利用大集合来量化平流层突然变暖及其前兆对北大西洋涛动的影响

P. Bett, Adam A. Scaife, S. Hardiman, H. Thornton, Xiao‐Hua Shen, Lin Wang, Bo Pang
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引用次数: 1

摘要

摘要平流层突然变暖(SSW)事件通常伴随着地表显著的天气和气候影响。通过影响北大西洋涛动(NAO), ssw可导致欧洲和北美部分地区出现极寒期。以前的研究使用观测和自由运行的气候模型来试图确定SSW之前的大气特征,这些特征可以确定随后对地面的影响。然而,有限的观测记录使得很难准确地量化这些关系。在这里,我们使用大量的季节性预测集合。我们首先测试后验是否再现了ssw的观测特征及其表面特征。我们发现,在每年冬季SSW的总体风险(56%)、NAO负响应的SSW频率(65%)、NAO响应的幅度和波数2主导的SSW频率(26%)方面,模拟结果与观测结果在统计上没有区别。我们还评估了在SSW后30 d内的先验条件与NAO反应之间的关系。我们发现,在前体状态中几乎没有信息来指导一个南纬风和另一个南纬风之间随后的NAO行为差异,反映了南纬风事件之间存在实质性的自然变异性。与NAO响应关系最密切的是ssw前极地帽上的海平面压力异常和平流层下层的纬向风异常,两者的相关系数都在0.3左右。南海前的NAO对南海后的状态影响不大。在10hpa的纬向风异常强度与NAO响应也不显著相关。最后,我们发现,在波2主导的SSWs发生后的前10天,平均NAO响应比波1的负响应要强烈得多。然而,无论主导波数如何,11-30天的后续反应非常相似。在所有情况下,复合平均响应是单个SSW事件非常广泛分布的结果,需要使用大集合进行概率分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using large ensembles to quantify the impact of sudden stratospheric warmings and their precursors on the North Atlantic Oscillation
Abstract. Sudden-stratospheric-warming (SSW) events are often followed by significant weather and climate impacts at the surface. By affecting the North Atlantic Oscillation (NAO), SSWs can lead to periods of extreme cold in parts of Europe and North America. Previous studies have used observations and free-running climate models to try to identify features of the atmosphere prior to an SSW that can determine the subsequent impact at the surface. However, the limited observational record makes it difficult to accurately quantify these relationships. Here, we instead use a large ensemble of seasonal hindcasts. We first test whether the hindcasts reproduce the observed characteristics of SSWs and their surface signature. We find that the simulations are statistically indistinguishable from the observations, in terms of the overall risk of an SSW per winter (56 %), the frequency of SSWs with negative NAO responses (65 %), the magnitude of the NAO responses, and the frequency of wavenumber-2-dominated SSWs (26 %). We also assess the relationships between prior conditions and the NAO response in the 30 d following an SSW. We find that there is little information in the precursor state to guide differences in the subsequent NAO behaviour between one SSW and another, reflecting the substantial natural variability between SSW events. The strongest relationships with the NAO response are from pre-SSW sea level pressure anomalies over the polar cap and from zonal-wind anomalies in the lower stratosphere, both exhibiting correlations of around 0.3. The pre-SSW NAO has little bearing on its post-SSW state. The strength of the pre-SSW zonal-wind anomalies at 10 hPa is also not significantly correlated with the NAO response. Finally, we find that the mean NAO response in the first 10 d following wave-2-dominated SSWs is much more strongly negative than in wave-1 cases. However, the subsequent response in days 11–30 is very similar regardless of the dominant wavenumber. In all cases, the composite mean responses are the result of very broad distributions from individual SSW events, necessitating a probabilistic analysis using large ensembles.
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