Abstract

Anomalies of monthly mean surface temperature observed at 109 stations in the United States from 1948 through 1981 are related to concurrent monthly mean 700 mb height anomalies at a network of 133 grid points in North America and the surrounding oceans. The data are screened by a stepwise forward selection procedure to yield multiple regression equations for specifying the monthly mean temperature anomaly at each city and month from the field of simultaneous 700 mb height plus the previous month's temperature anomaly. A short set of equations selected on a subjective basis and containing an average of five terms per equation tested as well as equations selected by any other cutoff criterion. Various properties of the short specification equations and related atmospheric characteristics are described on a regional, seasonal and month-to-month basis. Six features are mapped for the months of January, April, July and October: the reduction of variance, standard error of estimate, standard deviation, contribution of previous temperature, one-month lag autocorrelation, and frequency of grid-point selection; marked regional differences are noted. The first four of the above features are then averaged for the entire United States and graphed month by month. The annual cycle of other properties, including the composition of the specification equations and the value of various cutoff criteria used in their selection, is also described. Systematic spatial and temporal variations in the characteristics of temperature variability, persistence and specification equations are illustrated.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.