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| Titel |
Assimilation of surface versus lidar observations for PM10 forecasting |
| VerfasserIn |
Y. Wang, K. N. Sartelet, M. Bocquet, P. Chazette |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250059478
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| Zusammenfassung |
| Thanks to the new generation of portable lidar systems developed over the past several years,
one can now carry out spatially denser observations of aerosol optical properties in
the mid and lower troposphere. Data assimilation is an analysis technique which
can use these observations to reduce the uncertainties in input data, and improve
the forecast. In order to investigate the potential impact of future ground-based
lidar network LEONET (http://leo-net.eu/) on analysis and short-term forecasts of
PM10, an Observing System Simulation Experiment (OSSE) is built for PM10 data
assimilation using optimal interpolation over Europe for one month in 2001. Firstly,
we estimate the efficiency of the assimilation of lidar network measurements in
improving PM10 concentration analysis and forecast. It is compared to the efficiency of
assimilating concentration measurements from the AirBase ground network, which
includes about 500 stations in western Europe. It is found that the assimilation of
lidar observations is more efficient at improving PM10 concentrations in terms
of root mean square error and correlation after 12 hours of assimilation than the
assimilation of AirBase measurements. Moreover, the spatial and temporal influence of the
assimilation of lidar observations is larger and longer. Secondly, since a lidar is
a very costly instrument, a sensitivity study on the number of required lidars is
performed to help define an optimal lidar network for PM10 forecast. The results suggest
12 lidar stations over western Europe, because a network with 26 lidar stations is
more expensive and offers a limited improvement (less than 1 μg m-3 of root
mean square error on average) over the 12 lidar network. A comparison of two
networks with 12 lidar stations at different locations does not lead to substantial
differences. This result gives more freedom in choosing the lidar network configuration. |
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