Archive for the ‘CO2’ Category

“Well mixed” Carbon Dioxide Part 2: Sources and Sinks

June 26, 2016

Following from Part 1 (North vs South), this post looks at current sources and sinks for CO2.

Here are some images of surface CO2 concentration for today (June 26 in Australia) from nullschool.

Darker areas show lower CO2, lighter areas are higher.  I recommend the nullschool site!

Europe:

Europe

The industrialised Ruhr valley appears to have the highest CO2 concentration.  Paris Berlin and London are difficult to identify however.

South America (Argentina):

Buenos Aires

The high concentration appears to be from Buenos Aires- perhaps the satellite image of the CO2 is 200 km off target?

China, Korea, and Japan:

China Korea Japan

The highest concentration appears to be close to Japan’s larger cities.  Eastern China, including Shanghai and Beijing, is around 402ppm.

Southern Africa:

S Africa

Kinshasa and Johannesburg are close to the high concentrations, but dry season fires could also be the cause.

Indochina:

Indochina

Oddly, the high concentration is to the south west and west of Hanoi in a rural region.

USA:

USA

A large part of the USA seems to be one vast carbon sink at the moment.  New York and Chicago areas could be associated with some higher CO2, and there are those two areas in California, one of which I identified as Los Angeles in the previous post.  Now I’m not so sure.  More later.

Kamchatka yesterday:

high co2 kamchatchka peninsula

And today:

kamchatchka peninsula 26 june

The Kamchatka Peninsula features many active volcanoes and that’s what I think we are seeing here.  Yesterday afternoon the concentration peaked at 509ppm and today is down a lot but the “hot spots” are still distinct.

Australia:

Australia

Again inland eastern Australia is a carbon sink with large areas under 390ppm.  Melbourne may be the cause of a 408ppm area, but where is Sydney? Brisbane? Perth? Adelaide?

Southern California:

California

Note San Francisco does not appear to have over high CO2.  One of the high areas is indeed over the Los Angeles area, but the other is in the mountains to the north:  Kern County to be precise, where a bushfire has broken out.  The other ‘haze’ appears to be from the Santa Barbara fire.  See this map of fire locations.

firemap usa

It seems to me that it is hard to identify strong sources of CO2 associated with the world’s large cities and industrial areas.  However, it is the weekend, so perhaps this will change during the coming week.  We shall see.

On the other hand, very strong sources of CO2 can be traced to volcanoes and bushfires, and also decaying vegetation in the dry season.  Sinks as we have seen are clearly associated with rapidly growing crops, grasslands, and forests.

And today the Equatorial Pacific sink appears to match the cooler water being pushed westwards by the strengthening trade winds.  See for yourself at nullschool.

I will continue to monitor these sources and sinks as the seasons progress.

“Well Mixed” Carbon Dioxide Part 1: North vs South

June 24, 2016

This post addresses the question: How “well mixed” is carbon dioxide in Earth’s atmosphere?

Here are some images of surface CO2 concentration for yesterday (June 23 in Australia) from nullschool.

Darker areas show lower CO2, lighter areas are higher.  Very nifty.

Fig. 1:  Northern Hemisphere CO2:

co2 image NH

The dark areas with low CO2 are the northern forests and farm land, now growing strongly.  Note the cold, dry North Pole has high CO2.

Fig. 2: Southern Hemisphere:

co2 image SH

Cold, dry Antarctica has high CO2, whereas a broad area of inland Eastern Australia, which recently has had some decent rain, has lower CO2.

Fig. 3:The East:

co2 image EH

Fig. 4: The West:

co2 image WH

The contrast in South America is interesting!

Fig. 5:  The Pacific (a hemisphere on its own):

co2 image Pacific

Note the northern Pacific (north of 5 degrees north) is predominantly above 400ppm, while a broad band from about 5 degrees north to about 20 degrees south is about 395ppm.

Note also a tiny area in southern California pluming into the Pacific with a very high reading of 437ppm.  Los Angeles.

The IPCC and climate scientists generally refer to data from Mauna Loa in Hawaii.  The CSIRO in Australia also measures CO2 concentration at Cape Grim in Tasmania.  The next few charts compare Cape Grim data with that of Mauna Loa.

Fig. 6:  Comparison Mauna Loa and Cape Grim CO2 1976-2016

ML v CG co2

Here is a closer look at the most recent years:

Fig. 7:  Comparison Mauna Loa and Cape Grim CO2 2010-2016

ML v CG co2 2010-16

There are several points to note:

Cape Grim CO2 concentration is increasing at the same rate as Mauna Loa.

There are massive swings in Mauna Loa’s data, while Cape Grim fluctuates gently.  In 2016 there was no “bottom” at all.

Cape Grim is much lower- in fact the annual high points are at about the same level as Mauna Loa’s low points.

The records are out of phase.  Mauna Loa peaks in northern spring and bottoms out in northern autumn, whereas Cape Grim peaks in southern Spring and “bottoms out” in southern Summer.

Now I look at the seasonal change in concentration.

Fig. 8:  Seasonal rises and falls at Cape Grim

Inc decr CG

Fig. 9:  Seasonal rises and falls at Mauna Loa

Inc decr ML

Notice at Mauna Loa the annual rises from bottoms to peaks are getting larger, but so are the falls, while at Cape Grim there are slower rises but falls are lessening.  I compare rises and falls separately in the next two plots:

Fig. 10:  Seasonal increases compared

Incr ML v CG

Fig. 11:  Seasonal decreases compared

Decr ML v CG

I would interpret this as follows:

As emissions increase, carbon dioxide sinks (mainly growing plants) consume more and more.  However this is not enough to remove all of the additional CO2, so each year the growth continues.

In the Northern Hemisphere, sinks completely overwhelm sources in summer.

In the Southern Hemisphere there is a much less pronounced annual peak in spring, perhaps because there is less land, especially from 30 to 70 degrees south, and much of it is dry.  CO2 concentration has increased to the level at which vegetation CO2 sinks are becoming unable to make an impression (at least in El Nino years).

The bulk of CO2 increase originates in the Northern Hemisphere.  In northern winter as the Inter-Tropical Convergence Zone shifts south of the Equator, the north east trade winds move CO2 to the Southern Hemisphere where it is gradually mixed.  In northern summer (now), the ITCZ is north of the Equator, and the image of the Pacific in Figure 5 above shows trade winds crossing the Equator with less CO2 concentration than just to the north.

We know there are large changes to CO2 concentration following ENSO events.  This may be due to the changing circulation over the tropical Pacific as more or less CO2 is shifted by trade winds north and south. Or perhaps changing ocean currents, upwelling, or downwelling warm or cool large ocean areas.

Drier areas of the globe (deserts, Polar regions) have higher CO2 concentration than wetter areas.  Few growing plants, more CO2.  More and greener plants, less CO2.

And finally: CO2 is not “well mixed” globally, and an average concentration is as elusive as an average temperature.  There is a range of concentrations between areas of sources and sinks approaching 80ppm.

Trending Trends Continued: An Alternative View

February 26, 2016

No matter how much and how well we explain the methods for calculating the length of The Pause, Global Warming Enthusiasts will accuse us of cherry picking the start date.

In this post I will replicate the IPCC’s predicted estimates for temperatures, and show alternative scenarios with a range of trends to the end of 2035, through using an alternative  view which will be sure to please our friends on the other side of the fence- but will demonstrate the limited extent of the joy they should feel at the expected demise of The Pause. As well,  I will also demonstrate what temperatures will need to do before we skeptics can claim victory (our opponents will never admit defeat- that would be heresy).

In these figures I plot running trends of 12 month means of Temperatures of the Lower Troposphere (TLT) anomalies from UAH (Version 6 Beta 5), but starting from the beginning of the record (12 month means from November 1979).  Running trends will be used in this post to demonstrate the effects of changing data values over time.

Fig. 1: Running trends for global TLT to the present

Trend to 2016 all

Fig. 2: Running trends for global TLT to the present, closer view.

trend to 2016 closeup

Note to GWEs: there is no cherry picking: the start is from the start of the record. Each new month’s data point will either increase or decrease the long term trend, but with decreasing effect as the record grows in length. Peaks correspond to warming events, troughs to cooling events. Note also that the recent long term trend is near the lowest it has been since 1998. With the expected increase in temperatures following the El Nino, I anticipate the long term trend to the end of 2016 will be about +1.2C per 100 years.

What of the future? Now according to the IPCC Assessment Report 5, warming for the next 20 years is locked in, no matter what emissions scenario.

“The global mean surface temperature change for the period 2016–2035 relative to 1986–2005 is similar for the four RCPs and will likely be in the range 0.3°C to 0.7°C (medium confidence). This assumes that there will be no major volcanic eruptions or changes in some natural sources (e.g., CH4 and N2O), or unexpected changes in total solar irradiance.”

( https://www.ipcc.ch/pdf/assessment-report/ar5/syr/AR5_SYR_FINAL_SPM.pdf p8)

If I am still around in 2035, this prediction will not be a huge priority for me. However, to illustrate various possibilities, I shall calculate possible TLTs for the next 20 years. (Yes, I know the IPCC is talking about surface temperatures. However if tropospheric temperature change doesn’t reflect surface temperature change for another 20 years there are going to be some serious arguments in climate science circles!)

First, let’s replicate the IPCC predictions for 2016-2035- and in so doing, show The Pause in all its glory. The next figures plot running 12 month mean Temperatures of the Lower Troposphere (TLT) anomalies in degrees Celsius versus global atmospheric carbon dioxide concentration in parts per million (ppm), data from NOAA.  The global record commences in 1980.

Fig. 3: Running trend of Degrees C per 100 ppm CO2

Trend TLT v co2

Note again the peaks and troughs, and that the current trend is the lowest it has been since 1996.  The long term trend to December 2015 is +0.65C/ 100 ppm CO2. This is confirmed in the following plot:

Fig. 4: TLT anomalies vs CO2

tlt vs co2 1980-2015

Now let’s break the record in two: the first half of the CO2 rise and the second half.

Fig. 5:  TLT vs CO2: 1st 30.32ppm

tlt vs co2 1st half

Fig. 6:  TLT vs CO2: last 30.32ppm

tlt vs co2 2nd half

There you have The Pause: entirely un-cherry picked, as we are using exactly equal portions of the record: the first and last 30.32 ppm of the CO2 growth from 1980 to 2015.

The next graphs plot CO2 increase over time, from 2001 to 2015.

Fig. 7: CO2 growth (12 month running mean)

co2 to 2015 formula

Using this trend equation it is possible to estimate CO2 for the next 20 years, and from that, using (A) the trend of the first half of TLT vs CO2, i.e. rapid warming; (B) that of the whole 1980-2015 period, i.e. continuing the present long term trend; and (C) that of the second half of the CO2 growth, i.e. The Pause, calculate three theoretical estimates for the TLT in the best way- from observations. Here are series A and B.

Fig. 8:  Theoretical trends calculated from observations

Series A B calcs

Note that series A approximately tracks the observed TLTs until about 2002, when the disparity begins. This shows clearly why The Pause is so inconvenient, and why so much effort has been made to eradicate it.

Amazingly, the 2016-35 high mean of 0.7 above 1986-2005, and the low mean of +0.3, as predicted by the IPCC, have been replicated almost exactly by series A and B. (The UAH 1986-2005 mean is +0.02C).  It appears that the temperature trend for the rapidly warming phase up to 2001 exactly matches the trend needed to create the upper limit of their prediction for 2016-35, and the trend overall to 2015 is very close to that of the lower limit. The IPCC is banking on the warming trend from now to 2035 being at least as much as the 1980-2015 trend, and as much as that of the rapid warming to about 2001. Any continuation of a slowdown makes that much harder.

Obviously these series are imaginary, showing the theoretical TLT calculated from CO2 concentration, and without any of the bumps and dips caused by natural variation- volcanoes, ENSO events, and the like. However, they can be used to simulate what temperatures might do over the next 20 years.

I illustrate this with these scenarios, and a fourth, below.

Scenario A allows the 2016-2035 mean to be 0.7C above the 1986-2005 mean and necessitates temperatures sharply rising then continuing at the rate of the higher of the theoretical series (A). Scenario B very slightly exceeds the lower IPCC expectation of +0.3C, and represents a continuation of the current trend. Scenario C is calculated by multiplying expected CO2 concentration by the TLT per CO2 trend for the second half of CO2 growth, indexed to the 1996-2015 mean. As expected it is virtually flat with the 2016-35 mean at +0.14C. This represents an extension of The Pause by another 20 years. Scenario D shows a sharp drop to a 20 year plateau (shown as flat as we have no idea how temperatures may fluctuate) at -0.11C, the lowest 12 month mean of the last 20 years, and about the same average as the 1980-95 period. I have smoothed the beginning months of all four scenarios.

I repeat- these scenarios are entirely imaginary and represent approximate calculated values IF TLT responds to CO2 concentration as it has to now, and nothing else.

Fig. 9: Four scenarios to 2035

Scenarios to 2035

I have marked in the trend line for UAH to now.  Scenario A shows what would happen if The Pause came to an abrupt end, with temperatures rising to a record high for 2016, and then keeping on rising at the theoretical rate as if The Pause had never happened. I’m sure there are some Global Warming Enthusiasts who expect temperatures will do just that.

But the IPCC has an out clause- Scenario B. If the current long term trend continues, TLTs will reach IPCC expectations. Which is why GWEs are desperate for The Pause to end and warming to resume at (at least) the slow if not steady +1.1 to 1.2C per 100 years. If it doesn’t they’re in trouble.

Temperatures will need to trend below this to falsify the predictions- and not even as much as Scenario C, which represents an extension of The Pause. Scenario D represents a significant decrease.

The next plot compares the trends under these four scenarios.

Fig. 10: Trends in degrees Celsius per 100 years to 2035 under four TLT scenarios.

Trend scenarios to 2035

Ignore the artificial shape of the curves. At December 2035 the trend for each scenario will be about:
Scenario A: 2.1C/ 100 years
Scenario B: 1.2C
Scenario C: 0.6C
Scenario D: 0.0C

The IPCC expects trends to be between those of Scenarios A and B. A small step up (to a new 20 year mean of say +0.25C) and a new pause- which is entirely possible- would probably still be claimed to be “the hottest decade ever” and “consistent with global warming projections”. We need to emphasise that a pause doesn’t have to be completely flat. A 30 year period with a trend of +0.3C per 100 years should be enough to bring the global warming models into question. However, there will need to be a significant drop in temperatures, or a much longer plateau, for us to claim victory. A 57 year pause would be most embarrassing- but then they would probably blame it on volcanoes!

Finally, even if this El Nino is followed by a strong La Nina, as suggested by NOAA,  it is unlikely The Pause will return until the beginning of 2018, perhaps a little earlier. However, that is not important. The important thing is what happens next. Watch the next two or three ENSO cycles- especially the La Nina dips.

Global Warming Enthusiasts are desperate for rapid warming to resume at least as much as Scenario B. The long term trend must rise above the current rate if they are to feel vindicated. But then, who knows what the actual temperatures will do.

Time will tell.

Theory and Reality- Part 1: DTR

February 2, 2016

It was two years ago in 2013 that I last posted on the difference between climate scientists’ expectations and reality, so in this series of posts I bring these points up to date, and add a couple of related points.

What the climate scientists tell us:

Dr Karl Braganza in The Conversation on 14/06/2011 lists the “fingerprints” of climate change (my bold).

These fingerprints show the entire climate system has changed in ways that are consistent with increasing greenhouse gases and an enhanced greenhouse effect. They also show that recent, long term changes are inconsistent with a range of natural causes…..
…Patterns of temperature change that are uniquely associated with the enhanced greenhouse effect, and which have been observed in the real world include:
• greater warming in polar regions than tropical regions
• greater warming over the continents than the oceans
• greater warming of night time temperatures than daytime temperatures
• greater warming in winter compared with summer
• a pattern of cooling in the high atmosphere (stratosphere) with simultaneous warming in the lower atmosphere (tropopause).

and later

Similarly, greater global warming at night and during winter is more typical of increased greenhouse gases, rather than an increase in solar radiation.

This post will examine “greater global warming at night” and whether it can be attributed to increased greenhouse gases.

If night time temperatures (minima) increase faster than day time temperatures (maxima), then the difference between these, the Diurnal Temperature Range (DTR) will decrease.

I use BEST global land temperature data,

http://berkeleyearth.lbl.gov/auto/Global/Complete_TMAX_complete.txt
http://berkeleyearth.lbl.gov/auto/Global/Complete_TMIN_complete.txt

and annual CO2 concentration data from NOAA.

ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_annmean_mlo.txt

Fig. 1: Global DTR (derived from BEST Land Tmax and Tmin)

DTR globe

Yes, the long term linear trend shows globally DTR has decreased, at a rate of more than half a degree Celsius per century.

Case closed! That is, if you ignore the sudden turnaround in the early 1980s. Since then DTR has been increasing at +1.1C per 100 years.

The plot showing the relationship with CO2 concentration is even more revealing:

Fig. 2: Global DTR vs CO2 concentration

globe dtr v co2 all

If we break the series in two at the dogleg, we get the following plots:

Fig. 3: Global DTR vs CO2 concentration to 1982

globe dtr v co2 1

Fig. 4: Global DTR vs CO2 concentration 1982 to 2015

globe dtr v co2 2

Calling Global Warming Enthusiasts! I am puzzled:

Is DTR decreasing at 1.14 C/ 100 ppm CO2 or increasing at 0.61 C/ 100 ppm?
Can there be any logical explanation for this distinct turnaround?
Is there a problem with (a) the CO2 concentration data? (b) BEST data? (c) the theory behind decreasing DTR being an indicator of enhanced greenhouse warming? (d) all of these?

I now turn to the Australian context, with Australian surface data.

Fig. 5: Annual DTR Australia (from ACORN)

DTR Aust

While averaged across Australia, DTR has decreased since 1910, there has been a marked increase recently. As well, the pattern is different in different regions.

Fig. 6: DTR North Australia

DTR Aust nth

Fig. 7: DTR Southwest Australia

DTR Aust SW

Fig. 8: DTR South Australia

DTR Aust SA

Fig. 9: DTR Victoria

DTR Aust Vic

Fig. 10: DTR Tasmania

DTR Aust Tas

The effect is strongest in the tropical northwest and northeast, and weakest in the southwest and South Australia, Victoria, and Tasmania.

Moreover, the dominant influence on DTR is rainfall:

Fig. 11: DTR vs Rainfall

DTR Aust vs rain

Definitely not CO2!

Fig. 12: DTR vs CO2 concentration

DTR Aust vs CO2

Assessment of decreased DTR as evidence for the enhanced greenhouse effect: Fail.

Other factors- especially rainfall- overwhelm the enhanced greenhouse effect.

UPDATE:

Perhaps I should be more blunt:  If Global Warming Enthusiasts stick to decreasing DTR as an indicator of greenhouse warming, then this shows BEST and ACORN surface data are completely unreliable.  If they stick to claiming ACORN and BEST are “world’s best practice” then they must accept that DTR as an indicator of greenhouse warming is a dead duck.

Energy, Carbon Dioxide, and The Pause

December 16, 2015

Here’s an alternative way to view The Pause. Rather than analysing temperature trends over time, here I compare temperature with carbon emissions and carbon dioxide concentration, and on the way look at a couple of interesting facts that need highlighting.

I use energy data from the BP Statistical Review of World Energy 2015, CO2 data from NOAA, and Temperature data from UAH.

I need to get two important issues out of the way.

Firstly, total energy consumption. Figure 1 shows global energy consumption from all sources for 2014.

Fig. 1: Global Energy Consumption in Million Tonnes of Oil Equivalent
energy 1965 2014

I aggregated coal, oil, and gas into one fossil fuel category. It is plainly obvious that fossil fuels are going to be around for a long time, unless there is a massive multiplication of (a) nuclear energy production, which may not appeal to some environmentalists, or (b) hydro-electricity dams, but that may not appeal either, and are there enough rivers?, or (c) windfarms and large scale solar, with storage, to produce 30 times what they produce now just to meet current demand. Cheap, reliable energy supply is going to depend on technological breakthroughs in the next 100 years and fossil fuels in the meantime.

Secondly, the recent increase in carbon dioxide concentrations is almost entirely anthropogenic.

Figure 2: CO2 concentration as a function of global energy consumption from 1965 to 2014:
Energy vs co2

99% of CO2 increase can be explained by energy use in all forms.

Now, before Global Warming Enthusiasts drool all over their keyboards, let’s look at how this relates to temperature.
I have calculated 12 month running means of CO2 concentration and TLT anomalies. From November 1979 to November 2015- CO2 concentration increased from 336.6 ppm to 400.57 ppm. What happened in this period to global lower troposphere temperatures- arguably a better indicator of global warming than surface temperatures because they show what the bulk of the atmosphere is doing?

Fig. 3: Tropospheric temperature anomalies vs CO2 concentration:
TLT vs CO2 78-15

43.5% of the temperature increase over the satellite era can be explained by/ is associated with the increase of about 64 ppm of CO2. The relationship is anything but linear, however the linear trend indicates, if warming continues at the same rate while CO2 increases by 100 ppm, that temperature anomalies will increase by about 0.63C. By this estimate, doubling CO2 concentration from 280 ppm (what many believe to be pre-industrial concentration) will result in a temperature increase from whatever the global temperature was 250 years ago, of 1.76C. According to HadCruT4, we’ve already seen about 0.8C increase since 1850, so we’re nearly halfway there! Not only that, but we’ll stay below 2 degrees of warming without the need for any emissions reductions!

But the temperature increase is not linear. The next plot shows the tropospheric temperature/ CO2 relationship while temperatures have paused.

Fig. 4: TLT vs CO2, from 363 ppm to 400 ppm:
TLT vs CO2 Pause

That, my friends is the true indicator of The Pause: while CO2 has increased by almost 37 ppm (out of 64 ppm), temperature has remained flat. The trend is +0.01C per 100 ppm CO2.

Finally, I’ve separated the record into three phases: before, during, and after the large step change in the 1990s culminating in the 1997-98 El Nino and the following La Nina.

Fig. 5: Temperature vs CO2 during the first phase, when CO2 increased by 20 ppm:
Phase 1

Fig. 6: Temperature vs CO2 during the second phase, when CO2 increased by about 14 ppm:
Phase 2
Fig. 7: Temperature vs CO2 during the last phase, when CO2 increased by about 29.3 ppm:
Phase 3

Therefore I conclude:

Barring a miraculous breakthrough, renewable energy has no hope of replacing cheap, reliable fossil fuels in the foreseeable future- thankfully!
Greenhouse gas increase is anthropogenic;

CO2 increase has probably caused some small temperature increase;

The relationship between CO2 and temperature in the satellite era is weak, with 58% of the CO2 increase occurring while temperatures have paused;

Therefore temperature change is probably caused mainly by natural factors;

Even if the long term “linear” trend continues, this rate is not alarming, and would lead to a temperature increase during a doubling of CO2 of less than 1.8C.

I find it amusing that Global Warming Enthusiasts pin their hopes for an end to The Pause on a strong El Nino- in other words, on natural variability, the very thing that is supposed to have been overwhelmed by greenhouse warming.

The end of the scam is nigh!

Adjustments vs CO2

August 3, 2014

Steven Goddard has posted about the remarkable correlation between USHCN adjustments and atmospheric carbon dioxide concentrations:

goddard co2

Here’s my plot of Australian adjustments to minima, Acorn minus raw vs CO2 data (downloaded from NASA GISS at

http://data.giss.nasa.gov/modelforce/ghgases/Fig1A.ext.txt ):

acorn vs co2

R2= 0.777 not as impressive as 0.988, so not proof of anything except past cooling adjustments which we already knew.  Interesting all the same.

IPCC Dud Rainfall Predictions for the Murray-Darling Basin

April 4, 2014

The IPCC’s recently released 5th Assessment Report (AR5) dedicated Chapter 25 to impacts of climate change on Australasia. There was wide media reporting of these impacts, including that of decreasing rainfall- more droughts and floods. The relevant part of Chapter 25 outlines eight regional key risks, including:

For some impacts, severity depends on changes in climate variables that span a particularly large range, even for a given global temperature change. The most severe changes would present major challenges if realized:

……. significant reduction in agricultural production in the Murray-Darling Basin and far south-eastern and south-western Australia if scenarios of severe drying are realised; more efficient water use, allocation and trading would increase the resilience of systems in the near term but cannot prevent significant reductions in agricultural production and severe consequences for ecosystems and some rural communities at the dry end of the projected changes.

Section 25.2, Observed and Projected Climate Change, gives the details:

This pattern of projected rainfall change is reflected in annual average CMIP5 model results (Figure 25-1), but with important additional dimensions relating to seasonal changes and spread across models (seealso WGI Atlas, AI.70-71). Examples of the magnitude of projected annual change from 1990 to 2090 (percent model mean change +/- intermodel standard deviation) under RCP8.5 from CMIP5 are -20±13% in south-western Australia, -2±21% in the Murray Darling Basin, and -5±22% in southeast Queensland (Irving et al., 2012). Projected changes during winter and spring are more pronounced and/or consistent across models than the annual changes, e.g. drying in southwestern Australia (-32±11%, June to August), the Murray Darling Basin (-16±22%, June to August), and southeast Queensland (-15±26%, September to November), whereas there are increases of 15% or more in the west and south of the South Island of New Zealand (Irving et al., 2012). Downscaled CMIP3 model projections for New Zealand indicate a stronger drying pattern in the south-east of the South Island and eastern and northern regions of the North Island in winter and spring (Reisinger et al., 2010) than seen in the raw CMIP5 data; based on similar broader scale changes this pattern is expected to hold once CMIP5 data are also downscaled (Irving et al., 2012).

As the Murray-Darling Basin (MDB) is the nation’s major food bowl, contributing a very large proportion of our agricultural production, a Reality Check on these claims is in order.

The Murray-Darling Basin is the largest catchment in Australia, and is one of the Bureau of Meteorology’s climate regions:

Fig.1: MDBRegions

First, annual rainfall. The IPCC projects an annual change of -2% +/-16% from 1990 to 2090. Here are the rainfall anomalies for the MDB straight from the Bureau’s Climate Change page:

Fig.2: MDB Annual Rainfall Anomalies, 1900-2013:MDB annual anoms

Linear trends have limited use in such a manifestly non-linear dataset as rainfall, however I put one in just in case someone says rainfall is decreasing. Even with 2010 deleted the trend is still positive. Let’s now look at the 10 year means:

Fig.3: MDB Annual Decadal Means:MDB annual anoms 10yrs

Note that for the entire period before the 1950s, the 10 year mean was below the 1961-1990 mean, and in 1946 was 94mm below. While in 2009 the 10 year average was 69mm below the mean, this being the first time in six decades it had been below -60mm, for most of the 1940s it was more than 60mm below the mean. It is entirely possible that rainfall will be below average in the MDB for several more decades, and this would be completely normal.

I shall now project this historical trend through to 2090, with a 2090 rainfall of 512.35mm, 2% below that of 1990 (522.81mm).

Fig.4: MDB Annual Rain to 2090:MDB annual rain to 2090

So that’s what a decrease in rainfall looks like! Note the uncertainty range- well within historical norms, and the low figure (404.76mm) is in the below average (lowest 30% of years) rainfall category by less than 4mm.

Next, winter rainfall (-16% +/-22%, June to August). From BOM Climate Change,

Fig.5: MDB Winter Anomalies 1900-2013MDB winter anoms
There you can see the declining trend (BOM says -0.57mm per decade)- but note the size of the trend compared with the variability.

Interestingly, consider the same data for the last 54 years.

Fig.6: MDB Winter Anomalies 1960-2013MDB winter anoms 1960-2013
But of course, the authors have detected the drying trend since the 1990s!

Now, decadal means:

Fig.7: MDB winter decadal means:MDB winter anoms 10yrs

Note the 10 year mean about -10mm in past decade, but -15mm in the 1970s and -19mm in the 1940s. Note also that the 10 year average was below zero for the better part of two decades, twice, in the past. Below average winter rain for the next few years would be completely normal, if the past is anything to go by.

Here is a chart showing the number of dry winters per 10 year period in the MDB.

Fig.8: 10 year count of below average winters.MDB winter anoms  under30%10yrs

Below average winters were more frequent in the past.

Projecting the winter anomalies into the future, with a decrease of -16±22%, June to August, we get:

Fig.9: MDB Winter Rain to 2090:MDB winter rain to 2090

109.74mm is almost exactly the 1961-1990 mean (111.1mm). The low end of the uncertainties, 85.6mm, is in the below average range but well outside the severe deficiency or even serious deficiency level. Yet this will cause “significant reductions in agricultural production and severe consequences for ecosystems and some rural communities”?

Note: these projections are based on continued warming by up to 2 degrees. Consider that we have already seen warming in the MDB of about +0.8 C since 1910 (according to BOM analysis based on ACORN-SAT).

It appears that the IPCC can’t be wrong, whether rainfall is higher, lower, or stays the same. They’re having two bob each way.

In discussing agricultural production, I would have been less underwhelmed if rainfall in other seasons had been considered. If winter rain is down (marginally), but annual rain is up, when did it fall?
Briefly, autumn, like winter, is almost flat (-0.59mm per decade), spring is up by 1.61mm per decade, but summer rain has increased 3.86mm per decade. If heavy rain falls before the wheat harvest is off, the crop is seriously downgraded, so late spring- early summer rainfall increasing would be of concern.

Fig.10: MDB Summer Rain AnomaliesMDB summer anoms

Fig.11: MDB Decadal Summer RainMDB summer anoms 10yrs

Note that summer rain increase is all since 1950. For 60 years farmers have been contending with this. It’s nothing new. Farmers adapt farming methods to changing conditions and with new technology. Moreover, the recent decadal peak is about the same as the 1960s and 1990s. Note also that the low decadal mean of the Millennium Drought is nowhere near the levels of past dry periods.

The warming to now has ‘resulted’ in increased annual rain, made up mostly of stronger summer rains since 1950, and marginally less winter and autumn rain which is less variable than in the early decades of last century.  The IPCC’s projections are thus the result of climate models and not historic observation, are subject to large uncertainty, and not greatly different from patterns of the past 114 years.

The AR5 prediction of dire consequences for the Murray-Darling Basin, based on rainfall projections that are essentially no different from historical observations, is nonsense. It is beyond parody, beyond ridicule. It treats the citizens and farmers of Australia with contempt.

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 TLT.land 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 Nino.land 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 months.land v oceans v soi

 

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

 

 

 

Australian DTR – the Regional Context

January 12, 2014

I’ve been banging on about DTR in Australia for a while, showing that as an indicator of greenhouse warming, decreasing DTR trend has been lacking from Australian records for some time, such that the trend is flat since 1947.

Update:

DTR is Diurnal Temperature Range, the difference between Minimum and Maximum temperature daily.  Several previous posts discuss this.  Greenhouse gases slow back radiation, and thus night time temperatures are expected to be warmer than normal, and minima are expected to increase faster than maxima, so DTR should decrease.

Fig.1: Australian DTR anomalies, 1947 – 2013dtr1947-2013

I’ll now show what is happening on a regional basis.  This map shows the main meteorological regions of Australia.

Fig. 2: The regions.summer1213  regions

The main difference is between Northern Australia and Southern Australia.

Fig.3:  Northern Australian DTR anomalies, 1971 – 2013dtr nth oz 71-2013

43 years of flat trend in DTR!

Fig.4: Southern Australian DTR anomalies, 1938 – 2013dtr sth oz

76 years!

Fig. 5:  South-Western Australian DTR anomalies, 1941 – 2013dtr sw aus

73 years.  But the real eye opener is South Eastern Australia:

Fig. 6: South-Eastern Australian DTR anomalies, 1934 – 2013dtr se aus

That’s right, in South-East Australia, the DTR trend has been flat for 80 years!

Decreasing DTR as a “fingerprint” of greenhouse warming was championed by the 2004 paper by Dr Karl Braganza et.al,

“Diurnal temperature range as an index of global climate change during the twentieth century” Karl Braganza, School of Mathematical Sciences, Monash University, Clayton, Victoria, Australia; David J. Karoly, School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA; J. M. Arblaster, National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA

Braganza et. al. analysed global DTR from 1951 to 2000, finding a significant decline of ~0.4 degrees C.  If we compare Australian data for the same period we find this is corroborated.

Fig. 7:  Australian DTR anomalies 1951 – 2000dtr oz 51-2000

The observed decrease over this period is ~0.35  – 0.4 C.

With the benefit of an extra 13 years of data, we can check whether this continues to be the case.

Fig. 8:  Australian DTR anomalies 1951 – 2013dtr oz 51-2013

What a difference a few years make.

No Excess Winter Warming for 103 Years!

January 9, 2014

Greenhouse Myth Buster No. 2

Another key indicator of greenhouse warming, a pattern of temperature change “uniquely associated with the enhanced greenhouse effect” according to Dr Braganza, is greater warming in winter compared with summer.

Not in Australia.

This is a graph of summer annual means minus winter annual means for the years 1910 – 2012, straight from BOM’s time series data.

summ-wint2012

No winter increase over summer in 103 years.  This summer- we find out in early March- will have to be less than +0.7 C above average to make  the trend ever so slightly negative (to 5 decimal places).

But then how will we get another “Angry Summer”?