Are the TRACE-P measurements representative of the western Pacific during March 2001?

[1] Observations of CO and O-3 from the Transport and Chemical Evolution over the Pacific (TRACE-P) campaign are compared with modeled distributions from the FRSGC/ UCI CTM driven by the Oslo T63L40 ECMWF forecast meteorology. The model-measurement comparison is made within the context of how well the TRACE-P observations represent the springtime chemistry and ozone distributions over eastern Asia and the western Pacific in March 2001 and uses the four-dimensional (4-D) extended domain from the model to provide unbiased statistics. A key question is whether the limited sampling density or mission strategy led to a statistically biased sample. To address this question, we examine a diverse range of statistical analyses of the observations of CO and O-3. The middle percentiles of the cumulative probability functions for CO in the free troposphere are representative ( and reproduced by the CTM), but those in the boundary layer are not. The frequency of low-CO, stratospheric influence is well matched along flight tracks but is atypical of the extended domain. The percentiles of the latitude-by-height distribution of lidar O-3 show how the CTM reproduces the nonrepresentative clumpy nature of the observations but has too low a tropopause about the jet region (30-35N). Adaptive kernel estimation of the 2-D probability density of O-3-CO correlations shows a very good simulation of two different chemical regimes ( stratospheric and polluted) that is quite different from the extended domain but also highlights the failure to predict CO > 400 ppb. Empirical orthogonal function analysis of the O-3 vertical profiles shows how six EOFs can effectively describe the 4-D structures of O-3 over this entire domain. The latitude-by-longitude maps of the principal components provide an excellent test of the CTM simulation along flight tracks and clearly show the unique sampling of O-3 events by the TRACE-P flights. In many cases the ability of the model to simulate the nonrepresentative observations implies a clear skill in matching the unique meteorological and chemical features of the region.