An analog forecast method designed for monthly and
seasonal outlooks is applied to the Arctic. The analog selection process uses
pattern matches based on agreement with historical data to identify past years
with similar distributions of sea level pressure, upper-air geopotential
height, surface and upper-air temperatures, precipitation, and sea surface
temperatures. The evolution of the atmosphere in the analog years is then the
basis of a prediction for the target year. Users can choose the predictor
domain, the predictand domain, the variable to be predicted, and the number of
antecedent months on which the analog selection is based. We provide an example
of a monthly forecast generated by the analog forecast tool. In comparisons
with operational dynamical model forecasts over the period 2012-2019, the
analog system underperforms the dynamical models in middle latitudes but
generally outperforms the dynamical models in monthly forecasts of surface air
temperatures in the Arctic. The improvement over the dynamical models is
especially apparent in the late summer and early autumn (August-October).
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