BoM Victoria rain anomalies map downplays rain

September 6, 2018 Warwick Hughes 4 Comments

Hawkeyed reader Bob has sent in this example of the BoM August rainfall anomaly map for Victoria failing to reflect above average rain at BENDIGO AIRPORT (081123) 51.5 Norm, 56.4 in August , CASTLEMAINE PRISON (088110) 66.4 Norm, 66.6 in August. And then a little further south the anomalies contours make no sense either – DAYLESFORD (088020) 103.0 Norm, 111.4 in August, TRENTHAM (POST OFFICE) (088059) 124.8 Norm, 154.5 in August, and WOODEND (088061) 90.3 Norm, 91.3 in August. Larger map
The Daylesford daily data shows another type of error with rainfall left unrecorded in the gauge four times during the month – on the 8th the reading covered the previous 6 days. Well water evaporates so Daylesford rain for August was understated. Amazing with so much publicity about drought and wealthy Australia can not read a simple factor like rainfall to a proper standard.

4 thoughts on “BoM Victoria rain anomalies map downplays rain”

toorightmate says:

September 6, 2018 at 10:06 am

But we are reading a lot about Roger Federer losing a game of tennis due to global warming.
In twenty years time, he will lose a lot more games of tennis. That will also be due to global warming.
Nothing whatsoever to do with age.
Beachgirl says:

September 6, 2018 at 5:01 pm

Marree in SA looks like another error.
www.bom.gov.au/web03/ncc/www/awap/rainfall/anomaly/month/colour/latest.sa.hres.gif
Three Marree stations all above the August norm not enough for the BoM rain anomaly contouring maths.
www.australianweathernews.com/data/DS0817.HTM
Bob in Castlemaine says:

September 11, 2018 at 2:32 pm

Maybe this is where the rainfall anomaly map contour discrepancies come from i.e on the BOM website "an optimised Barnes successive correction technique"? Sounds a bit like homogenization and adjustment of rainfall data?

Gridded high resolution rainfall metadata

Under: Data Quality/Lineage

The analyses (grids) are computer generated using a sophisticated analysis technique. It incorporates an optimised Barnes successive correction technique that applies a weighted averaging process to the station data. Topographical information is included by the use of rainfall ratio (actual rainfall divided by monthly average) in the analysis process.
On the maps each grid-point represents an approximately square area with sides of about 5 kilometres (0.05 degrees). The size of the grids is limited by the data density across Australia.

This grid-point analysis technique provides an objective average for each grid square and enables useful estimates in data-sparse areas such as central Australia. However, in data-rich areas such as southeast Australia or in regions with strong gradients, "data smoothing" will occur resulting in grid-point values that may differ slightly from the exact rainfall amount measured at the contributing stations.
wazz says:

September 12, 2018 at 8:13 am

Thanks Bob. Nobody expects contouring to perfectly reflect underlying point data. However there should not be a bias one way or the other. If anybody can find equivalent map areas where rain is equally “exaggerated” – I will take this blog down.