%0 Journal Article %1 Davey2014Probability %A Davey, M. K. %A Brookshaw, A. %A Ineson, S. %D 2014 %J Climate Risk Management %K euporias %P 5--24 %R 10.1016/j.crm.2013.12.002 %T The probability of the impact of ENSO on precipitation and near-surface temperature %U http://dx.doi.org/10.1016/j.crm.2013.12.002 %V 1 %X The widespread influence of El Niño 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 Niño and La Niña 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.

@article{Davey2014Probability, abstract = {The widespread influence of El Ni\~{n}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\~{n}o and La Ni\~{n}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.}, added-at = {2019-08-14T18:35:35.000+0200}, author = {Davey, M. K. and Brookshaw, A. and Ineson, S.}, biburl = {https://www.bibsonomy.org/bibtex/2ce16fe76f1d7a11a67b54b05a6423a44/karinawilliams}, citeulike-article-id = {12905086}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.crm.2013.12.002}, doi = {10.1016/j.crm.2013.12.002}, interhash = {fa360013e68298a5b563f39978f02120}, intrahash = {ce16fe76f1d7a11a67b54b05a6423a44}, issn = {22120963}, journal = {Climate Risk Management}, keywords = {euporias}, month = dec, pages = {5--24}, posted-at = {2014-01-10 15:57:54}, priority = {2}, timestamp = {2019-08-14T18:35:35.000+0200}, title = {The probability of the impact of {ENSO} on precipitation and near-surface temperature}, url = {http://dx.doi.org/10.1016/j.crm.2013.12.002}, volume = 1, year = 2014 }