This website uses cookies. By continuing to use this website you are agreeing to our use of cookies. 



S-RIP: Zonal-mean dynamical variables of global atmospheric reanalyses on pressure levels

Latest Data Update: 2018-02-21
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2017-11-28
Download Stats: last 12 months
Dataset Size: 119.47K Files | 2TB


This dataset contains zonal-mean atmospheric diagnostics computed from reanalysis datasets on pressure levels. Primary variables include temperature, geopotential height, and the three-dimensional wind field. Advanced diagnostics include zonal covariance terms that can be used to compute, for instance, eddy kinetic energy and eddy fluxes. Terms from the primitive zonal-mean momentum equation and the transformed Eulerian momentum equation are also provided.

This dataset was produced to facilitate the comparison of reanalysis datasets for the collaborators of the SPARC- Reanalysis Intercomparison Project (S-RIP) project. The dataset is substantially smaller in size compared to the full three dimensional reanalysis fields and uses unified numerical methods. The dataset includes all global reanalyses available at the time of its development and will be extended to new reanalysis products in the future.

Citable as:  Martineau, P. (2017): S-RIP: Zonal-mean dynamical variables of global atmospheric reanalyses on pressure levels. Centre for Environmental Data Analysis, date of citation. doi:10.5285/b241a7f536a244749662360bd7839312.
Abbreviation: Not defined
Keywords: S-RIP, Zonal mean, Pressure levels, Momentum equation, Transformed Eulerian mean, TEM, E-P flux


Previous Info:
No news update for this record
Previously used record identifiers:
No related previous 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:

The dataset was created for the SPARC- Reanalysis Intercomparison Project (S-RIP). Data has been archived at the Centre for Environmental Data Anaylsis (CEDA).

Data Quality:
Data is as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)
File Format:
Data are netCDF formatted

Citations: 7

The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.

Boljka, L., & Birner, T. (2020). Tropopause-level planetary wave source and its role in two-way troposphere–stratosphere coupling. Weather and Climate Dynamics, 1(2), 555–575.
Gerber, E. P., & Martineau, P. (2018). Quantifying the variability of the annular modes: reanalysis uncertainty vs. sampling uncertainty. Atmospheric Chemistry and Physics, 18(23), 17099–17117.
Hitchcock, P. (2019). On the value of reanalyses prior to 1979 for dynamical studies of stratosphere–troposphere coupling. Atmospheric Chemistry and Physics, 19(5), 2749–2764.
Kuchar, A., Sacha, P., Eichinger, R., Jacobi, C., Pisoft, P., & Rieder, H. E. (2020). On the intermittency of orographic gravity wave hotspots and its importance for middle atmosphere dynamics. Weather and Climate Dynamics, 1(2), 481–495.
Martineau, P., Wright, J. S., Zhu, N., & Fujiwara, M. (2018). Zonal-mean data set of global atmospheric reanalyses on pressure levels. Earth System Science Data, 10(4), 1925–1941.
Orr, A., Lu, H., Martineau, P., Gerber, E. P., Marshall, G. J., & Bracegirdle, T. J. (2021). Is our dynamical understanding of the circulation changes associated with the Antarctic ozone hole sensitive to the choice of reanalysis dataset? Atmospheric Chemistry and Physics, 21(10), 7451–7472.
Ray, E. A., Portmann, R. W., Yu, P., Daniel, J., Montzka, S. A., Dutton, G. S., Hall, B. D., Moore, F. L., & Rosenlof, K. H. (2019). The influence of the stratospheric Quasi-Biennial Oscillation on trace gas levels at the Earth’s surface. Nature Geoscience, 13(1), 22–27.

Process overview

This dataset was generated by the computation detailed below.

S-RIP reanalysis


Three dimensional atmospheric fields were first downloaded from reanalysis data centers. Then, zonal-mean diagnostics were computed onto two distinct grids. The first is the grid originally provided by each data center. The second is a common 2.5 by 2.5 degrees grid onto which each data set is interpolated using bilinear interpolation. All diagnostics are performed using the same numerical methods for each reanalysis data set.

Input Description


Output Description


Software Reference


  • var_id: EPF_p_qg
  • var_id: EPF_p_qg_k1
  • var_id: EPF_p_qg_k2
  • var_id: EPF_p_qg_k3
  • units: hPa
  • standard_name: air_pressure
  • var_id: pressure
  • units: K
  • standard_name: air_temperature
  • var_id: t
  • units: m s-1
  • standard_name: eastward_wind
  • var_id: u
  • units: m
  • standard_name: geopotential_height
  • var_id: h
  • units: Pa s-1
  • var_id: omega
  • standard_name: lagrangian_tendency_of_air_pressure
  • units: m s-1
  • var_id: vstar
  • standard_name: meridional_residual_circulation
  • var_id: momconv
  • var_id: momconv_k1
  • var_id: momconv_k2
  • var_id: momconv_k3
  • units: m3 s-2
  • standard_name: northward_eliassen_palm_flux_in_air
  • var_id: EPF_phi_qg_k3
  • units: m s-1
  • standard_name: northward_wind
  • var_id: v
  • units: m s-2
  • standard_name: tendency_of_eastward_wind_due_to_advection_of_zonal_momentum_by_northward_residual_circulation
  • var_id: uvstar
  • units: m s-2
  • standard_name: tendency_of_eastward_wind_due_to_advection_of_zonal_momentum_by_vertical_residual_circulation
  • var_id: uomegastar
  • units: m s-2
  • var_id: fv
  • standard_name: tendency_of_eastward_wind_due_to_coriolis_torque
  • units: m s-2
  • standard_name: tendency_of_eastward_wind_due_to_coriolis_torque_resulting_from_northward_residual_circulation
  • var_id: fvstar
  • units: m s-2
  • standard_name: tendency_of_eastward_wind_due_to_eliassen_palm_flux_divergence
  • var_id: EPFD_phi_qg_k3
  • var_id: uv
  • units: m s-2
  • standard_name: tendency_of_eastward_wind_due_to_meridional_advection_of_zonal_momentum
  • units: m s-2
  • standard_name: tendency_of_eastward_wind_due_to_vertical_advection_of_zonal_momentum
  • var_id: uw
  • units: m s-2
  • standard_name: tendency_of_eastward_wind_due_to_vertical_momentum_flux_convergence
  • var_id: vertflux_k3
  • standard_name: upward_eliassen_palm_flux_in_air
  • units: m2 s-2 Pa
  • var_id: EPF_p_pr_k3
  • units: Pa s-1
  • standard_name: vertical_residual_circulation
  • var_id: omegastar
  • units: m Pa s-2
  • standard_name: zonal_covariance_of_eastward_wind_and_lagrangian_tendency_of_air_pressure
  • var_id: uomega_k3
  • units: m2 s-2
  • standard_name: zonal_covariance_of_eastward_wind_and_northward_wind
  • var_id: uv_k3
  • units: m K s-1
  • standard_name: zonal_covariance_of_northward_wind_and_air_temperature
  • var_id: vt_k3
  • units: K Pa s-1
  • standard_name: zonal_covariance_of_temperature_and_lagrangian_tendency_of_air_pressure
  • var_id: tomega_k3
  • units: m2 s-2
  • standard_name: zonal_variance_of_eastward_wind
  • var_id: uu_k3
  • units: m2 s-2
  • standard_name: zonal_variance_of_northward_wind
  • var_id: vv_k3
  • units: K2
  • standard_name: zonal_variance_of_temperature
  • var_id: tt_k3

Co-ordinate Variables

  • units: degree_north
  • standard_name: latitude
  • var_id: latitude
  • standard_name: time
  • var_id: time
Temporal Range
Start time:
End time:
Geographic Extent