The Boreal Winter El Nino Precipitation Response Over North America: Insights Into Why January Is More Difficult To Predict Than February

JOURNAL OF CLIMATE(2020)

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摘要
This study examines the within-season monthly variation of the El Nino response over North America during December-March using the NASA/GEOS model. In agreement with previous studies, the skill of 1-month-lead GEOS coupled model forecasts of precipitation over North America is largest (smallest) for February (January), with similar results in uncoupled mode. A key finding is that the relatively poor January skill is the result of the model placing the main circulation anomaly over the northeast Pacific slightly to the west of the observed, resulting in precipitation anomalies that lie off the coast instead of over land as observed. In contrast, during February the observed circulation anomaly over the northeast Pacific shifts westward, lining up with the predicted anomaly, which is essentially unchanged from January, resulting in both the observed and predicted precipitation anomalies remaining off the coast. Furthermore, the largest precipitation anomalies occur along the southern tier of states associated with an eastward extended jet-something that the models capture reasonably well. Simulations with a stationary wave model indicate that the placement of January El Nino response to the west of the observed over the northeast Pacific is the result of biases in the January climatological stationary waves, rather than errors in the tropical Pacific El Nino heating anomalies in January. Furthermore, evidence is provided that the relatively poor simulation of the observed January climatology, characterized by a strengthened North Pacific jet and enhanced ridge over western North America, can be traced back to biases in the January climatology heating over the Tibet region and the tropical western Pacific.
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关键词
Climate variability, El Nino, Seasonal forecasting, Climate models, Model evaluation/performance, Reanalysis data
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