National Climate Center, China Meteorological Administration
厄尔尼诺-南方涛动（ENSO）春季预报障碍是ENSO预测的一个难点问题，弄清影响春季热带太平洋地区海表温度(SST)变化的动力和热力作用对于理解ENSO关键区SST的异常变化及ENSO春季预报障碍成因非常重要。本文利用数值模拟手段，产生一套1986-2017年间相互协调的逐月海表风应力、感热、潜热、长波和短波净辐射能量、海洋流场等观测代用数据。利用这些数据对影响海温变化的动力和热力作用及其相对重要性进行了诊断分析，结果表明：（1）与其他季节相比，春季Ni?o3.4区海洋表层温度（后文中用 表示）呈现出独特的先增暖后趋冷的不对称季节性转换特征，这一变化主要是由于影响 的大气风应力、海流以及净能量在春季均表现出明显的季节性转换过程。进一步的分析表明，热力作用对局地海温的季节性变化影响最为重要，而经向平流输送起到了反向作用，不利于该区域 的季节性转变，纬向平流输送仅在春季转为弱的正贡献，浅层垂直平流输送对春季 变化的影响很小。（2）动力热力作用与 异常的变化倾向相关关系也表明，春季Ni?o3.4区热力作用与 异常变化呈现显著的正相关，纬向海流异常的输送项也表现为正相关，而经向海流输送项展现出由负相关向正相关转化的特征。（3）对Ni?o3.4区 变化的方差贡献分析结果表明，春季热力作用对 的异常变化的贡献达50%以上，相关系数超0.7，其次是纬向、经向平流项贡献，各占10-20%左右，但两者作用相反，其他项贡献较小。
The spring predictability barrier (SPB) of El Ni?o-Southern Oscillation (ENSO) is a difficult problem in the ENSO prediction. To understand how the dynamic and thermal factors affect the variability of sea surface temperature over the tropical Pacific Ocean during the spring is very important to understand the changes of SST in key area and resolve the SPB problem. In this work, a set of monthly data including sea surface wind stresses, sensible heat flux, latent heat flux, longwave radiation, shortwave radiation, and ocean current fields which are coordinated with each other during 1986 -2017 are generated by numerical model simulation. Based upon these data, we analyzed and diagnosed the dynamic and thermal influences and their contributions to the variability of the sea surface temperature (hereafter, ). The main results show as follows: (1) Compared with other seasons, the sea surface temperature presents a unique asymmetric seasonal shift that is from warming to cooling in the Ni?o3.4 area during the spring. It is due to a similar shift in the wind stress, net energy fluxes, and ocean current which have a robust relationship with . Further analyses demonstrate that the thermal effect plays an important role in the variability of local . Differently, the meridional advection always shows a negative contribution to the seasonal variability of . Meanwhile, the zonal advection terms turn into a cooling effect from a warming effect to during the spring, and the vertical advection effect is quite weak. (2) The interannual correlation between the tendency of anomaly and the dynamic/thermal effect shows that the thermal heating is positively associated with the Ni?o3.4 anomaly in the spring, as well as the zonal advection. However, the correlation between the meridional advection and the anomaly changes from negative to positive during the spring. (3) The quantitative analysis of the dynamic and thermal variance contributions in the Ni?o3.4 region also suggests that, the contribution rate of thermal effect is more than 50%, and the corresponding correlation coefficient is over 0.7. The contribution of zonal and meridional advection is about 10- 20%, respectively, but they are opposite to each other. And the other items provide less contribution.