1 / 22

Alice Grimm Dept. of Physics - Federal University of Paraná – Brazil Jeremy Pal and Filippo Giorgi

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

ghalib
Télécharger la présentation

Alice Grimm Dept. of Physics - Federal University of Paraná – Brazil Jeremy Pal and Filippo Giorgi

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

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

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

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

  6. Streamfunction anomalies - spring/summer of El Niño events 200 hPa 850 hPa

  7. Moisture flux anomalies - spring/summer of El Niño events Moisture flux Moisture 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 variationsDifferences El Niňo - La Niňa: Precipitation

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

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

  12. Domain and topography Resolution: 60 km

  13. Experiments IUnless 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 ParametersTotal Precipitation Fields – Grell + Fritsch-Chappell Control runs (1, 2) Changed Parameters (3,4) Observations

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

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

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

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

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

  22. Conclusions • The model is able to reproduce the intraseasonalreversal 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.

More Related