1 / 25

Mismatching Perturbations at the Lateral Boundaries in Limited-Area Ensemble Forecasting

Mismatching Perturbations at the Lateral Boundaries in Limited-Area Ensemble Forecasting. … or why limited-area ensemble forecasting can be more difficult than global ensemble forecasting. Jean-François Caron . Pros. Cons. Simple. No small-scales in the ensemble mean.

carl
Download Presentation

Mismatching Perturbations at the Lateral Boundaries in Limited-Area Ensemble Forecasting

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. Mismatching Perturbations at the Lateral Boundaries in Limited-Area Ensemble Forecasting … or why limited-area ensemble forecasting can be more difficult than global ensemble forecasting Jean-François Caron

  2. Pros Cons Simple No small-scales in the ensemble mean Ensemble Coherence: No mismatch between the IC from the two ensembles No small-scales in the IC perturbations Not appropriate for short-term forecasting & Perturbations Downscaling Small-scales in the ensemble mean No small-scales in the IC perturbations interpolation Perturbation Coherence: No mismatch between the ensemble perturbations IC perturbations derived from LAM Forecasts Small-scales in the ensemble mean Complex & Small-scales in the ensemble perturbations Ensemble method Risk of generating mismatches in the ensemble perturbations at the LBCs Appropriate for short-term forecasting and for ensemble DA From interpolation Limited-Area EPS: 3 approaches & FullFields Downscaling interpolation

  3. Outline • Description of a 1.5 km ETKF-based limited-area EPS for research purposes • An example of spurious perturbations triggered by mismatches between IC and LBC perturbations • To alleviate mismatches: A perturbation blending approach called ‘the scale-selective ETKF’ Impact of the new method on • Forecast performance • Ensemble-derived background error covariances

  4. Introduction • MOGREPS-G (60 km) – operational • MOGREPS-R (18 km) - operational • ETKF-1.5 km - research Purpose of this convective-permitting EPS • Examine 1-h forecast error covariances for the benefit of a NWP-based nowcasting system in development (Bannister et al., 2011,Tellus) • Predictability studies of very short-term weather events (Migliorini et al., 2011, Tellus) • Test hybrid VAR DA at convective scale 432 km 540 km

  5. ETKF 1.5km: The setup

  6. ETKF 1.5km: The setup • Control analysis from 3DVAR SUK 1.5km 1-h cycle with cloud and latent heat nudging and UK 4km LBC • 23 IC perturbations are produced by the ETKF using +1h forecast perturbations and the locations and the estimated errors of the assimilated observations. • Surface obs, Aircrafts • Radio-sondes • GPS, radiances • No localizations • Variable multiplicative inflation factor derived from surface obs (u, v, T) and aircraft data (u ,v, T) • No representation of model errors • LBC taken from MOGREPS-R

  7. ETKF 1.5km - Case study #3 00Z 05/12/2009 21Z 04/12/2009 00Z 05/12/2009 03Z 05/12/2009

  8. Relative difference (%) -20% +53% -50 -60 -25 -30 0 0 25 25 60 50 % Domain average =+9.9% Comparison of psurf spread MOGREPS-R : 12h fcst ETKF 1.5km : 1-h fcst hPa fields valid at 06z 05/12/2009

  9. Overestimation of psurf spread The Horror Movie The time-evolution of surface pressure perturbation in ensemble member #8 + 1 min + 5 min + 15 min + 30 min + 60 min + 90 min hPa

  10. CTRL LBC 1-h Incremental LBC Update (ILBCU) Sources of discontinuities at the LB (1) • The Incremental Analysis Update (IAU, i.e., how we add the IC perturbations) Initial Conditions Lateral Boundary Conditions Pert. Xa Pert. LBC Pert. LBC Xa CTRL Xa t t+30m t t+30m t-30m t-30m 1-h IAU

  11. Sources of discontinuities at the LB (1) • Relative difference in psurf spread : 1.5km ETKF vs. MOGREPS-R IAU only IAU + ILBCU Other sources of discontinuities between IC and the LBC must be present -20% +41% +53% -50 -60 -25 -30 0 0 25 25 60 50 -50 -60 -25 -30 0 0 25 25 60 50 % % Domain average =+9.90% Domain average =+9.95% 1h forecast valid at 06z 05/12/2009

  12. Perturbations Downscaling • Relative difference in psurf spread : 1.5km ETKF vs. MOGREPS-R Perturbation Downscaling ETKF with ILBCU +41% -50 -60 -25 -30 0 0 25 25 60 50 -50 -60 -25 -30 0 0 25 25 60 50 % % Domain average =+9.95% Domain average =-0.15% 1h forecast valid at 06z 05/12/2009

  13. Sources of discontinuities at the LB (2) • The construction of the IC perturbations Comparison of the ensemble perturbations from MOGREPS-R and the 1.5km-ETKF (at low resolution)

  14. Sources of discontinuities at the LB (2) • The construction of the IC perturbations Comparison of the ensemble perturbations from MOGREPS-R and the 1.5km-ETKF (at low resolution)

  15. Large-scale IC perturbations Low-Pass Filtering step Full IC perturbations High-Pass Filtering step ETKF step 1h small-scale forecast perturbations ETKF small-scale IC perturbations The Scale-Selective ETKF (SSETKF) Large-scale perturbation downscaling Driving-EPS forecast perturbations on LAM domain LAM 1h forecast perturbations Small-scale IC perturbations derived from LAM Forecasts

  16. Three flavours of SSETKF SSETKF-F48-96 SSETKF-F96-192 SSETKF-F192-384

  17. SSETKF: Impact on psurf spread • Relative difference in psurf spread : 1.5km ETKF vs. MOGREPS-R Perturbation Downscaling ETKF-ILBCU SSETKF-F48-96 SSETKF-F96-192 SSETKF-F192-384 -50 -60 -25 -30 0 0 25 25 60 50 %

  18. SSETKF: Impact on precipitation • Verification of 1-h precipitation rate (Brier Score) relative to the ETKF Positive (Negative) means a better (worse) forecasts than the ETKF

  19. SSETKF: Impact on B 1 Global and LAM Parameter transform 2 • The Met Office VAR control variable transform auto covariances only Vertical transform 3 Horizontal transform LAM 4 Global

  20. SSETKF: Impact on B • Degree of linear balance between mass and rotational wind Degree of balance

  21. SSETKF: Impact on B • Horizontal correlation lenghtscales based on a SOAR function

  22. SSETKF: Impact on B • Vertical auto-correlations with model level 30 (~700 hPa)

  23. Summary and discussion • As expected, applying the ETKF approach in a limited-area EPS generates mismatches between IC and LBC perturbations • This is likely to be true for all current limited-area EnDA approach • In our small domain, discontinuities were found to introduce significant spurious perturbations in the pressure field. • This is likely to be less important in larger domains. • Results from the scale-selective ETKF showed that mismatches at low wave numbers were responsible for the spurious perturbations. • The scale-selective ETKF has also improved slightly some other variables compared to both the ETKF and perturbation downscaling. • In terms of background error covariances, perturbation mismatches at the LBCs tend to: • Significantly reduce the degree of balance between mass and rotational wind • Reduce horizontal and vertical correlation lengths

  24. Summary and discussion Pros and Cons of the scale-selective (or blending) approach • Ensures that an a priory specified component of the IC perturbations is coherent with the driving EPS • The small scale IC perturbations are constructed without the knowledge of the large scale perturbations • The small scale IC perturbations could potentially be incoherent with the large scale component. Scale-selection is potentially better than traditional methods but is not the optimal approach. What’s the optimal approach?

  25. Questions

More Related