Open AccessLagrangian forecasting during ASHOE/MAESA: Analysis of predictive skill for analyzed and reverse‐domain‐filled potential vorticity
Author(s) -
Fairlie T. Duncan,
Pierce R. Bradley,
Grose William L.,
Lingenfelser Gretchen,
Loewenstein Max,
Podolske James R.
Publication year - 1997
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/96jd03507
Subject(s) - potential vorticity , environmental science , vorticity , climatology , meteorology , rdf , computer science , physics , geology , artificial intelligence , semantic web , vortex
A statistical analysis is conducted to determine to what extent analyzed and 5‐day reverse‐domain‐filled (RDF) potential vorticity (PV) obtained from meteorological analyses can predict ATLAS nitrous oxide (N 2 O) tracer structure encountered along the ER‐2 flight track during the Airborne Southern Hemisphere Ozone Experiment / Measurements for Assessing the Effects of Stratospheric Aircraft (ASHOE/MAESA) campaign. The results indicate that RDF PV shows no statistically significant improvement in forecast skill over analyzed PV in predicting tracer structure along the ER‐2 flight track. In fact, RDF generally shows a degradation in predictive skill. RDF does show some success in refining large‐scale gradients and small‐scale structures, present in the analyzed PV fields. In at least one case, RDF PV captured a filament encountered by the ER‐2, but in general, such structure is marked by low confidence in the RDF PV analyses.