ECMWF IFS CY41r2 High-Resolution Operational Forecasts

ECMWF has implemented a significant resolution upgrade and methodology for high-resolution forecasts (HRES) and ensemble forecasts (ENS) beginning January of 2016. HRES is now performed via a transform grid with a nominal grid point spacing of 9 kilometers (0.08 degrees), and is carried out with IFS (Integrated Forecast System) model cycle CY41r2. Improvements in computational efficiency and effective resolution have been brought about by implementing a triangular cubic octahedral reduced Gaussian grid in which the shortest spatial wavelength is represented by at least four grid points anywhere on the globe, as opposed to the former linear arrangement whereby the shortest wavelength was represented by two grid points, while at the same time retaining the same number of spherical harmonics and triangular truncation. (The term "cubic" is due to the ability of the grid to represent cubic products in the dynamical equations.) In addition, the reduction of grid points along latitude circles as one approaches the poles is achieved using a triangular to octahedral mapping which corresponds to a poleward reduction of four points per latitude circle and an optimization of the total number of grid points and their local mesh resolution. Based on IFS CY41r2, ECMWF has documented superior filtering properties at higher resolution, an improved representation of orography, improved global mass conservation properties, substantial efficiency gains, and more scalable locally compact computations of derivatives and other properties that depend on nearest-neighbor information only. More details may be found in the publications cited below and the documentation tab at the top of the dataset home page (to be added).

NCAR's Data Support Section (DSS) is performing and supplying a grid transformed version of ERA-Interim, in which variables originally represented as spectral coefficients or archived on a reduced Gaussian grid are transformed to a regular 5120 longitude by 2560 latitude N1280 Gaussian grid. In addition, DSS is also computing horizontal winds (u-component, v-component) from spectral vorticity and divergence where these are available.

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Questions? Email Resource Support Contact:

  • Dave Stepaniak
    UCAR/NCAR - Research Data Archive

Temporal Range

  • Begin:  2016-01-01T00:00:00Z
    End:  2023-06-07T18:00:00Z


Resource Type dataset
Temporal Range Begin 2016-01-01T00:00:00Z
Temporal Range End 2023-06-07T18:00:00Z
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links

Related Resource #1 : Tool to convert NetCDF data to WRF Intermediate file format

Additional Information N/A
Resource Format NetCDF4
Standardized Resource Format NetCDF
Asset Size 133483529 MB
Legal Constraints

Downloading/Accessing data from this dataset implies acceptance of ECMWF's Terms of Use []

Access Constraints Registration on the RDA web site is a requirement for access to the data.
Software Implementation Language N/A

Resource Support Name Dave Stepaniak
Resource Support Email
Resource Support Organization UCAR/NCAR - Research Data Archive
Distributor NCAR Research Data Archive
Metadata Contact Name N/A
Metadata Contact Email
Metadata Contact Organization NCAR Research Data Archive

Author European Centre for Medium-Range Weather Forecasts
Publisher Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
Publication Date 2016-06-20
Digital Object Identifier (DOI)
Alternate Identifier ds113.1
Resource Version N/A
Topic Category climatologyMeteorologyAtmosphere
Progress onGoing
Metadata Date 2023-06-08T09:05:02-07:00
Metadata Record Identifier edu.ucar.rda::ds113.1
Metadata Language eng; USA
Suggested Citation European Centre for Medium-Range Weather Forecasts. (2016). ECMWF IFS CY41r2 High-Resolution Operational Forecasts. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Accessed 08 June 2023.

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