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This title appears in the Scientific Report : 2015 

Assimilation of Satellite Data for Atmospheric Composition

Assimilation of Satellite Data for Atmospheric Composition

This overview addresses the state of the art of satellite data assimilation for several types of atmospheric constituents: inert and chemically reactive, or gas phase compounds or aerosols, except water. The diversity of motives and applications are addressed: stratospheric trace gas analyses for im...

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Personal Name(s): Elbern, Hendrik (Corresponding author)
Agusti-Panareda, Anna / Benedetti, Angela / Chevallier, Frederic / Emili, Emanuele / Inness, Antje / Kaiser, Johannes W. / Massart, Sebastien
Contributing Institute: Troposphäre; IEK-8
Imprint: 2015
Physical Description: 1-17
Conference: ECMWF: Use of Satellite Observations in Numerical Weather Prediction, Reading (UK), 2014-09-08 - 2014-09-12
Document Type: Contribution to a conference proceedings
Research Program: Tropospheric trace substances and their transformation processes
Publikationsportal JuSER

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This overview addresses the state of the art of satellite data assimilation for several types of atmospheric constituents: inert and chemically reactive, or gas phase compounds or aerosols, except water. The diversity of motives and applications are addressed: stratospheric trace gas analyses for improved retrievals and heating rate calculations or monitoring of key constituents like ozone, where space borne sensors include limb, occultation, and nadir viewing techniques. In the middle and lower troposphere only nadir looking sensors are applicable and usable for assimilation. A central application area is air quality forecasting, which typically mix in situ observations with space borne sensors. Close to the ground high spatial resolution is a challenging feature for satellite sensors, and in addition, emission rate estimation is an emerging task, which is extending the objectives of satellite data assimilation. Further topics, which are addressed, include tropospheric aerosol data assimilation, and greenhouse gas inversion and assimilation. Finally, the special case of fire data assimilation is presented.

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