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Comparison of dust-layer heights from active and passive satellite sensors
- Source :
- Atmospheric Measurement Techniques, Vol 11, Pp 2911-2936 (2018), Atmospheric Measurement Techniques, Atmospheric Measurement Techniques, 11(5)
- Publication Year :
- 2018
- Publisher :
- Copernicus Publications, 2018.
-
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 0.5–0.8 km 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 −0.5 km 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 1.3 km. 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 −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).
- Subjects :
- Atmospheric Science
010504 meteorology & atmospheric sciences
Meteorology
0211 other engineering and technologies
02 engineering and technology
Fjernmåling
Atmospheric sciences
01 natural sciences
Standard deviation
Thermal
Atmosphere and climate
Aerosoler og partikler
Mineralstaub
lcsh:TA170-171
Aerosol
021101 geological & geomatics engineering
0105 earth and related environmental sciences
lcsh:TA715-787
lcsh:Earthwork. Foundations
Remote sensing
Atmosfære og klima
SCIAMACHY
lcsh:Environmental engineering
Extinction (optical mineralogy)
13. Climate action
Trajectory
Environmental science
Satellite
Aerosols and particles
Geometric mean
Atmosphäre
effektive Höhe
Subjects
Details
- Language :
- English
- ISSN :
- 18678548 and 18671381
- Database :
- OpenAIRE
- Journal :
- Atmospheric Measurement Techniques, Vol 11, Pp 2911-2936 (2018), Atmospheric Measurement Techniques, Atmospheric Measurement Techniques, 11(5)
- Accession number :
- edsair.doi.dedup.....7b436596e39438733d0131b5589852ae