2008年初广东罕见低温雨雪冰冻天气的成因初探

利用常规气象观测资料、NCEP/NCAR再分析资料,以及国家气候中心的海温监测资料等,初步分析2008年初我国南方持续低温雨雪冰冻天气过程的成因的结果表明,此次罕见天气过程是在近年来最严重的一次"拉尼娜"事件背景下发生的,与欧亚地区持续大气环流异常密切相关。在"北脊南槽"和西太平洋副高偏北偏强的形势下,北方冷空气不断从青藏高原东北侧南下,同时孟加拉湾和南海地区源源不断的水汽往北到东北方向输送,冷暖气流在我国南方地区频繁交汇,使对流层中低层形成逆温层和局地经向环流产生异常,造成了持续低温雨雪冰冻过程。

2012年春节期间广东罕见低温阴雨天气特点及成因

利用常规气象观测资料、NCEP/NCAR分析资料,以及国家气候中心的海温监测资料等,初步分析了2012年春节前后广东极端低温阴雨天气过程的特点和成因。结果表明,此次过程具有极端温度低、低温范围广、阴雨时间长的特征;此次罕见天气过程是在"北极涛动"负位相活动和显著"拉尼娜"事件背景下发生,与欧亚地区持续大气环流异常密切相关。乌拉尔山阻塞高压建立后,中高纬稳定的"两脊一槽"形势下,有利于短波槽东南移影响华南;同时,高原南侧的南支西风槽加深增强了低纬水汽往华南地区输送,冷暖空气在华南长时间交绥,造成了持续的低温阴雨过程。过程期间,粤北近地层极端气温低,但中层暖层无论从强度、厚度及持续时间均未有2008年明显,因此过程主要以"低温"和"阴雨"为主,并未发生类似2008年初的粤北持续大范围"低温雨雪冰冻"天气。

Research on the Relationship of ENSO and the Frequency of Extreme Precipitation Events in China

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.

The“Spring Predictability Barrier” Phenomenon of ENSO Predictions Generated with the FGOALS-g Model

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.

Surface thermal centroid anomaly of the eastern equatorial Pacific as a unified Nio index

By analyzing the variability of global SST （sea surface temperature） anomalies, we propose a unified Nifio index using the surface thermal centroid anomaly of the region along the Pacific equator embraced by the 0.7~C contour line of the standard deviation of the SST anomalies and try to unify the traditional Nifio regions into a single entity. The unified Nifio region covers almost all of the traditional Nifio regions. The anomaly time series of the averaged SST over this region are closely correlated to historical Nifio indices. The anomaly time series of the zonal and meridional thermal centroid have close correlation with historical TNI （Trans-Nifio index） indices, showing differences among E1 Nifio （La Nifia） events. The meridional centroid anomaly suggests that areas of maximum temperature anomaly are moving meridionally （although slightly） with synchronous zonal movement. The zonal centroid anomalies of the unified Nifio region are found helpful in the classification of the Eastern Pacific （EP）/Central Pacific （CP） types of E1 Nifio events. More importantly, the zonal centroid anomaly shows that warm areas might move during a single warming/cooling phase. All the current Nifio indices can be well represented by a simple linear combination of unified Nifio indices, which suggests that the thermal anomaly （SSTA） and thermal centroid location anomaly of the unified Nifio region would yield a more complete image of each E1 Nifio/ La Nina event.

Phytoplankton and chlorophyll a relationships with ENSO in Prydz Bay, East Antarctica

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.