Reader Proust points me to this helpful BOM site showing rainfall trends in Australia. You can choose your own region, season and time period.
Here’s the most relevant to consideration of the effects of global warming, the trend since 1970, which demonstrates how much drier the climate has become over the period in which warming has been observed. As various people have pointed out, is was even drier during the famous Federation drought at the beginning of C20, so the role of global warming isn’t conclusively established, but it would certainly seem unwise to bet on a rapid return to the average observed in the historical record
82 thoughts on “The browning of Australia”
Roger, Iâ€™m hoping that you will be able to answer my question about the implications for modelled temperature of the steep decline in global sulphur dioxide emissions in the 1990s which has been identified in several studies published since the last IPCC Assessment Report.
The Summary for Policymakers of that report said that â€œThe higher projected temperatures [than in the previous Assessment Report] are due primarily to the lower projected sulphur dioxide emissions in the SRES scenarios relative to the IS92 scenarios.”
In your posting abve, you said that the highest temperature of the range I’d quoted for quoted for 2030 “is attached to the A1T scenario that has more aggressive sulphate emission reduction than the other SRES scenarios.” You also said that “the recent ABARE AP6 reference emission scenario gives an upper temperature almost as high in 2030 (0.05Â°C lower” and that “If more aggressive sulphate reductions were to occur, warming would be as high [as in A1T] by that time.”
If you assume, in accordance with the results of the studies cited above, that “more aggressive sulphate reductions” in line with the A1T projections for 2030 had already occurred by the mid-1990s, what does that imply for the increase in temperature that would occur from now on?
Specifically, if sulphur emissions as estimated in Stern D. I. (2005) “Global sulfur emissions from 1850 to 2000”, Chemosphere 58, 163-175 and the database supporting that paper are substituted for those that were used to produce the SRES and/or ABARE projections, what is the effect on the global mean temperature up to now, and the projected increase between now and 2030?
Is the ABARE temperature projection that you cited publicly available? And where do I find the projections of sulphur emissions that are used in the ABARE temperature projection that you cited?
re your last post. I can try this (substituting alternative SO2 pathways) using the MAGICC model, and it will be an interesting little test but it will have to wait until some of my contractual obligations are exhausted (that would be a fair while, if I was strict about putting such matters first all the time).
Note also that the raditiave uncertainties surrounding sulphates are large, so any analysis (like all of those discussed on this thread) would be informative rather than conclusive.
The ABARE temperatures in 2100 were quoted in their report (Matysek et al., 2006). I ran them through MAGICC (on the understanding that their origin would be acknowledged), so no, the full numbers are not yet publicly available (see the comment on contractual obligations above, it’s a time issue). The sulphur emissions in the scenario were assumed because the numbers were run really quickly for a short deadline. A sensitivity analysis using recent emissions estimates and some more aggressive reductions would also be interesting. Using “best bet” forcing estimates, early reductions in sulphates can accelerate warming by a few points of a degree.
Re the plausibility of radiative forcing. I stand by my earlier comment. If high emission rates are plausible, then we should be factoring the impacts due to these into risk assessments. The methods we have developed and are using draw on the breadth of emission pathways from low to high. If work comes out that suggests that part of that range is less likely to occur, we can assess that, but any underlying priors in the risk assessment are subjective. This is why we apply uncertainty analysis and Bayesian inference to the outcomes to see how much different types of information affect the results.
Thanks Roger. I realise that radiative uncertainties surrounding sulphates are large, and that’s why I found it surprising that the IPCC Summary for Policymakers in 2001 stated without qualification that the increase in the range of temperature increase to 2100 compared with that in the previous assessment in 1995 was “due PRIMARILY to the lower projected sulphur dioxide emissions in the SRES scenarios relative to the IS92 scenariosâ€?. (CAPITALS added). I questioned this statement in my initial correspondence on the IPCC emissions scenarios – it seems that analyses of the radiative effect of sulphate emissions are conclusive if they have been included in an IPCC SPM but are at best informative if carried out by other researchers.
Taken literally, the IPCC statement meant that the projected reduction in SOx emissions accounted for the greater part of the increase of 2.3Â°C in the upper end of the IPCC range. If one-third of this projected reduction had already occurred before the IPCC Report was published, as the evidence now available suggests, that seems to me to be one of the many issues that the IPCC should have investigated before deciding that ‘the SRES scenarios provide a credible and sound set of projections, appropriate for use in the AR4.â€™
I appreciate that you have contractual obligations that preclude you investigating this important matter for some time. However the IPCC’s decision to reuse the SRES projections in AR4 was made three years ago. It does seem rather extraordinary that the Panel decided that the scenarios were acceptable for this purpose, without reviewing the underlying assumptions in the light of all of the new evidence that had become available since the projections were prepared in the late-1990s.
Of course I agree with you that “If high emission rates are plausible, then we should be factoring the impacts due to these into risk assessments.” But how does one determine whether the high emission rates are plausible? In your paper (co-authored with Wenju Cai) presented to the Pan Evaporation Workshop at the Academy of Science in Canberra in late 2004, which I attended, you used the SRES A2 scenario projections to reach the conclusion that “By 2100, the equivalent CO2 reaches a level that is more than three times the level of 1870 (concentration ppm).”
But surely the projection of a global population of 15 billion in 2001 upon which the A2 scenario (and therefore your projection that the CO2 concentration may treble from 1870 levels) is predicated is no longer plausible, if it ever was? As long ago as 2001, the organisation that produced this projection for the IPCC (the International Institute of Applied Systems Analysis) published probabilistic estimates that put the 95% confidence limits for global population in 2100 at 4.3â€“14.3 billion. Now that another five years have passed without any upsurge in global fertility levels, the prospect of a 15 billion population by end-century must be vanishingly small.
The base year of the population projections produced for the IPCC by IIASA in 1996 was 1995, and the global population aged 0-4 was known to have decreased between 1990 and 1995 at the time that the projections were prepared. The A2 scenario projected an increase of more than 20% in the worldâ€™s population aged 0-4 between 1995 and 2005 â€“ in the event, according to UN and US Bureau of the Census estimates, there was a further DECREASE in the global pre-school age population during this period.
Did you and your co-author realise that the scenario that you used to project a trebling of CO2 concentrations in the 1870 to 2100 period rested on assumptions about one of the key driving forces that were entirely unrealistic?
You seem to be saying that it doesnâ€™t matter if the assumptions about driving forces are unsound as long as the emission rates themselves are plausible. But how do you determine that the emission rates are plausible, other than by considering the plausibility of the assumptions upon which they are based?
You say that “If work comes out that suggests that part of that range is less likely to occur, we can assess that.” But less likely to occur than what?
The IEA has estimated that cumulative energy-sector investment of $17 trillion (in 2004 dollars) will be required by 2030 in order to finance its Reference Scenario, and has said that â€œFinancing the required investments in non-OECD countries is one of the biggest sources of uncertainty surrounding our energy-supply projectionsâ€? (World Energy Outlook, 2005, p. 79).
The estimated increase in the global use of electricity between 2000 and 2030 under the IPCCâ€™s B1 scenario is more than twice as great as under the IEA Reference Scenario, and the increase under the IPCCâ€™s A1FI scenario is nearly three times as great.
Do you feed in this type of information into your uncertainty analysis? If the IEA is uncertain about the prospects of the investments required by its Reference Scenario being financed in developing countries, is there any real likelihood that the funds and infrastructure will be forthcoming to support two or three times the investment in power supply and distribution that the Agency is predicting on the basis of present policies?
I think that it is entirely fanciful to suppose that such a massive expansion in electricity generation and distribution capacity could take place, bearing in mind that the IEA’s much more modest estimates are supported by a mass of information supplied by governments and power supply authorities.
Ian, the object of modelling is to give reasonable projections of the variable of interest, so what matters is getting the important variables right. Climate change is a lagged result of cumulative emissions, so errors in forecasts of what will happen after 2050 are of much less importance than getting projections right for the next few decades – this is fortunate because of course we can’t know what will happen many decades into the future. For that reason, I think it’s a mistake to worry too much about the projected population in 2100 – what matters is the medium-term growth path. Here, the recent news is good, but not so good as to make our problems go away.
On any plausible business as usual scenario, emissions will grow substantially, while for any plausible climate science model, we need to reduce emissions substantially if we are to avoid highly damaging climate change.
Of course, the lower is the BAU projection, the lower the cost of stabilising concentrations of greenhouse gases and the better off we all are, so, like you, I’d welcome the use of more up-to-date population projections.
John, Of course the object of modelling is to give reasonable projections of the variables of interest, and of course the most important forecasts are those for the decades immediately ahead. As I’ve pointed out, the IEA’s current Reference Scenario projects the same growth in global CO2 emissions to 2030 as the IPCC’s B1. In practice the growth in emissions is likely to be considerably less than this, because the IEA Reference Scenario does not take account of new policies that are under consideration in many countries. Some of these are climate policy-related, but most are linked to other objectives – energy security, urban air quality etc.
Like all the IPCC scenarios, B1 does not assume that any measures are taken for climate policy reasons (e.g., Kyoto, or carbon sequestration). Yet, again as I’ve pointed out already on this blog, James Hansen and 45 other scientists from 12 research institutions have estimated that the warming to 2100 under the B1 scenario is 1.1Â°C. Cumulative emissions for the century under the IPCC’s B1T MESSAGE scenario are 20% lower than under B1. Do you think B1T is a plausible scenario? Because if it is, the cost of stabilising concentrations of greenhouse gases is nil. Concentrations under this scenario are stabilised at 540 ppm CO2 equivalent or thereabouts, and by assumption the implementation of expensive technologies for climate policy reasons is excluded.
On the ABC Four Corners documentary What Price Climate Change? on 28 August, Dr. John Wright, Director of CSIRO’s Energy Transformed Flagship said that the task of avoiding highly damaging climate change is “absolute immense.” He asked rhetorically “Can the world do it?” and answered “Mot without the sort of technologies we are trying to develop here [at CSIRO].”
Some of those technologies would not be contemplated other than for climate change reasons. Wouldn’t it be a good idea to try and get the IPCC “no policy” scenarios right first.
I agree with you that 2100 doesn’t matter much, but these poor population projections lead us astray well before then. For population under 20 in the year 2050, the UN’s population projections are: Low, 1.6 billion; medium 2.4 billion; and High, 3.4 billion. The IPCC’s A2 estimates 4.1 billion – not a good guide for policy.
I said above that the cost of stabilising GHGs under a particular “no climate policy” scenario IS nil. That was carelessly expressed. Of course I should have said that the cost WOULD be nil if the storyline, scenario and model quantification I was discussing were all to be realised.
Although the B1 scenarios seem to me to be far more plausible than the A2 or A1FI scenarios, the pervasive influence of uncertainty in all aspects of climate change debate must be recognised.
This was the theme of the policy paper â€œUncertainty and Climate Change: the Challenge for Policyâ€? which was published by the Academy of the Social Sciences in Australia in February 2005 (available at http://www.assa.edu.au/publications/op.asp?id=75 ). This paper incorporating articles by three leading Australian experts has been virtually ignored by the Australian Government and the media, including in the voluminous reading lists on climate change issues published on the websites of the Australian Greenhouse Office, CSIRO and the ABC.
I should also mention the very sensible article by Professor David Pannell of the University of Western Australia on this subject, which is available on his website at http://cyllene.uwa.edu.au/~dpannell/pd/pd0069.htm .
…all we get is blather.
Indeed, with yourself the greatest proponent of said art.
Just as a hint, Iâ€™ll start with (Pr(B|~A) = 0.25)…
And that proves what exactly? If you read my post, you’ll see I objected to your assumption for the ratio Pr(B|A) / Pr(B|~A), not your assumption for Pr(B|~A). Obviously it is the ratio that matters (although I disagree that the data gives 0.25 for Pr(B|~A) – a more justifiable upper bound would be 0.35-0.4, given the limited amount of data available)
Once again, instead of answering my objections, you make a clumsy attempt to obfuscate.
OK, Proust, let’s go on a couple more steps. Climate projections indicate that the likelihood of more severe droughts, such as the one we’re observing, increases under global warming. I estimate the ratio at 3, based on my reading of the literature on climate change. You claim to be able to prove me wrong. Go ahead – state and justify a lower number.
BTW, as noted above, I should have paid more attention to the role of increased evaporation in increasing the severity of drought, and reducing streamflow, the relevant variable for my analysis. So, please take this into account in formulating your response
I also note an error in your analysis so far. You state “a more justifiable upper bound would be 0.35-0.4, given the limited amount of data available)” but there’s no justification for using an upper bound here. Upper bounds don’t play the kind of role in Bayesian analysis you seem to want.
That link is broken.
I meant lower bound for Pr(B|~A), hence upper bounding the ratio (my mistake). Unless you are planning an infinite hierarchical Bayesian regress (prior on prior on prior…), bounds on prior probabilities are very important in Bayesian analysis.
Or, if you don’t like that approach, tell me your hyper-prior for Pr(B|~A) and justify it.
My objection is to your apparent desire to use a one-sided bound so as to get a probability substantially higher than the observed relative frequency. If you have a justification for this, state it.
I’d suggest starting with a diffuse prior over the observed range for annual rainfall, and updating on the observed data. With 100+ observations you should get a posterior distribution pretty close to the historical one, and there’s no reason to suppose a bias of the kind you want to include is going to emerge.
With 100+ observations…
There are not 100+ independent observations of the random variable relevant to your claim that the 1995-2006 drying is caused by AGW (wp 0.75). There are approximately 10 such observations (going back to 1900).
Another elementary error from the professor. But you’re on the right track now, keep trying.
Proust, I didn’t claim that the observations were independent, and your estimate assumes fixed 11-year cycles. As was stated way back in the thread, these are used just to even out year-to-year noise, the exact opposite of what you seem to be claiming here.
In any case, it’s time for you to put up or shut up. The data set is there – present your own analysis or admit that you don’t have a case.
If they’re not independent then your claim
is nonsensical. Tossing a coin once and then observing it 1,000,000+ times doesn’t get you any closer to a sharp posterior on the probability of heads.
Well, if you recall, it was you who picked 11 years:
You can put the 11 year cycles where you like. You can even make 100+ overlapping ones if you want. But there’s still only approximately 10 independent observations in there.
You seem remarkably out of your depth for someone in your position.
So far you have justified your estimate of Pr(B|~A) with an incorrect analysis of the probability of 11-year dry periods, and offered me a broken link as support for your estimate of Pr(B|A).
Sorry, you haven’t yet got the ball back over the net. At least fix the link.
Proust, this is nonsense. Check the first-order autocorrelation in the series. You need a value above 0.9 for your claims to stand up.
There is some short-run autocorrelation due to El Nino cycles but nothing like what you need for this claim.
The 11-year moving average was first mentioned by Ian Castles, not me, and, as I said, it has the exact opposite purpose to the one you claim. It’s meant to smooth out short run noise so long-run movements, if any, can be detected. The claim you’re supposed to be defending is that there are no long-run movements to detect, since all we have is random autocorrelated variation around a stable mean. (At least, I think that’s what you’re supposed to be defending – you haven’t stated a position).
Here’s the link
Finally got time to load the rainfall data for SE Australia into a spreadsheet.
Average rainfall 1900-2005: 601mm. Std dev: 103mm
Average rainfall 1995-2005: 585mm
6/11 years in the period 1995-2005 had rainfall above the long-term average
5/11 had rainfall below the long term average.
On that measure, the 11 years from 1995-2205 were about as unremarkable as it gets.
So, your claim that in the absence of any significant AGW effects,
with a probability of only 0.25 does not seem to be supported by the data at all.
Greens environmental consultant Aron Gingis says AGW has nothing to do with reduced rainfall:
According to Gingis, particles cause clouds to be “constipated.”
JQ on Ian Castles said: “I donâ€™t think itâ€™s appropriate to try and correlate rainfall in SE Australia with temperature in the same area.” Why not? global implies warming everywhere, so Australian temperature rises are just as relevant as – and are proxies for – rises in the oceans and elsewhere (which are indeed correlated with each other). Your original claim came close as may be to asserting the correlation you now qualify.
JQ again: “Itâ€™s my understanding (not expert) that sea-surface temperatures in the Pacific are more important for rainfall, and the Indian Ocean may also be relevant.” Yet it is clear from BoM that sea surface temperature trends around Australia broadly match the land trends, and elsewhere you have asserted that evaporation is part of the “browning” problem. I was taught that evaporation is part and parcel of the rainfall system. The “science” on this thread looks more and more dubious and the statistics even more again. Using the BoM 1960-1990 base period and deriving rainfall anomalies to match the mean temperature anomalies, there is always a significant (good ts) positive correlation between variations in both anomalies, even for 1970-2005. The browning map for 1970 to the present that began this thread is entirely an artifact of the very wet years at the beginning of that period, as Ian Castles has noted. Please note that the BoM maps for temperature and rainfall are not strictly comparable, as the former use anomalies and the latter use absolute values.
“On the final point, if we return to your original point, my article made the claim that it was appropriate to assume permanently lower levels, and proceeded to consider the implications. It appears you donâ€™t dispute this.”
Ian can and has answered for himself, from which I cannot see that he has agreed it is “appropriate to assume permanently lower levels (of rainfall)”; the BoM shows no such thing.
Perhaps I should spell it out more emphatically, this time regressing the 11-year moving averages of rainfall on temperature, which show that more heat implies more rain, with R2 at .24, the X coefficient at 2.85, standard error 0.547, and t at 5.2. The science underlying this is more heat to more evaporation to more rain, pace JQ. BTW, burning hydrocarbons yields both CO2 (more Heat) and H2O or water vapour (i.e more Rain). Curiously, the IPCC stress the physics and ignore such chemistry!
Proust, you can’t exclude 2006 which has been very dry. The rainfall deficiency so far is between 200 and 400 mm for most of SE Australia, and is unlikely to improve. The mean rainfall for the 11 years ending in 2006 is going to be well below the 585 you give for 1995-2005 and will be in the bottom quartile of the moving average values for the entire period, supporting the 25 per cent estimate I gave.
More importantly, as I’ve said several times now, in assessing the claim that the climate is hotter and drier you also have to take account of evaporation, which is now exacerbating droughts to the point that inflows to the Murray-Darling for 2006 are the lowest on record. (Post on this coming soon).
TOS, you should submit your interesting ideas to a scientific journal. If you want a quicker response, why don’t you give them a run over at RealClimate – for a softer ride, you might try Climate Audit or Jennifer Marohasy’s blog.
Thanks – your comment applies a fortiori to your new thread, I hope you will take your own advice. What goes up comes down so far as evaporation is concerned. If not where does it go? It’s certainly interesting when a professor considers statistically significant data showing a positive correlation between heating and rainfall is evidence for his faith in the opposite. Using Bayes, I will accept your odds for a bet on higher rainfall in 2007 than this year. As you would say, put up – or…
Professor Q, I’ll let you work out what is wrong with this reasoning, since you are, after all, a professor. But here is a hint: if the addition of one data point from a year that is not yet complete (2006), changes the conclusion from “unremarkable rainfall” to “remarkably dry”, what does that tell you about your approach?
[BTW, being in the bottom quartile is not the same as saying probability 0.25 – I’ll let you work that one out as well]
The map at the top of this post is a rainfall map. It is your blog, you can keep moving the goalposts if you want, but it doesn’t alter the fact that your original post was typical enviro-alarmism.
your reasoning would hold if what goes up comes down again in the same vicinity. Pity about atmospheric circulation. Global warming is increasing global average rainfall, but recent research by the UK Hadley Centre suggests that rainfall is becoming more spatially variable on a global basis. Harsher droughts, more deluges.
Furthermore, time series of annual average temperature and rainfall anomalies in temperate Australia are anti-correlated. This is because it rains when cloudy.
Roger Jones: of course I know about atmospheric circulation, but perhaps you will have more luck than Ian Castles and myself in getting JQ to agree that as you say “global warming IS (my emphasis) increasing global average rainfall”. So we have a distribution problem, indicating more dams in flood areas for transfer to drought areas (I previously worked on this in various parts of Africa until the World Bank joined the greens in banning dams). I am glad to see JQ’s new thread is a step in that direction.
However you are wrong about the time series: the actual coefficient on rainfall anomaly from 1960-1990 as function of mean temp anomaly is POSITIVE and statistically significant (t = 2.8) even for 1970-2005.
I am prepared to be wrong, but taking the 1950-2005 time series of annual temperature and rainfall from the area of SE Australia in the grid box bounded by 140.5Â°E to 154.5Â°E and 27.5Â°S to 39.5Â°S, rainfall is negatively correlated with temperature to the value of -0.46. This is comparable to the value one gets for individual sites in the region.
Thanks – but your comment about SE Australia conflicts with your previous comment on atmospheric circulation, as such a small area is unlikely to have a meaningful relationship between heat and rain however statistically significant your negative correlation may be (what is the t?).
Regressing your rainfall in SE Australia on mean temperature for the whole country from 1950 to 2005 produces once again a POSITIVE correlation with R2 = .27, X = 0.6, t = 4.5, so statistically significant and in this case climatically meaningful.
As for that part of the Murray catchment in SE Australia, with average annual rainfall of just 328mm in 1940-1947, against 579 in 1998-2005, I doubt the inflows then were better than over the 8 years before the present, pace JQ.
“perhaps you will have more luck than Ian Castles and myself in getting JQ to agree that as you say â€œglobal warming IS (my emphasis) increasing global average rainfallâ€?.”
If you have ever raised this issue before, TOS, I don’t remember it, and a quick scan of your comments didn’t find it. I have no reason to doubt that global warming is increasing mean global rainfall, and I’ve certainly never said anything different.
Proust, the arithmetic properties of a moving average are what they are. I didn’t pick 11 years, and it’s bit late for you to say now that it’s too sensitive to one very low year. As for your claims about quartiles, the probability that a single observation picked on an objective basis (in this case, the most recent observation on the moving average) will fall into the bottom quartile of a distribution is exactly 0.25. It’s certainly not 0.35, 0.4 or any other number you want to dream up. Of course if you cherry-pick a particular time period like TOS in the comment immediately above, you can get whatever you like – I assume you had something like this in mind, but it’s inapplicable here.
Coming back to the main point, if you want to continue the dispute over the conclusion that the weather is, as I said at the start of all this, getting hotter and drier [as we have discovered in the discussion, as a result of higher evaporation as well as lower rainfall], I suggest you move the discussion to the thread on “Drying out”.
I did the correlation but certainly did not assume that temperature drives the relationship. The negative correlation at location is, as I implied, due to local effects only. You left out your domain of analysis in previous posts, hence my quick check.
Nor am I convinced that your correlation is climatically meaningful. The following paper suggests the correlation of rainfall and max temp over Australia is strongly negative.
Nicholls, N. ; Lavery, B. ; Frederiksen, C. ; Drosdowsky, W. ; Torok, S. 1996 Recent apparent changes in relationships between the El NiÃ±o-Southern Oscillation and Australian rainfall and temperature
Geophys. Res. Lett. Vol. 23 , No. 23 , p. 3357 (96GL03166)
I have the Upper Murray inflows to 2000-1. Yes, the forties were low but I am reliably informed by the custodians of the data, that the latest accumulated natural inflows (since 1997) are the lowest on record.
That is as I understand it. I heard a climatologist explain on the radio that with a higher temperature the saturation point rises. Hence the atmosphere can hold more water. But when something disturbs it there is more up there to fall down.
I also recall a climatologist saying that we have been experiencing a predominance of large high pressure systems with the lows tracking further south in recent years. This was said to be related to tighter circulation patterns over Antarctica, I think to do with the ozone hole.
If this is so, it seems to my simple mind that there may be an upside in that the melting of Antarctica may be delayed, apart from the bit that sticks out. But then the sea is majorly in contact with the ice, especially under the large ice shelves, so I expect it will be chewed out eventually.
And I wonder what impact the 30% reduction in the thermohaline circulation in the North Atlantic in the last 12 years is having on our weather here.
But I’m wandering…
It is a matter of record that you picked 11 years, this is your statement:
At last!! I could not agree more. Cherry-picking is precisely what you are doing, as my analysis of 1995-2005 shows.
If, as you claim, 2006 will change the 11-year moving average from “unremarkable” to “astonishingly dry”, that tells you 2006 is an extreme outlier. Therefore, ending the timeseries in 2006 and not 2005 is cherry-picking your period (it just happens to be the most recent period, but 1995-2005 is also recent enough for the purpose of this disscussion, as is 1994-2004, 1993-2003, etc – all “unremarkable”).
It would be one thing if it had been overly dry for the last several years, for then your argument would be relatively insensitive to the chosen period. But it’s not; your argument depends critically on ending in 2006, not 2005. Which means the support for your argument is essentially one data point: 2006.
Proust, making up quotes, as you’ve done above, is usually an indication of desperation.
Including 2006 shifts the 11-year moving average for rainfall from below-average to well below average.
More importantly, the discussion has demonstrated quite clearly that hotter, drier weather, including higher evaporation, is leading to flows into catchments that are well below the historical average and, for the Murray-Darling at all-time (historical) lows. This was the original claim disputed by you and Ian. I’ve restated it in “Drying out”, so if you have anything further to say, please do so there.
Which quotes? Everything in blockquote tags is a direct quote of yours. The other quotes (“unremarkable”, “astonishingly dry”) are what is known as “scare quotes”. Look it up. As a general rule I don’t like them – but they slipped through here.
Yes, strictly speaking 585mm is below-average. But when the average is 600mm +- 100mm, 585mm is not significantly below average (in the statistical sense). So “unremarkable” is a more appropriate description.
You cherry-picked. Or just applied sloppy statistics, I don’t know which. Then when caught out, you simply shifted the goalposts. But I wouldn’t worry about it, you’re in good company – your approach seems to be the MO amongst many influential climate scientists.