Tropospheric ozone column retrieval at northern mid-latitudes from the Ozone Monitoring Instrument by means of a neural network algorithm
- 1Earth Observation Laboratory, Department of Computer, Systems and Industrial Engineering, Tor Vergata University, Via del Politecnico 1, 00133 Rome, Italy
- 2European Space Agency, Via Galileo Galilei, 00044 Frascati, Rome, Italy
- 3Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, MS-50, Cambridge, MA 02138, USA
- *now at: Laboratoire Inter-universitaire des Systèmes Atmosphériques, CNRS UMR7583, Universités Paris-Est et Paris Diderot, CNRS, 61 Avenue du Général de Gaulle, 94010 Créteil, France
Abstract. Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a neural network algorithm. An extended set of ozone sonde measurements at northern mid-latitudes for the years 2004–2008 has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.