the difference between southern Australian maxima and TLT can be explained by southern rainfall variation.

However, 24 month means are not as good a fit:

Fig. 15: Southern rain vs southern maxima- TLT difference: 24 monthly

Sth rain v Sth diff 24m

And the long term means are a much poorer fit:

Fig. 16: Southern rain vs southern maxima- TLT difference: decadal

Sth rain v Sth diff 120m

Only 34% of the decadal southern Australian maxima-TLT difference is due to rainfall variation.

In tabular form:

Fig. 17: Range of rainfall anomalies and R-squared values for regional rainfall vs regional surface maxima- national TLT differences

Table rain r2


Australian climate is dominated by the tropics, and tropical rainfall variation dominates the national surface- troposphere differences, and even more so the tropical surface – national troposphere temperature differences: the greater the rainfall variation, the greater the difference between surface and tropospheric temperatures.

For a better analysis, we would need UAH anomalies for Australia separated into north and south of 26 degrees South.

Why Are Surface and Satellite Temperatures Different?

November 20, 2015

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.

The context:

This map shows the location of the Acorn surface temperature observing sites.

Fig.1: ACORN-SAT sites

Acorn network

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

Rainfall network awap

Fig.3: mean annual rainfall:

Avg ann rain map

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.

The data:

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

Max v min

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

min v uah

Fig. 6:  Maxima vs TLT anomalies

max v uah

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

max v 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

min v 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

min diff v rain

However, Acorn maxima minus UAH matches rainfall remarkably well.

Fig.10: Acorn maxima anomalies minus TLT anomalies compared with rainfall anomalies

max diff v rain

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

Max-UAH v rain%

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

max diff v rain scatterplot

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.

Yes, but…

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

Vegetation Oct 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.

The Pause: October 2015 Update

November 11, 2015

UAH v6.0 data for October were released on today.  Here are updated graphs for various regions showing the furthest back one can go to show a zero or negative trend (less than +0.01C/ 100 years) in lower tropospheric temperatures.  The strongest El Nino since 1997-98 has struck down its  first victim!  There is now NO pause in the Northern Hemisphere data.  However, in some regions it has lengthened.  Note: The satellite record commences in December 1978.  The entire satellite record is 36 years and 11 months long.



Zero trend oct 2015 globe

There has been zero trend for over half the record.

Northern Hemisphere:

It might be something I’m getting wrong in my calculations, but the Pause has suddenly disappeared.

The trend since December 1997 is +0.17C/ 100 years +/-0.1C.

Southern Hemisphere:

Zero trend oct 2015 SH

The Pause has extended by several months.  For more than half the record the Southern Hemisphere has zero trend.


Zero trend oct 2015 tropics

Unchanged from last month.

Tropical Oceans:

Zero trend oct 2015 tropic oceans

Unchanged from last month.

North Polar:

Zero trend oct 2015 N Polar

The Pause has lengthened by one month.

South Polar:

Zero trend oct 2015 S Polar

For the whole of the satellite record, the South Polar region has had zero or negative trend.  So much for a fingerprint of warming due to the enhanced greenhouse effect being greater warming at the Poles!


Zero trend oct 2015 oz

The Pause has lengthened by two months.

USA 49 states:

Zero trend oct 2015 USA49

Four months shorter.

And now, in breaking news, for those who were waiting to hear whether satellite data confirm October 2015 as Australia’s hottest ever………

Oz October rankings

Sorry, but this October ranked 12th out of 37.  It made the hottest third (just).

The Pause continues.

Pause Update September 2015

September 11, 2015

UAH v6.0 data for August were released on Wednesday.  Here are updated graphs for various regions showing the furthest back one can go to show a zero or negative trend (less than +0.01C/ 100 years) in lower tropospheric temperatures.  The strongest El Nino since 1997-98 is affecting some regions more than others.


global aug

Due to the strong El Nino, global temperatures are expected to continue to increase until May or June of 2016 (at least until February).  This will shorten the Pause.

Northern Hemisphere:


Southern Hemisphere:

S hemis aug

Tropics (20N – 20S):

tropics aug

Tropical Oceans:

tropic oceans aug

The bulk of solar heating of the Earth occurs in the tropics, which is  mostly ocean, and ENSO events occur here.  Since October 1992, very much before the 1997-98 Super El Nino, there has been no warming at all.

North Polar:

N Pole aug

South Polar:

S Pole aug

Oops!  For the whole of the satellite record, there has been NO warming in the atmosphere above Antarctica.  Remember, one of the “fingerprints” of global warming due to the Enhanced Greenhouse Effect is greater warming towards the Poles.

USA 49 States:

USA aug


aust aug

There has been no warming in the atmosphere above Australia for almost the whole lives of the current cohort of 1st Year Uni students. Just for comparison, the Australian ACORN-SAT surface data show a pause since February 2002- since they were in Preschool.

aust acorn

The Pause continues.

“Pause” Update

July 9, 2015

With the release of June data, showing the marked impact of a moderately strong El Nino, using UAH v. 6.0 data I have calculated the longest period back that the length of the pause in tropospheric temperature has been less than +0.01 degrees Celsius per 100 years:


uah pause globe 0615

North Polar:

uah pause npol 0615

Northern Hemisphere:

uah pause nh 0615


uah pause tropics 0615

Southern Hemisphere:

uah pause sh 0615

South Polar:

uah pause spol 0615


uah pause oz 0615


uah pause usa 0615

The El Nino will affect the length of the pause in some regions, but not all.  The pause continues!

Not the third hottest year either

January 11, 2015

According to the Bureau’s surface temperature record, 2014 was the 3rd hottest year on record.  The satellite derived Lower Troposphere data from UAH (University of Alabama- Huntsville) show a different picture.

uah aust 2014

If rankings are important to you, 2014 at +0.40C was in equal seventh place with 2006, and cooler than 1980, and warmer than 1988 by 0.01C.

2013 0.71 1
2009 0.64 2
1998 0.63 3
2005 0.51 4
2007 0.50 5
1980 0.49 6
2014 0.40 7
2006 0.40 8
1988 0.39 9
2002 0.23 10
1991 0.22 11
2010 0.22 12
1996 0.17 13
2008 0.16 14
2012 0.14 15
2011 0.10 16
1990 0.09 17
2004 0.02 18
1981 -0.01 19
1995 -0.04 20
2003 -0.05 21
1982 -0.12 22
1979 -0.13 23
1999 -0.15 24
1985 -0.22 25
1989 -0.22 26
1987 -0.22 27
1997 -0.22 28
2000 -0.24 29
2001 -0.29 30
1986 -0.29 31
1993 -0.29 32
1983 -0.36 33
1994 -0.38 34
1992 -0.56 35
1984 -0.62 36

But don’t expect to find this reported by the ABC.

The Rhythm of Life has a Powerful Beat

January 30, 2014

Here’s a fresh look at global temperatures as calculated by the University of Alabama, Huntsville- the UAH dataset– from satellite measurements of the Temperature of the Lower Troposphere (TLT).

Warwick Hughes suggests that there has been a drift in the measurements since about 2005, such that calculated temperatures are too high, and we await a proposed correction.  However, we can live with that.

Here are plots of TLT for various regions of the globe.

Fig.1:  12 month running means of Global anomalies and Tropical anomalies (the region of the Earth between 20 degrees North and 20 South, which gets the majority of the solar radiation striking the Earth).Glob - Tropics

The two sets move in lock step, with a much larger variation in the Tropics than the world as a whole.

What causes these large variations?

Fig. 2: Global and Tropical anomalies with the SOI inverted, and scaled by a factor of 30.Glob - Tropics v SOI

SOI is the acronym for the Southern Oscillation Index, calculated from pressure differences between Tahiti and Darwin, and is a reasonably good indicator of El Nino or La Nina conditions.  The ENSO cycle (El Nino Southern Oscillation) originates in the tropical Pacific.  El Nino brings warmer temperatures to the world; La Nina is associated with cooler temperatures.  I have inverted the SOI to show this relationship, and scaled it down by 30 to fit on the graph.

Note how the 12 month mean of SOI precedes the temperature data.  Here’s a plot with the SOI advanced 5 months.

Fig.3:  SOI advancedGlob - Tropics v SOI adv'd

While the peaks (El Ninos) match very closely, I have marked periods following the major eruptions of El Chichon and Mt Pinatubo, which cooled temperatures for several years.  I also suggest that the atmospheric dust and cooler surfaces upset the ENSO cycle as traced by the SOI.  Note also that temperatures in the 2010-2011 La Nina appear higher than expected.

Fig.4: SOI advanced with Tropic and Australian land TLT.Australia

Note how Australian temperatures appear to fluctuate about as much as the Tropics (we’re one third north of 20S after all).  Australian temperatures are influenced by events in the Indian Ocean and Southern Ocean as well as the Pacific, so the match isn’t exact.

I will look at Australian data specifically in another post.

Finally, here’s a way to check on that other “finger print” of the enhanced greenhouse effect, as espoused by Dr Karl Braganza: land areas are expected to warm faster than oceans, supposedly showing that greenhouse gases, not ocean currents, drive global warming.

Fig. 5: Global Land and Ocean v oceans

Well of course that proves it- land areas are indeed warming faster than oceans.

However, have a closer look at the timing of the switches between warming and cooling.  If well mixed greenhouse gases are warming both land and oceans, it would be expected that oceans, with higher specific heat and enormous thermal inertia, would take longer to warm.  The land response would be almost immediate.  Oceans would not be expected to warm before the land, and if anything might show a slight lag.

Fig.6: close up of the 1998 Super El v oceans 1997-99

The oceans change phase about one month before the land.  They definitely do not lag behind.

And what causes these rapid changes?

Fig.7: Land, ocean, and the SOI advanced 5 v oceans v soi


The world’s temperatures respond to the powerful beat of ENSO events- as well as large explosive volcanic




Was 2013 the Hottest Year on Record? Update!

January 6, 2014

Update:  Warwick Hughes has reminded me of his post on 5 December at where he shows a distinct drift in UAH data compared with RSS, and in later posts he confirms this in southern Africa and the USA.  Warwick says:

"I have checked UAH against CRUT4 and GHCN CAMS for all Australia and it
looks like there was a drift in UAH 2005-2006.

Until UAH resolves the issue, I think their ranking of Australian hot
years is not worth repeating."

That may help explain the large divergence in recent years.  

I will leave this post as is, with the caveat that it is based on available UAH and Acorn data.


On Friday, 2 January, the BOM released its Climate Statement claiming 2013 as the hottest year on record.

The UAH dataset for lower troposphere temperatures has also been just released.

I have compared BOM monthly data with UAH by converting the BOM anomalies to the same reference period as UAH (1981-2010).

Here is the result:  UAH vs BOM 1978-2013 (12 month running means)uah v bom

It is plain to see that in the satellite era, Australian surface temperatures (as calculated by the BOM) reached a record last year.

For the 12 month periods to December, UAH agrees that 2013 was the hottest, just ahead of 1998 and 2009.

According to UAH, the 12 months period to October 2013 was just edged out by the 12 months to June 2010.

So, the BOM is right in saying 2013 was the hottest on their 104 year (and very much adjusted) record.

While the two datasets match reasonably well in most years, especially 1996-1999, they diverge markedly in recent extreme years.  It appears that the BOM area averaging algorithm accentuates extremes, probably because of the scarcity of observing sites in the remote inland, where warming and cooling are much greater.  Alice Springs, for example, being hundreds of kilometres from the nearest neighbouring site, contributes 7 – 10% of the national warming signal.

As well, the satellites’ remote sensors do not necessarily match the atmospheric conditions at ground level, depending on different seasonal conditions.  However, to quote Dr John Christy, “the temperature of the lower troposphere (TLT) more accurately represents what the bulk atmosphere is doing – which is the quantity that is most directly related to greenhouse gas impacts.”

So- if you are interested in the weather, how hot it is locally, consult the BOM- the old Weather Bureau.  If you are interested in whether the climate is changing due to greenhouses gases, consult the satellite data.

And yes, the weather has been hot (and still is where I live).

UAH for September

October 19, 2013

The UAH lower tropospheric temperature anomaly for Australia for September was +1.56C, up from +1.12C in August.  The 12 month running mean has now reached +0.72C, which as commenter barry noted is not statistically different from equal highest since 1979.  Nor is it a record- the 12 months to September is now the third hottest (after June and May 2010).  Uncertainty for UAH is +/- 0.1C.  We may yet see a record.

uah 12m sept13


2010 and 2013 marked.  Mean and +/- 2 standard deviations shown.

Australia’s warmest 12-month period on record- NOT

September 11, 2013

Ken Stewart

September 2013

Australia’s Bureau of Meteorology (BOM) was quick off the mark earlier this month when it proclaimed:

Australia’s warmest 12-month period on record

September 2012 to August 2013: the last 12 months

The past 12 months have been the warmest on record for Australia. The average temperature across Australia for the period 1 September 2012 to 31 August 2013 was 22.92 °C. This is 1.11 °C above the 1961–1990 average, surpassing the previous record of +1.08 °C that occurred between February 2005 and January 2006.”

The satellite data for the mid-troposphere for Australia- Land has just been released by the University of Alabama- Huntsville (UAH).  Unfortunately analysis of this data shows that the mean temperature for the 12 months to August 2013 was +0.668 Celsius, which makes this period the sixth warmest of the satellite era (since December 1978).


That’s 0.087 below the record set in the 12 months to June 2010.

Here is a graph of the 12 month running mean to August 2013:


Yes, it has definitely been warm.  The Sub-Tropical Ridge being so far north, and the dry conditions in the northern inland, may have something to do with that too.

The Bureau expects temperatures for the rest of the year to be above average, and claim that

“If a mean temperature of more than 1.0 °C above average is maintained over the next one-, two-, three- or four-month periods, each of the 12-month periods ending September, October, November and December would exceed the previous record from 2005–06 for the warmest 12-month period.”

On the other hand, if  UAH records data for the Australian region of +1.0C for the next four months, the 12 months to December will be +0.748, the warmest calendar year on the UAH record, but still in third position for the 12 month mean.

And there is no doubt that this could happen.  But only in 2006 and 2007 were there a total of just three months out of 12 above +1.0C, not five in a row.  I’m not holding my breath.

It depends which data you would trust, from satellites criss-crossing the globe 24 hours a day, or from 104 scattered stations recording a daily maximum and minimum.