Based on a daily precipitation observation dataset of 743 stations in China from 1951 2004, the F distribution function is used to calculate the probability distribution of daily precipitation and to define extreme pr...Based on a daily precipitation observation dataset of 743 stations in China from 1951 2004, the F distribution function is used to calculate the probability distribution of daily precipitation and to define extreme precipitation events. Based on this, the relationship of ENSO and the frequency of extreme precipitation events is studied. Results reveal that ENSO events have impact on extreme precipitation events, with different magnitudes at different regions and seasons. In general, during winter and spring, extreme precipitation events occur more often during E1 Nino events than during La Nina events. While during summer and autumn, the opposite is found. The relationship of a two season-lag ENSO and extreme precipitation frequency shows different pattern. Extreme precipitation events occur more often in several regions if an ENSO warm phase happened in the central-eastern tropical Pacific two seasons before. No similar impacts of El Nino and La Nina on the frequency of extreme precipitation events are found.展开更多
Using the sea surface temperature （SST） predicted for the equatorial Pacific Ocean by the Flexible Global Ocean-Atmosphere-Land System Model-gamil （FGOALS-g）, an analysis of the prediction errors was performed for...Using the sea surface temperature （SST） predicted for the equatorial Pacific Ocean by the Flexible Global Ocean-Atmosphere-Land System Model-gamil （FGOALS-g）, an analysis of the prediction errors was performed for the seasonally dependent predictability of SST anomalies both for neutral years and for the growth/decay phase of El Nino/La Nina events. The study results indicated that for the SST predictions relating to the growth phase and the decay phase of El Nino events, the prediction errors have a seasonally dependent evolution. The largest increase in errors occurred in the spring season, which indicates that a prominent spring predictability barrier （SPB） occurs during an El Nino-Southern Oscillation （ENSO） warming episode. Furthermore, the SPB associated with the growth-phase prediction is more prominent than that associated with the decay-phase prediction. However, for the neutral years and for the growth and decay phases of La Nifia events, the SPB phenomenon was less prominent. These results indicate that the SPB phenomenon depends extensively on the ENSO events themselves. In particular, the SPB depends on the phases of the ENSO events. These results may provide useful knowledge for improving ENSO forecasting.展开更多
The historical data of phytoplankton and chlorophyll a(Chl a)(1990–2002)obtained during the Chinese National Antarctic Research Expedition(CHINARE)in the Prydz Bay have been integrated.The results showed that the tem...The historical data of phytoplankton and chlorophyll a(Chl a)(1990–2002)obtained during the Chinese National Antarctic Research Expedition(CHINARE)in the Prydz Bay have been integrated.The results showed that the temperature,salinity,nutrients,and oxygen of seawater changed when El Nino/La Nina occurred.The variation of biological communities reflected the response of ecosystem to environmental changes.During El Ni?o period,Chl a concentration and phytoplankton community structure changed significantly,and the relative proportion of diatoms increased while dinoflagellates decreased.During La Ni?a period,the proportion of diatoms decreased,but the golden-brown algae and blue-green algae increased significantly.The variation of phytoplankton population directly affected the biodiversity of the bay,which were also quite sensitive to the marine environment changes.Meanwhile,the satellite remote sensing data of 2002–2011(December–March)have been used to study the temporal connection change of Chl a and phytoplankton in the Prydz Bay.We found that there were significant differences in the monthly variation characteristics of satellite remote sensing Chl a and sea surface temperature(SST),which had some links with sea ice melting and El Ni?o/La Ni?a events.We found that the start time of bloom advanced,lagged or synchronized with the changes of the SST,and we also found the occurrence time of phytoplankton bloom corresponded with the sea ice melting inner bay.To some extent,this study will help us understand the relationships between ENSO events and the phytoplankton bloom in the Southern Ocean.展开更多
基金supported by the program under Grant No.2007BAC29B04
文摘Based on a daily precipitation observation dataset of 743 stations in China from 1951 2004, the F distribution function is used to calculate the probability distribution of daily precipitation and to define extreme precipitation events. Based on this, the relationship of ENSO and the frequency of extreme precipitation events is studied. Results reveal that ENSO events have impact on extreme precipitation events, with different magnitudes at different regions and seasons. In general, during winter and spring, extreme precipitation events occur more often during E1 Nino events than during La Nina events. While during summer and autumn, the opposite is found. The relationship of a two season-lag ENSO and extreme precipitation frequency shows different pattern. Extreme precipitation events occur more often in several regions if an ENSO warm phase happened in the central-eastern tropical Pacific two seasons before. No similar impacts of El Nino and La Nina on the frequency of extreme precipitation events are found.
基金sponsored by the Knowledge Innovation Programof the Chinese Academy of Sciences (Grant No. KZCX2-YW-QN203)the National Basic Research Program of China (GrantNos. 2010CB950400 and 2007CB411800)
文摘Using the sea surface temperature （SST） predicted for the equatorial Pacific Ocean by the Flexible Global Ocean-Atmosphere-Land System Model-gamil （FGOALS-g）, an analysis of the prediction errors was performed for the seasonally dependent predictability of SST anomalies both for neutral years and for the growth/decay phase of El Nino/La Nina events. The study results indicated that for the SST predictions relating to the growth phase and the decay phase of El Nino events, the prediction errors have a seasonally dependent evolution. The largest increase in errors occurred in the spring season, which indicates that a prominent spring predictability barrier （SPB） occurs during an El Nino-Southern Oscillation （ENSO） warming episode. Furthermore, the SPB associated with the growth-phase prediction is more prominent than that associated with the decay-phase prediction. However, for the neutral years and for the growth and decay phases of La Nifia events, the SPB phenomenon was less prominent. These results indicate that the SPB phenomenon depends extensively on the ENSO events themselves. In particular, the SPB depends on the phases of the ENSO events. These results may provide useful knowledge for improving ENSO forecasting.
基金supported by the National Natural Science Foundation of China(Grant Nos.40876104,41076134,41306202,and 41376193)the Scientific Research Fund of the Second Institute,SOA(Grant Nos.JT1208,JG1217 and JG1218)
文摘The historical data of phytoplankton and chlorophyll a(Chl a)(1990–2002)obtained during the Chinese National Antarctic Research Expedition(CHINARE)in the Prydz Bay have been integrated.The results showed that the temperature,salinity,nutrients,and oxygen of seawater changed when El Nino/La Nina occurred.The variation of biological communities reflected the response of ecosystem to environmental changes.During El Ni?o period,Chl a concentration and phytoplankton community structure changed significantly,and the relative proportion of diatoms increased while dinoflagellates decreased.During La Ni?a period,the proportion of diatoms decreased,but the golden-brown algae and blue-green algae increased significantly.The variation of phytoplankton population directly affected the biodiversity of the bay,which were also quite sensitive to the marine environment changes.Meanwhile,the satellite remote sensing data of 2002–2011(December–March)have been used to study the temporal connection change of Chl a and phytoplankton in the Prydz Bay.We found that there were significant differences in the monthly variation characteristics of satellite remote sensing Chl a and sea surface temperature(SST),which had some links with sea ice melting and El Ni?o/La Ni?a events.We found that the start time of bloom advanced,lagged or synchronized with the changes of the SST,and we also found the occurrence time of phytoplankton bloom corresponded with the sea ice melting inner bay.To some extent,this study will help us understand the relationships between ENSO events and the phytoplankton bloom in the Southern Ocean.
