Wednesday, August 25, 2010

Time to Rain with BOM Radar

BOM Radar loop is very handy no matter what you are planning, a bike ride, a dash to the bus stop or a picnic with your girl friend. The images are nice and you can use your good old brain to work out the windows of rain free time. I would like to convert the rain from spatial views to time slice views at my location and forward shift to work out when the rain will hit me, just so that I can time that 10 min slot to go and get some lunch.

This will involve working out the velocity of the rain band and current location to estimate the time of arrival. The loop provides 4 or more images, these can be used to estimate the direction of travel of the rain band together with wind velocities reported.

You can get individual Radar frames over Adelaide with the following format
  • URL Base: http://www.bom.gov.au/radar/IDR642.T [x.T where x is the resolution level - 2,3,4]
  • Date code: YYYYMMDD in UTC
  • Time code: HHMM in UTC 
Only last 4 frames can be directly obtained from the server. Not to worry, I am sure someone is running a cron job somewhere and backing them up. Once you have sufficient frames to establish a time series the fun part begins. Here is a Python script to fetch the last 4 frames over Adelaide, be conservative and run it every 5 minutes ( just to satisfy Nyquist) and fetch the latest frame.

The rainfall is colour coded so we will need to perform a look-up to convert from colour to rain density. Next a quick FFT based convolution for the 4 images to estimate x and y shifts. You can also use a shift and difference approach while minimizing the difference to establish the rain velocity. Statistically test the results to establish constant velocity . If the velocity is not fairly constant our prediction accuracy falls off. Then the time machine part, propagate the last image through the shift field and estimate the rain intensity at the location of interest for the next 30minutes to 1hour, whatever the horizon of the radar and rain velocity lets you do.

Obviously all this can be done much easier from within BOM since they have the data at hand, but it is much more fun mashing a separate application together.

2 comments:

shenki said...

So did you implement the predictor? Do you have any code to share?

Tisham Dhar said...

Nope I am working on a simple feature detector using OpenCV-Scikits.image since I like numpy. Hopefully I can use the blob detection. Well all that remains to be done is to get it to build on windows. Meanwhile I am going to use standard OpenCv with adaptors.