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  1. Data portal
    The simplest way how to get rather smaller ad hoc data samples (approximately up-to 20 000 retrieved fields per request)  
  2. Batch access
    The ECMWF access in batch should be used for most common types of work (big data samples retrievals)
  3. CMA data portal
    2nd official TIGGE data portal where all data from all partners can be downloaded. The data on both official portals hosted at ECMWF and CMA is synchronized via LDM.
  4. NCAR data portal
    Until the end of 2015, TIGGE data up to the end of 2014 are also available via this research data portal at NCAR.
  5. TIGGE Tropical Cyclone Track Data (UCAR)
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ECMWF Tropical Cyclone Track Data (XML format) 

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  • TIGGE Museum
    The museum includes a set of scripts to download TIGGE data, and plot it (using GrADS ) in file TIGGE_sample.tar.gz - available directly from here.TIGGE Tropical Cyclone Track Data (UCAR)
  • Cyclone XML tools
    Tools for use with Cyclone XML data are available from the CAWCR CXML website.
  • NCAR Tools:
    • NCL
      The NCAR Command Language (NCL) is a free interpreted language designed specifically for scientific data processing and visualization. NCL has robust file input and output with support for NetCDF, HDF, GRIB-1 and GRIB-2 file formats, including support for all published TIGGE GRIB-2 parameters.
      NCL is provided with a couple of useful command line tools:
      • ncl_filedump - prints the contents of supported files in a netCDF-like view.
      • ncl_convert2nc - converts one or more files in any of the supported formats to netCDF formatted files.

    • PyNGL and PyNIO

      PyNGL and PyNIO provide a Python interface to most of the NCL tools and its functionality, with an emphasis on high quality 2D visualizations. PyNIO, in particular supports TIGGE GRIB-2 with the functionality provided by NCL.

    • MET
      Model EvaluationTools (MET) is a suite of software utilities designed by NCAR Developmental Testbed Center (DTC) to the provide the capability to validate model forecasts using observational data.

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