Comparison of dust-layer heights from active and passive satellite sensors
Arve Kylling (Norsk institutt for luftforskning)
Sophie Vandenbussche (Royal Belgian Institute for Space Aeronomy (BIRA-IASB))
Virginie Capelle (LMD Ecole Polytechnique)
Juan Cuesta (Institut Pierre Simon Laplace)
Lars Klüser (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Luca Lelli (Universität Bremen)
Thomas Popp (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Kerstin Stebel (Norsk institutt for luftforskning)
Pepijn Veefkind (TU Delft - Atmospheric Remote Sensing, Royal Netherlands Meteorological Institute (KNMI))
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Abstract
Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol-cci project, aerosol-layer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosol-layer heights estimated from CALIOP measurements. The Aerosol-cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOP-derived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: The cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5-0.8km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of -0.5km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by -1.097km (-0.961km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by -1.393km (-0.818km).
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