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Understanding Eastern Africa Rainfall Variability and Change (Towards Improved Prediction of Seasonal Precipitation) Brant Liebmann University of Colorado,

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Presentation on theme: "Understanding Eastern Africa Rainfall Variability and Change (Towards Improved Prediction of Seasonal Precipitation) Brant Liebmann University of Colorado,"— Presentation transcript:

1 Understanding Eastern Africa Rainfall Variability and Change (Towards Improved Prediction of Seasonal Precipitation) Brant Liebmann University of Colorado, Boulder, Colorado, USA Chris Funk U.S. Geological Survey, Sioux Falls, South Dakota, USA Martin Hoerling, Randall Dole NOAA, Boulder, Colorado, USA Ileana Bladé University of Barcelona, Barcelona, Spain

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3 Model: ECHAM5 Atmospheric Model (Roeckner et al. 2006) ~ 0.75-degree resolution (T159) 40-member ensemble Run with Specified Sea Surface Temperatures

4 Period of Study: 1979-2012

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6 “Change” = Trend (mm/yr) * length of record (34 years)

7 Seasonal Horn Precipitation Change

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9 October - December Trend removed

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11 Sign of Eastern Pacific SSTs correctly predicts Horn precipitation in 76.5% of years Ensemble Average

12 March - May

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14 Gradient in SST produces Low-level convergence over Indonesia Enhanced convection over Indonesia Upper-level outflow (westward shift of ‘Walker’ circulation) Enhanced subsidence over East Africa

15 Percent correct prediction of observed Horn precipitation based on sign of model Indonesia precipitation Ensemble Average

16 40-member ensemble of ECHAM 5 atmospheric Model run with specified SST s The interannual anomaly of October-December Horn precipitation is well-simulated by the model ensemble-average, although knowing SSTs in the east Pacific gives almost as good a result The ensemble-average correctly predicts the sign of precipitation anomaly in March-May in two-thirds of years (mostly from precipitation over Indonesia) Model simulates observed change of 1979-2012 Horn precipitation for both March-May (decrease) and October-December (increase)


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