Persistence of North Pacific Sea Surface Temperature and Atmospheric Flow Patterns

Jerome Namias Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

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Xiaojun Yuan Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

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Daniel R. Cayan Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

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Abstract

North Pacific monthly sea surface temperature (SST) anomalies are more persistent than a first-order Markev process, often lasting for more than 5 months. Sea surface temperature persistence undergoes an annual cycle that is attributable to the depth of the surface mixed layer and to the annual cycle of focing. For a given lag, the pattern correlation is minimum when it involves SST during the summer months and maximum when it involves SST during the winter months. Average winter SST anomalies that have exhibited greatest persistence during the last four decades have been negative in the central North Pacific and positive along the West Coast but antipersistent SST anomalies have not confermed to a repeated pattern. The atmospheric 700 mb height anomalies associated with high persistence SST cases indicate that strong SST persistence is associated with long-lasting atmospheric anomaly patterns. For highly persistent January SST anamalies, 700 mb anomalies often last from December through February. The high persistence 700 mb anomalies tend to be negative over the east-central North Pacific and positive over North America, with strong teleconnections. This pattern translates to strengthened westerlies over the subtropics and weakened westerlies in middle latitudes across the North Pacific—a zonal wind profile that is nearly opposite to that which appeared in low persistency SST cases.

Over the four decades since 1947, North Pacific SST persistence has undergone substantial multiyear variability, and has increased significantly since the beginning of this record. Related low-frequency fluctuations as well as linear trends, have occurred in the zonal mean subtropical westerlies across the North Pacific and in related large-scale atmospheric indices, the PNA pattern and the Southern Oscillation Index.

Abstract

North Pacific monthly sea surface temperature (SST) anomalies are more persistent than a first-order Markev process, often lasting for more than 5 months. Sea surface temperature persistence undergoes an annual cycle that is attributable to the depth of the surface mixed layer and to the annual cycle of focing. For a given lag, the pattern correlation is minimum when it involves SST during the summer months and maximum when it involves SST during the winter months. Average winter SST anomalies that have exhibited greatest persistence during the last four decades have been negative in the central North Pacific and positive along the West Coast but antipersistent SST anomalies have not confermed to a repeated pattern. The atmospheric 700 mb height anomalies associated with high persistence SST cases indicate that strong SST persistence is associated with long-lasting atmospheric anomaly patterns. For highly persistent January SST anamalies, 700 mb anomalies often last from December through February. The high persistence 700 mb anomalies tend to be negative over the east-central North Pacific and positive over North America, with strong teleconnections. This pattern translates to strengthened westerlies over the subtropics and weakened westerlies in middle latitudes across the North Pacific—a zonal wind profile that is nearly opposite to that which appeared in low persistency SST cases.

Over the four decades since 1947, North Pacific SST persistence has undergone substantial multiyear variability, and has increased significantly since the beginning of this record. Related low-frequency fluctuations as well as linear trends, have occurred in the zonal mean subtropical westerlies across the North Pacific and in related large-scale atmospheric indices, the PNA pattern and the Southern Oscillation Index.

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