Archive for the ‘climate’ Category

The Pause Update: March 2017

April 15, 2017

The complete UAH v6.0 data for March have been released. I present all the graphs for various regions, and as well summaries for easier comparison. I also include graphs for the North and South Temperate regions (20-60 North and South), estimated from Polar and Extra-Tropical data.

The Pause has ended globally and for all regions including the USA and the Southern Hemisphere, except for Southern Extra-Tropics, South Temperate, South Polar, and Australia. The 12 month mean to March 2017 for the Globe is +0.40 C- down 0.12 C in four months.

These graphs show the furthest back one can go to show a zero or negative trend (less than 0.1 +/-0.1C per 100 years) in lower tropospheric temperatures. I calculate 12 month running means to remove the small possibility of seasonal autocorrelation in the monthly anomalies. Note: The satellite record commences in December 1978- now 38 years and four months long- 460 months. 12 month running means commence in November 1979. The y-axes in the graphs below are at December 1978, so the vertical gridlines denote Decembers. The final plotted points are March 2017.
[CLICK ON IMAGES TO ENLARGE]

Globe:

Pause Mar 17 globe

The Pause has ended. A trend of +0.41 C/100 years (+/- 0.1C) since February 1998 is creeping up, but the 12 month means have peaked and are heading down.

And, for the special benefit of those who think that I am deliberately fudging data by using 12 month running means, here is the plot of monthly anomalies:

Pause Mar 17 globe monthly

Northern Hemisphere:

Pause Mar 17 NH

The Northern Hemisphere Pause has well and truly ended.

Southern Hemisphere:

Pause Mar 17 SH

The Pause has ended but temperatures for the last 19 years are rising very slowly.

Tropics:

Pause Mar 17 Tropics

The Pause in the Tropics (20N to 20S) has ended and the minimal trend is now +0.43C/ 100 years. 12 month means are dropping fast.

Northern Extra Tropics:

Pause Mar 17 NExT

Northern Temperate Region:

Pause Mar 17 NTemp

Using estimates calculated from North Polar and Northern Extra-Tropics data, the slowdown is obvious.

Southern Extra Tropics:

Pause Mar 17 SExT

The Pause has weakened and shortened but still persists.

Southern Temperate Region:

Pause Mar 17 STemp

Using estimates calculated from South Polar and Southern Extra-Tropics data, the Pause likewise persists.

Northern Polar:

Pause Mar 17 N polar

The trend has increased rapidly and will continue to do so even though 12 month means have started to fall.

Southern Polar:

Pause Mar 17 S polar

The South Polar region has been cooling (-0.17C) for the entire record. With 12 month means still rising, this cooling trend will slow over the next few months.

USA 49 States:

Pause Mar 17 USA49

The Pause has ended. It will not re-appear for some time.

Australia:

Pause Mar 17 Oz

The Pause is still 21 years 5 months- well over half the record.

The next graphs summarise the above plots. First, a graph of the relative length of The Pause in the various regions:

Pause Mar 17 Length

Note that the Pause has ended by my criteria in all regions of Northern Hemisphere, and consequently the Globe, and the Tropics, but all southern regions have a Pause for over half the record, including the South Polar region which has been cooling for the whole record. Note that the Tropic influence has been enough to end the Pause for the Southern Hemisphere.

The variation in the linear trend for the whole record, 1978 to the present:

Pause Mar 17 Trends 78

Note the decrease in trends from North Polar to South Polar.

And the variation in the linear trend since June 1998, which is about halfway between the global low point of December 1997 and the peak in December 1998:

Pause Mar 17 Trends 98

The imbalance between the two hemispheres is obvious. The lower troposphere over Australia has been strongly cooling for 18 years and 10 months- over half the record.  The Pause has disappeared from the USA and the Southern Hemisphere, but not the Southern Extra-Tropics, South Temperate, and South Polar regions, or Australia. El Nino tropical heat is rapidly decreasing, with all means except the South Polar region falling. The next few months will be interesting.

 

How Temperature is “Measured” in Australia: Part 2

March 21, 2017

By Ken Stewart, ably assisted by Chris Gillham, Phillip Goode, Ian Hill, Lance Pidgeon, Bill Johnston, Geoff Sherrington, Bob Fernley-Jones, and Anthony Cox.

In the previous post of this series I explained how the Bureau of Meteorology presents summaries of weather observations at 526 weather stations around Australia, and questioned whether instrument error or sudden puffs of wind could cause very large temperature fluctuations in less than 60 seconds observed at a number of sites.

The maximum or minimum temperature you hear on the weather report or see at Climate Data Online is not the hottest or coldest hour, or even minute, but the highest or lowest ONE SECOND VALUE for the whole day.  There is no error checking or averaging.

A Bureau officer explains:

Firstly, we receive AWS data every minute. There are 3 temperature values:
1. Most recent one second measurement
2. Highest one second measurement (for the previous 60 secs)
3. Lowest one second measurement (for the previous 60 secs)

Relating this to the 30 minute observations page: For an observation taken at 0600, the values are for the one minute 0559-0600.

Automatic Weather Station instruments were introduced from the late 1980s, with the AWS becoming the primary temperature instrument at a large number of sites from November 1 1996.  They are now universal.

An AWS temperature probe collects temperature data every second; there are 60 datapoints per minute.  The values given each half hour (and occasionally at times in between) at each station’s Latest Weather Observations page are samples: spot temperatures for the last second of the last minute of that half hour, and the Low Temp or High Temp values on the District Summary page are the lowest and highest one second readings within that minute of reporting.  The remaining seconds of data are filtered out.  There is no averaging to find the mean over say one minute or ten minutes.  There is NO error checking to flag rogue values.  The maximum temperatures are dutifully reported in the media, especially if some record has been broken.  Quality Control does not occur for two or three months at least, which then just quietly deletes spurious values, long after record temperatures have been spruiked in the media.

In How Temperature is “Measured” in Australia: Part 1 I demonstrated how this method has resulted in large differences recorded in the exact same minutes at a number of stations.

What explanation is there for these differences? 

The Bureau will insist they are due to natural weather conditions.  Some rapid temperature changes are indeed due to weather phenomena.  Here are some examples.

In semi-desert areas of far western Queensland, such as in this example from Urandangi, temperatures rise very rapidly in the early morning.

Fig. 1:  Natural rapid temperature increase

urandangi

For 24 minutes the temperature was increasing at an average of more than 0.2C per minute.  That is the fastest I’ve seen, and entirely natural- yet at Hervey Bay on 22 February the temperature rose more than two degrees in less than a minute, before 6 a.m., many times faster than it did later in the morning.

Similarly, on Wednesday 8 March, a cold change with strong wind and rain came through Rockhampton.  Luckily the Bureau recorded temperatures at 4:48 and 4:49 p.m., and in that minute there was a drop of 1.2C.

Fig. 2:  Natural rapid temperature decrease

Rocky 8 March

That was also entirely natural, and associated with a weather event.

For the next plots, which show questionable readings, I have supplemented BOM data with data from an educational site run by the UK Met Office, WOW (Weather Observations Worldwide).  The Met gets data from the BOM at about 10 minutes before the hour, so we have an additional source which increases the sample frequency.  The examples selected are all well-known locations in Queensland, frequently mentioned on ABC TV weather.  They have been selected purely because they are examples of large one minute changes.

This plot is from Thangool Airport near Biloela, southwest of Rockhampton, on Friday 10 March.  The weather was fine, sunny, and hot, with no storms or unusual weather events.

Fig. 3:  Temperature spike and rapid fall at Thangool

Thangool 10 march

This one is for Coolangatta International Airport on the Gold Coast on 20th February.

Fig. 4:  Temperature spike and rapid fall at Coolangatta

Coolangatta 20 Feb bom met

And Maryborough Airport on 15th February:

Fig. 5:  Temperature spike and rapid fall at Maryborough (Qld)

Mboro 15 Feb

Figure 5(b):  The weirdest spike and fall:  Coen Airport 21 March 

Coen 21 March

Thanks to commenter MikeR for finding that one.

All of these were in fine sunny conditions in the hottest part of the day.  It is difficult to imagine a natural meteorological event that would cause such rapid fluctuations- in particular rapid falls- as in the above examples.  It is possible they were caused by some other event such as jet blast or prop wash blowing hotter air over the probe during aircraft movement, quickly replaced by air at the ambient surrounding temperature.  It is either that or random instrument error.  Either way, the result is the same: rogue outliers are being captured as maxima and minima.

How often does this happen?

Over one week I collected 200 instances where the High Temps and Low Temps could be directly checked as they occurred in the same minute as the 30 minute observation.

The results are astounding.  The differences occurring in readings in the same minute are scattered across the range of temperatures.  Most High Temp discrepancies are of 0.1 or 0.2 degrees, but there is a significant number (39% of the sample) with 0.3C to 0.5C decreases in less than one minute, and five much larger.

Fig. 6:  Temperature change within one minute from maximum

Count diffs hi T graph

Notice that 95% of the differences were from 0.1C to 0.5C, which suggests that one minute ranges of up to 0.5C are common and expected, while values above this are true outliers.  The Bureau claims (see below) that in 90% of cases AWS probes have a tolerance of +/-0.2C, whereas the 2011 Review Panel mentioned the “the present +/- 0.5 °C”.  Is the tolerance really +/-0.5C?

Fig. 7:  Temperature change within one minute from minimum

Count diffs lo T graph

There was one instance where there was no difference.  The vast majority have a -0.1C difference, which is within the instruments’ tolerance.

This next plot shows the differences (temperature falls in one minute from the second with the highest reading to that of the final second) ordered from greatest to least.

Fig. 8:  Ordered count of temperature falls

Count diffs hi T

The few outliers are obvious.  More than half the differences are of 0.1C or 0.2C.

One minute temperature rises:

Fig. 9:  Ordered count of temperature rises

Count diffs lo T

Note the outlier at -2.1C: that was Hervey Bay Airport.  Also note only one example with no difference, and the majority at -0.1C.

Is there any pattern to them? 

The minimum temperature usually occurs around sunrise, although in summer this varies, but very rarely when the sun is high in the sky.  Therefore rapid temperature rise at this time will be relatively small, as the analysis shows: 80% of the differences between the Low Temps and corresponding final second observations were zero or one tenth of a degree, and 91% two tenths of a degree or less.  As the instrument tolerance of AWS sensors is supposed to be +/- 0.2C, the vast majority of Low Temps are within this range.  Therefore, the Low Temps are not significantly different from the Latest Observation figures.  Yet as it is the Lowest Temperature that is being recorded, all but one example have the Low Temp, and therefore daily minimum, cooler than the final second observation.  9% are outside the +/-0.2C range and show real discrepancy, i.e. very rapid temperature rise within one minute, that is worth investigating.  Remember, the fastest morning rise I’ve found averaged about 0.2C per minute.

The High Temps have 56% of discrepancies within the +/-0.2C tolerance range.  Day time temperatures are much more subject to rapid rise and fall of temperatures.  The 44% of discrepancies of 0.3C or more are worth investigation.  Many are likely due to small localized air temperature changes, the AWS probes being very sensitive to this, but the rapid decreases shown in the examples above, as well as the rapid rises in the Low Temp examples, mean that random noise is likely to be a factor as well.

Have they affected climate analysis? 

Comparison of values at identical times has shown that out of 200 cases, all but one had higher or lower temperatures at some previous second than at the last second of that minute, with a significant number of High Temp observations (39% of the sample) with 0.3C to 0.5C decreases in less than one minute, and five much larger.  There is a very high probability that similar differences occur at every station in every state, every day.

In more than half of the sample of High Temps, and over 90% of the Low Temps, the discrepancy was within the stated instrumental tolerance range, and therefore the values are not significantly different, but the higher or lower reading becomes the maximum or minimum, with no tolerance range publicised.

This would of course be an advantage if greater extremes were being looked for.

Nearly 10 percent of minimum temperatures were followed by a rise of more than 0.2C, and 44 percent of maxima were followed by a fall of more than 0.2C.  While many of these may have entirely natural causes, none of the very large discrepancies examined had an identifiable meteorological cause.   It is questionable whether mercury-in-glass or alcohol-in-glass thermometers used in the past would have responded as rapidly as this.  This must make claims for record temperatures questionable at best.

If you think that the +/- 0.2C tolerance makes no difference in the big picture, as positives will balance negatives and errors will resolve to a net of zero, think again.  Maximum temperature is the High Temp value for the day, and 44% of the discrepancies were more than +0.2C.  If random instrument error is the problem causing the apparent temperature spikes, (and downwards spikes in the hot part of the day are not reported unless they show up in the final second of the 30 minute reporting period), only the highest upwards spike, with or without positive error, is reported.  Negative error can never balance any positive error.

Further, these very precise but questionable values then become part of the climate monitoring system, either directly if they are for ACORN stations, or indirectly if they are used to homogenise “neighbouring” ACORN stations. They also contribute to temperature maps, showing for example how hot New South Wales was in summer.

Again, temperature datasets in the ACORN network are developed from historic, not very precise, but (we hope) fairly accurate data from slow response mercury-in-glass or alcohol-in-glass thermometers observed by humans, merged with very precise but possibly unreliable, rapid response, one second data from Automatic Weather Systems.  The extra precision means that temperatures measured by AWS probes are likely to be some tenths of a degree higher or lower than LIG thermometers in similar conditions, and the higher proportion of High Temp differences shown above, relative to Low Temp differences, will lead to higher maxima and means in the AWS era.  Let’s consider maxima trends:

Fig. 10:  Australian maxima 1910-2016

graph max trend

There are no error bars in any BOM graph.  Maxima across Australia as a whole have increased by about 0.9 C per 100 years according to the Bureau, based on analysis of ACORN data.  Even if across the whole network of 526 automatic stations the instrument error is limited to +/- 0.2C, that is 22.2% of the claimed temperature trend.  In the past, indeed as recently as 2011 (see below), instrument error was as high as +/-0.5C, or about half of the 107 year temperature increase.  No wonder the Bureau refuses to show error bands in its climate analyses.

There have been NO comparison studies published of AWS probes and LIG thermometers side by side.  Can temperatures recorded in the past from liquid-in-glass thermometers really be compared with AWS one second data?  The following quotes are from 2011, when an Independent Review Panel gave its assessment of ACORN before its introduction.

Report of the Independent Peer Review Panel p8 (2011)

Recommendations: The Review Panel recommends that the Bureau of Meteorology should implement the following actions:

A1 Reduce the formal inspection tolerance on ACORN-SAT temperature sensors significantly below the present ±0.5 °C. This future tolerance range should be an achievable value determined by the Bureau’s Observation Program, and should be no greater than the ±0.2 °C encouraged by the World Meteorological Organization.

A2 Analyse and document the likely influence if any of the historical ±0.5 °C inspection tolerance in temperature sensors, on the uncertainty range in both individual station and national multidecadal temperature trends calculated from the ACORN-SAT temperature series.

And the BoM Response: (2012)

… … …   An analysis of the results of existing instrument tolerance checks was also carried out. This found that tolerance checks, which are carried out six-monthly at most ACORN-SAT stations, were within 0.2 °C in 90% of cases for automatic temperature probes, 99% of cases for mercury maximum thermometers and 96% of cases for alcohol minimum thermometers.

These results give us a high level of confidence that measurement errors of sufficient size to have a material effect on data over a period of months or longer are rare.

This confirms LIG thermometers have more reliable accuracy than automatic probes, and that 10% of AWS probes are not sufficiently accurate, with higher error rates.  That is, at more than 50 sites.  If they are in remote areas, their inaccuracy will have an additional large effect on the climate signal.   It is to be hoped that Alice Springs, which contributes 7-10% of the national climate signal, is not one of them.

Conclusion

It is very likely that the 199 one minute differences found in a sample of 200 high and low temperature reports are also occurring every day at every weather station across Australia.  It is very likely that nearly half of the High Temp cases will differ by more than 0.2 degree Celsius.

Maxima and minima reported by modern temperature probes are likely to be some tenths of a degree higher or lower than those reported historically using Liquid-In-Glass thermometers.

Daily maximum and minimum temperatures reported at Climate Data Online are just noise, and cannot be used to determine record high or low temperatures.

These problems are affecting climate analyses directly if they are at ACORN sites, or indirectly, if they are used to homogenise ACORN sites, and may distort regional temperature maps.

Instrument error may account for between 22% and 55% of the national trend for maxima.

A Wish List of Recommendations (never likely to be adopted):

That the more than 50 sites at which AWS probes are not accurate to +/- 0.2 degree Celsius be identified and replaced with accurate probes as a matter of urgency.

That the Bureau show error bars on all of its products, in particular temperature maps and time series, as well as calculations of temperature trends.

That the Bureau of Meteorology recode its existing three criteria filter, to zero-out spurious spikes and preferably send them as fault flags into a separate file in order to improve Quality Control.

That the Bureau replace its one second spot maxima and minima  reports with a method similar to wind speed reports: the average over 10 minutes.  That would be a much more realistic measure of temperature.

The Pause Update: January 2017

February 12, 2017

The complete UAH v6.0 data for January have been released. I present all the graphs for various regions, and as well summaries for easier comparison. I also include graphs for the North and South Temperate regions (20-60 North and South), estimated from Polar and Extra-Tropical data.

The Pause has ended globally and for all regions including the USA and the Southern Hemisphere, except for Southern Extra-Tropics, South Temperate, South Polar, and Australia. The 12 month mean to January 2017 for the Globe is +0.48 C.

These graphs show the furthest back one can go to show a zero or negative trend (less than 0.1 +/-0.1C per 100 years) in lower tropospheric temperatures. I calculate 12 month running means to remove the small possibility of seasonal autocorrelation in the monthly anomalies. Note: The satellite record commences in December 1978- now 38 years and two months long- 458 months. 12 month running means commence in November 1979. The y-axes in the graphs below are at December 1978, so the vertical gridlines denote Decembers. The final plotted points are January 2017.
[CLICK ON IMAGES TO ENLARGE]

Globe:

pause-globe-jan17

The Pause has ended. A trend of +0.36 C/100 years (+/- 0.1C) since March 1998 is creeping up, but the 12 month means have peaked and are heading down.

And, for the special benefit of those who think that I am deliberately fudging data by using 12 month running means, here is the plot of monthly anomalies:

pause-globe-jan17-monthly

That’s since December 1997.

Northern Hemisphere:

pause-nh-jan17

The Northern Hemisphere Pause has well and truly ended.

Southern Hemisphere:

pause-sh-jan17

The Pause has ended- just.

Tropics:

pause-jan17-tropics

The Pause in the Tropics (20N to 20S) has ended and the minimal trend is now +.39C/ 100 years. 12 month means are dropping fast.

As Tropical Oceans closely mimic the Tropics overall, I won’t show their plot.

Northern Extra Tropics:

pause-jan17-next

The minimal trend is up to +0.64C/ 100 years= that’s one degree less than the whole trend.

Northern Temperate Region:

pause-jan17-ntemp

Using estimates calculated from North Polar and Northern Extra-Tropics data, while the trend since June 1998 of +0.28 +/- 0.1C per 100 years is more than my criterion for a Pause, it is 1.2C less than the trend for the whole period. The slowdown is obvious, and for Land areas the trend is zero.

Southern Extra Tropics:

pause-jan17-sext

The Pause persists strongly, however 12 month means are still rising, and the Pause may shorten or even disappear.

Southern Temperate Region:

pause-jan17-stemp

Using estimates calculated from South Polar and Southern Extra-Tropics data, the Pause is shorter than for Southern Extra-Tropics.

Northern Polar:

pause-jan17-np

The trend has increased rapidly and will continue to do so even though 12 month means have started to fall.

Southern Polar:

pause-jan17-sp

The South Polar region has been cooling for the entire record. With 12 month means still rising, this cooling trend will slow over the next few months.

USA 49 States:

pause-jan17-usa49

The Pause has ended- just. It will not re-appear for some time.

Australia:

pause-jan17-oz

The Pause is still 21 years 5 months. Heat in recent weeks may push the 12 month mean higher and shorten the Pause. (September, oops!)

The next graphs summarise the above plots. First, a graph of the relative length of The Pause in the various regions:

pause-length-jan17

Note that the Pause has ended by my criteria in all regions of Northern Hemisphere, and consequently the Globe, and the Tropics, but all southern regions have a Pause for over half the record, including the South Polar region which has been cooling for the whole record. Note that the Tropic influence has been enough to end the Pause for the Southern Hemisphere.

The variation in the linear trend for the whole record, 1978 to the present:

trend-78-jan-17

Note the decrease in trends from North Polar to South Polar.

And the variation in the linear trend since June 1998, which is about halfway between the global low point of December 1997 and the peak in December 1998:

trend-98-jan-17

The imbalance between the two hemispheres is obvious. The lower troposphere over Australia has been strongly cooling for more than 18 years- just shy of half the record.
The Pause has disappeared from the USA and Southern Hemisphere, but not the Southern Extra-Tropics, South Temperate, and South Polar regions, or Australia. El Nino tropical heat is rapidly decreasing, with all northern means falling, but will continue to affect the Southern Hemisphere in coming months.  Global TLT anomalies are now dropping rapidly. The next few months will be interesting.

Dig and Delve Part III: Temperate Regions

February 1, 2017

In this post I draw together ideas developed in previous posts- Poles Apart, Pause Updates, Dig and Delve Parts I and II– in which I lamented the lack of tropospheric data for the regions of the northern and southern hemispheres from 20 to 60 degrees North and South.  These regions between the Tropics and Polar regions I shall call Temperate regions, as that’s what I was taught in school.

A commenter of long standing, MikeR, who has always endeavoured to keep me on the straight and narrow, suggested a method of estimating temperature data for these regions using existing Polar and Extra-Tropical data.  I’ve finally got around to checking, and can now present the results.

The correct formula is:

T (20 to 60 degrees) = 1.256 x TexT ( 20 to 90 degrees) – 0.256 X T pole(60 to 90 degrees).

This gives an approximation for these regions in lieu of UAH data specifically for them.

And the results are very, very interesting.  Hello again, Pause.

All data are from the University of Alabama (Huntsville) (UAH) lower troposphere, V.6.0.

First of all, here are plots showing the Extra-Tropics (20-90), compared with  the corresponding Temperate regions (20-60).

Fig. 1:  Monthly UAH data for Northern Extra-Tropics (20-90N) and Estimate for Northern Temperate Region (20-60N)

 nth-temp-v-next

Fig. 2:  Monthly UAH data for Southern Extra-Tropics (20-90S) and Estimate for Southern Temperate Region (20-60S)

sth-temp-v-sext

As expected, the result of very slight differences is a slight cooling of the Northern Extra Tropics trend, and a slight warming for the Southern.   No surprise there.

The real surprise is in the Land and Ocean data.  In the Northern Temperate region, CuSum analysis reveals a large regime change which occurred at the beginning of 1998.  The following plots show trends in the data up to January 1998 and from February 1998 to December 2016.

Fig. 3: Estimated Northern Temperate data trends to January 1998 and from February 1998 to December 2016.

nth-temp-2-trends

Fig. 4: Estimated Northern Temperate data trends to January 1998 and from February 1998 to December 2016: Ocean areas.

nth-temp-2-trends-ocean

Fig. 5: Estimated Northern Temperate data trends to January 1998 and from February 1998 to December 2016: Land areas.

nth-temp-2-trends-land

Say hello to the Pause again.  Northern Temperate land areas- most of North America, Asia, Europe, and North Africa, containing the bulk of the world’s population, agriculture, industry, and CO2 emissions- has had zero trend for 18 years and 11 months.  While the trend for the whole record is +1.8C per 100 years, the record is clearly made of two halves, the first with a much milder +0.7C trend, then after an abrupt step change, the second half is flat- in spite of the “super El Nino” and the “hottest year ever”.

Compare this with the Extra-Tropics data, 20-90N.

Fig. 6: Northern Extra-Tropics data (20-90N) trends to January 1998 and from February 1998 to December 2016: Land areas.

next-land-2-trends

The step change is still there, but the trends are virtually unchanged- only 0.1C different +/- 0.1C.

Why the difference?  Northern Extra Tropics data (20-90N) includes the North Polar data (60-90N).  The major change in the North Polar region occurred in early 1995, as the next two figures show:

Fig. 7: Northern Polar data (60-90N) trends to February 1995 and from March 1995 to December 2016: Land areas.

np-land-2-trends

Fig. 8: Northern Polar data (60-90N) trends to February 1995 and from March 1995 to December 2016: Ocean areas.

np-ocean-2-trends

Massive changes in trend.  Note the change apparently occurred in land data before ocean, which is peculiar, and both in the dead of winter.  Polar regions, though much smaller, have a large impact on trends for the Extra-Tropics.

In the Southern part of the globe, once again say hello to the Pause.

Fig. 9: Estimated Southern Temperate data trends to January 1998 and from February 1998 to December 2016.

sth-temp-2-trends

While the step change is much smaller, using the same dates the Pause is still undeniable.

Fig. 10: Estimated Southern Temperate data trends to January 1998 and from February 1998 to December 2016- Land areas.

sth-temp-2-trends-land

Fig. 11: Estimated Southern Temperate data trends to January 1998 and from February 1998 to December 2016- Ocean areas.

sth-temp-2-trends-ocean

Most of the Southern Hemisphere is ocean, so it follows that a Pause in the ocean leads to a Pause overall.

It is important to stress that the figures I show for Northern and Southern Temperate regions are estimates, not actual data from UAH.  However, they are pretty good estimates, and until we have data from UAH, the best available.

Of the world’s regions, South Polar and Southern Temperate regions are paused, as is the Northern Temperate Land region, which is arguably the most important.  The Tropics fluctuate with ENSO.  Only the Arctic is strongly warming.

The Temperate regions are arguably the most important of the globe.  Together they cover more than half the surface area, and contain the bulk of the world’s population, agriculture, industry, and emissions.  I hope that Dr Spencer will be able to provide datasets for these regions as soon as possible.

Unprecedented South Australian Weather!

January 22, 2017

(and it has been like that for 178 years!)

There were more blackouts in South Australia a couple of days ago following a wild storm.  In a report in the Adelaide Advertiser, SA Power Networks spokesperson Paul Roberts is quoted:

“This is just another example of the unprecedented weather in the last six months,” Mr Roberts said, referring to bouts of wild weather that have hit power supplies hard this summer and the preceding spring.

21mm of rain was measured at the Kent Town gauge.

Just how “unprecedented” is Adelaide’s weather over the past few months?  I couldn’t find any records for the number of severe storms, so for a proxy I have made do with rainfall data from West Terrace and Kent Town in Adelaide.  The overlap period has very similar rainfall recordings so I joined the two series to give a record starting on 1 January 1839.  That’s 178 years of data.

When thinking about “unprecedented”, we need to check amount, intensity, and frequency.

Firstly, a few plots to give some context.  How unprecedented was Thursday’s storm?

Fig. 1: Rainfall for the first 21 days of January compared with Days 1 – 21 of every year

adelaide-rain-21-jan

Note Thursday’s rainfall had less rain than four previous occasions on this day alone, and 20 or so in previous Januarys.

Fig. 2: Rainfall for each day of 2016 compared with each day of every year:

adelaide-rain-2016

Note the December storm had extreme rain (for Adelaide) but not a record.

Amount and intensity has been higher in many previous years.  141.5mm was recorded on 7 February 1925.

Fig. 3: 7 day average rainfall over the years:

adelaide-rain-2016-7d-avg

The topmost dot shows the maximum 7 day average for each year.  2016 got to 13.4mm on 4 October- multiply by 7 to get the weekly total rain.  Note there were many wet and dry periods all through the record.

21mm of rain fell in a severe storm on Thursday, so I arbitrarily chose 20mm as my criterion for heavy rainfall in one day as a probable indicator of stormy weather.  I am the first to admit that 20mm might fall steadily all day and not be at all associated with wild winds, and wild winds can occur without any rain, but bear with me.

Fig. 4: Rain over 20mm throughout the year:

adelaide-rain-2016-above-20

There seems to be no increase in amount or intensity of rain at any time of the year.

Fig. 5: Frequency:

adelaide-rain-2016-cnt-above-20

Note 2016 had 7 days with above 20mm in 24 hours.  That’s the most since… 2000, when there were 8 days- and many previous years had 7 or 8 days, and 1889 had 9.  So no increase in frequency.

However, Mr Roberts was referring to the last six months, spring and summer.  So let’s look at rain events over 20mm from July to December, firstly amounts recorded:

Fig. 6: July to December Rain over 20mm:

adelaide-rain-above-20-last-6m

Nothing unusual about 2016.

Fig. 7:  Frequency of heavy rain July – December:

adelaide-rain-2016-cnt-above-20-last-6m

1973, 1978, and 1992 had the same or more days with over 20mm.

I now restrict the count to spring and summer only:

Fig. 8:  Spring and Summer frequency:

adelaide-rain-2016-cnt-above-20-last-4m

Not unprecedented: 1992 had one more.  Add in last Thursday’s event to make them equal.

Conclusion

Adelaide has a long climate record, showing daily rainfall has varied greatly over the years.  There is no recent increase in amount, intensity, or frequency for the whole year, or for the last six months or four months.  Spring and summer rainfall in 2016 was not unprecedented, and to the extent that spring and summer falls over 20mm are a proxy for storms, there is no evidence for an increase in wild weather.  This is normal.  Get used to it, Mr Roberts, and make sure the electricity network can cope.

 

The Pause Update: December 2016

January 5, 2017

The complete UAH v6.0 data for December have been released. I present all the graphs for various regions, and as well summaries for easier comparison. The Pause has ended globally and for the Northern Hemisphere, and the Tropics, and may soon disappear from the USA, and the Southern Hemisphere.  The 12 month mean to December 2016 for the Globe is +0.50 C.

These graphs show the furthest back one can go to show a zero or negative trend (less than 0.1 +/-0.1C per 100 years) in lower tropospheric temperatures. I calculate 12 month running means to remove the small possibility of seasonal autocorrelation in the monthly anomalies. Note: The satellite record commences in December 1978- now 38 years and one month long- 457 months. 12 month running means commence in November 1979. The y-axes in the graphs below are at December 1978, so the vertical gridlines denote Decembers. The final plotted points are December 2016.

[CLICK ON IMAGES TO ENLARGE]

Globe:

uah-dec-16-globe

The Pause has ended. A trend of +0.32 C/100 years (+/- 0.1C) since March 1998 is creeping up, but the 12 month means have peaked and are heading down.

And, for the special benefit of those who think that I am deliberately fudging data by using 12 month running means, here is the plot of monthly anomalies:

uah-dec-16-globe-monthly

That’s since December 1997.

Northern Hemisphere:

uah-dec-16-nh

The Northern Hemisphere Pause has well and truly ended.

Southern Hemisphere:

uah-dec-16-sh

For well over half the record, the Southern Hemisphere still has zero trend.  The Pause is about to end.

Tropics:

uah-dec-16-tropics

The Pause in the Tropics (20N to 20S) has ended and the minimal trend is now +.32C/ 100 years.  12 month means peaked mid-year.

As Tropical Oceans closely mimic the Tropics overall, I won’t show their plot.

Northern Extra Tropics:

uah-dec-16-next

The minimal trend is up to +0.6C/ 100 years.

Southern Extra Tropics:

uah-dec-16-sext

The Pause persists strongly, however 12 month means are still rising.

Northern Polar:

uah-dec-16-np

The trend has increased a lot to +2.35C and since February 2003 +0.88C/100 years.

Southern Polar:

uah-dec-16-sp

The South Polar region has been cooling for the entire record.

USA 49 States:

uah-dec-16-us49

The Pause has shortened again and is about to disappear altogether.

Australia:

uah-dec-16-oz

The Pause is still 21 years 5 months, and means have peaked.  Will the Australian Pause survive where others have failed?

The next graphs summarise the above plots. First, a graph of the relative length of The Pause in the various regions:

pause-length-dec-16

Note that the Pause has ended by my criteria in all regions of Northern Hemisphere, and consequently the Globe, and the Tropics, but all southern regions have a Pause for over half the record, including the South Polar region which has been cooling for the whole record.

The variation in the linear trend for the whole record, 1978 to the present:

trends-78-now-dec-16

Note the decrease in trends from North Polar to South Polar.

And the variation in the linear trend since June 1998, which is about halfway between the global low point of December 1997 and the peak in December 1998:

trends-98-now-dec-16

The imbalance between the two hemispheres is obvious. The lower troposphere over Australia has been strongly cooling for more than 18 years- just shy of half the record.

Global TLT anomalies are now dropping rapidly.  The next few months will be interesting. The Pause will disappear from the USA and Southern Hemisphere soon, but not the Southern Extra-Tropics or Australia. El Nino tropical heat is strongly affecting the North Polar region now, and will affect the Southern Hemisphere early this year.

Dig and Delve Part 1: Running Trends

December 22, 2016

This is the first in a series of posts in which I look at monthly Temperature of the Lower troposphere (TLT) anomaly data from the University of Alabama- Huntsville (UAH) in different ways, which readers may find interesting and perhaps useful.

In this post, I bring together ideas from former posts- Trending Trends: An Alternative View and Poles Apart – to compare trends in TLT using running trends.

 

Running Trends

Fig. 1: Global UAH with linear trend

linear-trend-global

This is the standard presentation.  It shows the linear trend as at November 2016.  With every new month of data, the linear trend changes.

By calculating a running trend, that is, the linear trend from the start of the series to every subsequent data point, the trend at each point is preserved, and the trend at the final point is instantly calculated.

Fig. 2:  Global UAH running trend

running-trend-global

Figure 2 shows the historical values of the linear trend at each point, and that global temperatures are demonstrably non-linear.  As I pointed out in Trending Trends: An Alternative View, each new data point will either increase, decrease, or maintain the trend.  The longer the data series, the harder it will be to change the trend: the effect diminishes with time.

(An interesting result of the diminishing effect of temperature on the running trend is that it becomes possible to identify what temperatures are doing from the shape of the running trend plot- in fact, to identify a pause or plateau.  To maintain the trend at say 1.2 degrees Celsius per 100 years, temperatures must continue to rise.  A flat-lining running trend is evidence of increasing temperatures; a rising running trend indicates a rapid increase in temperature; but a decreasing running trend is evidence of a pause or decline in temperatures.  This is not a different definition of the pause, just another indicator.)

For 10 to 15 years, the running trend swings wildly, but after this it settles.  Now it becomes useful for analysis and comparison.

In Figure 2 above, note the large effect of the 1997-98 El Nino on the trend, but the 2009-10 and 2015-16 El Ninos have much less effect on the trend.  They are still identifiable by the increase in trend.

Fig. 3:  Regional UAH running trends

running-trend-all-regions

As we have seen previously, the North Polar and South Polar regions are distinctly different from the rest of the world and from each other.  The North Polar region has had an increasing trend (rapidly increasing temperature) from 1994 to about 2007, then a slow down with another rapid rise in the last 12 months.  All other regions have had decreasing trends since 2002-3, with an uptick in the last 12-18 months, indicating the duration of The Pause.  The trend in the South Polar region has been much lower than the others, hovering about zero for the last seven or so years, and is currently negative.

For completeness, here are the running trends for continental USA and Australia.

Fig. 4:  UAH running trends:  USA 48 States

running-trend-usa48

Fig. 5:  UAH running trends:  USA 49 States

running-trend-usa49

Fig. 6:  UAH running trends:  Australia

running-trend-aus

The next plots compare Land, Ocean, and Mean running trends for the UAH regions.

Fig. 7:  Global UAH running trends: Mean Land, and Ocean

running-trend-land-ocean-mean-global

Note that the mean trend is close to that of the Ocean, but since 1995 and especially 1998, the trend of global land areas is much higher.  Because of the ocean’s large thermal inertia, land areas warm and cool more quickly.  However, since the 1997-98 El Nino, land trends did not decrease but remained high until 2007.  This graph, as any Global Warming Enthusiast (GWE) will tell you, is evidence of warming.  What they won’t tell you is that it is evidence of any type of warming whether natural or anthropogenic- it is not by itself evidence of greenhouse warming.

Fig. 8:  Northern Hemisphere UAH running trends: Mean Land, and Ocean

running-trend-land-ocean-mean-nh

Fig. 9:  Southern Hemisphere UAH running trends: Mean Land, and Ocean

running-trend-land-ocean-mean-sh

Land trends in the Southern Hemisphere, unlike the Northern, did decrease after the 1997-98 El Nino.

Fig. 10:  Tropical UAH (20N – 20S) running trends: Mean Land, and Ocean

running-trend-land-ocean-mean-tropics

Fig. 11:  Northern Extra-Tropics UAH (20N – 90N) running trends: Mean Land, and Ocean

running-trend-land-ocean-mean-next

Fig. 12:  Southern Extra-Tropics UAH (20S – 90S) running trends: Mean Land, and Ocean

running-trend-land-ocean-mean-sext

This region warmed rapidly to 2002-3, then trends decreased.

Fig. 13:  North Polar UAH (60N – 90N) running trends: Mean Land, and Ocean

running-trend-land-ocean-mean-np

Fig. 14:  South Polar UAH (60S – 90S) running trends: Mean Land, and Ocean

running-trend-land-ocean-mean-sp

In all tropical and northern regions, Land trends have been higher than Ocean trends since 1997-98 (2002 for South Polar and Southern Extra-Tropics).  However, North Polar Ocean trends have been higher than Land since 1998.  There is a greater area of ocean than land, and ocean areas have been warming more than land.  This is the opposite of what greenhouse theory predicts.  At the poles, where warming is expected to be greatest, only the North Pole is warming, and here the warming is not greatest over land, but over the ocean.

Summing up:

  • Running trends are an effective way of showing the linear trend at any given month of a data series.
  • They are useful for comparison and analysis after the first 10 to 15 years (the early 1990s).
  • A declining running trend indicates flat or declining temperatures, thus The Pause is visible from 2002-3 to 2014-5 in all regions apart from North Polar.
  • The North and South Polar regions are distinctly different from other regions and each other.
  • Apart from North Polar region, all regions show land areas warming more than ocean areas, indicating warming from whatever cause.
  • In the North Polar region, TLT running trends of ocean areas have been higher than land.
  • These trends, especially at the poles, are not consistent with greenhouse theory.

 

The next post in this series will use running trends to derive running detrended data.

The Pause Update: November 2016

December 3, 2016

The complete UAH v6.0 data for November were released yesterday evening- the quickest ever. I present all the graphs for various regions, and as well summaries for easier comparison. The Pause has ended globally and for the Northern Hemisphere, and the Tropics, and may soon disappear from the USA, but still refuses to go away in the Southern Hemisphere.

These graphs show the furthest back one can go to show a zero or negative trend (less than 0.1 +/-0.1C per 100 years) in lower tropospheric temperatures. I calculate 12 month running means to remove the small possibility of seasonal autocorrelation in the monthly anomalies. Note: The satellite record commences in December 1978- now 38 years long- 456 months. 12 month running means commence in November 1979. The y-axes in the graphs below are at December 1978, so the vertical gridlines denote Decembers. The final plotted points are October 2016.

[CLICK ON IMAGES TO ENLARGE]

Globe:

pause-nov-16-globe

The Pause has ended. A trend of +0.28 C/100 years (+/- 0.1C) since March 1998 is creeping up.

And, for the special benefit of those who think that I am deliberately fudging data by using 12 month running means, here is the plot of monthly anomalies:

pause-nov-16-globe-monthly

Northern Hemisphere:

pause-nov-16-nh

The Northern Hemisphere Pause has well and truly ended.

Southern Hemisphere:

pause-nov-16-sh

For well over half the record, the Southern Hemisphere still has zero trend.  The Pause has shortened by two months and may end shortly.

Tropics:

pause-nov-16-tropics

The Pause in the Tropics (20N to 20S) has ended and the minimal trend is now +.27C/ 100 years.

Tropical Oceans:

pause-nov-16-tropic-oceans

The Pause has ended for ocean areas.

Northern Extra Tropics:

pause-nov-16-next

The minimal trend is up to +0.56C/ 100 years.

Southern Extra Tropics:

pause-nov-16-sext

The Pause persists.

Northern Polar:

pause-nov-16-np

The trend has increased a lot to +2.32C and since February 2003 +0.7C/100 years.

Southern Polar:

pause-nov-16-sp

The South Polar region has been cooling for the entire record.

USA 49 States:

pause-nov-16-usa49

The Pause has shortened by one month and is about to disappear altogether.

Australia:

pause-nov-16-oz

One month longer- 21 years 5 months.

The next graphs summarise the above plots. First, a graph of the relative length of The Pause in the various regions:

pause-length-nov-16

Note that the Pause has ended by my criteria in all regions of Northern Hemisphere, and consequently the Globe, and the Tropics, but all southern regions have a Pause for over half the record, including the South Polar region which has been cooling for the whole record.

The variation in the linear trend for the whole record, 1978 to the present:

trends-78-now-nov-16

Note the decrease in trends from North Polar to South Polar.

And the variation in the linear trend since June 1998, which is about halfway between the global low point of December 1997 and the peak in December 1998:

trends-98-now-nov-16

The imbalance between the two hemispheres is obvious. The lower troposphere over Australia has been strongly cooling for more than 18 years- just shy of half the record.

Global TLT anomalies have remained stubbornly high.  The next few months will be interesting. The Pause may disappear from the USA and Southern Hemisphere soon, but not the Southern Extra-Tropics or Australia. El Nino tropical heat is strongly affecting the North Polar region now, and will begin to affect the Southern Hemisphere early next year.

Land and Sea Temperature: South West Australia Part II: TMin

November 29, 2016

This is a quick follow up to my last post, as an update:  I’ve been reminded to show Tmin as well.   My apologies.

In this post I examine minimum temperature for Winter in South-Western Australia, and Sea Surface Temperature data for the South West Region, all straight from the Bureau of Meteorology’s Climate Change time series page .

All temperature data are in degrees Celsius anomalies from the 1961-90 average.

Fig. 1:   Southwestern Australia Winter TMin Anomalies & SST

sw-tmin-sst

Note that TMin roughly matches SSTs, but there are differences from TMax.  CuSums will show this:

Fig. 2:  CuSums of Winter TMin and SST compared:

sw-tmin-cusums

Note that TMin has completely different change points, marked in red.  The major different ones are at 1949, 1956, 1964, 1990, 2000, and 2010.  There is a barely discernible point at 1976 (not 1975), so the next plots will use 1976 to show trends since then.

Fig. 3:  Trends in TMin:

sw-tmin-trends

Cooling since 1976 at -0.36C/100 years.

Detrending the data allows us to see where any of the winters “bucks the trend”.  In the following plots, the line at zero represents the trend as shown above.

Fig. 4:  TMin Detrended:

sw-tmin-detrended

2016 winter TMin is 0.5C below trend, and 0.38C below average, however winter this year in southwest WA was not as cold as 1986, 1990, 2001, 2006, 2008, or 2010- according to Acorn of course.

The action is with TMax.

Land and Sea Temperature: South West Australia

November 29, 2016

This year, the south-west of Western Australia has recorded some unexpectedly low temperatures.  Has this been due to rainfall, cloud, winds, or the cooler than normal Leeuwin Current and Sea Surface Temperatures in the South West Region?

In this post I examine maximum temperature and rainfall data for Winter in South-Western Australia, and Sea Surface Temperature data for the South West Region, all straight from the Bureau of Meteorology’s Climate Change time series page .

All temperature data are in degrees Celsius anomalies from the 1961-90 average.

Figure 1 is a map showing the various Sea Surface Temperature monitoring regions around Australia.

Fig. 1

sst-regions

The Southwest Region is just to the west and southwest of the Southwest climate region, and winter south westerlies impact this part of the continent first.  2016’s winter has seen maxima drop sharply.  In fact, it was the coldest winter since 1993:

Fig. 2:  Southwestern Australia Winter TMax Anomalies

sw-tmax

There is a relationship between rainfall and Tmax- as rain goes up, Tmax goes down, so here south west rainfall is inverted and scaled down by 100:

Fig. 3:  TMax and Rain:

sw-tmax-rain

The next plot shows TMax and the South West Region’s Sea Surface Temperature anomalies (SST):

Fig. 4:  TMax & SST:

sw-tmax-sst

Again, related: both have strong warming from the 1970s.  Next I check for whether there was a real change in direction in the 1970s, and if so, when.  To do this I use CuSums.

Fig. 5:  CuSums of Winter TMax and SST compared:

sw-tmax-sst-cusums

Both have a distinct change point: 1975, with SST warming since, but TMax appears to have a step up, with another change point at 1993 with strong warming since.  Rainfall however shows a different picture:

Fig. 6:  CuSums of Winter Rainfall

sw-rain-cusums

Note the major change at 1968 (a step down: see Figure 3), another at 1975 with increasing rain to the next change point at 2000, after which rain rapidly decreases.

I now plot TMax against rainfall and SST to see which has the greater influence.  First, Rain:

Fig. 7:  TMax vs Rain:

sw-tmax-vs-rain

100mm more rain is associated with about 0.5C lower TMax, but R-squared is only 0.22.

Fig. 8:  TMax vs SST:

sw-tmax-vs-sst

A one degree increase in SST is associated with more than 1.1C increase in TMax, and R-squared is above 0.51- a much closer fit, but still little better than fifty-fifty.

TMax is affected by rain, but more by SSTs.

I now look at data since the major change points in the 1975 winter.  The next three figures show trends in SST, Rain, and TMax.

Fig. 9:  Trends in SST:

sw-sst-trends

Warming since 1975 of +1.48C/ 100 years.

Fig. 10:  Trends in Rainfall:

sw-rain-trends

Decreasing since 1975 at 89mm per 100 years (and much more from 2000).

Fig. 11:  Trends in TMax:

sw-tmax-trends

Warming since 1975 at +2.14C per 100 years.

Detrending the data allows us to see where any of the winters “bucks the trend”.  In the following plots, the line at zero represents the trend as shown above.

Fig. 12:  SST Detrended:

sw-sst-detrended-75-to-16

Fig. 13:  Rainfall Detrended:

sw-rain-detrended-75-to-16

Fig. 14:  TMax Detrended:

sw-tmax-detrended-75-to-16

Note that SST in 2016 is just below trend, but still above the 1961-90 average.  Rainfall is only slightly above trend, and still below average.  However TMax is well below trend, and well below average, showing the greatest 12 month drop in temperatures of any winter since 1975.

My conclusions (and you are welcome to comment, dispute, and suggest your own):

  • Maximum temperatures in winter in Southwestern Australia are affected by rainfall, but to a much larger extent by Sea Surface Temperature of the South West Region.
  • The large decrease in winter temperature this year cannot be explained by rainfall or sea surface temperature.  Cloudiness may be a factor, but no 2016 data are publicly available.  Stronger winds blowing from further south may be responsible.