High Resolution Ozone Mapping Using Instruments on the Nimbus 7 Satellite and Secondary Information

The high natural variability of ozone concentrations across space-time and the different levels of accuracy of the algorithms used to generate data from measuring instruments can not be confronted satisfactorily by conventional interpolation techniques. This work suggests that the Bayesian Maximum Entropy (BME) method can be used efficiently to assimilate salient (although of varying uncertainty) physical knowledge bases about atmospheric ozone in order to generate and update realistic pictures of ozone distribution. On theoretical grounds, BME relies on a powerful scientific methodology that does not make any of the restrictive modelling assumptions of previous techniques and integrates a wide range of knowledge bases. A study is discussed in which BME assimilates data sets generated by measuring instruments on board the Nimbus 7 satellite as well as uncertain measurements and secondary information in terms of total ozonetropopause pressure empirical equations. The BME total ozone analysis eliminates major sources of error and produces high spatial resolution maps that are more accurate and informative than those obtained by conventional interpolation techniques.