1 / 24

Demands and expectations at SMHI on the European Reanalysis for observations and climate

Demands and expectations at SMHI on the European Reanalysis for observations and climate Per Und én Tomas Landelius SMHI. WP 2.1 4D-VAR developments and radar precipitation, a year of data – MO WP 2.2 3D-VAR downscaling, most of 20 years , 25 km SMHI

kirra
Download Presentation

Demands and expectations at SMHI on the European Reanalysis for observations and climate

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Demands and expectations at SMHI on the European Reanalysis for observations and climate Per Undén Tomas Landelius SMHI

  2. WP 2.1 4D-VAR developments and radar precipitation, a year of data – MO WP 2.2 3D-VAR downscaling, most of 20 years , 25 km SMHI WP 2.3 MESAN and SAFRAN downscaling, 12-4 km, MF and SMHI EURO4M • WP1 observational datasets • WP2 reanalysis and evaluation • WP 3 evaluation • WP 4 management and coordination

  3. What SMHI expects from EURO4M • Dynamical downscaling of ERA data using HIRLAM 3D/4D-VAR • Consistent data set for ~ 20 years or more • Access to observations additional to the ECMWF archive • 2D high resolution downscaling of HIRLAM • Using these auxiliary observations • Driven by consistent HIRLAM model fields • Consistent data set ~ 20 years or more

  4. Expect project members to share data

  5. User requirements at SMHI • 1961 - onwards • Every 3:rd hour • 5 km (0.05°) • Parameters for: • Evaluation of climate change models • Atmospheric environment models • Oceanographical models • Wind energy studies • Hydrological models • Surface radiation models • Observation monitoring and replacement

  6. EERA-40 ? >SMHI KOAKK 125 km -> HIRLAM reanalysis 22 km ->11 km? N Europe ? MESAN downscaling at 11 km SMHI KOAKK 40 years for QC of observations for climate • National archives of climate data have discrepancies • Need to be re-checked • Corrections when necessary and possible

  7. Observing systems including SST/ ICE improves: Better quality, more data types, higher time frequency Data-assimilation system, model and analysis, unchanged through the period Analysis product quality improves in time Reanalysis philosophy

  8. Intermittent data assimilation (06 UTC 3 h)‏ (12 UTC 3 h)‏ (18 UTC 3 h)‏ tid 06 UTC 18 UTC 12 UTC

  9. ITN 4/3 2010 4 Dimensional Variational Data Assimilation Iterative fitting of a Forecast trajectory to observations Over a time window of 6 hours

  10. SMHI expertise and resources • HIRLAM 3D and 4D-VAR • Observation handling • Re-analysis • ERA expertise • DAMOCLES coupled HIRLAM/HIROMB reanalysis • Surface parameterisation • Cloud parameterisation • Radar and satellite data and algorithms • HARMONIE (ALADIN) models and data assimilation 3D(4D) • MESAN 2D-analysis • OI with anisotrophic structure functions • Observation processing including radar, precip, satellite and road stations • Long operational experience • ERA-MESAN

  11. FoUp redov 0.0 0.3 0.6 0.9 1.2 1.5 1.8 2.1 2.4 2.7 3.0 HIRLAM ALADIN High Resolution Limited Area Modelling Aire Limitee Adaption Dynamique InterNationale

  12. Improved 2D reanalysis for Europe • ERA-40 as first guess • 1980 – 2004 • 00, 06, 12, and 18 UTC • 11 km (0.1°) ERA-MESAN

  13. 3D-VAR developments Jk MESAN/SAFRAN developments Snow/ orography etc Advanced features VARAN type structure functions Coupled surf-upper air 3D ? Validation KNMI/MO Workpackage 2.2 • ERA-Interim downscaling • 25 km ENSEMBLES area ? • ECMWF observations conv AMVs? • HIRLAM 3D-VAR 25 km • Jk ((large-scale mix)) • 1989-2009 • -> HIRLAM 3D-VAR 11 km EU area • MESAN downscaling • 11 km T2m, Td, uv, prec, clouds

  14. ERA-40 / ERA Interim ECMWF 125-79 km MESAN 11-4 km HIRLAM 22 km

  15. Signatur • HIRLAM - Large Scale Mixing, LSM Reruns from ECMWF analysis, updating first guess • Instead: Include ECMWF information in assimilation! • Related work done with ALADIN at Météo-France

  16. Signatur Constrain Vorticity • Begin as “simple” as possible: - Vorticity only - Univariate NMC statistics from ECMWF forecasts, interpolated to HIRLAM RCR geometry Vorticity, model state Short forecast, ECMWF

  17. HIRLAM rotated lat-long coordinates S.P. at -35º/20º three resolutions: 0.2º, 0.15º and 0.1º EURO4M downscaling with HIRLAM 4D-Var possible areas(Per Kållberg , Per Dahlgren – SMHI)

  18. 294*260 = 76 440 points 0.2º*0.2º (27/-31/-24.7/27.5)

  19. an example • one day 4D-Var 0.15º*0.15º • LBC from ERA_Interim • 1 January 2005 18Z 4D-Var and +12h fcst • ~215 System Billing units on C1A • one cycle took ~40 minutes (run on daytime Nov 17)

  20. 306x306 points 0.2 x 0.2 °

  21. another example • one 4D-Var 0.2º*0.2º • 2 outer loops • LBC from ERA_Interim • +12 h forecasts • Analysis 20 mins • Forecast 5 mins • => 25 mins per cycle • Possible to run 1D / 2h • Or 12 days / day (but depending on queues etc) • Special Project at ECMWF? Will apply ....

  22. 65 levels inst of 60 och 10 m lowest mod lv inst of 30

  23. Development of the MESAN 2D analysis Anisotropic structure functions Parameterized downscaling

More Related