South China Sea Sea Surface Temperature Research Articles

Prediction of Sea Surface Temperature Using U-Net Based Model

Sea surface temperature (SST) is a key parameter in ocean hydrology. Currently, existing SST prediction methods fail to fully utilize the potential spatial correlation between variables. To address this challenge, we propose a spatiotenporal UNet (ST-UNet) model based on the UNet model. In particular, in the encoding phase of ST-UNet, we use parallel convolution with different kernel sizes to efficiently extract spatial features, and use ConvLSTM to capture temporal features based on the utilization of spatial features. Atrous Spatial Pyramid Pooling (ASPP) module is placed at the bottleneck of the network to further incorporate the multi-scale features, allowing the spatial features to be fully utilized. The final prediction is then generated in the decoding stage using parallel convolution with different kernel sizes similar to the encoding stage. We conducted a series of experiments on the Bohai Sea and Yellow Sea SST data set, as well as the South China Sea SST data set, using SST data from the past 35 days to predict SST data for 1, 3, and 7 days in the future. The model was trained using data spanning from 2010 to 2021, with data from 2022 being utilized to assess the model’s predictive performance. The experimental results show that the model proposed in this research paper achieves excellent results at different prediction scales in both sea areas, and the model consistently outperforms other methods. Specifically, in the Bohai Sea and Yellow Sea sea areas, when the prediction scales are 1, 3, and 7 days, the MAE of ST-UNet outperforms the best results of the other three compared models by 17%, 12%, and 2%, and the MSE by 16%, 18%, and 9%, respectively. In the South China Sea, when the prediction ranges are 1, 3, and 7 days, the MAE of ST-UNet is 27%, 18%, and 3% higher than the best of the other three compared models, and the MSE is 46%, 39%, and 16% higher, respectively. Our results highlight the effectiveness of the ST-UNet model in capturing spatial correlations and accurately predicting SST. The proposed model is expected to improve marine hydrographic studies.

North–South Discrepancy of Interannual Sea Surface Temperature Anomalies over the South China Sea Associated with Eastern Pacific El Niño Events in the Spring

This paper discovers a spatial feature of interannual sea surface temperature (SST) anomalies over the South China Sea (SCS) in the boreal spring, based on the Simple Ocean Data Assimilation (SODA) monthly data in the period from January 1958 to December 2010. The Empirical Orthogonal Function (EOF) analysis of interannual SST anomalies shows a north–south discrepant pattern of the first mode, which is characterized by higher (lower) anomalies in the northern (southern) SCS and possessing seasonal phase locking (in the boreal spring). Besides, the high correlation coefficient between the time series of the first EOF mode and the Nino 3 SST anomalies during winter reveals that this discrepant pattern is likely caused by El Niño events. The composites of SST anomalies show that this discrepant pattern appears in the eastern Pacific (EP) El Niño events, while it does not exist in the Central Pacific (CP) El Niño events. It is believed that the western North Pacific anticyclone (WNPA) plays a key role in conveying the El Niño impact on the interannual variabilities of SCS SST in the EP El Niño events. The anomalous anticyclone in the Philippine Sea weakens the northeasterly monsoon over the SCS by its southwest portion during the mature phases of the EP El Niño events. This anomalous atmospheric circulation contributes to the north–south discrepant pattern of the wind stress anomalies over the SCS in the EP El Niño mature winters, and then leads to the north–south dipole pattern of the contemporaneous latent heat flux anomalies. The latent heat flux is a major contributor to the surface net heat flux, and heat budget analysis shows that the net heat flux is the major contributor to the SCS SST anomalies during the spring for the EP El Niño events, and the north–south discrepancy of SCS SST anomalies in the succeeding spring is ultimately formed.

The ocean-atmosphere interaction over a summer upwelling system in the South China Sea

Abstract The ocean-atmosphere interaction over a summer upwelling system in the South China Sea (SCS) is investigated. A strong positive correlation between sea surface temperature (SST) and wind stress exists near the southeast coast of Vietnam, where strong SST fronts occur during summertime. This air-sea coupling relationship indicates that the ocean drives the atmosphere and receives feedback at the oceanic mesoscale, in contrast with the case for large scales. The coupling process off the southeast coast of Vietnam is initiated by coastal upwelling, which is driven by wind-induced offshore Ekman transport in early summer. Cold upwelled water reduces the wind stress aloft and results in a positive wind stress curl. The Ekman pumping induced by the wind stress curl is on average 18% stronger than that of the offshore Ekman transport and occupies a larger extent. As the upwelling season terminates by the end of summer, the air-sea coupling also diminishes. Our results reveal that the SST-induced wind stress curl anomalies have a positive feedback on SST change and that wind stress curl anomalies can further reduce the SST magnitude by as much as 0.5 °C. The factors influencing the strength and interannual variability in ocean-atmosphere interaction are also explored. The wind stress directional steadiness (WSDS) plays an important role in the air-sea coupling over the SCS SST frontal regions. The coupling between the wind stress and SST can fully develop under high WSDS. Furthermore, the interannual variabilities in air-sea coupling are largely impacted by the El Nino events by changing the regional wind. The influence of a strong El Nino event on the summer upwelling system is characterized by a warmer SST and declining winds, which are associated with weakened SST gradients and mesoscale air-sea coupling. The present study reveals that the interannual climate signals have a significant impact on the mesoscale ocean-atmosphere interaction in a typical upwelling system. It provides an example for investigation of seasonal and interannual variability of mesoscale air-sea coupling in other coastal regions.

An Adaptive Scale Sea Surface Temperature Predicting Method Based on Deep Learning With Attention Mechanism

Sea surface temperature (SST) prediction plays an important role in ocean-related fields. It is challenging due to the nonlinear temporal dynamics with changing complex factors and the inherent difficulties in long-scale predictions. Conventional models often lack efficient information extraction and cannot meet the requirements of long-scale predictions. Therefore, the gate recurrent unit (GRU) encoder-decoder with SST codes and dynamic influence link (DIL), GRU encoder-decoder (GED), which considered both the static and dynamic influence, is proposed in this letter. Each SST code, capturing the static information more effectively, was computed by all hidden states of the encoder and was individually associated with each predicted SST. The DIL, capturing the dynamic influence, connected the SST code with the early predicted future SST for solving the long-scale dependence problem. GED was tested on the Bohai Sea SST data sets and South China Sea SST data sets and compared with full-connected long-short term memory (FC-LSTM) and support vector regression. The results demonstrated that GED outperformed others on different prediction scales and different prediction terms (daily, weekly, and monthly), especially in terms of long-scale and long-term predictions. In addition, attention relationships between historical and future SSTs were further explored, and there was a meaningful finding that each future daily mean SST of Bohai Sea most strongly correlated with the past 27th to 29th historical values.

Northern South China Sea SST changes over the last two millennia and possible linkage with solar irradiance

High-resolution surface temperature records over the last two millennia are crucial to understanding the forcing and response mechanism of Earth's climate. Here we report a bidecadal-resolution sea surface temperature (SST) record based on long-chain alkenones in a gravity sediment core retrieved from the northern South China Sea. SST values varied between 26.7 and 27.5 °C, with a total variability ∼1 °C over the last 2000 years. The general SST variation pattern matches well with total solar irradiance (TSI) changes. Relatively warm period between 800 and 1400 AD and cool period 1400-1850 AD could be identified, in agreement with the commonly defined periods of Medieval Warm Period and Little Ice Age. Within chronological uncertainty, notable short cooling events at 640-670 AD, 1030-1080 AD, 1260-1280 AD and 1420-1450 AD, coincide with large volcanic eruption events. The general coincidence of SST changes with TSI and volcanic eruption events suggests strong impact of external forcing on sea surface conditions in the studied area. In addition to the direct TSI changes, volcanic eruptions might have induced oceanic and atmospheric circulation adjustments which might be responsible for the short cooling events as revealed in the alkenone-SST record.

A shift in the upper-ocean temperature trends in the South China Sea since the late 1990s

In this paper, the interdecadal variability of upper-ocean temperature in the South China Sea (SCS) is investigated based on several objectively analyzed data sets and two reanalysis data sets. The trends of the SCS sea surface temperature (SST) have changed from warming to cooling since the late 1990s. A heat budget analysis suggests that the warming of the surface mixed layer during 1984–1999 is primarily attributed to the horizontal heat advection and the decrease of upward long wave radiation, with the net surface heat flux playing a damping role due to the increase of upward latent and sensible heat fluxes. On the other hand, the cooling of the surface mixed layer during 2000–2009 is broadly controlled by net surface heat flux, with the radiation flux playing the dominant role. A possible mechanism is explored that the variation of a sea level pressure (SLP) over the North Pacific Ocean may change the prevailing winds over the SCS, which contributes to the change of the SST in the SCS through the horizontal heat advection and heat fluxes.

Regime shift of the South China Sea SST in the late 1990s

Decadal variability of the South China Sea (SCS) sea surface temperature (SST) during 1982–2014 is investigated using observations and ocean reanalysis datasets. The SCS SST shows an abrupt transition from a cold-to-warm regime in the late 1990s. Based on the long-term SST variability two epochs are defined, 1982–1996 and 2000–2014 as cold and warm regimes respectively, spanning on either side of the 1997–1999 SCS warming. Despite the occurrence of strong El Nino induced warming events, the SST anomalies tend to be negative in the cold regime. Conversely during the warm regime, the positive SST anomalies have dominated over the La Nina driven cooling events. The cold (warm) SST regime is marked by net heat gain (loss) by the SCS. The long-term variations of net surface heat flux are mainly driven by the latent heat flux anomalies while the short wave flux plays a secondary role. Low-frequency variability of the South China Sea throughflow (SCSTF) appears to be closely related to the SCS SST regime shift. The SCSTF shows reversing trends during the cold and warm epochs. The weakened SCSTF in the warm regime has promoted the SCS warming by limiting the outward flow of warm water from the SCS. Meanwhile, enhanced SCSTF during the cold regime acts as a cooling mechanism and lead to persistent negative SST anomalies. The change in trend of the SCSTF and SST regime shift coincides with the switching of pacific decadal oscillation from a warm to cold phase in the late 1990s.

Reconstruction and analysis of long-term satellite-derived sea surface temperature for the South China Sea

Sea surface temperature (SST) is one of the key variables often used to investigate ocean dynamics, ocean-atmosphere interaction, and climate change. Unfortunately, the SST data sources in the South China Sea (SCS) are not abundant due to sparse measurements of in situ SST and a high percentage of missing data in the satellite-derived SST. Therefore, SST data sets with low resolution and/or a short-term period have often been used in previous researches. Here we used Data INterpolating Empirical Orthogonal Functions, a self-consistent and parameter-free method for filling in missing data, to reconstruct the daily nighttime 4-km AVHRR Pathfinder SST for the long-term period spanning from 1989 to 2009. In addition to the reconstructed field, we also estimated the local error map for each reconstructed image. Comparisons between the reconstructed and other data sets (satellite-derived microwave and in situ SSTs) show that the results are reliable for use in many different researches, such as validating numerical models, or identifying and tracking meso-scale oceanic features. Moreover, the Empirical Orthogonal Function (EOF) analysis of the reconstructed SST and the reconstructed SST anomalies clearly shows the subseasonal, seasonal, and interannual variability of SST under the influence of monsoon and El Nino-Southern Oscillation (ENSO), as well as reveals some oceanic features that could not be captured well in previous EOF analyses. The SCS SST often lags ENSO by about half a year. However, in this study, we see that the time lag changes with the frequencies of the SST variability, from 1 to 6 months.

Different Responses of Sea Surface Temperature in the South China Sea to Various El Niño Events during Boreal Autumn

Abstract This study investigates variations of sea surface temperature (SST) anomalies in the South China Sea (SCS) during developing autumn of various El Niño events. The warm SST anomalies are observed in the SCS for canonical El Niño and El Niño Modoki I, whereas the cold SST anomalies are found for El Niño Modoki II. The ocean heat budget analyses show that the latent heat flux change induced by various types of El Niño events is a major contributor to the SCS SST variations. An anomalous anticyclone resides near the Philippine Sea for canonical El Niño and El Niño Modoki I, which induces the southerly wind anomalies over the SCS and thus weakens the climatological northeasterly in boreal autumn. The weakened surface wind speed reduces heat loss from the ocean, leading to a warmer state in the SCS. However, for El Niño Modoki II, the anomalous anticyclone shifts westward to the west of the SCS, and thus the northeasterly wind anomalies appear in the SCS. The northeasterly anomalies enhance the climatological northeasterly monsoon, increase the wind speed, and increase heat loss from the ocean, thus resulting in a cooling in the SCS. The anomalous anticyclone associated with El Niño events also increases shortwave radiation. The increases of the shortwave radiation can also contribute to the SCS warming for canonical El Niño and El Niño Modoki I in addition to the warm effect from the latent heat flux. Because the cooling effect from the latent heat flux is larger than that of the shortwave radiation for El Niño Modoki II, the SCS for El Niño Modoki II tends to be cool.

Influence of the South China Sea Biweekly Sea Surface Temperature on the South China Sea Summer Monsoon Especially during the Indian Ocean Dipole

ABSTRACTThe influence of the biweekly sea surface temperature (SST) in the South China Sea (SCS) on the SCS summer monsoon, especially during the Indian Ocean Dipole (IOD) is presented using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) SST and rainfall data for April to June from 1999 to 2013. During positive IOD (PIOD) years the biweekly SST anomalies over the SCS lead the rain anomalies by three days, with a significant correlation (r = 0.8, at the 99% confidence level), whereas during negative IOD (NIOD) years, the correlation is only 0.2. The biweekly SST is observed to influence the westward and northward propagating rainfall anomalies over the SCS and, hence, affect the SCS summer monsoon, especially during PIOD years. No such propagation was seen during NIOD years. The biweekly intraseasonal oscillation of SST in the SCS results in enhanced sea level pressure and surface shortwave radiation, especially during PIOD years. The potential findings here indicate that the biweekly SST in the SCS is strongly (weakly) influenced during PIOD (NIOD) years. Further, it is observed that SST in the SCS has a strong (weak) effect on the SCS summer monsoon by westward and northward propagation of rainfall, especially during PIOD (NIOD) years. When a PIOD or NIOD exists over the tropical Indian Ocean, the SCS SST will be strongly (r = 0.6, at the 99% confidence level) or weakly correlated with the residual index, respectively.

Responses of atmospheric circulation to sea surface temperature anomalies in the South China Sea

Abstract. The sea surface temperature (SST) anomalies in the South China Sea (SCS) and their influences on global atmospheric circulation were studied. The results of a simple atmospheric model suggested that the SCS SST anomalies can induce several barotropic wave trains from the SCS to other regions such as North America, high latitudes of the Southern Hemisphere and the Mediterranean. The baroclinic stream function anomalies from the simple model showed an anticyclonic vortex pair in the Asian continent and the northern and southern Indian Ocean and a cyclonic vortex in the North Pacific and the southwestern Pacific. It is suggested that the spatial pattern of SST anomalies in the SCS can affect the magnitude of stream function anomalies, although it cannot affect the spatial pattern of atmospheric circulation.

Biweekly Sea Surface Temperature over the South China Sea and its association with the Western North Pacific Summer Monsoon

The association of the biweekly intraseasonal (BWI) oscillation in the Sea Surface Temperature (SST) over the South China Sea (SCS) and the Western North Pacific Summer Monsoon is authenticated using version 4 the Tropical Rainfall Measuring Mission Microwave Imager data (SST and rain) and heat fluxes from Ocean Atmosphere Flux project data during 1998–2012. The results suggest that the SCS involves ocean–atmosphere coupling on biweekly timescales. The positive biweekly SST anomalies lead the rain anomalies over the SCS by 3 days, with a significant correlation coefficient (r = 0.6, at 99 % significance levels) between the SST-rain anomalies. It is evident from lead/lag correlation between biweekly SST and zonal wind shear that warm ocean surface induced by wind shear may contribute to a favorable condition of the convective activity over the SCS. The present study suggests that ocean–to-atmospheric processes induced by the BWI oscillation in the SCS SST results in enhanced sea level pressure and surface shortwave radiation flux during the summer monsoon. Besides, it is observed that the SCS BWI oscillation in the changes of SST causes a feedback in the atmosphere by modifying the atmospheric instability. This suggests that the active/break biweekly cycle of the SST over the SCS is related by sea level pressure, surface heat fluxes and atmospheric instability. The potential findings here indicate that the biweekly SST over the SCS play an important role in the eastward and the southward propagation of the biweekly anomalies in the Western North Pacific.

Interdecadal Difference of Interannual Variability Characteristics of South China Sea SSTs Associated with ENSO

Abstract The correlation between sea surface temperature (SST) and El Niño–Southern Oscillation (ENSO) persists into post-ENSO September over the South China Sea (SCS), the longest correlation in the World Ocean. Slow modulations of this correlation are analyzed by using the International Comprehensive Ocean–Atmosphere Dataset (ICOADS). ENSO’s influence on SCS SST has experienced significant interdecadal changes over the past 138 years (1870–2007), with a double-peak structure correlation after the 1960s compared to a single-peak before the 1940s. According to the ENSO correlation character, the analysis period is divided into four epochs. In epoch 3, 1960–83, the SST warming and enhanced precipitation over the southeastern tropical Indian Ocean, rather than the Indian Ocean basinwide warming, induce easterly wind anomalies and warm up the SCS in the summer following El Niño. Besides the Indian Ocean effect, during epochs 2 (1930–40) and 4 (1984–2007), the Pacific–Japan (PJ) pattern of atmospheric circulation anomalies helps sustain the SCS SST warming through summer (June–August) with easterly wind anomalies. The associated increase in shortwave radiation and decrease in upward latent heat flux cause the SCS SST warming to persist into the summer. Meanwhile, the rainfall response around the SCS to ENSO shows interdecadal variability, with stronger variability after the 1980s. The results suggest that both the remote forcing from the tropical Indian Ocean and the PJ pattern are important for the ENSO teleconnection to the SCS and its interdecadal modulations.

Relative contribution of ENSO and East Asian winter monsoon to the South China Sea SST anomalies during ENSO decaying years

AbstractPresent study investigates respective contributions of El Niño‐Southern Oscillation (ENSO) and East Asian winter monsoon (EAWM) to two periods of sea surface temperature (SST) anomalies in the South China Sea (SCS), one subsequent to the ENSO mature phase and the other in the following summer, during 1982–2010. It is found that the SST anomalies in the first period are related to the EAWM and the ENSO impact independent of EAWM is weak, which differs from previous studies. The SST anomalies in the second period are mainly due to the ENSO effect. A heat budget analysis shows that changes in shortwave radiation and wind‐related surface latent heat flux as well as horizontal advections are the processes leading to the EAWM‐related SST anomalies in the first period. The ENSO‐related SST anomalies in the second period are contributed by shortwave radiation and latent heat flux anomalies as well as meridional advection and vertical upwelling processes near the southeast coast of Indochina Peninsula. The ENSO contribution to the SCS SST anomalies in the first period is larger before than after the late 1970s. This is attributed to an earlier development of ENSO events that is followed by larger equatorial central and eastern Pacific SST anomalies in boreal summer and, subsequently, larger North Indian Ocean SST anomalies around October. Consequently, anomalous surface anticyclone over the SCS is stronger, leading to larger surface heat flux anomalies and thus a larger SST increase around October before than after the late 1970s.

Interannual variability of winter precipitation in Southeast China

The observed winter (DJF) precipitation in Southeast China (1961–2010) is characterized by a monopole pattern of the 3-monthly Standardized Precipitation Index (SPI-3) whose interannual variability is related to the anomalies of East Asian Winter Monsoon (EAWM) systems. Dynamic composites and linear regression analysis indicate that the intensity of EAWM and Siberia High (SH), the position of East Asian Trough (EAT), and El Nino events and sea surface temperature (SST) anomalies over South China Sea (SCS) influence different regions of anomalous Southeast China winter precipitation on interannual scales. The circulation indices (EAWM index, SH index, and EAT index) mainly affect the winter precipitation in the eastern part of Southeast China. El Nino events affect the South China winter precipitation due to the anticyclone anomalies over Philippines. The effect of SCS SST anomalies on the winter precipitation is mainly in the southern part of Yangtze River. Thus, a set of circulation regimes, represented by a handful indices, provide the basis for modeling precipitation anomalies or extremes in future climate projections.

Asymmetric response of the South China Sea SST to El Niño and La Niña

The interannual variability of the sea surface temperature (SST) in the South China Sea (SCS) is investigated according to its relationship with El Nino/La Nina (EN/LN) using monthly products from ICOADS. The SCS SST bears two peaks associated with EN/LN and shows the asymmetric features. Coinciding with the mature phase of EN/LN, the first SST warming/cooling peaks in December(0)-February(1) (DJF(1)) and centers in the southern part. The major difference is in the amplitude associated with the strength of EN/LN. However, the SCS SST anomaly shows distinct difference after the mature phase of EN/LN. The EN SST warming develops a mid-summer peak in June-August(1) (JJA(1)) and persists up to September-October(1), with the same amplitude of the first warming peak. Whereas the LN SST cooling peaks in May(1), it decays slowly until the end of the year, with amplitude much weaker. Comparing with SST and atmospheric circulations, the weak response and early termination of the second cooling is due to the failure of the cyclonic wind anomalies to develop in the northwest Pacific during JJA(1).

Interannual and interdecadal atmospheric circulation anomalies of autumn dry/wet over the loess plateau and its multi-scalar correlation to SST

The ecological environment is vulnerable and extremely sensitive to climate change in the loess plateau. The interannual and interdecadal variations of dry/wet index are particularly obvious in this region. Up to now, the analisis of the dry/wet variation in the loess plateau has been basically understood during summer, but the autumn dry/wet evolution of the loess plateau and the atmospheric circulation characteristic are still laking in its knowledge. Based on the monthly mean rainfall and temperature of 589 China weather stations, the NCEP/NCAR reanalysis dataset and NOAA extended reconstructed sea surface temperature (SST) data from 1961 to 2010, using the EOF/REOF, bandpass filtering, wavelet technique and regression methods, the autumn dry/wet evolution of the loess plateau and the atmospheric circulation characteristic associated with them, and the multi-scale relationship between dry/wet index and SST were analyzed on the basis of classification of dry/wet over China region in autumn. The continuous wavelet transform shows that the autumn wet/dry index exists has ～4 a and 8 a period over the loess plateau, and the ～8 year oscillation from 1970–1990 is rather obvious. On the interannual scales, the atmospheric circulation anomalies of 500 hPa associated with the wet years exhibit a ’double-blocking’ in the mid-high latitude, and the westerly jet stream turns to be weakened and the jet axis moves to the north significantly. Japan-Okhotsk Sea is featured with anticyclone, and the east wind at the bottom of the anticyclone provides favorable moisture for the middle Loess plateau. On the interdecadal scales, the atmospheric circulation anomalies associated with the wet years show the negative geopotential height anomaly over East Asian, and the East Asian subtropical westerly jet stream of 200 hPa is weakened and moves north too. The vapour of the middle Loess plateau comes from two paths, one is the westerly water vapor transport in the middle latitude, and the other is the southerly water vapor transport from the Bay of Bengal and turns to the north at the Indo-China Peninsula. When the Nino3 index (Nino3I) is in advance of dry/wet index for 5 months, there is a significantly negative correlation between them. When the Bay of Benga and South China Sea SST index (BayI) goes shead of dry/wet index for 3 months, there is a significantly negative correlation between them. On the interannual scales, the cross wavelet transform indicates that both the Nino3I and BayI have significant connections with the dry/wet index (～4 a and 4–6 a cycles). On the interdecadal scales, only BayI has significant connections with dry/wet index (～10 a cycles). By establishing the interannual and interdecadal variations of dry/wet cycle of the loess plateau, recognizing the atmospheric circulation anomalies, and building the relationship between the dry/wet index and SST, this paper reveals the physical mechanism of the dry/wet variation and finds the early waring signals for drought climate change in the region.

Variability of tropical cyclone occurrence date in the South China Sea and its relationship with SST warming

Analyses of tropical cyclone (TC) occurrence dates in the South China Sea (SCS) for the past 60 yrs indicate a trend toward an earlier occurrence of the first annual TC in the SCS. On the other hand, a significant increasing trend in sea surface temperature (SST) in early summer (May–June) has been observed in the SCS. The negative correlation between the first annual TC occurrence date and SST in early summer during the period 1945–2009 suggests that the earlier occurrence of the first annual TC is related not only to the increasing of SST in the SCS, but also to the variability of SST in the Niño3.4 region. Quantitative analysis of the SCS TC occurrence date and SST by quantile regression also reveals such a relationship and confirms that the SCS early-season TCs tend to occur earlier when SSTs in the SCS and Niño3.4 region are increasing. Since the SCS SST anomalies are influenced by the El Niño-Southern Oscillation (ENSO), the relationship between the first annual TC occurrence date and ENSO-related large-scale atmospheric circulation including 850-hPa relative vorticity (RV), vertical wind shear (VWS), and moist static energy (MSE) in early summer are also investigated. It is found that variations of VWS and MSE have influences on first annual SCS TC occurrence dates, although there is not a statistically significant relationship between 850-hPa RV and first annual SCS TC occurrence date. These results suggest that the earlier occurrence of the first annual TC in the SCS is influenced not only by local SST, but also by ENSO through the alternation of early summer VWS and MSE in the SCS.

Interdecadal change in sea surface temperature anomalies associated with winter rainfall over South China

[1] The present study investigates the interdecadal change in winter (January-February-March, or JFM) rainfall over South China and in the South China JFM rainfall–sea surface temperature (SST) relationship by using station observations for the period of 1958–2002, the Met Office Hadley Centre's SST data for the period of 1900–2008, and the ERA-40 reanalysis for the period of 1958–2002. It is found that the relationship between South China JFM rainfall and SST experienced an obvious interdecadal change around the year 1978. The analyses show that the JFM rainfall anomalies during 1960–1977 and 1978–2002 were closely associated with the South China Sea (SCS) SST and El Nino–Southern Oscillation (ENSO), respectively. Moreover, southwesterly anomalies at 700 hPa dominate over the SCS for positive SCS SST anomaly years during 1960–1977 and for El Nino years during 1978–2002, respectively. These wind anomalies, which are associated with the enhancement of the western Pacific subtropical high, transport more moisture into South China, favoring increases in rainfall.

Monsoon-ocean coupled modes in the South China Sea and their linkage with the eastern Indian Ocean-western Pacific warm pool

Monsoon-ocean coupled modes in the South China Sea (SCS) were investigated by a combined singular value decomposition (CSVD) analysis based on sea surface temperature (SST) and sea surface wind stress (SWS) fields from SODA (Simple Ocean Data Assimilation) data spanning the period of 1950–1999. The coupled fields achieved the maximum correlation when the SST lagged SWS by one month, indicating that the SCS coupled system mainly reflected the response of the SST to monsoon forcing. Three significant coupled modes were found in the SCS, accounting for more than 80% of the cumulative squared covariance fraction. The first three SST spatial patterns from CSVD were: (I) the monopole pattern along the isobaths in the SCS central basin; (II) the north-south dipole pattern; and (III) the west-east seesaw pattern. The expansion coefficient of the SST leading mode showed interdecadal and interannual variability and correlation with the Indo-Pacific warm pool (IPWP), suggesting that the SCS belongs to part of the IPWP at interannual and interdecadal time scales. The second mode had a lower correlation coefficient with the warm pool index because its main period was at intra-annual time scales instead of the interannual and interdecadal scales with the warm pools. The third mode had similar periods to those of the leading mode, but lagged the eastern Indian Ocean warm pool (EIWP) and western Pacific warm pool (WPWP) by five months and one year respectively, implying that the SCS response to the warm pool variation occurred from the western Pacific to the eastern Indian Ocean, which might have been related to the variation of Indonesian throughflow. All three modes in the SCS had more significant correlations with the EIWP, which means the SCS SST varied much more coherently with the EIWP than the WPWP, suggesting that the SCS belongs mostly to part of the EIWP. The expansion coefficients of the SCS SST modes all had negative correlations with the Nino3 index, which they lag by several months, indicating a remote response of SCS SST variability to the El Nino events.