The dynamics and multi-year predictability of La Nina

拉尼娜是热带太平洋上的一种反复出现的冷却模式，人们认为它与美国南部冬季降水减少有关。历史观察表明，拉尼娜事件可以持续两年或更长时间，这一特征可能会使其相关的干旱影响更加持久。预报系统通常能够预测拉尼娜的爆发，因为它们几乎总是跟随厄尔尼诺。然而，人们对多年拉尼娜事件的可预测性知之甚少，因为目前可操作的ENSO预报仅限于8个月。这个项目解决了一系列问题，这些问题对于提高我们预测这些事件的能力至关重要。该项目将确定能够产生热带太平洋多年预测的过程、初始海洋状态和模式。预测拉尼娜现象是否会再次出现，对于预测全球范围内相关干旱的持续时间至关重要。这个项目的结果可能会提高我们预测拉尼娜引起的美国干旱的强度和持续时间的能力。观测表明，拉尼娜事件往往会持续一年，在世界各地造成持续的干旱和洪水影响。对这些为期两年的拉尼娜事件的预报通常不是由业务预报系统产生的，因为它们侧重于较短的筹备时间，通常长达八个月。该项目将展示熟练预测两年拉尼娜的可行性。将使用共同体地球系统模式第一版(CESM1)进行多年预报，这是一个模拟现实和高度可预测的两年拉尼娜的模式。将利用参与耦合模式相互比较项目(CMIP5)第五阶段的四个气候模式进行的十年气候预测，探讨两年可预测性的模式依赖性。这些用CESM1和CMIP5进行的回溯性预报(后播)将被用来探索造成历史2年拉尼娜可预报性的物理过程。高级诊断将被用来确定引起预报传播的过程。将分析历史上两年拉尼娜事件与其观测轨迹之间的差异，以确定其可预测和不可预测的驱动因素。用CESM1进行的一套现有的季节性预报将扩展到产生在3月、6月和9月启动的两年后播。与11月启动的现有十年预测套件一起，拟议的延期将用于探索不同提前期、初始状态和季节性的影响。这一奖励反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

La Niña, a recurrent cooling pattern over the tropical Pacific Ocean, has been linked to reduced wintertime precipitation across the southern tier of the United States. Historical observations show that La Niña events can last two years or longer, a feature that could make their associated drought impacts more persistent. Forecast systems are generally able to predict the onset of La Niña, as they virtually always follow El Niño. However, little is known about the predictability of multi-year La Niña events because current operational ENSO forecasts are limited to 8 months. This project addresses a series of questions that are critical to improve our ability to predict these events. The project will determine the processes, initial ocean states, and models that can produce skillful multi-year predictions of tropical Pacific. Predicting whether La Niña will return for a second year is critical for predicting the duration of associated droughts throughout the world. Results from this project can potentially improve our ability to predict both the strength and duration of US droughts caused by La Niña.Observations show that La Niña events tend to last for an additional year, causing persistent drought and flooding impacts in regions throughout the world. Forecasts of these 2-year La Niña events are not routinely generated by operational prediction systems because they focus on shorter lead times, typically up to eight months. This project will demonstrate the feasibility of skillful predictions of 2-year La Niña. Multi-year forecasts will be performed using the Community Earth System Model Version 1 (CESM1), a model that simulates realistic and highly predictable 2-year La Niña. Model dependence of 2-year predictability will be explored using decadal climate predictions performed by four climate models that participated in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). These retrospective forecasts (hindcasts) performed with CESM1 and CMIP5 will be used to explore the physical processes responsible for the predictability of historical 2-year La Niña. Advanced diagnostics will be used to attribute the processes causing forecast spread. Discrepancies in the hindcasts of historical 2-year La Niña events relative to their observed trajectory will be analyzed to identify their predictable and unpredictable drivers. An existing suite of seasonal predictions performed with CESM1 will be extended to produce 2-year hindcasts initialized in March, June, and September. Together with the existing suite of decadal predictions initialized in November, the proposed extension will be used to explore the impact of different lead times, initial state, and seasonality.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.