Abstract

AbstractTwo years of data from a 30 m instrumented tower are used to characterize the near‐surface atmospheric state over the Ross Ice Shelf, Antarctica. Stable stratification dominates the surface layer at this site, occurring 83% of the time. The strongest inversions occur for wind speeds less than 4 m s−1 and the inversion strength decreases rapidly as wind speed increases above 4 m s−1. In summer unstable stratification occurs 50% of the time and unstable conditions are observed in every season. A novel aspect of this work is the use of an artificial neural network pattern identification technique, known as self‐organizing maps, to objectively identify characteristic potential temperature profiles that span the range of profiles present in the 2 year study period. The self‐organizing map clustering technique allows the more than 100,000 observed potential temperature profiles to be represented by just 30 patterns. The pattern‐averaged winds show distinct and physically consistent relationships with the potential temperature profiles. The strongest winds occur for the nearly well mixed but slightly stable patterns and the weakest winds occur for the strongest inversion patterns. The weakest wind shear over the depth of the tower occurs for slightly unstable profiles and the largest wind shear occurs for moderately strong inversions. Pattern‐averaged log wind profiles are consistent with theoretical expectations. The log wind profiles exhibit a kinked profile for the strongest inversion cases indicative of decoupling of the winds between the bottom and top of the tower.

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