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DANIEL ALLASIA and CINTIA BERTACCHI UVO

CLIMATIC INFLUENCE ON RIVER VARIABILITY DANIEL ALLASIA and CINTIA BERTACCHI UVO F R O M INSTITUTE FOR HYDRAULICS RESEARCH AND L U N D U N I V E R S I T Y. DANIEL ALLASIA and CINTIA BERTACCHI UVO.

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DANIEL ALLASIA and CINTIA BERTACCHI UVO

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  1. CLIMATIC INFLUENCE ON RIVER VARIABILITYDANIEL ALLASIAand CINTIA BERTACCHI UVO FROM INSTITUTE FOR HYDRAULICS RESEARCH ANDLUNDUNIVERSITY

  2. DANIEL ALLASIA and CINTIA BERTACCHI UVO CLIMATIC INFLUENCE ON RIVER VARIABILITYINSTITUTE FOR HYDRAULICS RESEARCH AND L U N D U N I V E R S I T Y

  3. River Basin • Upper Paraguay River basin • Memory

  4. River Data – standardized annual average • River level at Ladário - green • Mean Annual Discharge • Porto Murtinho • Cuiabá

  5. SAM – Southern Annular Mode (Thompson and Solomon, 2002) PDO – Pacific Decadal Oscillation (Mantua et al., 1997) NAO – North Atlantic Oscillation (Hurrell et al., 2002) ENSO – El Niño – Southern Oscillation (NINO3.4) Climate indicators

  6. Indices

  7. Principal Components

  8. Monthly level forecast: Ladário

  9. Monthly level forecast: Ladário o forecast level with climate index + forecast level without climate index ---- observed level

  10. Monthly anomalous composites for circulation and precipitable water from NCEP Reanalysis SAM – ENSO effect extracted. NAO ENSO PDO -1std > SAM -1std < SAM < 1std SAM > 1std Composites

  11. Composite – January SAM > 1 std

  12. Composites – February SAM < -1std

  13. Composites - February • SAM < -1std SAM > 1std

  14. Anomalous composite: precipitable water • December NAO>1std January

  15. Anomalous composite: precipitable water • February • NAO < -1std

  16. Standardize levels at Ladário and PDO _ + +

  17. Effect of climate phenomena on river level at Ladário

  18. Relation to North Atlantic SST

  19. Conclusions: Climate Phenomena • ENSO and NAO affects the Ladário level by monitoring the North Atlantic SST • SAM affects Ladário level by monitoring the circulation • PDO – long term signal influenced by the other phenomena.

  20. Conclusions: Statistical Modelling • Linear regression capture the relationship with SAM • Non-linear methods could better represent the non-linear relations among the other climate phenomena.

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