Hi Jennifer,
There has been substantial discussion on the blog over the last few months as to the severity of the current drought afflicting much of Australia and its cause. A fair emphasis has been as to whether the current drought is the “absolute worst” on record or whether they have been “historical anecdotes and personal rainfall data sets before sufficient formal Bureau records, or paleological droughts recorded in coral cores” that were worse. Via the Australian newspaper, Barrie Hunt has contributed the results of a 10,000 year Global Climate Model run to further complicate this argument suggesting we only have a narrow view of what our real climate variability involves.
To some extent does it really matter? Is it just a public bar sports debating point. We know that the drought is widespread, severe, entrenched and multi-year in nature. It’s not much fun if you’re in the middle of it. Surely it is “among” the worst droughts on record in many important areas. All droughts have their own unique signatures and different areas show different impacts. It is simply not possible to say whether this drought is other than natural variability – although one can argue there may be climate change aspects or influences exacerbating the situation. We’ll know for sure in 30-40 years time.
What does matter is to whether we are adapting and responding to drought risk, water security, land use and population changes in a more mature manner. This involves seeing drought as part of normal and planning for it appropriately at farm, regional, industry, state and national levels.
Nevertheless I believe we do need a better spatial understanding of this multi-year drought which some have said has been building for 5, 6 or 7 years. A reasonable way to do this is to undertake a decile analysis of rainfall for the Australian rainfall network. We need to examine how bad the sequence of years are for rainfall deficit. The Bureau of Meteorology has come under quite a bit of criticism by blog commentators, but notwithstanding, I asked Dr David Jones, Head of Climate Analysis, from the National Climate Centre to supply a 5 year and a 7 year decile sequence analysis for their reference network which he has kindly provided. Why debate the issue in a data free vacuum when we can make a phone call or email !
The analyses are included as maps below.
The maps represent a 5 and 7 year decile analyses based on the sequence of 1900 till now. For example – where does the recent 5 or 7 annual rainfall sequences fit into any of the sequences since 1900.
Anyone can easily do these analyses for a single station or stations – you just need to do the mathematics of adding up the year-totals in a running mean fashion and grouping your data into decile bins. So for the five year decile – arrange your data from earliest to latest records, add up the first 5 years in the record and record the total, move the band along one on the rainfall record sequence and do it again, and so on and so on. When all done, rank the new totals highest to lowest in decile bins (0-10%, 20-30%, 30-40% and so on). You can then see where any individual sequence, or the last 5 years in this case, fits in the distribution of all 5 year sequences. Or in fine detail the lowest and highest on record.
Similar logic for the 7 year analysis.
But as you may appreciate a lot of work to do spatially and interpolate the results.
And it is important that it is done as a sequence of years – one cannot add the individual year deciles/percentiles together.
The maps unlike the time series show we live in two Australias – one wetter and one drier. In the majority of areas where we have major agriculture or urban populations we have drought issues – some moderate – some severe in parts. Meanwhile life in the Gibson desert is pretty good (relatively speaking). This why the times series data are not helpful – the addition of real good and real bad = average which doesn’t represent reality
Of course this is only rainfall – there are obvious issues of pattern and intensity of rainfall, how plants and soil respond, and antecedent conditions (i.e catchments currently dry as a chip) - if we’re debating streams and rivers I really think one needs the same analysis but on streamflow.
Similarly one can use a pasture or crop model to get decile crop yields or pasture biomass (decile of wheat and grass!) However experience suggests that often these further analyses amplify effects and it will look worse for drought. Usually same with streamflow.
I understand the Bureau will be undertaking some more work on this issue in coming months.
I encourage any readers to do their own numbers with their own data – but please explain what you have done so we’re all clear.
Cheers,
Luke.
PS obviously where station density is low – i.e. central Australia and central WA the spatial interpolation is only as good as the data point grid. But I believe we have a sufficient grid for some intelligent analysis in areas that people live or major agriculture occurs. One could obviously argue the spatial interpolation mathematics and accuracy in fine small areas (i.e. SE Qld). The data do not start in the 1890s and the Bureau do have issues with station quality before 1900. The data are of mixed quality.
your all wrong
could you please give me the facts about the current drought in Australia.
it wasnt helpfull
I hope and pray that the current "DROUGHT" will end sooner rather than latter,but should it continue, we may yet be destined to experience a looming disaster of biblical proportion.
This drought may yet inflict such a catastrophe to the equivalence of, or worse than that of a major tropical river drying up completely leaving the riverbed exposed to the mercy of extreme superheat temperatures.
At that state, only the most hardy of plants will remain even on the riverbed which means noxious weeds/creepers.
This ominous scenario may be avoided "If" we, in humility, humbly examine our ways and perhaps change direction, an exercise commonly known in the "HEAVENLY REALM as REPENTANCE".
Warwick: I’ve been telling Jennifer on this blog for some time; we only have to look out the window to confirm BoM data like they used in your map noted above.
Have a good look a the Capital to see what’s going to drive the ideas of a few pollies on their way home too.
Warwick - I don't have any special contacts/favours with the Bureau. The information here was a straight request to Head of Climate Analysis Section, National Climate Centre - Dr David Jones. Suggest you email David re your request and ask.
On that issue I understand they will undertake a further more detailed analysis with more stations included in coming months.
As I have said above whether it's actually "worst" on record is somewhat complex given the varying spatial extent of different droughts, and also one should probably get away from rainfall alone into simulated river flows, or percentiles of simulated crop and/or pasture yield if you wish to integrate all the biophysical, seasonal and distribution issues missing from a straight rainfall analysis.
Luke,
Is it possible that your BoM contacts could make another set of higher resolution version maps, this time with place names added on as per BoM "High Resolution" State Rainfall Deficiency maps that can be made now on the BoM website.
For eamples of place names see;
ftp://ftp.bom.gov.au/anon/home/ncc/www/drought/6month/colour/latest.vc.hres.gif
Gentlemen and others: This has to be rough considering the time.
Data obsessions and building a model perspective using our imagination, versus some simple reality tests.
Defending old positions is a great pastime if we are going nowhere.
Peer group assessment looks nicest when we are all just out of the same mould Given that we can each be what we want to be with a little bit of mental development we can each see what we want to see in any picture at any given time.
Although our brain structure can evolve towards building an individual personality for processing external and internal events, letting the old brain free wheel gets harder with time.
Try astro travelling to the far side of the world for a better view. This probably comes best with our ability to understand others. Authors may do much better than scientists in this field. The question that must arise immediately is how much fiction does it all become in the eyes of the reader.
Our fastest mental analysing ability comes from near instant processing of our visual images. Individual vision remains our best tool for understanding both weather and climate change. Other people’s models may provide us with more insight on how we should feel about a particular observation but not the world at large.
A touch of dyslexia can help with sending a standard on its way and putting a routine on its head. It also helps with 3D jigsaw puzzles in physics and engineering.
The law however becomes an ass no mater how we chose to look at it and when was it ever truly connected with us?
Even a skilled landscape artist (and portrait painter) can be seen at times with his brush held at arm’s length, horizontally then vertically.
Desperate lab craft out in the bush comes down to spitting carefully into the palm of the hand after finding the odd ph4 buffer tablet left in the RH pocket then crushing it with stumpy screwdriver for the same pocket to calibrate a suspected wayward effluent meter below the old cheese factory.
That’s almost as effective as putting a piece of very hard to find rusty fencing wire broken at ¼ lambda measured by bare foot ½ way up Cradle Mountain strapped to a dry stick and on to the only VHF radio relay for miles around. Some volunteer carried my guestimate quickly back over his leg. That was during an invitation only “ultra” silly overland event.
OK Peter - see where you are coming from and I yield. However my defence was not so much about a definition of deterministic vs stochastic in the pure sense but moreover the representation of uncertainty at all.
Pielke made some interesting comments on this issue early last year.
.. .. .. “the representation of model uncertainty is a developing subject”.
This is an important conclusion that needs to be widely recognized by the climate community.
He identifies three currently used methods to assess uncertainty including multi-model ensembles, perturbed-parameter ensembles, and stochastic physics. Multi-model ensembles have been utilized in multi-decadal retrospective predictions, such as in the CCSP report “Temperature Trends in the Lower Atmosphere: Understanding and Reconciling Differences” . However, the use of perturbed-parameter ensembles (where uncertainties in the tunable parameters within model parameterizations are used to run the models with different values of these paramters), and stochastic physics (where the parameterizations include a statistical component) have not been completed with climate models. "
So the whole issues of how uncertainty is represented is an area of research, as are experimental formulations of stochastic models. Some commentators have also labelled conventional climate models as quasi-deterministic.
Luke,
Sorry cannot agree that climate models not deterministic in nature. The almost absolute focus on ensuring that some sub models are able to precicely match CO2 and temp proxies demonstrates what I am on about. I know that they are ot the only sub models int he conglomerate that is climate modelling but they are fundamental drivers.
I also think that you may have misunderstood my "concern" with models. I am not against models as such. Indeed I use and develop models in my own work. What I am concerned about is the seemingly absolute acceptance of model output regardless of the caveats placed upon the model by those who develop them.
Models are just that, a representation of something real, that is either too large or complex to build anew or that is less well understood. I used climate models as an example(large and complex and less well understood) however it applies to all things modeled.
Given our current state of knowledge it is still not possible to "model" climate systems with the degree of accuracy and precision that experts, NGO's, and other political types pass comment with.