1 Variability of the South America Monsoon System: The present Climate and projections for a global change scenario Rodrigo J. Bombardi and Leila M. V.

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Presentation transcript:

1 Variability of the South America Monsoon System: The present Climate and projections for a global change scenario Rodrigo J. Bombardi and Leila M. V. Carvalho University of Sao Paulo GEM-Group for Studies in Multi-Scales

2 OBJECTIVES  Investigate the Onset, Duration and total precipitation during the SA Monsoon in coupled IPCC models  Examine the performance of IPCC models in simulating SAMS in the 20 th century climate and projections for future scenarios.  Provide guidance on the use of IPCC models to force regional climate models “Garbage in – Garbage out” (Jeremy Pal)

Models 3 MODELCENTERRESOLUTIONVERTICAL20CMA1BKEY NAME COUNTR YLat x LonLEVELS RUN S REFERENCE CGCM3.1(T63)Canada~ 2.8 x Flato et al. (2000) CSIRO-Mk3.0Australia~ 1.9 x Gordon et al. (2002) CNRM-CM3France~ 2.8 x Salas-M é lia et al (2005) ECHAM5Germany~ 1.9 x Roeckner et al. (2003) FGOALS-g1.0China~ 2.8 x Yu et al. (2004) GFDL-CM2.0USA2.0 x Delworth et al. (2006) GFDL-CM2.1 USA2.0 x Delworth et al. (2006) MIROC3.2(hires) Japan~ x Hasumi and Emori (2006) MIROC3.2(medres) Japan~ 2.8 x Hasumi and Emori (2006) MRI-CGCM2.3.2 Japan~ 2.8 x Yukimoto et al. (2006)

4 Observations Global Precipitation Climatology Project (merge satellite and Stations) Time- resolution: pentads Spatial Resolution: 2.5 x 2.5 (lat,lon)

5 Rn= Pentad Precipitation Liebmann and Marengo 2001 – J. Climate Onset- Demise Methodology

6 Simulation of the 20 th Century Climate

7 Mean Annual Cycle of precipitation GFDL MIROC Western Amazon (70;5.5S) S Amazon (55.0W;10S) NW S. America(72;2.5S)

8 Mean Annual Cycle of precipitation GFDL No variability Amazon Delta (50;0.0S)Cerrado (50;17.5S) Central Amazon(60;5.5 S) SACZ(37.5;30.0 S)

9 Mean DJF Precipitation (solid lines) and Standard Deviation S (shaded) Light gray → 3 mm ≤ S ≤ 5mm Dark gray → S > 5 mm CSIRO-3 -Australia GFDL2.0 - USA GFDL2.1 - USA MIROC-hires - JapanMIROC-medres - Japan GPCP - Observed

10 GPCP - Observed Mean DJF Precipitation (solid lines) and Standard Deviation S (shaded) Light gray → 3 mm ≤ S ≤ 5mm Dark gray → S > 5 mm CGCMT63 - Canada CNRM - France ECHAM5 - Germany FGOALS - China MRI - Japan

11 Median of Onset of the Rainy Season

12 (France) (China) (Australia) (Japan) (Observation) Pentad 60

13 (Observation) (Canada) (USA) (Japan) (Germany) (USA) Pentad 60

14 Onset Variability Defined by the Interquartile Range (IQR)

15 (Observation)(France) (China)(Australia) (Japan) 3-4 Pentads

16 Median of Duration of the Rainy Season

17 36 Pentads (Observation) (Japan) (France) (China) (Canada)

18 36 Pentads (Observation) (Australia) (Japan) (USA) (Germany)

19 Duration Variability Defined by the Interquartile Range (IQR) 5 best simulations (based on the median)

20 4 Pentads (Observation) (Japan) (France) (Australia) (Canada)

21 Median of Total Precipitation During the Rainy Season

22 (Japan) (China) (France)

23 (USA) (Australia) (Canada) (Germany)

24 Total Precipitation Variability Defined by the Interquartile Range (IQR)

25 (Japan) (China) (France) (Observation)

26 Inter-model Variability described by the Standard Deviation of the Ensemble

27

28 Simulation of the 21 th Century Climate (scenario A1B) Difference between Median Monsoon Precipitation 21th - 20 th

29 (Japan) (China) (France)

30 (USA) Echam-5 not included (Australia)

31 CONCLUSIONS Most IPCC models simulate SAMS observed climatological features (ie, median and interquartile range) over central-eastern South America Poor representationPoor representation of the annual cycle of Precipitation is observed over N and W Amazon (stronger ITCZ) Best PerformanceBest Performance of SAMS precipitation Patterns: CNRM (France), FGOALS (China), MIROC3.2-hires e MIROC3.2-mdres (Japan) Worst PerformanceWorst Performance: ECHAM5 (Germany), GFDL2.0, 2.1 (USA) Low Spreadamong model’s simulations (Onset, End, Duration)Low Spread among model’s simulations (Onset, End, Duration) is oberved over central Brazil and High spread is observed over Amazon Low spread among model’s simulations of total PrecipitationLow spread among model’s simulations of total Precipitation is observed over S and SE Brazil and adjascent Atlantic Ocean indicate statistically significant decrease of total precipitation over eastern BrazilMIROC-H and M1, FGOALS, GFDL, indicate statistically significant decrease of total precipitation over eastern Brazil (Cerrado region) for the A1B scenario (~ -100 to -200mm). increase in precipitationCNRM, on the other hand, show increase in precipitation (~ mm) approximately for the same area No statistically significantNo statistically significant differences are observed in any model regarding differences in Onset, Demise and duration of SAMS