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Aladin consortium activities in data assimilation

Aladin consortium activities in data assimilation. Claude Fischer & Gergely Bölöni Stolen material from a real big number of really nice collaborators. Overview. Mainframe 3D-VAR application Background error statistics: « B » matrix Observations and OSE

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Aladin consortium activities in data assimilation

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  1. Aladin consortium activities in data assimilation Claude Fischer & Gergely Bölöni Stolen material from a real big number of really nice collaborators EWGLAM/SRNWP meetings

  2. Overview • Mainframe 3D-VAR application • Background error statistics: « B » matrix • Observations and OSE • Surface assimilation => talk by JF Mahfouf • Plans and collaborations EWGLAM/SRNWP meetings

  3. Mainframe 3D-VAR in Aladin • Example of Aladin-France • Preparations at CHMI • Aladin Rapid Update Cycle • Digital filter blending • 3D-VAR Aladin coupled with IFS LBC EWGLAM/SRNWP meetings

  4. Mainframe 3D-VAR: example of Aladin-France • Incremental 3D-VAR • Continuous assimilation cycle, 6 hour frequency, long cut-off assimilation cycle and short cut-off production, coupled with Arpège, Analysis=Model gridmesh=9.5km • Observations: • SHIP winds, synop & radome Ps, T2m, RH2m, V10m • Aircraft data • SATOB motion winds • Drifting buoys • Soundings (TEMP, PILOT) • Satellite radiances: AMSU-A, MHS, HIRS (NOAA & METOP), Meteosat-9 SEVIRI • QuikSCAT winds • Ground-based GPS zenital delays • Digital filter initialisation (non incremental) EWGLAM/SRNWP meetings

  5. Implementation of ALADIN 3DVAR at CHMI (A. Trojakova) Present status: • operational surface OI (together with a DF blending cycle) • use of ODB (SYNOP and TEMP data) News: • B matrix computed for the CZ domain (standard and lagged NMC for Autumn 2006) • validation of 3DVAR is on the way (CY32) • observation preprocessing further developed for SEVIRI (phased to CY32) standard NMC lagged NMC EWGLAM/SRNWP meetings

  6. Blending by Digital Filter (M. Bellus, M. Derkova) • Blending by DF implemented in ALADIN/SHMU • DF settings tuned for the SHMU domain • DF Blending cycle in parallel suite since the 6th of August 2007 => operationally implementedsince September 19th, 2007 • case studies and subjective evaluation good results (localization of precipitation) EWGLAM/SRNWP meetings

  7. Blending by Digital Filter Case study 11/08/2007 Better localization of the precipitation in the DF blending suite verif oper blending EWGLAM/SRNWP meetings

  8. ALADIN Rapid Update Cycle (G. Bölöni, S. Kertesz, B. Strajnar) • 3 and 1 hourly RUC compared to the usual 6h cycle • cycle setup changed for RUC (LBC and obs extraction) • expected extra from RUC:  more SYNOPs (only Ps)  smaller error in the innovation vector (due to more frequent analysis) • preliminary results from parallel suites with RUC 3h are presented  results depend a lot on the obs usage of the reference RUC6: 6h cycle using the same cut-off as RUC3, i.e. +/-1.5 h (some aircrafts and satellites excluded) ARPE: 6h cycle using an operational cut-off, i.e. +/-3h (all aircrafts and satellites) EWGLAM/SRNWP meetings

  9. ALADIN Rapid Update Cycle Reference: ARPE (…strictly the impact of more SYNOPs and a more exact innovation vector…) Red: improvement for U Result as one would expect… U Blue: degradation for RHU Deficiency in the 3h background forecast (non-appropriate Jb)? RHU EWGLAM/SRNWP meetings

  10. ALADIN 3DVAR cycle coupled with ECMWF LBC (S. Kertesz) • Dynamical adaptation and 3DVAR assimilation cycle coupled with ECMWF LBC • operational constraint: at 00UTC ECMWF LBCs from theprevious 18UTC run are available Conclusions:  Surface initial field should be ARPEGE or local analysis (ECMWF surface inconsistent with ISBA)  Dynamical adaptation: coupling with ARPEGE 00UTC is better than coupling with ECMWF 18UTC  Assimilation: coupling with ECMWF 18UTC run is better than coupling with ARPEGE 00UTC run (slight improvement for the upper air, similar results on the surface)  The 6h shift in the LBC has a very large impact i.e. coupling with 00UTC ECMWF is much better than coupling with ARPEGE 00UTC both for Dyn. Adap and 3DVAR assimilation EWGLAM/SRNWP meetings

  11. ALADIN 3DVAR cycle coupled with ECMWF LBC Verification against radiosondes Dyn. Ad Assim LBC: ECMWF 18UTC – ARPEGE 00UTC (taking into account the operational constraint) Red: ECMWF better than ARPEGE GEO U EWGLAM/SRNWP meetings

  12. « B matrix » evolutions • Structure functions: new humidity control • Sampling data for statistics: ensembles • A posteriori tuning: … EWGLAM/SRNWP meetings

  13. The new formulation of the Humidity control variable in Aladin (L. Berre, R. El Ouaraini) Context • Following the work by Elias Holm at ECMWF • Humidity seems to have the least Gaussian and the least homogeneous background errors of all analysis variables. • Improving the description of the humidity background errors may improve the humidity analysis. • This can be done by changing the current humidity control variable to one in which the errors are more Gaussian and homogeneous. EWGLAM/SRNWP meetings

  14. The new humidity control variable We change δq (specific humidity) by the normalized relative humidity δRH_n: δRH_n = δRH/ σ(RHb+δRH/2) P.S.: • The standard deviation σ depends on the humidity guess value RHb. • This new formulation avoids negative and supersatured humidity (Smaller σbnear 100% and 0% : see figure) EWGLAM/SRNWP meetings

  15. Some results The new humidity control variable (Experiment) The current humidity control variable (Reference) • Both analyzes lead to a dryer analyzed state than the first guess (in blue) with only local moistening (of smaller amplitude). • The drying is however less pronounced with the new control (maximum of –39 % against –63 %). • The spatial patterns of drying are wider spread and more homogeneous with the new control. EWGLAM/SRNWP meetings

  16. Ensemble B at HMS in operational 3D-VAR (G. Bölöni) • Arpege ensemble downscaled with CY30 (new ensemble B + tuned sigmab’s [Désroziers’ a posteriori tuning]) • 1 month parallel suite (comparison with the operational [NMC]) • good scores  ensemble B in operation since end of August • RMSE vertical cross-sections: • 00 UTC run • comparison against ECMWF analysis • reddish: ensemble better than NMC GEO T RHU EWGLAM/SRNWP meetings

  17. Observations & O.S.E. • Surface emissivities, surface temperature and radiances over land • Radar winds • Radar reflectivities EWGLAM/SRNWP meetings

  18. Land Surface Emissivity at Microwave Frequencies For Satellite Data Assimilation (F. Karbou) Over land: • The surface emissivity is higher (~1.0) than over sea (~0.5)  the surface contribution to the measured radiance is larger • The land emissivity varies at least with surface condition, roughness, moisture, … • Residual uncertainties about land emissivity and skin temperature  Only microwave channels that are the least sensitive to the surface are assimilated Existing emissivity models : facilitate the assimilation of channels that receive a contribution from the surface BUT….. The models need accurate input parameters hardly available at global scale Need for alternatives to estimate the land emissivity EWGLAM/SRNWP meetings

  19. Overview • Three land surface parameterizations with increasing complexity have been tested using AMSU-A, MHS (AMSU-B) and SSM/I observations (Karbou et al. 2006): • EXP_ATLAS: Averaged emissivities over 2 weeks prior to the assimilation period; Ts is taken from the model’ FG. • EXP_DYN: Dynamically varying emissivities derived at each pixel using only one channel of each instrument; Ts is taken from the model FG. • EXP_SKIN: Averaged emissivities + dynamically estimated skin temperature Ts at each pixel using one (or two) channel(s) of each instrument All surface parameterizations are handled by the RTTOV model (Eyre 1991; Saunders et al. 1999; Matricardi et al. 2004) • The land surface emissivity methods have also been tested within the IFS system and have been adapted to SSMI/S, TMI, AMSR-E observations in addition to AMSU, SSM/I (Karbou et al. 2007, SAF/NWP Report) Karbou, F., E. Gérard, and F. Rabier, 2006, Microwave Land Emissivity and Skin Temperature for AMSU-A & -B Assimilation Over Land, Q. J. R. Meteorol. Soc., vol 132, No. 620, Part A, pp. 2333-2355(23) . Karbou, F., N. Bormann, and J-N., Thépaut, 2007 , Towards the assimilation of SSMI/S observations over land, RAPPORT NWP-SAF EWGLAM/SRNWP meetings

  20. Main Results • Improvement in the performances of the RTTOV model: bias/std, increase of the number of observations that could be assimilated • Forecast scores globally neutral to positive for humidity, temperature and geopotential height. • Precipitation forecasts improved for West Africa. Further evaluation will be performed for AMMA (summer 2006) and with a limited area model for intense Mediterranean events. Exp_dyn: 5 SSM/I channels over land IR- Meteosat: 20050827-18h Control Cloud forecasts (20050827+18h) • Ongoing experiments to better understand the impact of changes in the surface (emissivity/skin temperature), bias correction, cloud identification • Sensitivity studies to assimilate cloudy/rainy microwave observations over sea/land EWGLAM/SRNWP meetings

  21. Results: Observation operator simulations Fg-departures (obs-guess) global histograms, 15-31 August 2005 ATLAS+SKIN  from 50GHz, Ts from 23GHz EMIS-DYN  from 23GHz ATLAS  from 50GHz Control 50.3 GHz Ch3 AMSU-A 89 GHz Ch15 AMSU-A 150 GHz Ch2 AMSU-B EWGLAM/SRNWP meetings

  22. Assimilation of radar data (T. Montmerle & C. Faccani) The ARAMIS radar network Current status : 16 Doppler C-band Radars performing between 2 and 11 PPIs / 15’ • 1 double polarimetric (Trappes) Assimilation of reflectivities Tested in AROME, still technical developments to perform Assimilation of Doppler winds Tested with ALADIN, currently running in pre-operational mode in AROME Doppler Radar Future Doppler Radar EWGLAM/SRNWP meetings Future Radar with double polarisation

  23. Assimilation of radial winds in AROME 3DVar Without Radar 72LM With Radar Analysis of divergence (z=2500m) 20070525 - 15 UTC Main convergence line is shifted by ~ 60 km Independent wind retrieval from multiple radar measurements (CMR / Muscat) EWGLAM/SRNWP meetings

  24. Without radar R-15UTC 1h Cumulated rainfall 16UTC->18UTC AROME Spin-up With radar Main convergence line is well analyzed thanks to Doppler observations => Squall line forecast is more realistic with a better persistence of rain Observations (Trappes radar) However: no real impact when the dynamical structure of convective systems is not sampled in and at the top of the boundary layer EWGLAM/SRNWP meetings

  25. Reflectivity assimilation (E. Wattrelot, O. Caumont, M. Jurašek, G. Haase, …) Goal : Operationnally assimilate radar reflectivities in AROME by 2009-2010 Status : • Volumic (3D) reflectivity data routinely available since August 2007, in real time. Pre-processing check to remove erroneous data (soil and sea clutters, …) • Reflectivity observation operator ready, simulates modelled reflectivities. • Quality control check by a gross comparison of observed and modelled columns. • Assimilation in the AROME system via a 1D+3DVar: reflectivities are inverted into pseudo-observations of relative humidity profiles (whose impact is expected to be bigger than when modifying the hydrometeor fields). EWGLAM/SRNWP meetings

  26. Impact of reflectivity assimilation on the case of 1st August 2007 21H Raw Radar Composite 21H REFLEC 21H REFERENCE 00H Raw Radar Composite REFERENCE 00H REFLEC 00H • 2 experiments : • REF run is an AROME 3h RUC without reflectivities (4 assimilation/forecast cycles at 18h) • REFLEC with assimilated reflectivities by 1D+3DVar method Composite radar images (left panels), 3h forecasts of the 2500 m reflectivity simulated by the REFLEC experience (middle panels) and the REF (right panels) experiments at 21h UTC (top panels) and at 00h UTC the 2nd of August (bottom panels) EWGLAM/SRNWP meetings

  27. Impact of reflectivity assimilation on the case of 1st-2nd August 2007 • 2 experiments : • REF run is an AROME 3h RUC without reflectivities (4 assimilation/forecast cycles starting 01/08/07 at 18 UTC) • REFLEC with assimilated reflectivities by 1D+3DVar method Top left panel: 3 h modelled precipitations (6-3 h lead times) in REFLEC Top right panel: ibid without reflectivity assim Bottom left panel: 3h raingauge aggregates Bottom right panel: POD v/s FAR diagram for REFLEC (red) and REF (green) EWGLAM/SRNWP meetings

  28. Future work: • Improvement of pre-processing for erroneous clutters (by data providers). For instance, fix echoes can be almost perfectly eliminated on polarimetric radars. Signal damping by precipitations also can be well corrected on polarimetric radars. • Improvement on the observation operator: inclusion of a minimum height of visibility within the width of the beam (useful for the vertical interpolation of model data on the path of the beam) • Improvement of the 1D Bayesian retrieval method: ensure a better consistency between the sets of modelled columns and the observed ones (allow for « wet columns » in rainy areas even if surrounding model has no rain and vice versa). Extend the 1D inversion to temperature, wind … • Evaluation of the 1D+3DVar method on convective cases poorly forecast by Arome • Improvement of quality control and thinning of radar inverted profiles (presently relies on what is done for radiosoundings). EWGLAM/SRNWP meetings

  29. Concept of visibility in the observation operator • the visibility is the minimum height which is detectable by the radar main lobe. It depends on the elevation angle, the beam width and the topography • Currently, topographical beam blockage is not considered. This might cause problems in mountaineous regions where the interpolation considers model levels which are not visible by the radar • By using visibility maps for standard propagation the vertical interpolation becomes more realistic where the radar beam is partly blocked Vertical interpolation from model to radar space (along dashed lines). The black solid line corresponds to the beam center while the dotted lines mark the beam width of the unblocked beam. The red solid line defines the actual visibility at this elevation angle assuming atmospheric standard conditions. The circles indicate the integration limits used in the vertical interpolation for the blocked (red) and unblocked beam (black), respectively Topography interpolated on Bollène radar geometry (left), visibility of the lowest elevation of Bollene radar (middle) and differences of simulations with and without taking into account beam blockage information through visibility maps (right) EWGLAM/SRNWP meetings

  30. Surface assimilation • O.I. scheme (CANARI) in Arpège and Aladin (CZ and MO; tested in HU and FR) • Same algorithm to be ported into the externalized surface scheme (SURFEX) • New system for 2D analysis (PBL fields and spatialisation tool) ? • Development of a new 2D-VAR (aka dynamical O.I.) assimilation for soil fields, including an ensemble component => talk by J.-F. Mahfouf EWGLAM/SRNWP meetings

  31. Plans for 2007 and outlook • B matrix and background std dev.: • Errors of the day for screening • Gridpoint maps of b’s for minimization • Filtering of the ensemble bg errors (low-pass) • Wavelets (A. Deckmyn; T. Landelius; L. Berre) • Algorithms: • 4D-VAR in a nutshell • Some kick-off on a simplified microphysics scheme for the mesoscale ? • Towards an integrated « Ensemble/Variational » data assimilation system; ETKF => Hirlam EWGLAM/SRNWP meetings

  32. Plans for 2007 and outlook • Observations: • SEVIRI radiances in Hungary and Morocco ? • SEVIRI/CSR monitoring and bias correction; surface emissivity for IR SEVIRI channels (M. Stengel, Hirlam) • Radar radial winds in the Aladin-FR and Arome assim. • Continuation on radar reflectivity obs. op. & retrieval methods (M. Jurašek, LACE; G. Haase, Hirlam) • Operations: • Aladin-France: IDFI+radar winds+retuned b’s+60 levels • Arome RUC: 3h frequency, 4 times a day, 30h range, incl. Radar winds and reflectivities, 2.5 km over France • Aladin-Hungary: T2m+RH2m+SEVIRI • Aladin-Morocco: 3D-VAR plus NOAA and MSG radiances EWGLAM/SRNWP meetings

  33. Thank you for your attention

  34. Contributors Ludovic Auger (Aladin-FR 3D-VAR) Martin Bellus (DF Blending) Loïk Berre (new humidity control, ensemble B) Gergely Bölöni (ensemble B) Bernard Chapnik (FGAT, a posteriori diagnostics) Alex Deckmyn (wavelet Jb) Máriá Derková (DF blending) Rachida El Ouaraini (new humidity control) Claudia Faccani (radar radial winds) Claude Fischer (Aladin-FR 3D-VAR) Günther Haase (radar reflectivities) Marian Jurasek (radar reflectivities) Fatima Karbou (radiances over land) Sándor Kertész (FGAT, RUC, ECMWF LBC) Michal Májek (SEVIRI) Thibaut Montmerle (SEVIRI, radar radial winds) Roger Randriamampianina(SEVIRI) Benedikt Strajnar (RUC) Alena Trojaková (3DVAR in CZ, SEVIRI) Eric Wattrelot (radar reflectivities) And we’re sorry for those we forgot … EWGLAM/SRNWP meetings

  35. ALADIN Rapid Update Cycle Reference: RUC6 (…in RUC6 one analysis uses the same amount of data as in RUC3 which means that we exlude data around 03, 09, 15, 21 UTC…) U Red: improvement for all variables (U and RHU shown as examples) …the meaning of this test is not so practical… RHU EWGLAM/SRNWP meetings

  36. Complex wavelets for LAM (A. Deckmyn) • Wavelets are (partially) localised in both grid point space and Fourier space. • Diagonalization of B in wavelet space can reproduce local variations in the structure functions and standard deviations. • Current work is focussing on reproducing 3D structure functions for different variables (Alex Deckmyn, Tomas Landelius, Loik Berre) Standard deviations of Temperature error at the lowest vertical level: from data (left) and from wavelet-B (right). EWGLAM/SRNWP meetings

  37. Simulated Reflectivity factor in « beam volum bv» Antenna’s radiation pattern: gaussian function for main lobe (side lobes neglected) Resolution volum, ray path: standard refraction (4/3 Earth’s radius) model level Assimilation of Reflectivity : Observation operatorimplemented in the 3DVar ALADIN N r j q z h • Bi-linear interpolation of the simulated hydrometeors (T,q, qr, qs, qg) • Compute « radar reflectivity » on each model level Diameter of particules Resolution volum, ray path : standard refraction (4/3 Earth’radius) Backscattering cross section: Rayleigh (attenuation neglected) Microphysic Scheme in AROME EWGLAM/SRNWP meetings

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