comparisons between sciamachy and ground-based ftir data for total columns of co, ch4, co2 and n2o

comparisons between sciamachy and ground-based ftir data for total columns of co, ch4, co2 and n2o

;B. Dils;M. De Mazière;J. F. Müller;T. Blumenstock;M. Buchwitz;R. de Beek;P. Demoulin;P. Duchatelet;H. Fast;C. Frankenberg;A. Gloudemans;D. Griffith;N. Jones;T. Kerzenmacher;I. Kramer;E. Mahieu;J. Mellqvist;R. L. Mittermeier;J. Notholt;C. P. Rinsland;H. Schrijver;D. Smale;A. Strandberg;A. G. Straume;W. Stremme;K. Strong;R. Sussmann;J. Taylor;M. van den Broek;V. Velazco;T. Wagner;T. Warneke;A. Wiacek;S. Wood
Journal of agricultural and food chemistry 2006 Vol. 6 pp. 1953-1976
165
dils2006atmosphericcomparisons

Abstract

Total column amounts of CO, CH4, CO2 and N2O retrieved from SCIAMACHY nadir observations in its near-infrared channels have been compared to data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers. The SCIAMACHY data considered here have been produced by three different retrieval algorithms, WFM-DOAS (version 0.5 for CO and CH4 and version 0.4 for CO2 and N2O), IMAP-DOAS (version 1.1 and 0.9 (for CO)) and IMLM (version 6.3) and cover the January to December 2003 time period. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of reliable coincidences that satisfy the temporal and spatial collocation criteria, the SCIAMACHY data have been compared with a temporal 3rd order polynomial interpolation of the ground-based data. Particular attention has been given to the question whether SCIAMACHY observes correctly the seasonal and latitudinal variability of the target species. The present results indicate that the individual SCIAMACHY data obtained with the actual versions of the algorithms have been significantly improved, but that the quality requirements, for estimating emissions on regional scales, are not yet met. Nevertheless, possible directions for further algorithm upgrades have been identified which should result in more reliable data products in a near future.

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