Applying the empirical orthogonal function (EOF) analysis to the sea surface temperature (SST) field of the tropical Pacific and Indian Oceans for determination of the first eigenvector field, the current work reveals...Applying the empirical orthogonal function (EOF) analysis to the sea surface temperature (SST) field of the tropical Pacific and Indian Oceans for determination of the first eigenvector field, the current work reveals that there are significant zonal gradients of SST in all seasons of the year in the northwestern and eastern Indian Ocean and equatorial central and eastern Pacific and western Pacific. It is also found that the variance contribution rates of the first EOF mode of every season is more than 33%. This shows that this kind of spatial distribution of the SST is stable. This pattern is named Pacific-Indian Oceans SSTA mode. Through careful analysis and comparison, an index of the mode was defined.展开更多
The work is a general survey using SSTA data of the Indian Ocean and of precipitation at 160Chinese weather stations over 1951～1997 (47 years). It reveals that the dipole oscillation of SST, especially the dipole ind...The work is a general survey using SSTA data of the Indian Ocean and of precipitation at 160Chinese weather stations over 1951～1997 (47 years). It reveals that the dipole oscillation of SST, especially the dipole index of March～May, in the eastern and western parts of the ocean correlates well with the precipitation during the June～August raining season in China. As shown in analysis of 500-hPa Northern Hemisphere geopotential height height by NCEP for 1958～1995, the Indian Ocean dipole index (IODI) is closely related with geopotential height anomalies in the middle- and higher- latitudes in the Eurasian region. As a negative phase year of IODI corresponds to significant Pacific-Japan (P J) wavetrain, it is highly likely that the SST for the dipole may affect the precipitation in China through the wavetrain. Additionally, correlation analysis of links between SST dipole index of the Indian Ocean region and air temperature in China also shows good correlation between the former and wintertime temperature in southern China.展开更多
Aim to linking the variability of drought in northwest China to the oceanic influence of North Atlantic SSTs at the background of global warming and at the regional climate change shifting stages, year aridity index v...Aim to linking the variability of drought in northwest China to the oceanic influence of North Atlantic SSTs at the background of global warming and at the regional climate change shifting stages, year aridity index variations in northwest China and summer North Atlantic sea surface temperature （SST） variations are examined for the 44 a period of 1961-2004 using singular value decomposition （SVD） analysis. Results show that the SST anomalies （SSTA）in the North Atlantic in summer reflected three basic models. The first SVD mode of SST pattern shows a dipole - like variation with the positive center located at southwest and negative center at northeast of extratropical North Atlantic. And it strongly relates to the positive trend in AI variation in northwest China. The second coupled modes display the coherent positive anomalies in extratropical North Atlantic SST and the marked opposite trend of AI variability between north and south of Xinjiang. In addition, the lag correlation analysis of the first mode of SSTA and geopotential heights at 500 hPa variations also shows that the indication of the former influencing the latter configuration, which result in higher air temperature and less precipitation when the SSTA in the North Atlantic Ocean in summer motivated Eurasian circulation of EA pattern, further to influence the wet - dry variations in northwest China by the ocean-to - atmosphere forcing.展开更多
Based on an empirical orthogonal function (EOF) analysis of the monthly NCEP Optimum Interpolation Sea Surface Temperature (OISST) data in the South China Sea (SCS) after removing the climatological mean and trends of...Based on an empirical orthogonal function (EOF) analysis of the monthly NCEP Optimum Interpolation Sea Surface Temperature (OISST) data in the South China Sea (SCS) after removing the climatological mean and trends of SST,over the period of January 1982 to October 2003,the corresponding TCF correlates best with the Dipole Mode Index (DMI),Nio1+2,Nio3.4,Nio3,and Nio4 indices with time lags of 10,3,6,5,and 6 months,respectively.Thus,a statistical hindcasts in the prediction model are based on a canonical correlation analysis (CCA) model using the above indices as predictors spanning from 1993/1994 to 2003/2004 with a 1-12 month lead time after the canonical variants are calculated,using data from the training periods from January 1982 to December1992.The forecast model is successful and steady when the lead times are 1-12 months.The SCS warm event in 1998 was successfully predicted with lead times from 1-12 months irrespective of the strength or time extent.The prediction ability for SSTA is lower during weak ENSO years,in which other local factors should be also considered as local effects play a relatively important role in these years.We designed the two forecast models:one using both DMI and Nio indices and the other using only Nio indices without DMI,and compared the forecast accuracies of the two cases.The spatial distributions of forecast accuracies show different confidence areas.By turning off the DMI,the forecast accuracy is lower in the coastal areas off the Philippines in the SCS,suggesting some teleconnection may occur with the Indian Ocean in this area.The highest forecast accuracies occur when the forecast interval is five months long without using the DMI,while using both of Nio indices and DMI,the highest accuracies occur when the forecast interval time is eight months,suggesting that the Nio indices dominate the interannual variability of SST anomalies in the SCS.Meanwhile the forecast accuracy is evaluated over an independent test period of more than 11 years (1993/94 to October 2004) by comparing the model performance with a simple prediction strategy involving the persistence of sea surface temperature anomalies over a 1-12 month lead time (the persisted prediction).Predictions based on the CCA model show a significant improvement over the persisted prediction,especially with an increased lead time (longer than 3 months).The forecast model performs steadily and the forecast accuracy,i.e.,the correlation coefficients between the observed and predicted SSTA in the SCS are about 0.5 in most middle and southern SCS areas,when the thresholds are greater than the 95% confidence level.For all 1 to 12 month lead time forecasts,the root mean square errors have a standard deviation of about 0.2.The seasonal differences in the prediction performance for the 1-12 month lead time are also examined.展开更多
By using the monthly average dataset of NCEP/NCAR reanalysis and the monthly average ocean temperature data of NOAA satellite center,we analyzed and probed into the relationship between Siberian high anomaly and SSTA,...By using the monthly average dataset of NCEP/NCAR reanalysis and the monthly average ocean temperature data of NOAA satellite center,we analyzed and probed into the relationship between Siberian high anomaly and SSTA,and found that the sea area anomaly is a bigger area,which have greater effect on the variation of Siberian high.The results indicated that there was a wonderful contemporaneously correlation between the area and intensity index of Siberian high and ocean temperature.The correlation type of the synchronous correlative areas between the central intensity index of Siberian high and ocean temperature have structural similarities with the correlative field's structure of area index,but the positive correlative regions expanded,and the intensity of negative correlative regions weakened significantly.The correlation among the area index of Siberian high and the central intensity index,as well as the ocean temperature anomaly of the North Atlantic during spring,autumn and summer of the same year was remarkable.The area index and the central intensity index of Siberian high anomaly have obvious correlation with the ocean temperature anomaly of Southwest Atlantic Ocean during spring,summer and autumn,however,they have apparent seasonal differences with the prominent negative correlative areas of subtropical South Indian Ocean and tropical South Pacific Ocean as well as Southwest Atlantic Ocean.The correlative index of area anomaly is greater than those of intensity anomaly.Larger impact on the variability of Siberian high anomaly are the SSTA of subtropical South Indian Ocean,mid and high latitudes of North Pacific Ocean,North Atlantic,tropical South Pacific Ocean,Southwest Atlantic Ocean,etc.several areas.展开更多
基金The research on the variation of southeast Asian monsoons and their effect on the wetness inYunnan and neighboring areas - a national foundation project (40365001)
文摘Applying the empirical orthogonal function (EOF) analysis to the sea surface temperature (SST) field of the tropical Pacific and Indian Oceans for determination of the first eigenvector field, the current work reveals that there are significant zonal gradients of SST in all seasons of the year in the northwestern and eastern Indian Ocean and equatorial central and eastern Pacific and western Pacific. It is also found that the variance contribution rates of the first EOF mode of every season is more than 33%. This shows that this kind of spatial distribution of the SST is stable. This pattern is named Pacific-Indian Oceans SSTA mode. Through careful analysis and comparison, an index of the mode was defined.
基金Research on the Mechanism and Prediction of Major Climatic Calamities in China a national key program for developing basic science (G199804090303) Science Foundation of Yunnan (97D022G)
文摘The work is a general survey using SSTA data of the Indian Ocean and of precipitation at 160Chinese weather stations over 1951～1997 (47 years). It reveals that the dipole oscillation of SST, especially the dipole index of March～May, in the eastern and western parts of the ocean correlates well with the precipitation during the June～August raining season in China. As shown in analysis of 500-hPa Northern Hemisphere geopotential height height by NCEP for 1958～1995, the Indian Ocean dipole index (IODI) is closely related with geopotential height anomalies in the middle- and higher- latitudes in the Eurasian region. As a negative phase year of IODI corresponds to significant Pacific-Japan (P J) wavetrain, it is highly likely that the SST for the dipole may affect the precipitation in China through the wavetrain. Additionally, correlation analysis of links between SST dipole index of the Indian Ocean region and air temperature in China also shows good correlation between the former and wintertime temperature in southern China.
基金The National Natural Science Foundation of China under contract No.904110017
文摘Aim to linking the variability of drought in northwest China to the oceanic influence of North Atlantic SSTs at the background of global warming and at the regional climate change shifting stages, year aridity index variations in northwest China and summer North Atlantic sea surface temperature （SST） variations are examined for the 44 a period of 1961-2004 using singular value decomposition （SVD） analysis. Results show that the SST anomalies （SSTA）in the North Atlantic in summer reflected three basic models. The first SVD mode of SST pattern shows a dipole - like variation with the positive center located at southwest and negative center at northeast of extratropical North Atlantic. And it strongly relates to the positive trend in AI variation in northwest China. The second coupled modes display the coherent positive anomalies in extratropical North Atlantic SST and the marked opposite trend of AI variability between north and south of Xinjiang. In addition, the lag correlation analysis of the first mode of SSTA and geopotential heights at 500 hPa variations also shows that the indication of the former influencing the latter configuration, which result in higher air temperature and less precipitation when the SSTA in the North Atlantic Ocean in summer motivated Eurasian circulation of EA pattern, further to influence the wet - dry variations in northwest China by the ocean-to - atmosphere forcing.
基金Supported by National Natural Science Foundation of China (No. 40706011)the Key Program of Knowledge Innovation Project of Chinese Academy of Sciences (No. KZCX1-YW-12)+2 种基金the National Science Foundation of China (Nos. 405201 and 40074)the International Cooperative Program of the Ministry of Science and Technology (No. 2006DFB21630)by the Open Foundation of Key Laboratory of Marine Science and Numerical Modeling (MASNUM)
文摘Based on an empirical orthogonal function (EOF) analysis of the monthly NCEP Optimum Interpolation Sea Surface Temperature (OISST) data in the South China Sea (SCS) after removing the climatological mean and trends of SST,over the period of January 1982 to October 2003,the corresponding TCF correlates best with the Dipole Mode Index (DMI),Nio1+2,Nio3.4,Nio3,and Nio4 indices with time lags of 10,3,6,5,and 6 months,respectively.Thus,a statistical hindcasts in the prediction model are based on a canonical correlation analysis (CCA) model using the above indices as predictors spanning from 1993/1994 to 2003/2004 with a 1-12 month lead time after the canonical variants are calculated,using data from the training periods from January 1982 to December1992.The forecast model is successful and steady when the lead times are 1-12 months.The SCS warm event in 1998 was successfully predicted with lead times from 1-12 months irrespective of the strength or time extent.The prediction ability for SSTA is lower during weak ENSO years,in which other local factors should be also considered as local effects play a relatively important role in these years.We designed the two forecast models:one using both DMI and Nio indices and the other using only Nio indices without DMI,and compared the forecast accuracies of the two cases.The spatial distributions of forecast accuracies show different confidence areas.By turning off the DMI,the forecast accuracy is lower in the coastal areas off the Philippines in the SCS,suggesting some teleconnection may occur with the Indian Ocean in this area.The highest forecast accuracies occur when the forecast interval is five months long without using the DMI,while using both of Nio indices and DMI,the highest accuracies occur when the forecast interval time is eight months,suggesting that the Nio indices dominate the interannual variability of SST anomalies in the SCS.Meanwhile the forecast accuracy is evaluated over an independent test period of more than 11 years (1993/94 to October 2004) by comparing the model performance with a simple prediction strategy involving the persistence of sea surface temperature anomalies over a 1-12 month lead time (the persisted prediction).Predictions based on the CCA model show a significant improvement over the persisted prediction,especially with an increased lead time (longer than 3 months).The forecast model performs steadily and the forecast accuracy,i.e.,the correlation coefficients between the observed and predicted SSTA in the SCS are about 0.5 in most middle and southern SCS areas,when the thresholds are greater than the 95% confidence level.For all 1 to 12 month lead time forecasts,the root mean square errors have a standard deviation of about 0.2.The seasonal differences in the prediction performance for the 1-12 month lead time are also examined.
文摘By using the monthly average dataset of NCEP/NCAR reanalysis and the monthly average ocean temperature data of NOAA satellite center,we analyzed and probed into the relationship between Siberian high anomaly and SSTA,and found that the sea area anomaly is a bigger area,which have greater effect on the variation of Siberian high.The results indicated that there was a wonderful contemporaneously correlation between the area and intensity index of Siberian high and ocean temperature.The correlation type of the synchronous correlative areas between the central intensity index of Siberian high and ocean temperature have structural similarities with the correlative field's structure of area index,but the positive correlative regions expanded,and the intensity of negative correlative regions weakened significantly.The correlation among the area index of Siberian high and the central intensity index,as well as the ocean temperature anomaly of the North Atlantic during spring,autumn and summer of the same year was remarkable.The area index and the central intensity index of Siberian high anomaly have obvious correlation with the ocean temperature anomaly of Southwest Atlantic Ocean during spring,summer and autumn,however,they have apparent seasonal differences with the prominent negative correlative areas of subtropical South Indian Ocean and tropical South Pacific Ocean as well as Southwest Atlantic Ocean.The correlative index of area anomaly is greater than those of intensity anomaly.Larger impact on the variability of Siberian high anomaly are the SSTA of subtropical South Indian Ocean,mid and high latitudes of North Pacific Ocean,North Atlantic,tropical South Pacific Ocean,Southwest Atlantic Ocean,etc.several areas.
