Improvement of the Umkehr ozone profile by the neural network method: analysis of the Belsk (51.80°N, 20.80°E) Umkehr data

Abstract

Vertical profiles of atmospheric ozone by the neural network (NN) method are compared with those obtained by the standard Umkehr inversion algorithm – UMK92. Both methods used the same input, the so-called N values, derived from Umkehr measurements at Belsk (51.80°N, 20.80°E), Poland, by the Dobson spectrophotometer No 84. The vertical profiles of ozone from satellite observations, Microwave Limb Sounder (MLS) overpasses for the period 2004–2009, and from ozonesoundings performed at the nearby aerological station, Legionowo (52.4° N, 21.0° E), for the period 2000–2009 provide a reference data set for the NN model building. The NN methodology appears to be a promising tool for extracting information about the vertical ozone profile from ground-based Umkehr measurements, despite some limitations of the NN method itself, such as the results being limited to the analysed station, sensitivity to errors in the reference data sets, and lack of possibility to determine the actual retrieval errors. Accuracy of the NN ozone profiles is better for all Umkehr layers than that by the standard Umkehr inversion algorithm when NN and UMK92 profiles are compared with the reference profiles. It is especially pronounced for comparisons with the ozonesonde profiles for layers 4 and 1, where the absolute error changes from 10.6 Dobson units (DU) (UMK92) to 4.4 DU (NN) and from 6.6 DU (UMK92) to 3.5 DU (NN), respectively (1 Dobson unit is equal to 2.69 × 1020 molecules/m2). The mean (over all Umkehr layers) correlation coefficient between NN-MLS, and NN-ozonesonde profiles is 0.75 and 0.85, respectively. The corresponding correlation coefficients for the comparison with UMK92 profiles are lower, i.e. 0.61 and 0.64, respectively.