1 / 30

Teleconnection Patterns and Seasonal Climate Prediction over South America The Final Chapter???

Teleconnection Patterns and Seasonal Climate Prediction over South America The Final Chapter???. Tércio Ambrizzi and Rosmeri P. da Rocha University of São Paulo, São Paulo, Brazil. EUROBRISA 2010 – Barcelona, Spain. OBJECTIVE.

yelena
Download Presentation

Teleconnection Patterns and Seasonal Climate Prediction over South America The Final Chapter???

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. Teleconnection Patterns and Seasonal Climate Prediction over South America The Final Chapter??? Tércio Ambrizzi and Rosmeri P. da Rocha University of São Paulo, São Paulo, Brazil EUROBRISA 2010 – Barcelona, Spain

  2. OBJECTIVE To analyze in detail 21 years of ECWMF seasonal forecast simulations using basic statistical methods and particularly the linear wave theory, in order to evaluate the seasonal forecast skill and its useful value

  3. (1/3º x 1/3º and 0,83º lat x 1,25º lon) (1º x 1º and 1,25º lat x 1,825º lon) (Dawson et al 2010 – CD)

  4. 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: DJF (Summer), MAM (Fall), JJA (Winter), • and SON (Spring) • To create the seasonal datasets it was used the third month of each • six months forecasting (PREV3) and three months seasonal forecasting (3MES) • 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

  5. PREV3 Autum 3MES Winter Spring Summer

  6. REGIONS WHERE THE MODEL WILL BE VALIDATED CONSIDERING THE 3MES AND PREV3

  7. Zonal and Meridional Seasonal Wind at 200 hPa for ERA 40 and 3MES inside the previous four regions ND ND Model superstimate the zonal wind and understimate the meridional wind CO CO SD SD RS RS

  8. TOTAL AMPLITUDE OF U AND V WIND FOR EACH ENSEMBLE MEMBER AND EACH FORECASTING MONTH (RS BOX) U (200 hPa) V (200 hPa) U (850 hPa) V (850 hPa)

  9. ZONAL AND MERIDIONAL WIND ERRORS FOR THE SUMMER MERIDIONAL WIND ZONAL WIND ND ND CO CO SD SD RS RS

  10. ZONAL AND MERIDIONAL WIND ERRORS FOR WINTER ZONAL WIND MERIDIONAL WIND ND ND CO CO SD SD RS RS

  11. ZONAL WINDA COMPOSITES FOR DJF AND JJA (200 hPa – m/s) JJA DJF ERA40 PREV3 3MES

  12. ZONAL WIND CROSS SECTION AT 30o AND 50oS FOR 3MES AND DJF - JJA (m/s) DJF JJA 30oS 50oS

  13. LATITUDINAL MEAN SEASONAL ZONAL WIND at 200 hPa - (m/s) MAM DJF JJA SON

  14. ZONAL WIND ERRORS PREV3/3MES – ERA40 JJA DJF PREV3 3MES

  15. STATIONARY WAVENUMBER (Ks) - DJF Ks Meridional cross section ERA40 120oE 120oW 3MES 65oW

  16. STATIONARY WAVENUMBER (Ks) - JJA Ks Meridional cross section ERA40 120oE 180o 3MES 65oW

  17. SEASONAL RAY TRACING ANALYSIS FOR WAVE NUMBERS=2 and 3 (WN=2-3) (ERA40 AND ALL 11 MEMBERS) WN2 WN3 DJF MAM JJA SON

  18. PRECIPITATION MODEL’S BEHAVIOUR

  19. SUMMER PRECIPITATION COMPARISON BETWEEN CMAP AND ERA40 CMAP ERA40 - CMAP ERA40

  20. WINTER PRECIPITATION COMPARISON BETWEEN CMAP AND ERA40 CMAP ERA40 - CMAP ERA40

  21. SEASONAL ZONAL MEAN PRECIPITATION (mm/day) CMAP DJF MODEL MAM SON JJA

  22. SEASONAL PRECIPITATION COMPARISON BETWEEN CMAP AND MODEL FOR THE NORTHEAST BRAZIL“ND” CMAP Model El Niño years DJF MAM JJA SON

  23. SEASONAL PRECIPITATION ANOMALIES IN THE NORTHEAST BRAZIL BOX (ND) – ALL ENSEMBLE MEMBERS MAM DJF SON JJA

  24. SEASONAL PRECIPITATION COMPARISON BETWEEN CMAP AND MODEL AND SEASONAL PRECIPITATION ANOMALIES IN THE CENTER WEST BRAZILIAN BOX (CO) – ALL ENSEMBLE MEMBERS DJF MAM SON JJA

  25. SEASONAL PRECIPITATION COMPARISON BETWEEN CMAP AND MODEL AND SEASONAL PRECIPITATION ANOMALIES IN THE SOUTHEAST BOX (SD) – ALL ENSEMBLE MEMBERS DJF MAM SON JJA

  26. SEASONAL PRECIPITATION COMPARISON BETWEEN CMAP AND MODEL AND SEASONAL PRECIPITATION ANOMALIES IN THE SOUTH BOX (RS) – ALL ENSEMBLE MEMBERS El Niño DJF MAM SON JJA

  27. 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 zonal and meridional wind over different regions of South America. • The precipitation is overestimated in the hemispheric analysis but the model underestimate it in the different regions over South America. • 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. Bigger wavenumber larger variability among the trajectories.

  28. IS THIS THE END??

  29. FUTURE WORK • 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. We have to look more careful at ENSO years • A Scientific paper is underway containing the main results of the first part of this work • One M.Sc. Dissertation was concluded and the work was presented in some international conferences.

  30. GRUPO DE ESTUDOS CLIMÁTICOS CLIMATE STUDIES GROUP THANK YOU FOR YOUR ATTENTION AND TO EUROBRISA FOR THE OPPORTUNITY TO WORK IN THIS PROJECT

More Related