1. Local forcing and intra-seasonal modulation of the South America summer monsoon: Soil moisture, SST and topography Alice Grimm Dept. of Physics - Federal University of Paraná – Brazil Jeremy Pal and Filippo Giorgi International Centre for Theoretical Physics

2. Motivation The summer monsoon season is the peak rainy season in most of South America, and its forecast needs improvement and higher temporal resolution. There are significant intraseasonal changes in the ENSO impacts possibly due to regional processes that overcome remote influences. There is also intraseasonal variability in the same time-scale in non-ENSO years. The mechanisms leading to these intraseasonal changes may involve soil moisture and surface temperature at the beginning of the season, as well as topographic effects, and SST anomalies off the southeast coast of Brazil.

3. Monthly mean precipitation percentiles expected for the indicated month of El Niño events. Shadowed areas have precipitation anomalies consistent over 90% confidence level. Intraseasonal variation of the El Niño impact within the monsoon season (Grimm 2003, J. Climate)

4. Monthly mean precipitation percentiles expected for the indicated month of La Niña events. Shadowed areas have precipitation anomalies consistent over 90% confidence level. Intraseasonal Variation of the La Niña impact within the monsoon season (Grimm 2004, Climate Dynamics)

5. Shadowed areas have temperature anomalies consistent over 90% confidence level. El NiñoLa Niña Surface Temperature anomalies

6. Streamfunction anomalies - spring/summer of El Niño events 200 hPa850 hPa

7. Moisture flux anomalies - spring/summer of El Niño events Moisture fluxMoisture divergence

8. SST Anomalies in spring/summer of El Niño events associated with precipitation in East Brazil Correlation coefficients between January precipitation in the region marked in eastern Brazil and SST in November (left) and in January (right). The correlation in the SACZ is positive in November and negative in January. Shadowed areas have correlation coefficients significant over 95% confidence level.

9. Seasonal runs with RegCM & intraseasonal variations Differences El Niňo - La Niňa: Precipitation

10. Seasonal runs with RegCM & intraseasonal variations Differences El Niňo - La Niňa: 850 hPa wind

11. Seasonal runs & intraseasonal variations Differences El Niňo - La Niňa: Temperature 2m

12. Domain and topography Resolution: 60 km

13. Experiments I Unless stated differently, all experiments use the Grell cumulus scheme w/ F&C closure assumption. 1) CTRL8901 : Experiment for Jan89, w/ default parameters in regcm.in. 2) CTRL9801 : Experiment for Jan98, w/ default parameters in regcm.in. 3) hn_sk02_mcl50_8901 htmin=-9999; htmax=+9999; skbmax=0.2; mincld=50. (Best results). 4) hn_sk02_mcl50_9801 htmin=-9999; htmax=+9999; skbmax=0.2; mincld=50. (Best results). 5) hn_sk02_mcl50_t40_8901 (precipitation much to south). htmin=-9999; htmax=+9999; skbmax=0.2; mincld=50; dtauc=40. 6) hn_sk02_mcl50_t40_9801 (precipitation much to south). htmin=-9999; htmax=+9999; skbmax=0.2; mincld=50; dtauc=40. 7) hsm_sm-_9801 : As in (4), w/ soil moisture*0.5 in East Brazil (10S-24S;38W-48W). 8) hsm_sm+_9801 : As in (4), w/ soil moisture*1.5 in East Brazil. 9) CTRL8901_BM : As in (1), with Betts-Miller scheme (Bad results). 10) hsm_to_9801 : As in (4), w/ topography limited to 400m in East Brazil. 11) hsm_sst+_9801 : As in (4), with SST +1° off SE Brazil coast (16S-24S;30W-48W).

14. Experiments II 12) hsm_sm--_9801 : As in (4), with soil moisture * 0.1 in East Brazil. 13) hsm_to-9801 : As in (4), w/ topography limited to 100 m in East Brazil. 14) sm-_sst+_9801 : As in (4), w/ soil moisture*0.5 in East Brazil plus SST off SE Brazil coast + 1°. 15) sm-_SE_9801 : As in (4), w/ soil moisture*0.5 in southern SE Brazil (17S-24S; 38W-48W). 16) sm-_SEn_9801 : As in (4), w/ soil moisture*0.5 in central-east Brazil (13S-23S; 38W-48W). 17) sm-SE+S_9801 : As in (4), w/ soil moisture*0.5 in northern SE Brazil (13S-23S; 38W-48W), plus soil moisture*1.5 in (23S-33S; 48W-58W). 18) sm-SE+S_SST_9801 : As in (17), w/ SST +1° off SE Brazil coast. 19) sm-_CE_9801 : As in (4), w/ soil moisture *0.5 in northern SE Brazil (10S-18S;38W-48W). 20) sm-_to-9801 : As in (4), w/ soil moisture *0.5 in East Brazil (10S-24S; 38W-48W) plus topography limited to 100m in region (5S-30S; 30W-60W).

15. Sensitivity to Convective Parameters Total Precipitation Fields – Grell + Fritsch-Chappell Control runs (1, 2)Changed Parameters (3,4)Observations

16. Sensitivity to Soil Moisture Soil moisture * 0.5 in East Brazil (Exp. 7) Control run (2)PrecipitationWind&Temp. 850 hPa

17. Sensitivity to Soil Moisture Soil moisture * 1.5 in East Brazil (Exp. 8) Control run (2)PrecipitationWind&Temp. 850 hPa

18. Sensitivity to Soil Moisture and SST Soil moisture * 0.5 in East Brazil & SST + 1° off the SE Brazil coast (Exp. 14) Control run (2)PrecipitationWind&Temp. 850 hPa

19. Sensitivity to Soil Moisture Soil moisture * 0.5 in southern Southeast Brazil (Exp. 15) Control run (2)PrecipitationWind&Temp. 850 hPa

20. Sensitivity to Soil Moisture Soil moisture * 0.5 in northern Southeast Brazil (Exp. 19) Control run (2)PrecipitationWind&Temp. 850 hPa

21. Sensitivity to Soil Moisture and Topography Soil moisture * 0.5 in East Brazil and topography limited to 100m (Exp. 20) Control run (2)PrecipitationWind&Temp. 850 hPa

22. Conclusions  The model is able to reproduce the intraseasonal reversal of the rainfall and wind anomalies in certain regions, mainly in Southeast Brazil, during ENSO events.  The results indicate a significant role of the soil moisture in setting up temperature anomalies and circulation anomalies that might explain the intraseasonal changes reported by Grimm (2003, 2004).  Atlantic SST anomalies, off the southeast coast of Brazil, do also seem to exert influence on regional rainfall.  An interesting effect of the orography in central-east Brazil on the monsoon circulation and precipitation is disclosed by experiments with flat terrain in this region. This is a new aspect, since up to the moment the studies on the influence of orography on the South American climate have been focused on the role of the Andes Mountains.