GRIB Practical Exercise 1: Data Discovery

July 14, 2015
Posted by: RDA Team

Note: This page was originally sourced from our Blogger page: http://ncarrda.blogspot.com/2015/07/grib-practical-exercise-1-data-discovery.html

If you want to learn more about a specific data format, scroll down to the blue box at the bottom of the NCAR RDA home page and follow the links.  The Format Descriptions link to the encyclopedic WMO documentation for people who need to write interfaces to GRIB data.

Scroll to the bottom of rda.ucar.edu and follow the links to GRIB documentation.

The links to the WMO standards documentation can be intimidating for the neophyte user.  Worry not; you need not understand all the details to get started.  The documentation will make more sense after you take a few GRIB datasets out for a spin.

First, take a moment to explore the NCAR RDA GRIB holdings by using our faceted search tool, which you can invoke through the 'Find Data' tab.  That produces a drop down menu.  Select 'All Datasets'.
Click on the 'Find Data' tab and select 'All Datasets' to perform a faceted search.
This generates a list of the over 600 datasets in our archive.  Narrow the search by  selecting 'Data Format'.  You will find the GRIB datasets under WMO GRIB.  Older holdings may be in GRIB, aka GRIB0.  Most are in GRIB1, the format that superceded/extended the original GRIB.

Narrow down the search by 'Data Format' and scroll to the bottom to find WMO GRIB0, GRIB1, and GRIB2.
Some are in GRIB2, which extends GRIB1 with compression (more on that in a later post).  Notice that more datasets are in GRIB1 than any other data format.  GRIB2 has been embraced by NOAA/NCEP, but is not yet in wide use by national weather services outside of the USA. With the advent of GRIB2, Version 2, other national centers will switch to GRIB2.

Next, we will take a sample GRIB2 dataset out for a test spin using a simple Graphical User Interface (GUI). After that, we will set up wgrib/wgrib2, powerful command line tools that can process data in a faster and more automated fashion.