1 / 27

How well are Southern Hemisphere teleconnection patterns predicted by seasonal climate models?

How well are Southern Hemisphere teleconnection patterns predicted by seasonal climate models? The return!!. Rosmeri P. da Rocha and Tércio Ambrizzi University of São Paulo, São Paulo, Brazil. EUROBRISA 2009 – Exeter, UK. Rossby Wave Theory. Basic Theory – Rossby (1939, 1945).

ondrea
Télécharger la présentation

How well are Southern Hemisphere teleconnection patterns predicted by seasonal climate models?

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. How well are Southern Hemisphere teleconnection patterns predicted by seasonal climate models? The return!! Rosmeri P. da Rocha and Tércio Ambrizzi University of São Paulo, São Paulo, Brazil EUROBRISA 2009 – Exeter, UK

  2. Rossby Wave Theory Basic Theory – Rossby (1939, 1945) The barotropic vorticity equation is: Assuming that And defining the perturbed streamfunction ψ, we have: Assuming the wave solution We get: or

  3. Some characteristics of Rossby waves are: • They propagate to the west • They are dispersive The group velocity is given by: and For a stationary wave (ω=0; c=0): Playing with the equations, it is possible to define the ray path radius of curvature which is given by the simple expression (Hoskins e Ambrizzi 1993)

  4. Schematic Ks profiles and ray path refraction • Simple refraction • (b) Reflection from a turning latitude YTL, at which Ks = k • (c) Reflection of all wavenumbers before a latitude YB at which * = 0 • (d) Refraction into a critical latitude Y CL at which U = 0 • (e) waveguide effect of aKs maximum. (Hoskins e Ambrizzi 1993)

  5. Main teleconnection patterns obtained from observational analysis and numerical modeling - DJF observational analysis numerical modeling (Hoskins e Ambrizzi 1993)

  6. Main teleconnection patterns obtained from observational analysis and numerical modeling - JJA observational analysis numerical modeling (Ambrizzi et al 1995)

  7. DATA AND METHODOLOGY • Climatological Data used : ECMWF/ERA40 – period 1982 – 2001 • ECMWF Coupled GCM – Hindcast Period – 1982 – 2001 – 11 ensemble • members – 6 months forecasting • The seasons are: JFM (Summer), AMJ (Fall), JAS (Winter), • and OND (Spring) • To create the seasonal datasets it was used the third month of each • six months forecasting • Pearson linear correlation was used in some of the analyzes • The basic variables used in this presentation is Zonal (U) and Meridional • Wind (V) • Ray tracing analysis will be presented as well

  8. Mean Seasonal Zonal Wind Cross Section at 50ºS ERA40

  9. Mean Seasonal Zonal Wind Cross Section at 30ºS ERA40

  10. SEASONAL MERIDIONAL WIND BIAS: PREV3 – ERA40 (200 hPa)

  11. BOXES TO BE USED IN THE CORRELATION ANALYSIS

  12. SEASONAL ZONAL WIND BIAS (PREV3-ERA40) AT RS BOX In general the signal of bias is the same for each member ensemble

  13. SEASONAL MERIDIONAL WIND BIAS (PREV3-ERA40) AT RS BOX

  14. TIME SERIES OF THE ZONAL WIND AT RS AND NE (ERA40 and PREV3) PREV3: mean of 11 members Bar: maximum and minimum member value

  15. SUMMER: ZONAL WIND CORRELATION (200 hPa) BETWEEN RS BOX AND ERA40, PREV3, THE WORST AND THE BEST ENSEMBLE MEMBERS 11 ENSEMBLE MEMBERS P R E V 3 E R A 4 0 W O R S T B E S T

  16. SUMMER: MERIDIONAL WIND CORRELATION (200 hPa) BETWEEN RS BOX AND ERA40, PREV3, THE WORST AND THE BEST ENSEMBLE MEMBERS 11 ENSEMBLE MEMBERS W O R S T B E S T

  17. WINTER: ZONAL WIND CORRELATION (200 hPa) BETWEEN RS BOX AND ERA40, PREV3, THE WORST AND THE BEST ENSEMBLE MEMBERS 11 ENSEMBLE MEMBERS W O R S T B E S T

  18. WINTER: MERDIONALWIND CORRELATION (200 hPa) BETWEEN RS BOX AND ERA40, PREV3, THE WORST AND THE BEST ENSEMBLE MEMBERS 11 ENSEMBLE MEMBERS W O R S T B E S T

  19. SUMMER: ZONAL WIND CORRELATION (200 hPa) BETWEEN NE BOX AND ERA40, PREV, THE WORST AND THE BEST ENSEMBLE MEMBERS 11 ENSEMBLE MEMBERS W O R S T B E S T

  20. SUMMER: MERIDIONAL WIND CORRELATION (200 hPa) BETWEEN NE BOX AND ERA40, PREV3, THE WORST AND THE BEST ENSEMBLE MEMBERS W O R S T B E S T

  21. WINTER: ZONAL WIND CORRELATION (200 hPa) BETWEEN NE BOX AND ERA40, PREV3, THE WORST AND THE BEST ENSEMBLE MEMBERS W O R S T B E S T

  22. WINTER: MERIDIONAL WIND CORRELATION (200 hPa) BETWEEN NE BOX AND ERA40, PREV, THE WORST AND THE BEST ENSEMBLE MEMBERS W O R S T B E S T

  23. SEASONAL RAY TRACING ANALYSIS FOR WAVE NUMBER=2 (WN=2) (ERA40 AND ALL 11 MEMBERS)

  24. SEASONAL RAY TRACING ANALYSIS FOR WN=3 (ERA40 AND ALL 11 MEMBERS)

  25. summary • The GCM is not able to correctly represent the position of the maximum and minimum hemispheric zonal wind (large variability among the ensemble members) • There are considerable errors in the amplitudes of the SH Rossby waves reproduced by the ensemble mean, particularly during the summer and spring seasons • The correlation maps suggests that there some ensemble members that reproduce quite well the zonal and meridional wind spatial pattern while there are others that completely fail to do this. • Ray tracing analyzes clearly suggest that the model is not able reproduce the expected wave trajectory because it does not represent the Southern Hemisphere zonal wind variability.

  26. FUTURE WORK • Analyze the seasonal forecasts taking into account the first three months of the integration • Repeat all previous analyzes for the Meteo Office and CPTEC hindcast data. • Select some specific years to analyze the atmospheric circulation over South America in order to determine some dynamical aspects of the model ensemble members and their deviation.

  27. GRUPO DE ESTUDOS CLIMÁTICOS CLIMATE STUDIES GROUP THANK YOU FOR YOUR ATTENTION

More Related