Dataset
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
Abstract
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. https://dx.doi.org/10.5285/b241a7f536a244749662360bd7839312
Abbreviation: Not defined
Keywords: S-RIP, Zonal mean, Pressure levels, Momentum equation, Transformed Eulerian mean, TEM, E-P flux
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Access to these data is available to any registered CEDA user. Please Login or Register for a CEDA account to gain access.
Use of these data is covered by the following licence(s): http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ 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 Data has been archived at the Centre for Environmental Data Anaylsis (CEDA).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)
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| File Format: |
Data are netCDF formatted
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Related Documents
Citations: 12
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, 555–575. https://doi.org/10.5194/wcd-1-555-2020 https://doi.org/10.5194/wcd-1-555-2020 |
| Chrysanthou, A. (2019) Reply to Anonymous Referee #2. https://doi.org/10.5194/acp-2019-260-ac2 https://doi.org/10.5194/acp-2019-260-ac2 |
| Fujiwara, M., Martineau, P., Wright, J.S., Abalos, M., Šácha, P., Kawatani, Y., Davis, S.M., Birner, T. & Monge-Sanz, B.M. (2024) Climatology of the terms and variables of transformed Eulerian-mean (TEM) equations from multiple reanalyses: MERRA-2, JRA-55, ERA-Interim, and CFSR. Atmospheric Chemistry and Physics 24, 7873–7898. https://doi.org/10.5194/acp-24-7873-2024 https://doi.org/10.5194/acp-24-7873-2024 |
| Gerber, E.P. & Martineau, P. (2018) Quantifying the variability of the annular modes: reanalysis uncertainty vs. sampling uncertainty. Atmospheric Chemistry and Physics 18, 17099–17117. https://doi.org/10.5194/acp-18-17099-2018 https://doi.org/10.5194/acp-18-17099-2018 |
| Gerber, E.P. & Martineau, P. (2018) Quantifying the variability of the annular modes: Reanalysis uncertainty vs. sampling uncertainty. https://doi.org/10.5194/acp-2018-585 https://doi.org/10.5194/acp-2018-585 |
| Hitchcock, P. (2019) On the value of reanalyses prior to 1979 for dynamical studies of stratosphere–troposphere coupling. Atmospheric Chemistry and Physics 19, 2749–2764. https://doi.org/10.5194/acp-19-2749-2019 https://doi.org/10.5194/acp-19-2749-2019 |
| 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, 481–495. https://doi.org/10.5194/wcd-1-481-2020 https://doi.org/10.5194/wcd-1-481-2020 |
| 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, 1925–1941. https://doi.org/10.5194/essd-10-1925-2018 https://doi.org/10.5194/essd-10-1925-2018 |
| not a doi https://doi.org/2115/72073 |
| Orbe, C., Plummer, D.A., Waugh, D.W., et al. (2020) Description and Evaluation of the specified-dynamics experiment in the Chemistry-Climate Model Initiative. Atmospheric Chemistry and Physics 20, 3809–3840. https://doi.org/10.5194/acp-20-3809-2020 https://doi.org/10.5194/acp-20-3809-2020 |
| 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, 7451–7472. https://doi.org/10.5194/acp-21-7451-2021 https://doi.org/10.5194/acp-21-7451-2021 |
| 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, 22–27. https://doi.org/10.1038/s41561-019-0507-3 https://doi.org/10.1038/s41561-019-0507-3 |
Process overview
This dataset was generated by the computation detailed below.
| Title | S-RIP reanalysis |
| Abstract | 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 | None |
| Output Description | None |
| Software Reference | None |
- 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
Coverage
Temporal Range
Start time:
1958-01-01T00:00:00
End time:
2016-12-31T23:59:59
Geographic Extent
90.0000° |
||
-180.0000° |
180.0000° |
|
-90.0000° |
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