HIRLAM model runs have ended

The use of the HIRLAM weather forecasting model at the Finnish Meteorological Institute has been ended in the end of October 2022, after which its forecasts are not available through the open data services. HARMONIE (MEPS) forecasts are available through the our open data services.

During the past fifteen years, the main focus in forecast model development has been on a more accurate model with improved resolution. The resulting HARMONIE (MEPS) model is capable of 2.5 km horizontal resolution (compared to 7.5 km of HIRLAM) and able to predict small scale phenomena more accurately. HARMONIE (MEPS) forecasts are now available through the open data services.

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Tools to handle the data

The data is stored in GRIB2-files. Below is listed few possible tools to handle the data.

PanoPly

PanoPly provides an easy UI to view GRIB, NetCDF and HDF files.

Example image of PanoPly's user interface visualizing total cloud cover in northern hemisphere
Example image of PanoPly's user interface visualizing total cloud cover in northern hemisphere

Integrated Data Viewer (IDV)

Compared to PanoPly Integrated Data Viewer (IDV) provides a slightly more complicated but more versatile user interface for browsing and analysing geographical data.

Example image of Intergrated Data Viewer's user interface visualizing long wave radiation data
Example image of Intergrated Data Viewer's user interface visualizing long wave radiation data

GRIB-tools

Bunch of tools exist for batch processing the data:

ECMWF GRIB tools provides number of convenient command line tools to process the data. For more information, please consult their wiki:

NOAA's WGRIB2 (and WGRIB for GRIB1 files) can for example: inventory and read grib2 files, create subsets and export data to ieee, text, binary, CSV, netcdf and mysql.

http://www.cpc.ncep.noaa.gov/products/wesley/wgrib2/

Geospatial Data Abstraction Library GDAL supports GRIB as well

http://www.gdal.org/frmt_grib.html

SmartMet Server

If you are using the data in an operational manner and live in web environment, SmartMet Server is a great resource to extract the data as JSON or GML and visualize it via WMS.

For more information, please consult: https://github.com/fmidev/smartmet-server

Additional Resources

http://en.ilmatieteenlaitos.fi/numerical-weather-prediction http://en.ilmatieteenlaitos.fi/open-data-manual-forecast-models https://aws.amazon.com/public-datasets/fmi-hirlam/