Empirical orthogonal function (EOF) analysis reveals a co-variability of Sea surface temperatures (SSTs) in the Southern Hemisphere (0°-60°S). In the South Indian and Atlantic Oceans, there is a subtro...Empirical orthogonal function (EOF) analysis reveals a co-variability of Sea surface temperatures (SSTs) in the Southern Hemisphere (0°-60°S). In the South Indian and Atlantic Oceans, there is a subtropical dipole pattern slanted in the southwest-northeast direction. In the South Pacific Ocean, a meridional tripole structure emerges, whose middle pole co-varies with the dipoles in the South Indian and Atlantic Oceans and is used in this study to track subtropical Pacific variability. The South Indian and Atlantic Ocean dipoles and the subtropical Pacific variability are phase-locked in austral summer. On the inter-decadal time scales, the dipoles in the South Indian and Atlantic Oceans weaken in amplitude after 1979/1980. No such weakening is found in the subtropical South Pacific Ocean. Interestingly, despite the reduced amplitude, the correlation of the Indian Ocean and Atlantic dipoles with E1 Nino and Southern Oscillation (ENSO) are enhanced after 1979/1980. The same increase in correlation is found for subtropical South Pacific variability after 1979/1980. These inter-decadal modulations imply that the Southern Hemisphere participates in part of the climate shift in the late 1970s. The correlation between Southern Hemisphere SST and ENSO reduces after 2000.展开更多
We analyzed the temporal and spatial variation, and interannual variability of the North Pacific meridional overturning circulation using an empirical orthogonal function method, and calculated mass transport using Si...We analyzed the temporal and spatial variation, and interannual variability of the North Pacific meridional overturning circulation using an empirical orthogonal function method, and calculated mass transport using Simple Ocean Data Assimilation Data from 1958-2008. The meridional streamfunction field in the North Pacific tilts N-S; the Tropical Cell (TC), Subtropical Cell (STC), and Deep Tropical Cell (DTC) may be in phase on an annual time scale; the TC and the STC are out of phase on an interannual time scale, but the interannual variability of the DTC is complex. The TC and STC interannual variability is associated with ENSO (El Nifio-Southem Oscillation). The TC northward, southward, upward, and downward transports all weaken in E1 Nifios and strengthen in La Nifias. The STC northward and southward transports are out of phase, while the STC northward and downward transports are in phase. Sea-surface water that reaches the middle latitude and is subducted may not completely return to the vopics. The zonal wind anomalies over the central North Pacific, which control Ekman transport, and the east-west slope of the sea level may be major factors causing the TC northward and southward transport interannual variability and the STC northward and southward transports on the interannual time scale. The DTC northward and southward transports decrease during strong E1 Nifios and increase during strong La Nifias. DTC upward and downward transports are not strongly correlated with the Nifio-3 index and may not be completely controlled by ENSO.展开更多
A heat center (HC) of the western Pacific warm pool (WPWP) is defined, its variability is examined, and a possible mechanism is discussed. Analysis and calculation of a temperature dataset from 1945-2006 show that...A heat center (HC) of the western Pacific warm pool (WPWP) is defined, its variability is examined, and a possible mechanism is discussed. Analysis and calculation of a temperature dataset from 1945-2006 show that the mean position of the HC during this period was near 0.4°S/169.0°E, at 38.0 m depth. From a time series of the HC, remarkable seasonal variability was found, mainly in the meridional and vertical directions. Interannual variabilities were dominant in the zonal and vertical directions. In addition, semiannual variation in the HC depth was discovered. The longitude of the HC varies with ENSO events, and its latitude is weakly related to ENSO on time scales shorter than a decade. The variation of the HC longitude leads the Nifio-3 index by about 3-4 months, and its depth lags the index for approximately 3 months. It is concluded that the HC depth results from a combination of its longitudinal and latitudinal variations. Low-pass-filtered time series reveal that the HC has moved eastward since the mid 1980s.展开更多
Using interpolation and averaging methods, we analyzed the sea surface wind data obtained from December 1992 to November 2008 by the scatterometers ERS-1, ERS-2, and QuikSCAT in the area of 2°N-39 °N, 105...Using interpolation and averaging methods, we analyzed the sea surface wind data obtained from December 1992 to November 2008 by the scatterometers ERS-1, ERS-2, and QuikSCAT in the area of 2°N-39 °N, 105°E-130°E, and we reported the monthly mean distributions of the sea surface wind field. A vector empirical orthogonal function (VEOF) method was employed to study the data and three temporal and spatial patterns were obtained. The first interannual VEOF accounts for 26% of the interannual variance and displays the interannual variability of the East Asian monsoon. The second interannual VEOF accounts for 21% of the variance and reflects the response of China sea winds to E1 Nifio events. The temporal mode of VEOF-2 is in good agreement with the curve of the Nifio 3.4 index with a four-month lag. The spatial mode of VEOF-2 indicates that four months after an E1 Nifio event, the southwesterly anomalous winds over the northern South China Sea, the East China Sea, the Yellow Sea, and the Bohai Sea can weaken the prevailing winds in winter, and can strengthen the prevailing winds in summer. The third interannual VEOF accounts for 10% of the variance and also reflects the influence of the ENSO events to China Sea winds. The temporal mode of VEOF-3 is similar to the curve of the Southern Oscillation Index. The spatial mode of VEOF-3 shows that the northeasterly anomalous winds over the South China Sea and the southern part of the East China Sea can weaken the prevailing winds, and southwesterly anomalous winds over the northern part of the East China Sea, the Yellow Sea, and the Bohai Sea can strengthen the prevailing winds when E1 Nifio occurs in winter. If E1 Nifio happens in summer, the reverse is true.展开更多
Based on gridded Argo profile data from January 2004 to December 2010, together with the P-vector inverse method, the three-dimensional structure, annual and inter-annual variations in volume of the Western Pacific Wa...Based on gridded Argo profile data from January 2004 to December 2010, together with the P-vector inverse method, the three-dimensional structure, annual and inter-annual variations in volume of the Western Pacific Warm Pool (WPWP) are studied. The variations of latitudinal and longitudinal warm water flowing into and out of the WPWP and the probable mecha- nism of warm water maintenance are also discussed. From the surface to the bottom, climatic WPWP tilts southward and its area decreases. The maximum depth could extend to 120 m, such that its volume could attain 1.86x10^5 m3. Annual variation of the WPWP volume shows two obvious peaks that occur in June and October, whereas its inter-annual variations are related to ENSO events. Based on a climatic perspective, the warm water flowing latitudinally into the pool is about 52 Sv, which is mainly through upper layers and via the eastern boundary. Latitudinally, warm water flowing outward is about 49 Sv, and this is mainly through lower layers and via the western boundary. In contrast, along the latitude, warm water flowing into and out of the pool is about 28 Sv and 23 Sv, respectively. Annual and inter-annual variations of the net transportation of the warm water demonstrate that the WPWP mainly loses warm water in the west-east direction, whereas it receives warm water from the north-south direction. The annual variation of the volume of WPWP is highly related to the annual variation of the net warm water transportation, however, they are not closely related on inter-annual time scale. On the inter-annual time scale, in- fluences of ENSO events on the net warm water transportation in the north-south direction are much more than that in the west-east direction. Although there are some limitations and simplifications when using the P-vector method, it could still help improve our understanding of the WPWP, especially regarding the sources of the warm water.展开更多
Although deep learning has achieved a milestone in forecasting the El Niño-Southern Oscillation(ENSO),the current models are insufficient to simulate diverse characteristics of the ENSO,which depends on the calen...Although deep learning has achieved a milestone in forecasting the El Niño-Southern Oscillation(ENSO),the current models are insufficient to simulate diverse characteristics of the ENSO,which depends on the calendar season.Consequently,a model was generated for specific seasons which indicates these models did not consider physical constraints between different target seasons and forecast lead times,thereby leading to arbitrary fluctuations in the predicted time series.To overcome this problem and account for ENSO seasonality,we developed an all-season convolutional neural network(A_CNN)model.The correlation skill of the ENSO index was particularly improved for forecasts of the boreal spring,which is the most challenging season to predict.Moreover,activation map values indicated a clear time evolution with increasing forecast lead time.The study findings reveal the comprehensive role of various climate precursors of ENSO events that act differently over time,thus indicating the potential of the A_CNN model as a diagnostic tool.展开更多
基金jointly supported by the National Basic Research Program(2012CB955603,2010CB950302)National High Technology Research and Development Program of China(No.2010AA012304)the Knowledge Innovation Program of the Chinese Academy of Sciences(SQ201006 and XDA05090404)
文摘Empirical orthogonal function (EOF) analysis reveals a co-variability of Sea surface temperatures (SSTs) in the Southern Hemisphere (0°-60°S). In the South Indian and Atlantic Oceans, there is a subtropical dipole pattern slanted in the southwest-northeast direction. In the South Pacific Ocean, a meridional tripole structure emerges, whose middle pole co-varies with the dipoles in the South Indian and Atlantic Oceans and is used in this study to track subtropical Pacific variability. The South Indian and Atlantic Ocean dipoles and the subtropical Pacific variability are phase-locked in austral summer. On the inter-decadal time scales, the dipoles in the South Indian and Atlantic Oceans weaken in amplitude after 1979/1980. No such weakening is found in the subtropical South Pacific Ocean. Interestingly, despite the reduced amplitude, the correlation of the Indian Ocean and Atlantic dipoles with E1 Nino and Southern Oscillation (ENSO) are enhanced after 1979/1980. The same increase in correlation is found for subtropical South Pacific variability after 1979/1980. These inter-decadal modulations imply that the Southern Hemisphere participates in part of the climate shift in the late 1970s. The correlation between Southern Hemisphere SST and ENSO reduces after 2000.
基金Supported by the National Basic Research Program of China(973 Program)(Nos.2012CB417402,2007CB816002)
文摘We analyzed the temporal and spatial variation, and interannual variability of the North Pacific meridional overturning circulation using an empirical orthogonal function method, and calculated mass transport using Simple Ocean Data Assimilation Data from 1958-2008. The meridional streamfunction field in the North Pacific tilts N-S; the Tropical Cell (TC), Subtropical Cell (STC), and Deep Tropical Cell (DTC) may be in phase on an annual time scale; the TC and the STC are out of phase on an interannual time scale, but the interannual variability of the DTC is complex. The TC and STC interannual variability is associated with ENSO (El Nifio-Southem Oscillation). The TC northward, southward, upward, and downward transports all weaken in E1 Nifios and strengthen in La Nifias. The STC northward and southward transports are out of phase, while the STC northward and downward transports are in phase. Sea-surface water that reaches the middle latitude and is subducted may not completely return to the vopics. The zonal wind anomalies over the central North Pacific, which control Ekman transport, and the east-west slope of the sea level may be major factors causing the TC northward and southward transport interannual variability and the STC northward and southward transports on the interannual time scale. The DTC northward and southward transports decrease during strong E1 Nifios and increase during strong La Nifias. DTC upward and downward transports are not strongly correlated with the Nifio-3 index and may not be completely controlled by ENSO.
基金Supported by the National Natural Science Foundation of China Major Project (Nos. 40890150, 40890151)the National Basic Research Program of China (973 Program) (No. 2007-CB411802)
文摘A heat center (HC) of the western Pacific warm pool (WPWP) is defined, its variability is examined, and a possible mechanism is discussed. Analysis and calculation of a temperature dataset from 1945-2006 show that the mean position of the HC during this period was near 0.4°S/169.0°E, at 38.0 m depth. From a time series of the HC, remarkable seasonal variability was found, mainly in the meridional and vertical directions. Interannual variabilities were dominant in the zonal and vertical directions. In addition, semiannual variation in the HC depth was discovered. The longitude of the HC varies with ENSO events, and its latitude is weakly related to ENSO on time scales shorter than a decade. The variation of the HC longitude leads the Nifio-3 index by about 3-4 months, and its depth lags the index for approximately 3 months. It is concluded that the HC depth results from a combination of its longitudinal and latitudinal variations. Low-pass-filtered time series reveal that the HC has moved eastward since the mid 1980s.
基金Supported by the Knowledge Innovation Program of Chinese Academy of Sciences (Nos. KZCX1-YW-12, KZCXZ-YW201)National Natural Science Foundation of China (No. 90411013)
文摘Using interpolation and averaging methods, we analyzed the sea surface wind data obtained from December 1992 to November 2008 by the scatterometers ERS-1, ERS-2, and QuikSCAT in the area of 2°N-39 °N, 105°E-130°E, and we reported the monthly mean distributions of the sea surface wind field. A vector empirical orthogonal function (VEOF) method was employed to study the data and three temporal and spatial patterns were obtained. The first interannual VEOF accounts for 26% of the interannual variance and displays the interannual variability of the East Asian monsoon. The second interannual VEOF accounts for 21% of the variance and reflects the response of China sea winds to E1 Nifio events. The temporal mode of VEOF-2 is in good agreement with the curve of the Nifio 3.4 index with a four-month lag. The spatial mode of VEOF-2 indicates that four months after an E1 Nifio event, the southwesterly anomalous winds over the northern South China Sea, the East China Sea, the Yellow Sea, and the Bohai Sea can weaken the prevailing winds in winter, and can strengthen the prevailing winds in summer. The third interannual VEOF accounts for 10% of the variance and also reflects the influence of the ENSO events to China Sea winds. The temporal mode of VEOF-3 is similar to the curve of the Southern Oscillation Index. The spatial mode of VEOF-3 shows that the northeasterly anomalous winds over the South China Sea and the southern part of the East China Sea can weaken the prevailing winds, and southwesterly anomalous winds over the northern part of the East China Sea, the Yellow Sea, and the Bohai Sea can strengthen the prevailing winds when E1 Nifio occurs in winter. If E1 Nifio happens in summer, the reverse is true.
基金supported by the Special Program for the National Basic Research (Grant No. 2012FY112300)SOED HPCC of the Second Institute of Oceanography, State Oceanic Administration for support and assistance
文摘Based on gridded Argo profile data from January 2004 to December 2010, together with the P-vector inverse method, the three-dimensional structure, annual and inter-annual variations in volume of the Western Pacific Warm Pool (WPWP) are studied. The variations of latitudinal and longitudinal warm water flowing into and out of the WPWP and the probable mecha- nism of warm water maintenance are also discussed. From the surface to the bottom, climatic WPWP tilts southward and its area decreases. The maximum depth could extend to 120 m, such that its volume could attain 1.86x10^5 m3. Annual variation of the WPWP volume shows two obvious peaks that occur in June and October, whereas its inter-annual variations are related to ENSO events. Based on a climatic perspective, the warm water flowing latitudinally into the pool is about 52 Sv, which is mainly through upper layers and via the eastern boundary. Latitudinally, warm water flowing outward is about 49 Sv, and this is mainly through lower layers and via the western boundary. In contrast, along the latitude, warm water flowing into and out of the pool is about 28 Sv and 23 Sv, respectively. Annual and inter-annual variations of the net transportation of the warm water demonstrate that the WPWP mainly loses warm water in the west-east direction, whereas it receives warm water from the north-south direction. The annual variation of the volume of WPWP is highly related to the annual variation of the net warm water transportation, however, they are not closely related on inter-annual time scale. On the inter-annual time scale, in- fluences of ENSO events on the net warm water transportation in the north-south direction are much more than that in the west-east direction. Although there are some limitations and simplifications when using the P-vector method, it could still help improve our understanding of the WPWP, especially regarding the sources of the warm water.
基金This work was supported by the National Research Foundation of Korea(NRF)(NRF-2020R1A2C2101025).
文摘Although deep learning has achieved a milestone in forecasting the El Niño-Southern Oscillation(ENSO),the current models are insufficient to simulate diverse characteristics of the ENSO,which depends on the calendar season.Consequently,a model was generated for specific seasons which indicates these models did not consider physical constraints between different target seasons and forecast lead times,thereby leading to arbitrary fluctuations in the predicted time series.To overcome this problem and account for ENSO seasonality,we developed an all-season convolutional neural network(A_CNN)model.The correlation skill of the ENSO index was particularly improved for forecasts of the boreal spring,which is the most challenging season to predict.Moreover,activation map values indicated a clear time evolution with increasing forecast lead time.The study findings reveal the comprehensive role of various climate precursors of ENSO events that act differently over time,thus indicating the potential of the A_CNN model as a diagnostic tool.