Predictability of 2-year La Nia events in a coupled general circulation model
Predictability of 2-year La Nia events in a coupled general circulation model
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DOI：
10.1007/s00382-017-3575-3
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发表时间：
2017-12-01
期刊：
影响因子：
4.6
通讯作者：
Karspeck, Alicia
中科院分区：
文献类型：
--
作者：
DiNezio, Pedro N.;Deser, Clara;Karspeck, Alicia
拉尼娜现象持续时间的可预测性是使用共同体地球系统模式第1版（CESM 1）评估的，CESM 1是一个耦合气候模式，能够模拟厄尔尼诺/南方涛动现象的关键特征，包括拉尼娜现象的多年持续时间。一个1800年长的控制模拟的统计分析表明，一个强的温跃层放电或强厄尔尼诺现象可以导致拉尼娜现象的条件，最后2年（以下称为2年LN）。这种关系表明，2年LN可能提前18至24个月预测。完美的模型预测CESM 1被用来进一步探讨2年LN和“放电”和“厄尔尼诺峰”预测之间的联系。Encourage预测初始化1月和7月的厄尔尼诺峰值振幅和峰值温跃层放电分别与海洋状态相吻合。三种情况下，这些预测因素的不同幅度被认为是在总共六个合奏。每个“峰值厄尔尼诺”和“排放”集合预报分别由30或20个成员组成，通过向每个成员特有的大气初始条件添加无限小的扰动而产生。预报结果表明，用第二年SST指数-3.4的潜在预报效用（PPU）衡量的2年LN的可预报性与初始条件的大小有关。强温跃层放电或强峰厄尔尼诺振幅初始化的预测显示较高的PPU比那些初始条件较弱的幅度。从较弱的预测特征的状态初始化的预测是较难预测的，主要是因为整体平均信号较小，因此PPU由于预测传播的影响而降低。的误差增长的预测，测量的-3.4 SST指数的传播，是独立的初始条件，似乎是由风变率驱动的东南热带太平洋和赤道西太平洋。对观测数据的分析支持了模拟结果，表明“温跃层放电”和“厄尔尼诺峰”预测因子也可用于诊断自然界发生多年拉尼娜事件的可能性。这些结果表明，CESM 1可以提供熟练的长期业务预报在特定的初始条件下。
The predictability of the duration of La Nia is assessed using the Community Earth System Model Version 1 (CESM1), a coupled climate model capable of simulating key features of the El Nio/Southern Oscillation (ENSO) phenomenon, including the multi-year duration of La Nia. Statistical analysis of a 1800 year long control simulation indicates that a strong thermocline discharge or a strong El Nio can lead to La Nia conditions that last 2 years (henceforth termed 2-year LN). This relationship suggest that 2-year LN maybe predictable 18 to 24 months in advance. Perfect model forecasts performed with CESM1 are used to further explore the link between 2-year LN and the "Discharge" and "Peak El Nio" predictors. Ensemble forecasts are initialized on January and July coinciding with ocean states characterized by peak El Nio amplitudes and peak thermocline discharge respectively. Three cases with different magnitudes of these predictors are considered resulting in a total of six ensembles. Each "Peak El Nio" and "Discharge" ensemble forecast consists of 30 or 20 members respectively, generated by adding a infinitesimally small perturbation to the atmospheric initial conditions unique to each member. The forecasts show that the predictability of 2-year LN, measured by the potential prediction utility (PPU) of the -3.4 SST index during the second year, is related to the magnitude of the initial conditions. Forecasts initialized with strong thermocline discharge or strong peak El Nio amplitude show higher PPU than those with initial conditions of weaker magnitude. Forecasts initialized from states characterized by weaker predictors are less predictable, mainly because the ensemble-mean signal is smaller, and therefore PPU is reduced due to the influence of forecast spread. The error growth of the forecasts, measured by the spread of the -3.4 SST index, is independent of the initial conditions and appears to be driven by wind variability over the southeastern tropical Pacific and the western equatorial Pacific. Analysis of observational data supports the modeling results, suggesting that the "thermocline discharge" and "Peak El Nio" predictors could also be used to diagnose the likelihood of multi-year La Nia events in nature. These results suggest that CESM1 could provide skillful long-range operational forecasts under specific initial conditions.