%0 Journal Article %1 JOC:JOC4263 %A Cannon, Alex J. %D 2015 %I John Wiley & Sons, Ltd %J International Journal of Climatology %K ENSO GEV USA nonlinear nonstationarity precipitation %P n/a--n/a %R 10.1002/joc.4263 %T Revisiting the nonlinear relationship between ENSO and winter extreme station precipitation in North America %U http://dx.doi.org/10.1002/joc.4263 %X While researchers have identified teleconnections between El Niño-Southern Oscillation (ENSO) and extended winter precipitation extremes in North America using generalized extreme value (GEV) models, the regional form of the statistical relationship remains an open question. Past work has shown that relatively warm ENSO conditions may be needed to trigger a nonlinear response over North America. However, studies that stratify winters into La Niña, neutral, and El Niño phases have found that precipitation extremes in neutral/La Niña winters respond differently than in El Niño winters, whereas studies that stratify ENSO data into cold/warm conditions have not found evidence for a coherent nonlinear response. Data and methodological differences have made direct comparison between results difficult. In this study, evidence for a nonlinear association between ENSO and precipitation extremes is reassessed by fitting stationary and linear/nonlinear GEV regression models, with the Niño3.4 index as a covariate, to 1-, 5-, and 10-day extended winter precipitation maxima. Two types of nonlinear model – both one-sided GEV regressions where linear relationships are allowed to differ above/below a Niño3.4 index threshold – are considered. In the first, following past work, the breakpoint is fixed at zero, that is stratifying data into warm/cold conditions. In the second, to see whether there is evidence for a differential neutral/La Niña and El Niño response, the breakpoint is allowed to vary freely. Due to the non-nested nature of the set of models, the Akaike Information Criterion is used to assess the relative support for each model. Depending on accumulation time-scale, the strength of evidence favours nonlinear models at 28%–30% of stations when the Niño3.4 breakpoint is free to vary, versus just 3% with a fixed breakpoint. Optimum Niño3.4 breakpoints are positive (> +0.4°C) in the majority of the nonlinear models, confirming that ENSO/precipitation relationships differs between La Niña/neutral and El Niño winters.

@article{JOC:JOC4263, abstract = {While researchers have identified teleconnections between El Niño-Southern Oscillation (ENSO) and extended winter precipitation extremes in North America using generalized extreme value (GEV) models, the regional form of the statistical relationship remains an open question. Past work has shown that relatively warm ENSO conditions may be needed to trigger a nonlinear response over North America. However, studies that stratify winters into La Niña, neutral, and El Niño phases have found that precipitation extremes in neutral/La Niña winters respond differently than in El Niño winters, whereas studies that stratify ENSO data into cold/warm conditions have not found evidence for a coherent nonlinear response. Data and methodological differences have made direct comparison between results difficult. In this study, evidence for a nonlinear association between ENSO and precipitation extremes is reassessed by fitting stationary and linear/nonlinear GEV regression models, with the Niño3.4 index as a covariate, to 1-, 5-, and 10-day extended winter precipitation maxima. Two types of nonlinear model – both one-sided GEV regressions where linear relationships are allowed to differ above/below a Niño3.4 index threshold – are considered. In the first, following past work, the breakpoint is fixed at zero, that is stratifying data into warm/cold conditions. In the second, to see whether there is evidence for a differential neutral/La Niña and El Niño response, the breakpoint is allowed to vary freely. Due to the non-nested nature of the set of models, the Akaike Information Criterion is used to assess the relative support for each model. Depending on accumulation time-scale, the strength of evidence favours nonlinear models at 28%–30% of stations when the Niño3.4 breakpoint is free to vary, versus just 3% with a fixed breakpoint. Optimum Niño3.4 breakpoints are positive (> +0.4°C) in the majority of the nonlinear models, confirming that ENSO/precipitation relationships differs between La Niña/neutral and El Niño winters.}, added-at = {2015-02-16T13:10:20.000+0100}, author = {Cannon, Alex J.}, biburl = {https://www.bibsonomy.org/bibtex/2f8f61c8b80c2d9e237db8b4780ffd830/marsianus}, description = {Revisiting the nonlinear relationship between ENSO and winter extreme station precipitation in North America - Cannon - 2015 - International Journal of Climatology - Wiley Online Library}, doi = {10.1002/joc.4263}, interhash = {0bb0db781b8e55305bd50b7431e11af6}, intrahash = {f8f61c8b80c2d9e237db8b4780ffd830}, issn = {1097-0088}, journal = {International Journal of Climatology}, keywords = {ENSO GEV USA nonlinear nonstationarity precipitation}, pages = {n/a--n/a}, publisher = {John Wiley & Sons, Ltd}, timestamp = {2015-02-16T13:10:20.000+0100}, title = {Revisiting the nonlinear relationship between ENSO and winter extreme station precipitation in North America}, url = {http://dx.doi.org/10.1002/joc.4263}, year = 2015 }