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ECMWF ERA-Interim: reduced N256 Gaussian gridded surface level invariant parameter data (ggis)

Update Frequency: Not Planned
Latest Data Update: 2011-10-16
Status: Completed
Online Status: ONLINE
Publication State: Published
Publication Date: 2014-08-26
Download Stats: last 12 months
Dataset Size: 9 Files | 6MB


Surface level invariant parameters on a reduced N256 Gaussian grid from the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA-Interim programme.

The ERA-Interim global atmospheric reanalysis of the covers 1979 to August 2019. This follows on from the ERA-15 and ERA-40 re-analysis projects

This subset of the ERA-Interim dataset contains 11 parameters.

Citable as:  European Centre for Medium-Range Weather Forecasts (2014): ECMWF ERA-Interim: reduced N256 Gaussian gridded surface level invariant parameter data (ggis). NCAS British Atmospheric Data Centre, date of citation.
Abbreviation: Not defined
Keywords: ECMWF, ERA, ERA, Interim, reanalysis, model, invariant, surface level


Previous Info:
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Previously used record identifiers:
Access rules:
Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access.
Use of these data is covered by the following licence: When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

Data are generated by the ERA-Interim project at European Centre for Medium-Range Weather Forecasts (ECMWF) before being prepared by ECMWF and uploaded to Centre for Environmental Data Analysis (CEDA) for ingestion into the archive.

Data Quality:
ECMWF quality controlled data.
File Format:
Data are netCDF formatted.

Process overview

This dataset was generated by the computation detailed below.

ECMWF ERA-Interim Re-analysis Model deployed on ECMWF Computer


This computation involved: ECMWF ERA-Interim Re-analysis Model deployed on ECMWF Computer. The data assimilation system used to produce ERA-Interim is based on a 2006 release of the IFS (Cy31r2). The system includes a 4-dimensional variational analysis (4D-Var) with a 12-hour analysis window. The spatial resolution of the data set is approximately 80 km (T255 spectral) on 60 vertical levels from the surface up to 0.1 hPa.

Input Description


Output Description


Software Reference


  • units: rad
  • long_name: Angle of sub-gridscale orography
  • var_id: ANOR
  • names: Angle of sub-gridscale orography, ANOR
  • long_name: Anisotropy of sub-gridscale orography
  • var_id: ISOR
  • names: ISOR, Anisotropy of sub-gridscale orography
  • units: m**2 s**-2
  • long_name: Geopotential
  • standard_name: geopotential
  • var_id: Z
  • names: Geopotential, geopotential, Z
  • units: (0 - 1)
  • long_name: High vegetation cover
  • var_id: CVH
  • names: High vegetation cover, CVH
  • units: (0 - 1)
  • long_name: Land-sea mask
  • standard_name: land_binary_mask
  • var_id: LSM
  • names: land_binary_mask, LSM, Land-sea mask
  • units: (0 - 1)
  • long_name: Low vegetation cover
  • standard_name: geopotential_height_anomaly
  • var_id: CVL
  • names: CVL, Low vegetation cover, geopotential_height_anomaly
  • long_name: Slope of sub-gridscale orography
  • var_id: SLOR
  • names: Slope of sub-gridscale orography, SLOR
  • units: m
  • long_name: Standard deviation of filtered subgrid orography
  • standard_name: medium_cloud_area_fraction
  • var_id: SDFOR
  • names: Standard deviation of filtered subgrid orography, SDFOR, medium_cloud_area_fraction
  • long_name: Standard deviation of orography
  • var_id: SDOR
  • names: Standard deviation of orography, SDOR
  • long_name: Type of high vegetation
  • var_id: TVH
  • names: Type of high vegetation, TVH
  • long_name: Type of low vegetation
  • var_id: TVL
  • names: TVL, Type of low vegetation
  • units: degrees_north
  • var_id: latitude
  • long_name: latitude
  • names: latitude
  • units: degrees_east
  • var_id: longitude
  • long_name: longitude
  • names: longitude
  • units: level
  • var_id: surface
  • long_name: surface
  • names: surface
  • var_id: t
  • long_name: t
  • names: t

Co-ordinate Variables

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