IS THE JANUARY THAW A STATISTICAL PHANTOM?

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The existence of the January thaw, a purported systematic anomalous warming in daily mean temperatures at northeastern U.S. stations during late January, is investigated quantitatively. A key idea in the analysis is that winter temperatures are intrinsically more variable, and this property must be accounted for when judging the unusualness of excursions of daily mean temperatures from a smooth climatic mean function. Accordingly the daily mean temperature departures are expressed nondimensionally by dividing by appropriate standard deviations that vary through the year. The warm excursion in observed records for late January is not always the most extreme such excursion in the nondimensionalized data, even when the definition of “excursion” is optimized to emphasize the late January event. Hypothesis tests based on time series models with smoothly varying climatologies (i.e., with no anomalous features such as the January thaw, by construction) are used to evaluate the statistical significance of the observed January thaws. The synthetic series produce many apparent events of similar character and magnitudes, although occurring randomly throughout the year and equally divided between warm and cool deviations. It is thus concluded that the effects of sampling in finite climate records are wholly adequate to account for the existence of January thaw “features” in northeastern U.S. temperature data.

Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York

NOAA National Severe Storms Laboratory, Norman, Oklahoma

CORRESPONDING AUTHOR: Daniel S. Wilks, Dept. of Earth and Atmospheric Sciences, Cornell University, I 123 Bradfield Hall, Ithaca, New York 14853-1901, E-mail: dsw5@cornell.edu

The existence of the January thaw, a purported systematic anomalous warming in daily mean temperatures at northeastern U.S. stations during late January, is investigated quantitatively. A key idea in the analysis is that winter temperatures are intrinsically more variable, and this property must be accounted for when judging the unusualness of excursions of daily mean temperatures from a smooth climatic mean function. Accordingly the daily mean temperature departures are expressed nondimensionally by dividing by appropriate standard deviations that vary through the year. The warm excursion in observed records for late January is not always the most extreme such excursion in the nondimensionalized data, even when the definition of “excursion” is optimized to emphasize the late January event. Hypothesis tests based on time series models with smoothly varying climatologies (i.e., with no anomalous features such as the January thaw, by construction) are used to evaluate the statistical significance of the observed January thaws. The synthetic series produce many apparent events of similar character and magnitudes, although occurring randomly throughout the year and equally divided between warm and cool deviations. It is thus concluded that the effects of sampling in finite climate records are wholly adequate to account for the existence of January thaw “features” in northeastern U.S. temperature data.

Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York

NOAA National Severe Storms Laboratory, Norman, Oklahoma

CORRESPONDING AUTHOR: Daniel S. Wilks, Dept. of Earth and Atmospheric Sciences, Cornell University, I 123 Bradfield Hall, Ithaca, New York 14853-1901, E-mail: dsw5@cornell.edu
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