| Table of Contents |
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1. Ensemble version | |
|---|---|
| Ensemble identifier code | RUMS |
| Short Description | Global ensemble system that simulates initial uncertainties using breeding method. It is based on 20 members, run weekly (Wednesday at 00Z) up to day 61. |
| Research or operational | Operational |
| Data time of first forecast run | 07/01/2015 |
2. Configuration of the EPS | |
| Is the model coupled to an ocean model ? | No |
| If yes, please describe ocean model briefly including frequency of coupling and any ensemble perturbation applied | |
| Is the model coupled to a sea Ice model? | No - Sea ice initial conditions are persisted up to day 15 and then relaxed to climatology up to day 45. |
| If yes, please describe sea-ice model briefly including any ensemble perturbation applied | |
| Is the model coupled to a wave model? | No |
| If yes, please describe wave model briefly including any ensemble perturbation applied | |
| Ocean model | |
| Horizontal resolution of the atmospheric model | 1.125 x 1.40625 degrees lat-lon |
| Number of model levels | 28 |
| Top of model | 5 hPa |
| Type of model levels | sigma |
| Forecast length | 61 days (1464 hours) |
| Run Frequency | weekly (Wednesday 00Z up to May 2017, Thursdays 00Z since June 2017) |
| Is there an unperturbed control forecast included? | Yes |
| Number of perturbed ensemble members | 19 |
| Integration time step | 36 minutes |
3. Initial conditions and perturbations | |
| Data assimilation method for control analysis | 3D Var |
| Resolution of model used to generate Control Analysis | 0.5 degrees |
| Ensemble initial perturbation strategy | Breeding perturbations added to control analysis |
| Horizontal and vertical resolution of perturbations | 1.125 x 1.40625 degrees lat-lon. |
| Perturbations in +/- pairs | No |
4. Model uncertainties perturbations | |
| Is model physics perturbed? | No |
| Do all ensemble members use exactly the same model version? | Yes |
| Is model dynamics perturbed? | No |
| Are the above model perturbations applied to the control forecast? | No |
5. Surface boundary perturbations | |
| Perturbations to sea surface temperature? | No |
| Perturbation to soil moisture? | No |
| Perturbation to surface stress or roughness? | No |
| Any other surface perturbation? | No |
| Are the above surface perturbations applied to the Control forecast? | No |
| Additional comments - | |
6. Other details of the models | |
| Description of model grid | Regular lat-lon grid, sigma-coordinate in vertical. |
| List of model levels in appropriate coordinates | .0001, .0092, .01935, .03234, .04904, .06975, .09376, .12045, .15003, .1837, .2231, .2692, .3204, .3751, .4321, .4905, .5503, .6101, .6692, .72532, .77773, .82527, .86642, .90135, .93054, .95459, .97418, .99, 1.0 |
| What kind of large scale dynamics is used? | Finite-difference semi-implicit semi-Lagrangian, vorticity-divergence formulation (Tolstykh, JCP 2002; section 2 in Shashkin, Tolstykh, GMD 2014) |
| What kind of boundary layer parameterization is used? | pTKE scheme (Geleyn, J.-F., et al 2006) with shallow convection included |
| What kind of convective parameterization is used? | Bougeault (MWR 85), Ducrocq and Bougeault (95), Gerard and Geleyn (QJ 2005) |
| What kind of large-scale precipitation scheme is used? | Geleyn et al 1994 |
| What cloud scheme is used? | Xu-Randall (JAS 96), diagnostic |
| What kind of land-surface scheme is used? | ISBA |
| How is radiation parametrized? | Ritter, Geleyn (1992), Geleyn et al (2005) |
| Other relevant details? | |
7. Re-forecast Configuration | |
| Number of years covered | 26 |
| Produced on the fly or fix re-forecasts? | On the fly |
| Frequency | Produced on the fly once a week to calibrate the Wednesday 00Z real-time forecasts. The re-forecasts consist of a 10-member ensemble starting the same day and month as the Wednesday real-time forecasts for the years 1985-2010. |
| Ensemble size | 10 members |
| Initial conditions | quasiassimilation with ERA Interim data |
| Is the model physics and resolution the same as for the real-time forecasts | Yes |
| If not, what are the differences | N/A |
| Is the ensemble generation the same as for real-time forecasts? | Yes |
| If not, what are the differences | N/A |
| Other relevant information | HMCR re-forecasts are produced on the fly. Every week a new set of re-forecasts is produced to calibrate the real-time ensemble forecast of the given day. The ensemble re-forecasts consist of a 10-member ensemble starting the same day and month as a Wednesday real-time forecast, but covering 1985-2010 years. The re-forecast dataset is therefore updated every week in the S2S archive. |
8. References
Description of the model and its parameterizations
- Tolstykh M. A. Global semi-Lagrangian numerical weather prediction model, FOP, Obninsk, Moscow, Russia, pp. 111, 2010 [Russian]
- Dynamics is presented in sections 2.1 and 2.2 in V. V. Shashkin and M. A. Tolstykh, Inherently mass-conservative version of the semi-Lagrangian absolute vorticity (SL-AV) atmospheric model dynamical core, Geosci. Mod. Dev. 2014 V 7 P 407-417.
Parameterizations
- L.Gerard, and Geleyn J.-F., 2005: Evolution of a subgrid deep convection parametrization in a limited area model with increasing resolution. Quart. J. Roy. Meteor. Soc., 131, 2293–2312.
- Catry, B., Geleyn J.-F., F. Bouyssel, J. Cedilnik, R. Brožková, M. Derková and R. Mladek, 2008: A new subgrid scale lift formulation in a mountain drag parameterisation. Meteorologische Zeitschrift, 17, pp. 193-208.
- Noilhan, J. and Planton S., 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117, pp. 536-549.
- Ritter B. and Geleyn J.-F., 1992: A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations. Mon. Wea. Rev., 120, pp. 303-325.
- Geleyn J.-F., Fournier R., Hello G. and Pristov N., 2005: A new bracketing technique for flexible and economical computation of thermal radiative fluxes, scattering effects included on the basis the Net Exchanged Rate (NER) formalism. WGNE ‘Blue Book’ 2005, pp. 4/7-8.
- Brožková R., Derkova M., Bellus M., Farda A., 2006: Atmospheric forcing by ALADIN/MFSTEP and MFSTEP-oriented atmospheric tunings. Ocean Sci., 2, pp. 113–121.
- Geleyn J.-F., Váňa F., Cedilnik J., Tudor M. and Catry B., 2006: An intermediate solution between diagnostic exchange coefficients and prognostic TKE methods for vertical turbulent transport. WGNE ‘Blue Book’ 2006, pp. 4/11-12.
Some results of the extended range forecasts
- Tolstykh M.A., Diansky N.A., Gusev A.V., Kiktev D.B., 2014: Simulation of seasonal anomalies of atmospheric circulation using coupled atmosphere–ocean model. Izvestiya, Atmospheric and Oceanic Physics, Vol. 50, No. 2, pp. 111–121.