What KMNI has done is really great. Need more of it. Cheers

There is a problem with monthly data sets being prepared at BOM and that problem is missing data. It's almost as if those with something to contribute to method need to get together to resolve an agreed in fill method that is transparent and portable. In filling does not change the sense of the data much, mostly, but it makes working with the data far more tedious. It also encourages multiple users to devise their own infills, some of which are not reproducible by others. So there are increasingly more versions getting around in the literature and not all of them can be correct.

Yes, I'd very much like tabulation of monthly Tmax and T min at as many stations as practical.

source(”http://www.climateaudit.org/scripts/station/australia/functions.bom.txt”)
station= get.bom(id=AusInfo$id[i])

I can scrape monthly station data from the BoM website.

Here are the first few months from Charters, Qld which I read directly into R:

1 19620101 19620131 28.5
2 19620201 19620228 27.6
3 19620301 19620331 26.1
4 19620401 19620430 22.8
5 19620501 19620531 21.4
6 19620601 19620630 19.4
…

If BoM wishes some assistance, I'd be happy to help them.

http://www.ncdc.noaa.gov/oa/climate/research/ca...

And it strikes me as odd that, although one may wish for a little more transparency on NOAA's part, that BoM can't be bothered to even do that much work. Suffice it to say that my opinion of the Australian agency is now greatly diminished relative to NOAA here in the states, which I don't hold in particularly high regard anyway.

David is talking about the presentation of these figures in a way that makes it easy to inform. Sure, if you are a programmer, they are reasonably easy to manipulate. But it is more efficient for the central controller to manipulate them into a presentation form, than for myriads of public users out there to do their own thing.

As well as data reported on a daily basis, it would be handy to have an official version using in fill of minor missing values by an explained algorithm, followed by tabulation of monthly and yearly averages for each acceptable station. Probably, these are the forms most used in studies.

What is lacking, but is being worked on, is the transcription of meta data such as station changes and other recorded factors that might influence the record.

On the BOM website, the data records tend to commence later. A decision seems to have been made that uncertainties about the start of use of Stevenson screens requires deletion of much data before 1910 or so. Later, there has been a minor trend to report data after about 1950, for reasons that elude me. One day we might see data only after 2000, or whatever was the actual year when the last of the Mercury thermometers was replaced by thermocouple or thermistor devices. It is becoming clearer that Tmax and Tmin from a Hg thermometer is less useful than the Tmax and Tmin from a near-continuous recorder, which can be estimated optionally after smoothing and filtering.

At present, there is no single “official” version of the Australian temperature record, because it is being changed from time to time. This has a bad knock-on effect when other users such as GISS and HadCRU take the same data and do their own adjustments to it. I simply do not know which record to use for studies, because there can be differences in the average of a given year of several degrees C from one source to another.

I suspect that this effect alone has already invalidated some studies that attempted to calibrate proxy data in the instrumented era.