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Climate variability in South America: Influence of the SH large-scale conditions

Climate variability in South America: Influence of the SH large-scale conditions. Carolina Vera CIMA-Department of Atmospheric and Ocean Sciences University of Buenos Aires, Buenos Aires, Argentina. The South American Monsoon System.

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Climate variability in South America: Influence of the SH large-scale conditions

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  1. Climate variability in South America: Influence of the SH large-scale conditions Carolina Vera CIMA-Department of Atmospheric and Ocean Sciences University of Buenos Aires, Buenos Aires, Argentina

  2. The South American Monsoon System Climatological seasonal mean precipitation (shaded), & vertically integrated moisture fluxes (arrows) (Vera et al., 2006, J. Climate)

  3. LA PLATA BASIN (LPB) • LPB is one of the largest river basins in the world, drain approximately one-fifth of the South American continent. • LPB is home of more than 100 million people, including the capital cities of 4 of the 5 countries. • Agriculture and Hydroelectric energy production are two of the main activities

  4. Interannual Variability JFM AMJ Year-to-year Seasonal Precipitation Standard Deviation Both ENSO and AAO signature on precipitation variability are largest over La Plata Basin during austral spring JAS OND

  5. ENSO OND (1979-1999) Correlations between ElNino3.4 SST anomalies and (left) precipitation and (right) 500-hPa geopotential height anomalies. Significant values at 90, 95 and 99% are shaded. NCEP reanalysis data. (Vera et al. 2006)

  6. AAO OND (1979-1999) Correlations between AAO index and (left) precipitation and (right) 500-hPa geopotential height anomalies. Significant values at 90, 95 and 99% are shaded. NCEP reanalysis data. (Vera et al. 2006)

  7. Interannual Variability in the La Plata Basin (LPB) Positive OND precipitation anomalies -ENSO warm events -AAO negative phase (1979-1999) LPB Correlations between precipitation anomalies in LPB and (left) SST anomalies and (right) 500-hPa geopotential height anomalies. Significant values at 90, 95 and 99% are shaded. NCEP reanalysis data. (Vera et al. 2006)

  8. AAO variability • Although the AAO is an internal atmospheric mode, tropical SSTs force PSA-like patterns across the Southern Ocean, interfering with the annular-like structure, while extratropical cooler SSTs strengthen the SAM and vice versa (Marshall and Connolley, 2006, GRL). • The connections between ENSO and AAO appear only in the seasons when the ENSO forcing is particularly strong, namely, austral spring and summer (Fogt and Browmich 2006, L´Hereux and Thompson, 2006, JClimate). • Besides the well known trend, AAO exhibits significant variability on • intraseasonal (e.g. Mathews and Meredith, 2004, GRL), • interannual (e.g. Mo 2000, JClimate), and • interdecadal timescales (e.g. Fogt and Browmich 2006, JClimate)

  9. AAO and ENSO Variations AAO mensual (1957-2004) 19571965 1974 1982 1990 2000 19571965 1974 1982 1990 2000

  10. Interdecadal changes in the AAO influence on precipitation interannual variability in La Plata Basin 1983-1999 1957-1982 1957-1999

  11. 1977-1995 1957-1976 Correlations between AAO index and (left) SST anomalies and (right) 500-hPa geopotential height anomalies for OND.

  12. SST´ and z´(500 hPa) NCEP reanalyses

  13. Precipitation anomalies 1982 1994 1982-1994 CMAP

  14. Numerical Simulations 1982-1994 1982- (1982 SSTs, 1994 Boundaries) 500-hPa Geopotential- height anomalies Precipitation anomalies

  15. JFM Precipitation Trends (Liebmann et al. 2004) River stream flow Precipitation SW Atlantic SSTs Normalized annual departures of SALLJ-event annual counts

  16. Climatological seasonal mean precipitation(1970-1999) IPCC-AR4 models

  17. Number of models depicting (1st row) positive changes and (2nd row) negative changes between 2070-2099 (SRESA1B) and 1970-1999 periods. Contour level is 1, values larger than 4 are shaded. Vera et al. (2006, GRL)

  18. 500-hPa geopotential height changes between (2070-2099) and (1970-1999) MPI Model

  19. Year-to-year precipitation variability(1970-1999) from IPCC-AR4 models OND

  20. ENSO signal in SH Circulation anomalies in IPCC models for (1970-1999) OND Correlations between ENSO index and 500-hPa geopotential height anomalies. Significant values at 90, 95 and 99% are shaded.

  21. ENSO signal in South America precipitation anomalies in IPCC models for (1970-1999) OND Correlations between ENSO index and precipitation anomalies. Significant values at 90, 95 and 99% are shaded.

  22. AAO signal in SH circulation anomalies in IPCC models for (1970-1999) OND Correlations between AAO index and 500-hPa geopotential height anomalies. Significant values at 90, 95 and 99% are shaded.

  23. AAO signal in South America precipitation anomalies in IPCC models for (1970-1999) OND Correlations between AAO index and 500-hPa geopotential height anomalies. Significant values at 90, 95 and 99% are shaded.

  24. Precipitation over South America exhibits considerable year-to-year variability. Both ENSO and AAO signature are largest over La Plata Basin during austral spring. • There are considerable decadal changes in the connection between ENSO and AAO, altering the signature on the interannual variability of both the circulation in the SH and the precipitation in South America. • IPCC-AR4 models are able to reproduce in some extent the main features of the precipitation seasonal cycle over South America. There is a generalized consensus among models that the precipitation changes projected are mainly: i) an increase of summer precipitation over southeastern subtropical South America; ii) a reduction of winter precipitation over most of the continent; and iii) reduction of precipitation during the four seasons along the southern Andes. • IPCC-AR4 simulations have serious deficiencies in reproducing the location and intensity of the regions with maximum interannual variability. While a few models are able to reproduce in some extent, the ENSO influence, most of the them are not able to reproduce the AAO signature on precipitation interannual variability in South America. Concluding Remarks

  25. Data and Methodology • IPCC-AR4 20c3m runs were used for the period 1970-1999 • Anomalies were defined removing the seasonal cycle and the long-term trend. • EOFs, correlation and regression maps were based on monthly mean anomalies and calculatedd over the whole year. • They were computed per individual run and then the results were averaged over all the runs available for each model.

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