Posts Tagged ‘climate’

How Accurate Is Australia’s Temperature Record? Part 1

January 7, 2021

In my last post I showed that maximum temperature (Tmax) as reported by ACORN-SAT (Australian Climate Observations Reference Network-Surface Air Temperature) appears to be responsible for the growing divergence of the difference between Tmax and tropospheric temperatures from Australia’s rainfall.

In this post I show how Tmax is related to rainfall, and show that while this relationship holds for discrete periods throughout the last 110 years, Tmax has apparently diverged from what we would expect.  In other words, the Acorn Tmax record is faulty and unreliable.

For much of this analysis I am indebted to Dr Bill Johnston who has posted a number of papers at Bomwatch using the relationship between Tmax and rainfall.

At any land based location annual maximum temperature varies with rainfall: wet years are cooler, dry years are warmer.  More rainfall (with accompanying clouds that reflect solar radiation) brings cooler air to the ground; provides more moisture in the air, streams, waterholes, and the soil which cools by evaporation; causes vegetation to grow, the extra vegetation shading the ground and retaining moisture, with transpiration providing further cooling; and in moist conditions deep convective overturning moves vast amounts of water and heat high into the troposphere- especially evident in thunderstorms.  Less rainfall means the opposite: more solar radiation reaches the ground with fewer clouds and less vegetation; there is less moisture available to evaporate; less vegetation growth and transpiration; and much less heat is transferred to the troposphere through convective overturning.

While more rainfall than the landscape can hold results in runoff in rivers and streams, thus removing some moisture from the immediate area, this affects large regions only in tropical coastal catchments- the Kimberleys, the Gulf rivers, the Burdekin and Fitzroy.  Across the bulk of Australia there is very little discharge of water to the oceans.  In the Murray-Darling Basin, on average less than 0.005% of rainfall is discharged from the Murray mouth. (BOM rainfall data and 1891-1985 discharge data from Simpson et al (1993))

This temperature ~ rainfall relationship is particularly evident in desert areas far from any marine influence.  Alice Springs provides a good example.  Figure 1 shows how annual maximum temperatures at Alice Springs Airport vary with rainfall since 1997.  Data are from ACORN.

Fig. 1: Tmax and Rainfall, Alice Springs

The slope of the trend line shows that for every extra millimetre of rain, Tmax falls by 0.0047 of a degree Celsius, which is about half a degree less for every 100 mm.  The R-squared value shows that there is a good fit for the data- 79% of temperature change is due to rainfall.

I said above that this relationship holds for land locations.  An island, with a little land surrounded by water, is mostly affected by sea temperature and wind direction.  Locations near the coast are also affected by marine influence.  At Amberley in south-east Queensland daily maximum temperature can be moderated by the time of arrival of a sea breeze or whether it arrives at all.  (Site changes also can change Tmax recorded.)

Fig. 2: Tmax and Rainfall, Amberley

Further inland, the relationship is strong: at Bathurst, there is 0.4C temperature variation per 100mm of rainfall and 61% of temperature change is due to rainfall alone.

Fig. 3: Tmax and Rainfall, Bathurst

The BOM has sophisticated algorithms for area averaging temperature and rainfall across Australia and provide national climate records back to 1900 for rainfall and 1910 for maxima.  Averaged across Australia individual station idiosyncrasies are submerged so that the 1997 to 2019 relationship between Tmax and rainfall is very strong (and similar to that of Alice Springs):

Fig. 4: Tmax and Rainfall, Australia 1997-2019

However, the relationship is not strong throughout the whole record:

Fig. 5: Tmax and Rainfall, Australia 1910-2019

The relationship from 1910 to 2019 is poor.

In the next figure I compare the Tmax – rainfall relationships for the first 10 years of the record with the last 10 years.

Fig. 6: Tmax and Rainfall, Australia, first and last decades

The trendlines are almost exactly parallel, with tight fits, showing strong relationships 100 years apart- but the trendline for 2010 to 2019 is about 1.7 degrees above that for 1910 – 1919.  How can that be?

It is possible to compare rainfall and temperature throughout the last 110 years.  In the next figure, rainfall is inverted and scaled down so as to match Tmax at 1910.

Fig. 7: Tmax and Inverted Scaled Rain, Australia

Running 10 year means allow us to see long term patterns of rainfall and temperature more easily:

Fig. 8: Tmax and Inverted Scaled Rain, Decadal Means, Australia

Rainfall has increased over the last 110 years (despite what you might hear in the media), and so apparently have maximum temperatures.  In the above figures Tmax and rainfall track roughly together until the mid-1950s, then Tmax takes off.

I calculated an “index” of temperature ~ rainfall variation by subtracting scaled, inverted rainfall from Tmax, commencing at zero in 1919.  This allows us to identify when temperature appears to diverge markedly from inverted rainfall:

Fig. 9: Index of Temperature ~ Rainfall Variation: Tmax minus Inverted Scaled Rain, Decadal Means, Australia

There is a small increase from the mid-1950s, but the really large divergence commences in the 1970s, with the decade from 1973 to 1982 about 0.6 units above the decade to 1972.  The index decreases to 1995, then there is another steep increase to 2007, and a final surge to 2019.

This index alone shows how poorly the official temperature record represents the temperature of the past.

 While there are other times, in the next figures I compare four periods: 1910 to 1972, 1973 to 1995, 1996 to 2007, and 2008 to 2019.  Here I use annual data.

Fig. 10: Tmax and Rainfall, Australia, four periods

Again, trendlines are almost parallel with similar slopes, showing that the Tmax ~ rainfall relationship is fairly constant for all periods- (about 0.5C per 100mm after 1995 and about 0.4C per 100mm before 1995).  However, the lines are separated.  Temperature for each later period is higher than the ones preceding, such that the temperature recorded now is about 1.5 degrees Celsius higher than it would have been for similar rainfall before 1973. And rainfall has increased in that time.

Global Warming Enthusiasts and apologists for the BOM will claim that these breaks between separate periods are real and caused by changes in circulation patterns due to climate change- in particular the Southern Annular Mode.  That will be the subject of Part 2.

Whatever the reasons, Australia wide the Tmax ~ rainfall relationship has remained constant for the past 110 years (as it should) but the temperatures reported in the Acorn dataset have increased by more than 1.5 degrees Celsius relative to rainfall.

Conclusion:

The ACORN-SAT temperature dataset is an unreliable record of Australia’s maximum temperatures.

CO2vid Watch: August

September 10, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

The CO2 concentration number for August is now published: 412.55 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is still 2.61 ppm above the figure for August last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to August 2020- Mauna Loa

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Figure 3 shows the 12 month change in CO2 concentration since the record began.

Fig. 3:  12 month change in CO2 concentration since 1958 to August 2020- Mauna Loa

Annual growth has been above zero since the mid 1970s, and has not been below 1 ppm since 2011. The annual rate of change is increasing, in other words CO2 concentration growth is accelerating.

Note that so far this year, 12 month changes continue to remain firmly in the normal or even upper range, and there is no sign of any slow down. And there won’t be!

This paper by J. Reid explains why.

http://blackjay.net/?p=1021%20%3Chttp://blackjay.net/?p=1021%3E

CO2 growth appears to be an entirely natural process.

Unless something dramatic happens, I don’t think I will continue this series any longer. There’s nothing to see.

CO2vid Watch: July

August 7, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

The CO2 concentration number for July is now published: 414.38 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is 2.61 ppm above the figure for July last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to July 2020- Mauna Loa

Notice the amount of 12 month change has increased a bit more.

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Note that so far this year, 12 month changes continue to remain firmly in the normal or even upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

CO2vid Watch: June

July 13, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

(In a coming post I will update my expectations for the end of the year and next year.) 

The CO2 concentration number for June is now published: 416.39 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is 2.47 ppm above the figure for June last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to June 2020- Mauna Loa

Notice the amount of 12 month change has increased a little.

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Note that so far this year, 12 month changes are in the normal or even upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

Covid-19 and Global Warming: Two Problems, Two Responses

June 24, 2020

Skeptics have often faced the argument, “You trust medical experts, so you should trust the climate experts”.  The science, after all, is settled.

That argument is nonsense- there is no comparison between them.

Medical researchers, in the fight against Covid-19, are using the time honoured scientific method used for decades in the search for treatments, vaccines, or cures for a host of crippling and deadly diseases- cancer, diabetes,  HIV, to name a few.

This usually involves years of careful examination of patient data and all existing information and literature, forming an hypothesis to test, designing studies, writing protocols, implementing and evaluating laboratory trials, designing and conducting animal trials, designing and conducting clinical trials, analyzing results, and then reporting findings.  It is a continuous process built on past and current evidence. 

The sought-after treatment or vaccine must pass the tests of safety and efficacy.  Doctors are enjoined: First, do no harm.  As well, the treatment must be effective.  There are many examples of trials that were stopped because they were causing higher risk of harm or were showing no benefit. 

It would be too much to expect automatic success from any of the programs under way around the world to find a safe and effective Covid-19 vaccine.

The same approach is not used in climate science:-

It is assumed that the patient (the world) has an unusually high and increasing temperature, even though patient records indicate periods of higher temperature in the past.

It is assumed that this will continue and will worsen.

It is assumed that this is dangerous and must be treated.

It is assumed that we know the cause, because of an untested hypothesis that increasing concentrations of greenhouse gases in the atmosphere, caused by the burning of fossil fuels, lead to increasing temperatures.

It is assumed that “the science is settled”, (and, even more dangerously, conflicting opinions have been actively suppressed.)

Based on these assumptions, all manner of treatments have been rushed into service, with no testing and no thought for safety or efficacy.   Unwanted and dangerous side-effects have been ignored.  Enormously expensive treatments with no proven or even possible benefit have been implemented, while other treatments (e.g. nuclear energy) are beyond consideration.

Why do I trust medical experts?

When discussing a cancer diagnosis, I trusted my specialist because he showed me the evidence, welcomed a second opinion, discussed the benefits and side-effects of different treatments (and none), gave me research papers on the safety and efficacy of the recommended treatment, and gave me time to think about it.  Nearly three years later the treatment is (so far) successful.

Thank God climate experts are not involved in the search for a Covid-19 vaccine- or cancer treatment.

A Closer Look at CO2 Growth

June 11, 2020

For a while I have been looking at atmospheric carbon dioxide data from stations around the world.  This post draws together some observations, many of which are pretty much common knowledge- but some of what I’ve found is surprising.

So I’ll start by listing some of this common and not so common knowledge:-

-The often quoted figures for global CO2 levels are not at all global, but are the local readings at Mauna Loa in Hawaii.

-The long term carbon dioxide record shows continuing increase at all stations, indicating greater output than sinks can absorb. 

-Southern Hemisphere CO2 concentration is increasing but more slowly than the Northern Hemisphere.  Their trends are diverging.

-Seasonal peaks in CO2 concentration occur in late winter and spring in both hemispheres.

-There is very great inter-annual variation in the seasonal cycle of CO2, which can be even more than the average annual increase.

-This inter-annual variation occurs at the same time in both hemispheres, even though the seasonal cycles are 6 months apart.  This implies a global cause, such as the El Nino Southern Oscillation (ENSO).  Large volcanic eruptions also have an impact.  There are likely to be other factors.

-Sea surface temperature change precedes CO2 change by 12 to 24 months.  It is difficult to reconcile this with ocean out-gassing as a cause of the inter-annual CO2 changes.  It is nonsense to claim that CO2 change leads to sea surface temperature change.

-ENSO changes occur at about the same time as CO2 changes.

-CO2 concentration increases during La Ninas. 

-El Ninos precede higher sea temperatures by 4 to 6 months.

-Because of the “oscillation” part of ENSO events, strong events are followed by opposite conditions 16 to 24 months later.  In this way a strong El Nino will lead to strong ocean warming often followed by La Nina conditions and higher CO2 concentration.

-The slowing Southern Hemisphere trend and flattening curve at the South Pole lacks satisfactory explanation.

CO2 measuring stations

Geoffrey Sherrington has shown differences existing between NOAA and Scripps daily CO2 data at Mauna Loa, and that uncertainty in daily data must be much greater than the claimed 0.2 part per million.  His article confirmed my decision to use Scripps instead of NOAA data.  In this post I use Scripps monthly data from many stations across the Pacific, and data from the CSIRO station at Cape Grim in Tasmania, to compare observations from different locations.

Figure 1 shows the locations of stations in the Scripps network, and Cape Grim.

Figure 1:  Scripps stations and Cape Grim

Point Barrow is the most northerly part of the USA, and Alert is the most northerly part of Canada.

The often quoted figures for global CO2 levels are not at all global.  They are not the global average, nor are they representative of other locations.  They are in fact the local CO2 concentration from the slopes of Mauna Loa in Hawaii.  The trend in CO2 increase is similar to, but not the same as, those in other locations.

Figure 2 shows monthly CO2 concentrations from all of the Scripps stations.

Figure 2:  Monthly CO2 at all locations

It is clear that all stations show a similar rising trend, and all show seasonal variation of varying degrees.  However, few stations have long term records, and most have periods of missing data. 

Differences, similarities, and divergence

Figure 3 shows monthly differences from the Mauna Loa record of stations with fairly complete records. 

Figure 3:  Six stations’ difference from Mauna Loa

Monthly differences show huge seasonal variation, so Figure 4 shows 12 month average differences.

 Figure 4:  Six stations’ difference from Mauna Loa, 12 month averages

Clearly, there are major differences between the different records: 

-La Jolla has too many gaps for further analysis. 

-There are differences between Cape Grim and South Pole from about 1980 to the early 1990s.

-Southern Hemisphere stations (American Samoa, Cape Grim, and South Pole) are diverging from Mauna Loa, and from Barrow Point and Alert.  Figure 5 shows these trends more clearly.

Figure 5:  Barrow Point and South Pole difference from Mauna Loa, 12 month averages

While South Pole and Mauna Loa are strongly diverging, Barrow Point and Mauna Loa are becoming slightly more similar.

In Figure 6, the divergence of South Pole data is evident in monthly readings.

Figure 6:  Monthly CO2 concentrations, Mauna Loa, Barrow Point, and South Pole

Note how much larger the Barrow Point seasonal range is.  More importantly, note how South Pole data begin well within the Mauna Loa range, but 50 years later barely reach the bottom of the Mauna Loa range, as Figures 7 and 8 show.

Figure 7:  Monthly CO2 concentrations, Mauna Loa and South Pole 1965-1975

Figure 8:  Monthly CO2 concentrations, Mauna Loa and South Pole 2010 -2020

Why the divergence?  How can a well-mixed gas show a lower trend at the South Pole?  Why is it that the South Pole summer draw down has decreased and is now a plateauing?

Seasonal change

Now zooming in to look at seasonal swings in just two years, 2011 and 2012:

Figure 9:  Monthly CO2 concentrations, Mauna Loa, Barrow Point and South Pole

The Barrow Point range from low to high is nearly three times the size of the Mauna Loa range, and the South Pole range is tiny.  The peak concentrations at Barrow Point and Mauna Loa are in late spring, with a sharp drop at Barrow Point to August and a smoother curve at Mauna Loa to lows in autumn; while at the South Pole the annual curve is better described as a shallow rise in winter followed by a “peak” in spring and a long plateau over summer, with a very small decrease in late summer.  The next three plots show the timing of highs and lows at these three stations for the whole record.

Figure 10:  Timing of seasonal high and low CO2 concentrations, Mauna Loa

Annual lows are in September or October, and highs are almost always in May.

Figure 11:  Timing of seasonal high and low CO2 concentrations, Barrow Point

Lows are always in August, while highs are spread across late winter to late spring, with a plateau from February to May (and extending twice into June).

Figure 12:  Timing of seasonal high and low CO2 concentrations, South Pole

At the South Pole, seasonal highs are reached in spring or early summer, with lows in late summer and early autumn, with one instance in June.

Inter-annual changes

While the seasonal cycles appear to be regular, the timing and size of seasonal changes can vary considerably from year to year.

The next plots show detrended data since 1985 for several locations (few have good data before 1985).  Detrending allows us to compare inter-annual variation more easily.  We do this for each record by subtracting the trend.

Figure 13:  Detrended monthly CO2, Mauna Loa

Figure 14:  Detrended monthly CO2, Barrow Point and Alert

Figure 15:  Detrended monthly CO2, South Pole and Cape Grim

While the seasonal range is different for each location, there is remarkable similarity in timing of changes, for example the late 1980s- early 1990s and 2009-2013.  Note how close Cape Grim and South Pole are, although Cape Grim is at 40.68 degrees South, 49 degrees north of the South Pole.  The South Pole data appear to be representative of a large part of the Southern Ocean.

Because the detrended data retain enormous seasonal variations, it is necessary to show the detrended data (this time from 1979) with monthly means subtracted, for Barrow Point in the far north, Mauna Loa in the middle, and South Pole at the extreme south.  Here are the seasonal signals:

Figure 16: Seasonal signals of monthly CO2 data

As an example, Figure 17 compares detrended data from Barrow Point with monthly means:

Figure 17:  Detrended monthly CO2 with monthly means, Barrow Point

Subtracting the monthly means shows the residual variation in carbon dioxide for Barrow Point:

Figure 18:  Detrended monthly CO2 with seasonal signal removed, Barrow Point

Figure 19 combines the three stations:

All three records follow the same pattern, with a large increase from 1979 to the late 1980s, followed by decrease in the 1990s.  There appears to be another steep increase from 2012 to the present.  Notice that Mauna Loa and South Pole values can be from 1 ppm below to 2 ppm above the trend, while at Barrow Point the range can be from 4ppm below to 5 ppm above the trend, which is about 2.5 ppm per year. 

However, there is still a large amount of variation in the monthly figures.  A centred 13 month rolling mean makes comparison much easier.

Figure 20:  Centred 13 month mean of detrended monthly CO2 with seasonal signal removed

The similar pattern followed by stations from north to south, from the Arctic Ocean, across the Pacific, to the Antarctic, far from any industrial or cropping contamination, is immediately obvious.  The Barrow Point record appears to lag behind Mauna Loa and South Pole data by from one to five months.  South Pole can be a few months ahead to a few months behind Mauna Loa, even though South Pole absolute monthly concentration peaks are from four to seven months later.

Ocean temperature effects

In Figure 14 of my post on 2nd May, Will Covid-19 Affect Carbon Dioxide Levels? I showed that CO2 change lags one year behind sea surface temperatures (SSTs).  The next plot shows the centred 13 month mean of HadSST4 data, scaled up to compare with CO2 data.

Figure 21:  Scaled, centred 13 month mean of detrended monthly HadSST4 and CO2 data with seasonal signal removed

Now the same data with SSTs lagged 12 months…

Figure 22:  Scaled, centred 13 month mean of detrended monthly HadSST4 and CO2 data with seasonal signal removed, HadSST4 lagged 12 months

Large change in CO2 concentrations appears closely linked with sea surface temperature a year before- (or even two years, as between 2002 and 2010).  Sea surface temperatures have a global effect.

ENSO effects

Another cause of CO2 variation is the El Nino- Southern Oscillation (ENSO) which appears in the swings between El Nino and La Nina conditions.  ENSO has a great effect on weather conditions globally, affecting winds, clouds, rainfall and temperature.  Figure 18 shows how CO2 levels respond to the Southern Oscillation Index (SOI), which is a good indicator of ENSO conditions.

Figure 23:  Centred 13 month means, scaled SOI and detrended CO2 levels

CO2 increases in La Ninas.  The pattern becomes more intriguing when we plot inverted SOI levels with sea surface temperatures, as in Figure 19.

Figure 24:  Scaled, centred 13 month mean of detrended monthly HadSST4 with seasonal signal removed and scaled inverted SOI

Inverted SOI data indicate SST data 4 to 6 months later.  (The early 1980s and early 1990s don’t match because of the huge volcanic eruptions of El Chichon and Pinatubo.)  In other words, an El Nino will raise ocean temperatures, and a La Nina will lower ocean temperatures, 6 months later.  Because of the oscillating nature of ENSO, El Ninos and La Ninas approximately reflect each other 16 to 24 months later, as Figure 20 shows.  (Again, El Chichon and Pinatubo have a large impact.)

Figure 25:  Scaled SOI, normal and inverted

That pattern recurs, with varying lag times, throughout the whole 144 year SOI history.

Which is why SSTs will probably increase to about February of 2021…

Figure 26:  Scaled SOI, normal and inverted, and detrended HadSST4

…and with them, CO2 concentration.

Figure 27:  Scaled SOI, normal and inverted, and detrended HadSST4, with South Pole CO2 data

This image has an empty alt attribute; its file name is soi-inv-sst-co2-1.jpg

Discussion

The long term carbon dioxide record shows continuing increase at all stations, indicating greater output than sinks can absorb. 

CO2 concentrations and trends, while similar, have discernible differences at different locations, notably between the hemispheres.

CO2 concentrations at Southern Hemisphere stations are increasing, but more slowly than those in the Northern Hemisphere, such that their trends are diverging.

On the long term CO2 rise are seasonal rises and falls, most likely due to seasonal vegetation, crop, and phytoplankton growth and decay. 

Peaks in CO2 concentration occur after winter and spring in both hemispheres- February to May at Barrow Point, April and May at Mauna Loa, and September-December at the South Pole.  This is not due however to a six month delay in CO2 mixing from sources in the Northern Hemisphere to the Southern, otherwise the South Pole trend would be the same.  It is lower, and becoming more so. 

There is great variety in seasonal range of CO2 at different locations, with greatest variation in the Arctic and the least in the Southern Hemisphere.

The amount and timing of these seasonal rises and falls varies from year to year.  These inter-year changes in CO2 concentrations can be as much as or greater than the normal annual increase.

Even though the South Pole station is far from the Southern Ocean, especially in winter when sea ice extends further, and even further from any vegetated land areas, its data appear representative of a great part of the Southern Hemisphere.

Small inter-annual changes in sea surface temperatures have a large impact on these changes in CO2 concentrations at South Pole and Mauna Loa about 12 to 24 months later.  There can be a further delay of up to five months in the effect at Point Barrow. 

This is not controversial.  According to the CSIRO, these variations “have been shown to correlate significantly with the regular El Niño-Southern Oscillation (ENSO) phenomenon and with major volcanic eruptions. These variations in carbon dioxide are small compared to the regular annual cycle, but can make a difference to the observed year-by-year increase in carbon dioxide.”

While sea surface temperature rise precedes CO2 concentration increase, there is no evidence at all of CO2 concentration change preceding sea surface temperature change.

With an apparent approximate 12 – 24 month delay between ocean temperature change and inter-annual CO2 change, changes in ocean out-gassing and absorption rates appears to be an unlikely mechanism.  Changes in land vegetation, forests, crops, and oceanic phytoplankton, moderated by the changing circulation, rainfall, cloud, and temperature patterns of ENSO events, appears to be a more likely mechanism, with the much smaller land area of the Southern Hemisphere accounting for the much smaller changes. 

The unresolved problem

This does not however explain the decreasing amount of summer draw down at the South Pole, and the divergence from Northern Hemisphere data.   Perhaps Southern Ocean phytoplankton are not decreasing as much during winter, so the CO2 sink is slightly increasing, slowing the CO2 growth trend a little and smoothing the CO2 growth curve.  Who knows?  I have yet to see a satisfactory- or any- explanation.

CO2vid Watch: May

June 8, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

(In a coming post I will update my expectations for the end of the year and next year.) 

The CO2 concentration number for May is now published: 417.07 p.p.m. (parts per million).  That’s an increase of 0.86 ppm over the April figure, and 2.41 ppm above the figure for May last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to May 2020- Mauna Loa

Notice the amount of 12 month change has decreased a little.

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Note that so far this year, 12 month changes are in the normal or even upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

CO2vid Watch: April

May 7, 2020

In my last post I wondered whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

I concluded:  I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

 Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March (as in Figure 6 of my previous post):

Fig. 1:  12 month change in CO2 concentration since 2015- Mauna Loa

The CO2 concentration number for April is now published: 416.21 p.p.m. (parts per million).  That’s an increase of 1.71 ppm over the March figure, and 2.89 ppm above the figure for April last year.  Figure 2 is the April update on Figure 1.

Fig. 2:  Updated 12 month change in CO2 concentration since 2015- Mauna Loa

Notice the amount of 12 month change has increased, despite at least two months of downturn in China and at least a month in most other countries.

Figure 3 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 3:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Figure 4 shows the range of 12 month changes for each decade since the record began in 1958:

Fig. 4:  Updated 12 month changes in CO2 concentration all decades- Mauna Loa

Figure 5 shows the same, but just since 2000:

Fig. 5:  Updated 12 month changes in CO2 concentration since 2000- Mauna Loa

Note that so far this year, 12 month changes are in the upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

The Wacky World of Weather Stations: No. 60- Bombala AWS (NSW)

August 29, 2019

Time for some comic relief.  Only in Australia!

Please refer back to my first post for site specifications.

Station:  Bombala AWS 70328

Opened: 1988

Daily Temperature data from: 1990

Data used to adjust Acorn sites at: —

Location: Co-ordinates  -37.0016 149.2336

BombalaAWS map

About 370km south of Sydney, and about 6km from Bombala.

2019 Google satellite image:

BombalaAWS aerial

Looks perfect?  Looks can be deceiving.

BOM site plan 2014:

BombalaAWS plan

Far from having vegetation trimmed to a few centimetres, the screen is surrounded by grass up to half a metre high.  The tipping bucket rain gauge and screen are often both mounted on a metal arm.  Cattle rubbing on the arm and/or screen will cause vibration at the least, not to mention heat from bovine body temperature and possible fresh manure and urine.

So we have a problem.  There are many stations not in an enclosure, and in many of them livestock graze nearby.  This is the first I have seen where the annual inspection reveals cattle rubbing on the apparatus.  That was in 2014.  I wonder if anything has been done about it?  As they have evidently recognised the Buffalo Fly problem, and a fence is out of the question, perhaps the Bureau has added an insecticidal back rubber to the bar?  Or recommended introduction of Brahman bloodlines?

Shh!  The Bureau would not want word getting out, people might laugh at them.

This station is not compliant, with temperatures reported at Latest Weather Observations but not used to adjust data at Acorn sites.

FAIL

The Wacky World of Weather Stations: No. 7- Adelaide (SA)

August 2, 2019

Please refer back to my first post for site specifications.

Station:  Adelaide 23090

Opened: 1977

Daily Temperature data from: 1977

Data used to adjust Acorn sites at:  Port Lincoln, Ceduna, Nuriootpa

Location: Co-ordinates  -34.9211  138.6216

Adelaide map

2019 satellite image:

Adelaide aerial

The screen is the white dot in the red ellipse.

2018 BOM Site Map:

Adelaide plan

The screen is on a flat lawn between two bitumen streets and above a bitumen carpark.

Street view from College Rd:

Adelaide collegeroad

Street view from Little Young Street:

Adelaide LittleYoungSt

This site is recognised by the BOM as being subject to Urban Heat Island (UHI) effect.  It is non-compliant, so temperatures recorded here are not reliable.  Adelaide’s temperatures are published at the BOM Latest Weather Observations page, and also used by the BOM in weather reports, potentially including extremes of heat or cold. Adelaide’s UHI does not prevent it from being one of the sites used to adjust temperatures at ACORN-SAT sites at Port Lincoln, Nuriootpa, and Ceduna. Acorn sites are used for climate analysis- whether winters are getting warmer and summers hotter for example.  So the lack of quality at any site DOES MATTER!

Another FAIL.