摘要
The authors analyze climate extremes indices (CEI) of rainfall over the largest basins of the Brazilian territory: Amazon (AMA), S?o Francisco (SF), Tocantins (TO) and Paraná (PAR) rivers. The CEI represent the frequency of heavy precipitation events (R30mm and R95p) and short duration extreme rainfall (RX5day and RX1day). Droughts (CDDd) are identified based on two indicators: The longest dry period (CDD) and the annual cycle. The results demonstrate that CDDd, RX1day and RX5day occurred with more frequency and intensity in SF basin during El Ni?o events. CDDd was of greater magnitude in the TO basin during La Ni?a events, while an increase of RX1day occurred in El Ni?o. The strong El Ni?o events (1983 and 1997) caused more intense and frequent RX1day and R30mm over the PAR basin. Amazon droughts occurred in two out of the six El Ni?o events. Moreover, the relationship between the positive (negative) sea superficial temperatures anomalies in North (South) Tropical Atlantic and drought in AMA basin was corroborated. A gradual warming of SST was observed at the start of 2003 until it achieved a maximum in 2005 associated with the southwestern Amazon drought. The second highest anomaly of SST was in 2010 linked with drought that was more spatially extensive than the 2005 drought. The spatial distribution of annual trends showed a significant increase of CDD in south-eastern AMA, Upper SF, northern PAR and throughout the TO basins. R20mm, RX1day and RX5day tend to increase significantly in southwestern (northeast) PAR (AMA) and northwestern TO basins. Comparisons between CEI derived from daily precipitation data from Climate Prediction Center (CPCp) and of the ETA_HadCM3 model showed that the model overestimated RX1day, RX5day and CDD, in the four basins. Future scenarios show that dry periods will occur with greatest magnitude in all the basins until 2071-2099 time slice, while RX1day will be more intense in the TO and SF basins.
The authors analyze climate extremes indices (CEI) of rainfall over the largest basins of the Brazilian territory: Amazon (AMA), S?o Francisco (SF), Tocantins (TO) and Paraná (PAR) rivers. The CEI represent the frequency of heavy precipitation events (R30mm and R95p) and short duration extreme rainfall (RX5day and RX1day). Droughts (CDDd) are identified based on two indicators: The longest dry period (CDD) and the annual cycle. The results demonstrate that CDDd, RX1day and RX5day occurred with more frequency and intensity in SF basin during El Ni?o events. CDDd was of greater magnitude in the TO basin during La Ni?a events, while an increase of RX1day occurred in El Ni?o. The strong El Ni?o events (1983 and 1997) caused more intense and frequent RX1day and R30mm over the PAR basin. Amazon droughts occurred in two out of the six El Ni?o events. Moreover, the relationship between the positive (negative) sea superficial temperatures anomalies in North (South) Tropical Atlantic and drought in AMA basin was corroborated. A gradual warming of SST was observed at the start of 2003 until it achieved a maximum in 2005 associated with the southwestern Amazon drought. The second highest anomaly of SST was in 2010 linked with drought that was more spatially extensive than the 2005 drought. The spatial distribution of annual trends showed a significant increase of CDD in south-eastern AMA, Upper SF, northern PAR and throughout the TO basins. R20mm, RX1day and RX5day tend to increase significantly in southwestern (northeast) PAR (AMA) and northwestern TO basins. Comparisons between CEI derived from daily precipitation data from Climate Prediction Center (CPCp) and of the ETA_HadCM3 model showed that the model overestimated RX1day, RX5day and CDD, in the four basins. Future scenarios show that dry periods will occur with greatest magnitude in all the basins until 2071-2099 time slice, while RX1day will be more intense in the TO and SF basins.
基金
funding from the projects Rede CLIMA,the National Institute of Science and Technology for Climate Change(INCTCC),from the FAPESP—Assessment of Impacts and Vulnerability to Climate Change in Brazil and strategies for Adaptation options project(Ref.2008/58161-1).
