Are the TRACE-P measurements representative of the western Pacific during March 2001?
Abstract
Observations of CO and O3 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 O3. 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 O3 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 O3-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 O3 vertical profiles shows how six EOFs can effectively describe the 4-D structures of O3 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 O3events 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.