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repository for the Australian rOpenSci unconference 2016!
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Assess the quality of satellite sea surface and depth temperature data using physical measures #31

Open mensurationist opened 8 years ago

mensurationist commented 8 years ago

One of the persisting challenges in biosecurity is to predict the parts of a system that will be vulnerable to invasion by a pest. Here, we focus on the possible invasion of pests into Australian ports using ballast water as a vector. Marine vessels routinely exchange ballast water as a safety and efficiency measure. Unfortunately, ballast water carries biota, so exchange within ports can create a risk of invasion.

Presently CEBRA engages with ABARES within the Department of Agriculture and Water Resources to improve the quality of sea temperature data in order to identify ports that are vulnerable to invasion from one of several marine pests. Sea temperature is measured at a number of different scales by different organizations for different means. This challenge is to automate the collection, assessment, and comparison of different sources of sea temperature data.

1) simplify and/or automate access to satellite-based sea surface and depth temperature time series data for Australian ports

2) identify, access, and ease access to any kind of sea temperature data as measured physically, including tidal gauges, buoys, fishing data, and so on.

3) develop models and graphical displays that will simply and compactly compare the satellite to the locally measured data, focusing on: differences in means, min, max, amplitude, and so on.

suren-rathnayake commented 8 years ago

Sounds interesting.

mensurationist commented 8 years ago

Information access is through IMOS and to get ocean data you need any browser except Internet Explorer, which is not supported.

Data are provided as netCDF files; we will need to use the ncdf4 package to access this data type.

Data access page: https://imos.aodn.org.au/imos123/home From here, the two datasets needed are satellite and buoy.

There is background information on satellite remote sensing here: http://imos.org.au/srs.html And buoys here: http://imos.org.au/nationalmooringnetwork.html -> http://imos.org.au/nrs.html

Satellite Parameter:

Platform

From there subset spatially and temporally.

It would be helpful to use data from 2009 so we can compare results with what we are doing. In terms of spatial extent, we should subset spatially around whichever of the buoys below we are interested in doing the comparison with - see below. The three day composite is time stamped on the middle day of the three day series. So 3 April comprises data from 2, 3 & 4 April. The dataset file name should look something like this: 20090101092000-ABOM-L3S_GHRSST-SSTfnd-AVHRR_D-3d_dn.nc. SSTfnd means that it is the “foundation” sea surface temperature, i.e. temperature at a depth of c. 2m, which is what we want. If the file name has skin in it – that isn’t what we want. Each netCDF file has up to 17 variables. It is the first variable, sea_surface_temperature that contains the actual data. But it is necessary to process the data first – see below. There are instructions here: http://imos.org.au/reading-data.html and a description of the variables here: http://imos.org.au/sstdata_ghrsstfilefields.html.

The processing steps required for foundation SST data are as follows:

  1. Check that the data are in floating point.
  2. Adjust for biases, which means subtracting sses_bias (one of the variables) from sea_surface_temperature (first variable).
  3. Convert to Celsius. The data are in kelvins so subtract 273.15. (I think that buoy temperature data is in Celsius – but if not, all the calculations can be done in kelvins and then converted to Celsius at the end).
  4. Use only Quality flagged data 3 and above (to avoid cloud contamination)

Buoy Parameter:

Platform

From there subset buoys. From our perspective the priority would be as follows: Darwin, Esperance, Rottnest, Maria Island, Port Hacking & Yongala. These sites are in increasing distance from a tide gauge. All would be useful but if time is limited, I suggest focussing on the highest priorities. The buoys may have temperature sensors at different depths. It is the highest level, but still sub-surface that we are interested in. If the buoy has a radiometer measuring skin temperature – we are not interested in that.

The buoys collect a large amount of data, not only temperature. The temperature sensors take bursts of 60 samples every 15 minutes, which equates to 5760 records per day. We will need to find the temperature data in the netCDF data file and then work out how to compare all that data with the single figure that the satellite records for one day - although there will be multiple pixels around the buoy.

After all that, what we are interested in is how satellite foundation SST compares with buoy sub-surface temperature data. Some plots and statistical comparisons would be very useful. It most likely will not be feasible to compare over a year – it will take too long to download the data. We can decide themselves how to go about making the comparisons.

Any progress towards this goal is valuable!