Assimilation of stratospheric ozone GOMOS data with the isentropic transport model MIMOSA: Comparison between sub-optimal Kalman filter and kriging
Résumé
GOMOS (Global Ozone Monitoring by Occultation of Stars) is the first space instrument dedicated to the study of the atmospheric composition by the technique of stellar occultations. The experiment aboard ENVISAT satellite was designed in order to evaluate stratospheric ozone concentration and trend (and other atmospheric minor constituents) over the Earth during the last few years. Ozone concentration is variable in space and time. Spatial variability may be observed by a sufficient number of occultations and time variability by recording time series. GOMOS measurements are randomly distributed in space and time. A continuous field at grid points evenly spaced is needed to obtain a good estimate of ozone trend, climatology and variability. It allows also to interpolate satellite data at the location of ground-based NDACC measurements for validation. We present here a comparison between a heavy method consisting in the assimilation of GOMOS data in the high resolution isentropic transport model MIMOSA using a sub-optimal Kalman filter with a simple and fast multidimensional interpolation method: kriging.