The significance of synoptic patterns identified by the Kirchhofer technique: A Monte Carlo approach

✍ Scribed by Kaufmann, Robert K.; Snell, Seth E.; Gopal, Sucharita; Dezzani, Ray

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 423 KB
• Volume: 19
• Category: Article
• ISSN: 0899-8418
• DOI: 10.1002/(sici)1097-0088(199905)19:6<619::aid-joc385>3.0.co;2-9

✦ Synopsis

The Kirchhofer technique for identifying spatial patterns in climate data depends on the threshold and minimum size used to define the groups. As a result, the analyst cannot be sure whether the groups defined by the Kirchhofer technique represent meaningful meteorological phenomena or whether they emerge due to random chance. Monte Carlo techniques are used to generate a three-dimensional surface that can be used to evaluate the statistical significance of the groups identified from the historical record for summertime maximum daily temperature in the mid-continental region of the US. Statistically meaningful groups can be identified using stringent criteria for threshold and minimum group size. Choosing among these values depends on how the groups are used and the importance of parsimony to that process. The reliability of critical values can be evaluated by comparing the statistical significance of results for individual groups generated by existing techniques.