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The probability of the impact of {ENSO} on precipitation and near-surface temperature

机译:{ENSO}影响降水和近地表温度的可能性

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摘要

Abstract The widespread influence of El Ni?o Southern Oscillation (ENSO) events on regional climate is well known, and such events can have considerable socio-economic impact. Thus an aspect of practical importance is the chance of the occurrence of various climate categories given that {ENSO} conditions are predicted or underway. Using observational and re-analysis datasets for precipitation and near-surface temperature this aspect is analysed systematically in terms of three near-equiprobable categories (below normal, near normal, above normal) to quantify the probability of their occurrence when central-east equatorial Pacific sea surface temperatures are abnormal, as during El Ni?o and La Ni?a events, with emphasis on land areas and on seasonal (three-month average) values. By using recently available gridded datasets, this analysis complements and updates previous analyses of {ENSO} impact. Spatial maps of the rate of occurrence of various categories conditional on {ENSO} state are obtained by point-by-point analysis of the global datasets. Consistent with previous analyses, several regions with rates well above those expected by chance are identified, in both tropical and extratropical sectors. Regional averages are used to examine a selection of these in more detail, in particular to describe the strong seasonal dependencies of {ENSO} influences. These depend on the interplay between the seasonality of ENSO, of teleconnection pathways and of local climate: indeed in several locations opposite effects arise at different times of year. The methodology is based on contingency tables calculated from historical records, and effectively quantifies the probability that, for example, above-normal rainfall will occur in a given season and location conditional on the state of equatorial Pacific sea surface temperature. The rates of occurrence provide more directly relevant information for risk assessment and management than do statistics such as correlations or composites. Each {ENSO} event is different and occurs in conjunction with other climatic factors, so while the historical rates provide general guidance they should not be regarded as a prediction of impacts for a particular imminent or ongoing {ENSO} event.
机译:摘要厄尔尼诺南方涛动(ENSO)事件对区域气候的广泛影响是众所周知的,这些事件可能具有相当大的社会经济影响。因此,鉴于{ENSO}状况已被预测或正在进行,实际意义上的一个方面是出现各种气候类别的机会。使用观测和重新分析数据集的降水和近地表温度,系统对这三个方面进行了系统分析,包括近乎可划分的三个类别(低于正常水平,接近正常水平,高于正常水平),以量化它们在赤道中东部出现的可能性在厄尔尼诺现象和拉尼娜事件期间,海表温度异常,并着重于陆地面积和季节性(三个月的平均值)值。通过使用最近可用的网格化数据集,此分析可以补充和更新先前对{ENSO}影响的分析。通过对全局数据集进行逐点分析,可以获得以{ENSO}状态为条件的各种类别的发生率的空间图。与以前的分析一致,在热带和温带地区,发现了几个率远高于偶然预期的区域。区域平均值用于更详细地检查这些选项,尤其是描述{ENSO}影响的强烈季节性依存关系。这些取决于ENSO的季节性,远程连接路径和当地气候之间的相互影响:确实,在某些地方,一年中的不同时间会产生相反的影响。该方法基于从历史记录中计算得出的列联表,并有效地量化了概率,例如,在给定的季节和位置(以赤道太平洋海表温度状态为条件),将出现高于正常水平的降雨。与诸如相关性或综合性等统计数据相比,发生率为风险评估和管理提供了更直接相关的信息。每个{ENSO}事件都是不同的,并且与其他气候因素一起发生,因此,尽管历史汇率提供了一般指导,但不应将其视为对即将到来或正在进行的{ENSO}事件的影响的预测。

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