基于HYCOM设计了3组数值试验,分别采用KPP(K-Profile Parameterization),KT(Kraus and Turner),MY(Mellor and Yamada)2.5三种垂向混合方案,比较分析了这3种混合方案对全球大洋的模拟能力。结果表明:KPP方案和MY2.5方案模拟的温度场十分类似,在中高纬度几乎一致,在赤道断面上MY2.5方案的最大误差小于KPP方案,对于暖池区SST的模拟MY2.5方案的误差也稍小于KPP方案,但二者的差别并不明显。在模拟赤道潜流时,MY2.5方案暴露出明显不足,其模拟效果要明显差于KPP方案和KT方案。KT方案模拟效果的好坏依赖于混合层底的确定是否准确,其在中高纬度海域的模拟效果要明显优于热带海域。总之,在热带海域,KPP方案的模拟整体效果最好,在中高纬度海域,KPP方案和MY2.5方案差别不大,而KT方案则更适用于中高纬度。
El Nino, as characterized by above average sea surface temperatures in the equatorial tropical Pacific, is the largest source of natural climate variability from sea- sonal to interannual scales and can profoundly reshape the global weather patterns. Currently, the tropical Pacific Ocean appears to be primed for a potentially significant El Nino event, and some similarities exist between the oce- anic and atmospheric states in early 2014 compared to the observations shortly before the onset of the 1997/1998 Super El Nino event. For example, as one of the most important early signs of El Nino, a splitting eastbound propagation of the subsurface warm water is evident over the equatorial Pacific since January 2014. In this study, the pulses of subsurface warm water are reflected by the Kel- vin waves over the equatorial Pacific estimated from the satellite altimetry data. Results show that the current （i.e., March 2014） Kelvin wave over the equatorial Pacific has achieved the largest amplitude compared to those in the corresponding period prior to the E1 Nifio events since the availability of satellite altimetry, and is even significantly larger than the one that preceded the 1997/1998 Super El Nifio event. As the Kelvin waves can help induce El Nino conditions within about 2--4 months, the current fastest/ strongest eastbound propagation of subsurface warm water indicates that the likelihood of an El Nino event will sig- nificantly increase during the next several months in 2014.
ABSTRACT The impact of both initial and parameter errors on the spring predictability barrier （SPB） is investigated using the Zebiak Cane model （ZC model）. Previous studies have shown that initial errors contribute more to the SPB than parameter errors in the ZC model. Although parameter errors themselves are less important, there is a possibility that nonlinear interactions can occur between the two types of errors, leading to larger prediction errors compared with those induced by initial errors alone. In this case, the impact of parameter errors cannot be overlooked. In the present paper, the optimal combination of these two types of errors [i.e., conditional nonlinear optimal perturbation （CNOP） errors] is calculated to investigate whether this optimal error combination may cause a more notable SPB phenomenon than that caused by initial errors alone. Using the CNOP approach, the CNOP errors and CNOP-I errors （optimal errors when only initial errors are considered） are calculated and then three aspects of error growth are compared： （1） the tendency of the seasonal error growth; （2） the prediction error of the sea surface temperature anomaly; and （3） the pattern of error growth. All three aspects show that the CNOP errors do not cause a more significant SPB than the CNOP-I errors. Therefore, this result suggests that we could improve the prediction of the E1 Nifio during spring by simply focusing on reducing the initial errors in this model.
基于HYCOM(Hybrid Coordinate Oceanic Circulation Model),以OFES(OGCM for the Earth Simulator)资料为参考,分析了KPP、MY2.5、KT三种不同混合方案对北太平洋西边界流系的模拟结果的影响。结果表明:三种不同混合方案模拟的上层海洋平均流场与OFES资料相似,但在流向和流幅上略有差异,其中KPP方案模拟的流速与OFES资料最为接近,MY2.5方案次之,KT方案与其差别最大。通过代表性断面上流速的对比分析,对模式就北赤道流、棉兰老流、棉兰老潜流、黑潮的模拟效果进行比较,KPP方案模拟的效果同前人的观测和研究最为接近。分析了北赤道流,棉兰老流,棉兰老潜流,黑潮的流量的季节变化特征,其中KPP方案与OFES资料计算的棉兰老流和棉兰老潜流的季节变化特征与前人描述比较一致,表现为春强秋弱。KPP方案和OFES资料的计算结果表明,北赤道流和棉兰老流大致上是同向变化的,而在冬季棉兰老流同黑潮的变化基本上是一致的。
Collaboration of interannual variabilities and the climate mean state determines the type of E1 Nifio. Recent studies highlight the impact of a La Nifia-like mean state change, which acts to suppress the convection and low-level convergence over the central Pacific, on the predominance of central Pacific （CP） E1 Nifio in the most recent decade. However, how interannual variabilities affect the climate mean state has been less thoroughly investigated. Using a linear shallow-water model, the ef- fect of decadal changes of air-sea interaction on the two types of El Nifio and the climate mean state over the tropical Pacific is examined. It is demonstrated that the predominance of the eastem Pacific （EP） and CP E1 Nino is dominated mainly by relationships between anomalous wind stresses and sea surface temperature （SST）. Furthermore, changes between air-sea interactions from 1980-98 to 1999-2011 prompted the generation of the La Ninalike pattern, which is similar to the background change in the most recent decade.
The accurate simulation of the equatorial sea surlhce temperature （SST） variability is crucial for a proper representation or prediction of the El Nino-Southern Os- cillation （ENSO）. This paper describes the tropical variability simulated by the Max Planck Institute （MPI） forr meteorology coupled atmosphere-ocean general circulation model （CGCM）. A control simulation with pre-industrial greenhouse gases is analyzed, and the simulation of key oceanic features, such as SST, is compared with observa- tions. Results from the 400-yr control simulation show that the model＇s ENSO variability is quite realistic in terms of structure, strength, and period. Also, two related features （the annual cycle of SST and the-phase locking of ENSO events）, which are significant in determining the model＇s performance of realistic ENSO prediction, are further validated to be well reproduced by the MPI cli mate model, which is an atmospheric model ECHAM5 （which fuses the EC tbr European Center and HAM for Hamburg） coupled to an MPI ocean model （MPI-OM）, ECHAMS/MPI-OM.
The sea surface temperature （SST） in the In- dian Ocean affects the regional climate over the Asian continent mostly through a modulation of the monsoon system. It is still difficult to provide an a priori indication of the seasonal variability over the Indian Ocean. It is widely recognized that the warm and cold events of SST over the tropical Indian Ocean are strongly linked to those of the equatorial eastern Pacific. In this study, a statistical prediction model has been developed to predict the monthly SST over the tropical Indian Ocean. This model is a linear regression model based on the lag relationship between the SST over the tropical Indian Ocean and the Nino3.4 （5°S-5°N, 170°W-120°W） SST Index. The pre- dictor （i.e., Nino3.4 SST Index） has been operationally predicted by a large size ensemble E1 Nifio and the Southern Oscillation （ENSO） forecast system with cou- pled data assimilation （Leefs_CDA）, which achieves a high predictive skill of up to a 24-month lead time for the equatorial eastern Pacific SST. As a result, the prediction skill of the present statistical model over the tropical In- dian Ocean is better than that of persistence prediction for January 1982 through December 2009.
Targeted observation is an observation strategy by which the concerned phenomenon is observed. In geoscienee, targeted ob- servation is mainly related to the forecasts of weather events or predictions of climate events. This paper will first review the history of targeted observation, and then introduce the main methods used in targeted observation. The discussion on the theo- retical basis of targeted observation includes its advantages and limitations. After presenting the current situation of domestic and international targeted observations in atmospheric and oceanic sciences, the methods used for targeted observation, and their effect evaluation and testing are mainly discussed here. Finally, the author presents his suggestion about the prospect of further development in the field, and how to extend the method of targeted observation to deal with numerical model errors.
Optimal precursor perturbations of El Nino in the Zebiak-Cane model were explored for three different cost functions. For the different characteristics of the eastern-Pacific （EP） El Nino and the central-Pacific （CP） El Nino, three cost functions were defined as the sea surface temperature anomaly （SSTA） evolutions at prediction time in the whole tropical Pacific, the Nino3 area, and the Nino4 area. For all three cost functions, there were two optimal precursors that developed into El Nino events, called Precursor Ⅰ and Precursor Ⅱ. For Precursor Ⅰ, the SSTA component consisted of an east-west （positive-negative） dipole spanning the entire tropical Pacific basin and the thermocline depth anomaly pattern exhibited a tendency of deepening for the whole of the equatorial Pacific. Precursor Ⅰ can develop into an EP-El Nino event, with the warmest SSTA occurring in the eastern tropical Pacific or into a mixed El Nino event that has features between EP-El Nino and CP-El Nino events. For Precursor Ⅱ, the thermocline deepened anomalously in the eastern equatorial Pacific and the amplitude of deepening was obviously larger than that of shoaling in the central and western equatorial Pacific. Precursor Ⅱ developed into a mixed El Nino event. Both the thermocline depth and wind anomaly played important roles in the development of Precursor Ⅰ and Precursor Ⅱ.
