|From||delanoe julien <firstname.lastname@example.org>|
|Date||Mon, 02 Mar 2015 18:26:22 +0100|
PhD opportunity at (LATMOS and DLR): A 3 year contract funded by CNES (French Spatial Agency)/DLR (German Aerospace Center) on the “Development and evaluation of multisensor methods for EarthCare mission based on A-Train and airborne measurements”
· 18 months in France (Guyancourt) at LATMOS and then,
· 18 months in Germany (Oberpfaffenhofen) at DLR (Deutsches Zentrum für Luft- und Raumfahrt - Institut für Physik der Atmosphäre)
We are looking for a motivated PhD candidate. The applicant must have a Master degree or Engineer degree (or equivalent) in at least one of the following areas of expertise: Remote Sensing / Physics / Applied Mathematics / Environmental Sciences. He or she must be interested in active and passive remote sensing of clouds. We are also expecting good computational skills in python, C, IDL and/or Fortran.
Clouds have a strong effect on the Earth’s climate, but the level of understanding of their climate impact and of cloud-climate feedbacks is still low. In recent years, space-borne radar and lidar measurements on board CloudSat and CALIPSO as part of NASA’s A-Train have achieved notable improvements in studying the vertical cloud occurrence and properties. Furthermore, the combination of these active measurements with passive radiometers allows comprehensive studies of the cloud properties and their radiative effect. The future satellite mission EarthCARE of the European Space Agency, scheduled for launch in 2018, will continue and improve the characterization of cloud distribution and cloud properties on global scale. By applying a Doppler radar together with a High Spectral Resolution Lidar, an infrared-visible radiometer and a Broad Band Radiometer on the same platform, EarthCARE employs a new and outstanding instrumentation.
This PhD work will aim to characterize the cloud phase and the microphysical and radiative properties of clouds by exploiting the synergy of active (Doppler radar, High Spectral Resolution Lidar) and passive (visible and infrared radiometer) remote sensors. In preparation for EarthCARE, the successful candidate will use A-Train radar and lidar, and airborne radar and lidar data collected during RALI (airborne radar-lidar-radiometer developed at the LATMOS) campaigns as well as during DLR campaigns with the research aircraft HALO. During this PhD thesis all the improved/developed algorithms will be tested on airborne measurements collected with multi frequency-wavelength instruments (Doppler radar at 95 GHz and 35 GHz, and High Spectral Resolution Lidar at 355 nm and 532nm). During this work the synergistic algorithms for the determination of cloud properties, developed by our team, will be adapted with respect to the instrumental improvements of EarthCARE compared to A-Train. The retrieval algorithms DARDAR (v2) and those developed EarthCare oriented will be validated using airborne measurements. These retrievals from the A-Train and airborne campaigns will then be used to perform statistical analyses of cloud properties and to study mechanisms involved in the cloud life-time.
HALO : http://www.halo.dlr.de
-- ----------------------------- Dr Julien Delanoë LATMOS/IPSL/UVSQ 11 Boulevard D'Alembert 78280 Guyancourt France Tel.: +33 1 80 28 52 19 http://www.latmos.ipsl.fr http://rali.projet.latmos.ipsl.fr/ -----------------------------
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