Analyzing the applications of an assimilation model as a method for validation of satellite data

Abstract

An analysis was performed to illustrate that data assimilation is an appropriate method for validation of satellite measurements when very few coincidences are available between satellite, measurements and balloon sondes. Results showed that the mean differences between the Isentropic Assimilation model for Stratospheric Ozone (IASCO) model ozone profiles and collocated ozonesondes shared systematic differences similar to those obtained from collocated MIPAS and ozonesonde coincidences. The spatial and temporal constraints of 12 hours and 800 km produced the optimal number of MEPAS/sonde matches for a statistical analysis. The largest residual between the IASCO/sonde mean difference and MIPAS/sonde mean difference, using these constraints, was less than 0.25 ppmv, between potential temperature levels of 425-975 K. By using the assimilation model coincidences, we also conclude that the maximum time/distance constraint sizes that can be used when obtaining matches between satellite measurements and in situ measurements should be no more than 24 hours and a maximum of 1500-2000 km. However, local conditions such as the presence of a dynamical feature, for example the edge of the polar vortex, may of course greatly restrict these limits. Copyright 2007 by the American Geophysical Union.