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We investigate the effectiveness of trajectory mapping(TM) as a data validation tool. TM combines a dynamical model of the atmosphere with trace gas observations to provide more statistically robust estimates of instrument performance over much broader geographic areas than traditional techniques are able to provide. We present four detailed case studies selected so that the traditional techniques are expected to work well. In each case the TM results are equivalent to or improve upon the measurement comparisons performed with traditional approaches. The TM results are statistically more robust than those achieved using traditional approaches since the TM comparisons occur over a much larger range of geophysical variability. In the first case study we compare ozone data from the Halogen Occultation Experiment (HALOE) with Microwave Limb Sounder(MLS). TM comparisons appear to introduce little to no error as compared to the traditional approach. In the second case study we compare ozone data from HALOE with that from the Stratospheric Aerosol and Gas Experiment TT(SAGE TT). TM results in differences of less than 5% as compared to the traditional approach at altitudes between 18 and 25 km and less than 10% at altitudes between 25 and 40 km.In the third case study we show that ozone profiles generated from HALOE data using TM compare well with profiles from five European ozonesondes. In the fourth case study we evaluate the precision of MLS H20 using TM and find typical precision uncertainties of 3-7% at most latitudes and altitudes. The TM results agree well with previous estimates but are the result of a global analysis of the data rather than an analysis in the limited latitude bands in which traditional approaches work. Finally, sensitivity studies using the MLS H20 data show the following: (1) a combination of forward and backward trajectory calculations minimize uncertainties in isentropic TM; (2) although the uncertainty of the technique increases with trajectory duration,TM calculations of up to 14 days can provide reliable information for use in data validation studies; (3) a correlation coincidence criterion of 400 km produces the best TM results under most circumstances; (4) TM performs well compared to (and sometimes better than) traditional approaches at all latitudes and in most seasons and; (5) TM introduces no statistically significant biases at altitudes between 22 and 40 km.