Global Assessment of Atmospheric River Prediction Skill
Global Assessment of Atmospheric River Prediction Skill
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DOI：
10.1175/jhm-d-17-0135.1
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发表时间：
2018-02-01
影响因子：
3.8
通讯作者：
Vitart, Frederic
中科院分区：
文献类型：
--
作者：
DeFlorio, Michael J.;Waliser, Duane E.;Vitart, Frederic
大气河流（ARs）是一种水平输送水汽的全球性现象，与水文极端事件有关。在这项研究中，大气河流技能（ATRISK）算法的介绍，量化AR预测技能，在基于对象的框架下，使用亚季节到季节（S2 S）项目的全球后报数据从欧洲中期天气预报中心（ECMWF）模型。AR预测技能的依赖性是全球性的季节，提前时间，观测和预测的AR之间的距离。平均值的每日AR预测技能饱和约7-10天，季节变化是最高的北方半球的海洋盆地，AR预测技能增加了15%-20%，在7天的领先期在北方冬季相对于北方夏季。AR命中率和虚警率被明确考虑使用相对工作特性（ROC）曲线。该分析表明，在正厄尔尼诺-南方涛动（ENSO）条件下，AR预测效用在北太平洋/美国西部地区提前10天增加，在北大西洋/英国提前7天和10天增加。在负的北极涛动（AO）条件下，北太平洋/美国西部地区在负的太平洋-北美（PNA）遥相关条件下提前10天减少。在厄尔尼诺+正PNA条件下，北太平洋/美国西部的AR预测效用异常大幅增加，提前10天，在拉尼娜+负PNA条件下，北大西洋/英国提前7天。这些结果代表了AR预测技能的第一次全球评估，并突出了调节区域AR预测技能的气候变率条件。
Atmospheric rivers (ARs) are global phenomena that transport water vapor horizontally and are associated with hydrological extremes. In this study, the Atmospheric River Skill (ATRISK) algorithm is introduced, which quantifies AR prediction skill in an object-based framework using Subseasonal to Seasonal (S2S) Project global hindcast data from the European Centre for Medium-Range Weather Forecasts (ECMWF) model. The dependence of AR forecast skill is globally characterized by season, lead time, and distance between observed and forecasted ARs. Mean values of daily AR prediction skill saturate around 7-10 days, and seasonal variations are highest over the Northern Hemispheric ocean basins, where AR prediction skill increases by 15%-20% at a 7-day lead during boreal winter relative to boreal summer. AR hit and false alarm rates are explicitly considered using relative operating characteristic (ROC) curves. This analysis reveals that AR forecast utility increases at 10-day lead over the North Pacific/western U.S. region during positive El Nino-Southern Oscillation (ENSO) conditions and at 7-and 10-day leads over the North Atlantic/U.K. region during negative Arctic Oscillation (AO) conditions and decreases at a 10-day lead over the North Pacific/western U.S. region during negative Pacific-North America (PNA) teleconnection conditions. Exceptionally large increases in AR forecast utility are found over the North Pacific/western United States at a 10-day lead during El Nino + positive PNA conditions and over the North Atlantic/United Kingdom at a 7-day lead during La Nina + negative PNA conditions. These results represent the first global assessment of AR prediction skill and highlight climate variability conditions that modulate regional AR forecast skill.