Assimilation of MIPAS observations using a three-dimensional global chemistry-transport model

Abstract

MIPAS observations are assimilated using a modified version of the chemistry-transport model ROSE to derive consistent global chemical analyses of the stratosphere. Due to different retrieval schemes applied, available MIPAS datasets are expected to differ in quality and coverage. In this study we investigate the sensitivity of the data assimilation scheme to two different sample datasets. ENVISAT/MIPAS baseline observations of H2O, O3, HNO3, CH4, N2O and NO2, covering October-November 2003, are considered. Sequential assimilation is performed using an optimum interpolation scheme with error propagation. It is shown that all assimilated model species benefit significantly from observations. Results are analysed using observation minus first-guess error statistics and are additionally compared to UARS/HALOE data. Optimized assimilation parameters are derived using Chi2 diagnostics. Two different MIPAS data products are examined: the European Space Agency operational product and the Institute for Meteorology Karlsruhe (IMK) scientific product. Assimilation results show some significant differences with respect to the dataset type used. For example, regions with increased stratospheric H2O concentrations near the tropical tropopause are only present when IMK data are applied. Both datasets are found to be well suited for global assimilation experiments to study the chemistry and dynamics of the middle atmosphere.