Aerosol distribution above Munich using remote sensing techniques

Aerosols are an important part of our atmosphere. As they are very
inhomogenously distributed both in time and space the estimation of
their influence on the climate is very complex. So it is important
to improve the knowledge about the aerosol distribution. In this
study the distribution of aerosols above the region around Munich,
Germany in the time period 2007 to 2010 is studied with
measurements from remote sensing instruments. Thereby the main
focus is set on the lidar data from the ground based lidar system
MULIS of the Meteorological Institute Munich and the space lidar
CALIOP onboard the satellite CALIPSO which both deliver aerosol
information height resolved. As an addition and for a better
comparison with previous studies, aerosol information from the
AERONET Sunphotometer in Munich and the satellite spectroradiometer
MODIS are used. With help of these four datasets several aerosol
parameters could be studied: on average the aerosol optical depth
(AOD) above the Munich region is at 1064 nm about 0.05 to 0.06, at
532 nm about 0.12 to 0.17, and at 355 nm about 0.22 to 0.28. The
height of the boundary layer top decreases from 1.68 km in spring
to 0.73 km in winter, while the thickness of the elevated layers is
more stable (spring: 1.43 km, winter: 1.02 km). The occurrence of
ELs is highest in spring (in 75 % of all measurements), and lowest
in winter (36 %). Measurements of the particle linear
depolarization ratio and the Ångström exponent show that the
aerosols in elevated layers clearly differ from the aerosols in the
PBL. Especially in spring the average EL depolarization is large
(25 %) indicating transportation of strongly depolarizing aerosols
like Saharan dust in the free troposphere. The dominant aerosol
type in the Munich region is smoke (also called biomass burning),
polluted continental can occur in high concentrations especially
during summer time. Dust occurs only in rare occasions, mainly
mixed with other aerosol types (polluted dust). One important
finding from the comparison of the four datasets is that CALIPSO
strongly underestimates the AOD. To study the significances of
different causes for this, the CALIPSO extinction coefficient
profiles are compared with coincidentally performed measurements of
MULIS. The underestimation of the AOD above Munich by CALIPSO is
mainly found to be due to the failure of the layer detection: its
effect on the AOD underestimation is about 36 %. Also the wrong
assumption of the lidar ratio contributes to the underestimation,
though on a smaller account of about 5 %. The influence of clouds
in the surroundings on the AOD is not quantifiable, but the
analysis shows that clouds lead to an overestimation of the AOD. To
compensate these reasons and to get detailed profiles from CALIPSO,
it could be shown that -for case studies- it is very efficient to
calculate the extinction coefficients from CALIPSO raw data (L1B)
manually.