California Winter Precipitation Predictability: Insights From the Anomalous 2015–2016 and 2016–2017 Seasons

The unexpected dry 2015–2016 El Niño winter and extremely wet 2016–2017 La Niña winter in California challenged current seasonal prediction systems. Using the Met Office GloSea5 forecast ensemble, we study the precipitation and circulation differences between these seasons and identify processes rel...

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Bibliographic Details
Main Authors: Singh, Deepti, Ting, Mingfang, Scaife, Adam A., Martin, Nicola
Format: Text
Language:unknown
Published: Columbia University 2018
Subjects:
Online Access:https://dx.doi.org/10.7916/d8k08n7b
https://academiccommons.columbia.edu/doi/10.7916/D8K08N7B
Description
Summary:The unexpected dry 2015–2016 El Niño winter and extremely wet 2016–2017 La Niña winter in California challenged current seasonal prediction systems. Using the Met Office GloSea5 forecast ensemble, we study the precipitation and circulation differences between these seasons and identify processes relevant to California precipitation predictions. The ensemble mean accurately predicts the midlatitude atmospheric circulation differences between these years, indicating that these differences were predictable responses to the strong oceanic forcing differences. The substantial California precipitation differences were poorly predicted with large uncertainty. Notable differences in high-latitude circulation anomalies associated with internal variability distinguish the ensemble members that successfully simulate precipitation from those that do not. Specifically, accurate representation of the Arctic Oscillation phase differences improves the accuracy of simulated precipitation differences but these differences were not well predicted in the ensemble mean for these seasons. Improved representation of high-latitude processes such as the Arctic Oscillation and polar-midlatitude teleconnections could therefore improve California seasonal predictions.