Access Gridded Data

SILO's gridded datasets are hosted on Amazon Web Services under the AWS Public Data Program.

How can I access the data?

You can download the annual files here:

Year*
Variable*

To ensure you obtain the most recent version of the selected dataset, please clear your browser cache before downloading.

SILO’s gridded datasets are arranged in annual blocks. Each annual file contains all of the grids for the selected year and variable.

Each annual file (for daily variables) is approximately 410 MB in size. The annual files for monthly rainfall are smaller (14 MB) because they only contain 12 monthly grids, instead of 365 or 366 daily grids.

Annual files are available for:

  • Mean sea level pressure: 1957 - current year
  • Evaporation - Class A pan: 1970 - current year
  • All other variables: 1889 - current year

How else can I access the data?

The gridded data are stored on Amazon S3 and arranged in a directory structure of the form annual/<variable>/<year>.<variable>.nc where variable is the variable's short name. The datasets can be accessed by the following methods:


  • Using the AWS command line interface:
    For example, the 2005 data for monthly rainfall can be downloaded as follows:
    aws s3 cp s3://silo-open-data/annual/monthly_rain/2005.monthly_rain.nc .

    Alternatively, all monthly rainfall files can be downloaded to your current directory as follows:
    aws s3 sync s3://silo-open-data/annual/monthly_rain/ .

  • Direct access via URL:
    Datasets can be downloaded via URL using a web browser, scripting APIs (such as netCDF4-python for Python) or command line tools such as curl or wget. The URL has the form:
    https://s3-ap-southeast-2.amazonaws.com/silo-open-data/annual/<variable>/<year>.<variable>.nc

    For example, the 2015 data for class A pan evaporation can be downloaded using curl as follows:
     curl "https://s3-ap-southeast-2.amazonaws.com/silo-open-data/annual/evap_pan/2015.evap_pan.nc" --remote-name

How can I interact with the gridded data?

Use the tools and examples provided below to get started.

Python

The example shows how to import a NetCDF dataset and analyse.

Read more
NetCDF Operators

The example shows how NCO tools can be used to process NetCDF datasets.

Read more
Convert NetCDF files

The example shows how NetCDF files can be converted to other formats.

Read more

Last updated: 9 July 2019