1 / 26

C20C simulations at ICTP : Overview and analysis of teleconnections

C20C simulations at ICTP : Overview and analysis of teleconnections. Franco Molteni, Fred Kucharski and Annalisa Bracco Abdus Salam Int’l Centre for Theoretical Physics Third C20C Workshop, Trieste, 19-23 April 2004. C20C ensemble simulations at ICTP.

creda
Download Presentation

C20C simulations at ICTP : Overview and analysis of teleconnections

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. C20C simulations at ICTP : Overview and analysis of teleconnections Franco Molteni, Fred Kucharski and Annalisa Bracco Abdus Salam Int’l Centre for Theoretical Physics Third C20C Workshop, Trieste, 19-23 April 2004

  2. C20C ensemble simulations at ICTP AGCM with simplified param.: SPEEDY T30 L8 (ver. 40) Prescribed SST from HadISST • 50-member ensemble for 1949-2002, global obs. SST (monthly means of full output) • 10-member ensemble for 1870-2002, global obs. SST (monthly m. from 1870 + selected daily means from 1949) • 9-member ensemble for 1949-2002, obs. SST in the tropics (25N-25S) + 50-m slab mixed-layer elsewhere (selected monthly means)

  3. Results: • A “minimal” model climatology • Regression maps vs. Nino3.4 index • EOFs of 500_hPa geop. height for different regions of the NH extratropics • Time series of PNA PC-1 vs Nino3.4 • Interdecadal trends of NH Z_500 from the 1950’s: • Ensemble mean vs. re-analysis • Taylor diagrams (amplitude – correlation with E.M.) • Single-run trends • Interdecadal variations in PDF of NH (PC1, PC2)

  4. The ICTP simplified AGCM (SPEEDY): features and advantages • PE dynamical core (GFDL), simplified parametrizations of radiation, convection, large-scale cond., vertical diff. and surface fluxes of momentum, heat and moisture (ICTP). • 5, 7 or 8-level versions, T30 (3.75 deg.) hor. resolution. • Simple program structure: makes easy to develop and test code updates. • Computationally efficient (~25 min-CPU/year on Xeon 2.4 GHz): a 50-year simul. can be run in < 1 day on 1 proc. • Large ensembles of simulations may be run to address climate predictability issues on multi-decadal time scales. • Results (mostly) comparable to state-of-the-art AGCMs.

  5. SPEEDY progress: the 500-hPa height climatology in DJF

  6. DJF rainfall climatology

  7. Regressions vs. the Nino3.4 index from HadISST (DJF 1950-2002)

  8. Speedy Re-analysis EOF1 WNH (210W 30E) EOF2

  9. Speedy Re-analysis EOF1 Eu-Atl (90W 60E) EOF2

  10. Speedy Re-analysis EOF1 PacNA (210W 60W) EOF2

  11. Nino3.4 vs. PNA PC-1 in DJF Nino 3.4PC1 ReAn. (cor = 0.46) Ens. Mean PC1 (cor = 0.84) Ens. Member PC1 (cor = 0.45 – 0.65)

  12. Interdecadal trends of SST and 500-hPa height in DJF 1977/2001-1952/76 What part of the height trend can be interpreted as a response to the SST trend, and what part is due to internal atmospheric variability ?

  13. How robust is the 50-yr trend of ENSO indices ? Linear trend of the bivar. ENSO index estimated from:

  14. Observed vs. ensemble-mean trend of 500-hPa height (1977/2001 – 1952/1976) Note : ens. mean contour scale is half of re-analysis scale

  15. Taylor diagrams for interdecadal trendsr = rms amplitude / obs. amplitudex = norm. projection on ens. mean y = component orthogonal to ens. meancos(a) = pattern correlation with ens. mean

  16. How close are trends simulated in single experiments to the observed trend ? Best match in the 50-member ensemble (same scale!)

  17. Interdecadal variations of (PC1, PC2) PDF for the NH : ReAnalysis P(x,y) - P(x)*P(y) P(x,y) – P(x)*P(y) 1977-2001 P(x,y) P(x,y) – P(x)*P(y) 1952-1976

  18. Interdecadal variations of (PC1, PC2) PDF for the NH : Speedy P(x,y) - P(x)*P(y) P(x,y) – P(x)*P(y) 1977-2001 P(x,y) P(x,y) – P(x)*P(y) 1952-1976

  19. Conclusions (1) • Regression patterns vs Nino3.4 are fairly well simulated by SPEEDY in DJF, but the u-stress in the Nino4 region is too weak. Also, an excessive intensification of summer monsoon rainfall over SE Asia is produced. • EOFs of monthly-mean 500-hPa height in various sectors of the NH in DJF show a close resemblance to the observed EOFs (less so for 2nd Eur-Atl EOF). • The Nino3.4 index is highly correlated to the leading PC of the PNA sector in the ensemble mean (84%).

  20. Conclusions (2) • Interdecadal differences in DJF 500-hPa height are fairly well reproduced in terms of pattern correlation (67%), but with an amplitude ranging from 40% to 60% of the observed signal when the ensemble mean is considered. • Trend patterns in a few individual ensemble members show an amplitude close to the observed one. • Interdecadal differences in the PDF of 500-hPa height PCs can be reproduced to a good extent for the last half of the 20th century, with stronger signature of regime-like behaviour in the 3rd quarter than in the last 25 years.

More Related