Claude Research ALADIN DA

Research directions in ALADIN data assimilation: 

Research directions in ALADIN data assimilation Claude Fischer, With less stolen material than in Medullin …

Slide2: 

Background error statistics « the Jb » Assimilation cycles Observations TL/AD computations: the ALATNET study of C. Soci Technical state of the art General conclusions

Background error statistics: the « Jb »: 

Background error statistics: the « Jb » -plane (El Ouaraini and Berre) Off-diagonal terms in B (Stefanescu and Berre) Isotropic assumtion revisited (Bölöni) Compactly supported correlations (Guidard) Wavelets (Deckmyn – paper submitted) Relocatable B (Bouttier) – Arome Goals: more anisotropy in C+I, less wrap-around problems, better portability

Background error statistics: the « Jb »: 

Background error statistics: the « Jb » Mesoscale short range structure functions: lagged NMC method (Široka etal., 2003) Sensitivity of the NMC samples with respect to forecast range and difference (Bölöni) Ensemble of forecasts derived from Arpège (Stefanescu and Berre) Tuning of b by a posteriori validation (Sadiki and Fischer, paper in preparation) Lönnberg-Hollingsworth methods Goals: find better tunings for error variances and correlation lengthscales

Blending and BlendVar assimilation cycles (Brožkova etal., 2001, Bölöni and Široka, 2001) : 

Blending and BlendVar assimilation cycles (Brožkova etal., 2001, Bölöni and Široka, 2001) Blending: digital filter blend for 3D fields + linear combination of Surface fields, in order to combine Arpège analyzed large scales with Aladin forecast small scales Aladin 3D-VAR analysis: J = Jb + Jo Several Jb formulations exist: Standard Jb (large scale) Lagged Jb (mesoscale) LBC0 LBC1 Arp Analysis Ald 6h fct

« Large scale » cost-function Jk (Guidard): 

« Large scale » cost-function Jk (Guidard) J(x) = Jb(x) + Jo(x) + Jk(x), where H1 : global  LAM low resolution H2 : LAM high resolution  LAM low res. V : « large scale » error covariances xAA : global analysis

Large scale update - evaluation: 

Large scale update - evaluation BO versus BOK: observation over all the domain LAM background BOK analysis BO analysis global analysis truth Statistically: No difference between BO and BOK + observation

3D-VAR/Aladin in a doubly nested model, Aladin/Hungary (S. Alexandru & A. Horanyi / ALATNET PhD) : 

3D-VAR/Aladin in a doubly nested model, Aladin/Hungary (S. Alexandru & A. Horanyi / ALATNET PhD) Comparisons between several 3D-VAR assimilation suites, with different coupling data (Ald/Hun, Ald/LACE, Arp), different initialization, different coupling strategies The « Budapest solution » of a nested LAM assimilation cycle: standard NMC Jb, no blending, DFI inside DA cycle, coupling with Arpège Case studies and monitoring scores

Observations : 

Observations Screen level (Ps, U10, RH2m) (Moll, Jurašek, Horvath) High resolution « mesonet » in 3D-VAR (Auger) in 2004 Satellite radiances: ATOVS/AMSU-B (Randriamampianina, Sahlaoui), Meteosat SEVIRI (Montmerle) Humidity boguses (Nuret, Hdiddou) Radar reflectivities: start in 2004

TL/AD computations: sensitivity computations using the adjoint model (Cornel Soci, Alatnet PhD): 

TL/AD computations: sensitivity computations using the adjoint model (Cornel Soci, Alatnet PhD) Goal – improvement of 6 h precipitation forecast – in this case study: diminish CAPE to trigger the second convective nucleus ! 27 18

Sensitivity computations and modification of the initial conditions (Cornel Soci, Alatnet PhD) : 

Sensitivity computations and modification of the initial conditions (Cornel Soci, Alatnet PhD) Lessons: Many problems were encountered with simplified physics at 10km resolution: Tuning of parameters Numerical instabilities driven by inadequate parametrizations (Kessler scheme) Computational cost Not all cases showed sensitivity to the initial conditions: LBC or model formulation Convective case study: no impact of verifying analysis, though a « useful » signal was obtained from the adjoint model Do these results bring us closer or further away from 4D-VAR ?

Technical state of the art: 

Technical state of the art LAMFLAG geographical preprocessing to C+I 3D and 4D screening run 3D-VAR minimization stable Eulerian hydrostatic TL/AD models safe (?) Desired evolutions of the system: 3D-FGAT, SL TL/AD, CONGRAD, new obs operators (radar) Is it worth to spend time and energy on exotic configurations like NHS/TL+AD ?

General conclusions: 

General conclusions The push for more observations must be maintained (denser data, experience on data analysis + ODB, link with verifications) Surface analysis: OI (CANARI), 2D-VAR Scientific program 2002/04: Gourdon, Toulouse, Medullin discussions The three pillars of variational assimilation: scientific goals, local 3D-VAR consolidation, maintenance of the code Screening and 3D-VAR installed in Toulouse, Budapest, Casablanca and Prague Aladin -> Arome and vice versa in DA

Large scale update – evaluation (2): 

Large scale update – evaluation (2) BO versus BOK: obs. over a part of the domain LAM background BOK analysis BO analysis global analysis truth Statistically: BOK better than BO + observation