Document Type
Article
Abstract
Meteorologists who work in the energy commodities market continue to investigate ways to enhance predictions of seasonal temperature anomalies using oceanic/atmospheric indices. This study examines the relationship of three climate indices – ENSO (El Niño/Southern Oscillation), PNA (Pacific North American) and NAO (North Atlantic Oscillation) – to heating degree day (HDD) totals accumulated in 11 cities in the Midwest and northeastern United States, to determine which, if any, has predictive power. The data covers the 48-year period between 1951/52 and 1998/99, and focuses on two periods either side of 1 January (i.e. the winter months of October–December and January–April). The index most strongly related to the HDD anomalies during both winter periods was NAO. NAO values were negative for cold (above-average HDD) anomalies occurring prior to and after 1 January, while the NAO values were generally positive during warm (below-average HDD) anomalies. During cold anomalies, the PNA values were generally positive in the three months before 1 January and negative afterwards, indicating that different atmospheric teleconnection patterns cause similar temperature anomalies in these regions. The relationship between the equatorial Pacific sea-surface temperatures (SST) data and temperature anomalies was the weakest. Confidence in these relationships increased when the extreme HDD anomaly years were examined. These results indicated that the relationships of climate indices to HDD anomalies exist and that these would be useful in developing and improving seasonal predictions for business applications.
Publication Date
1-1-2002
Recommended Citation
Changnon, D., J. Thompson, T. April, E. Schmidt, M. Falout, J.B. Davis, and M. Russo, 2002: Efforts to improve predictions of urban winter heating anomalies using various climate indices. Meteorological Applications, 9, 105-111.
Original Citation
Changnon, D., J. Thompson, T. April, E. Schmidt, M. Falout, J.B. Davis, and M. Russo, 2002: Efforts to improve predictions of urban winter heating anomalies using various climate indices. Meteorological Applications, 9, 105-111.
Department
Department of Geographic and Atmospheric Sciences
Legacy Department
Department of Geography
ISSN
1350-4827
Language
eng
Publisher
Royal Meteorological Society
Comments
D0 Collaboration