A34E-03
Synergy of spaceborne remote sensing and airborne in situ observations for the study of Arctic mixed phase clouds at regional and small scales

Wednesday, 16 December 2015: 16:30
3004 (Moscone West)
Guillaume Mioche, Laboratoire de Météorologie Physique Observatoire de Physique du Globe de Clermont-Ferrand, Aubiere Cedex, France
Abstract:
Clouds radiation feedback processes in the Arctic have been identified as one of the greatest sources of uncertainties in the prediction of global climate in GCMs. In particular, mixed phase clouds (MPC) occur very frequently at low-level altitudes in the Arctic, representing between 30% and 50% of the clouds all along the year. However, the characterization of MPC on the whole Arctic region is not yet accurate enough to better understand cloud-radiation interactions. Thus, the knowledge of arctic MPC properties has to be improved.

The aim of this study is to characterize MPC properties from regional scale to small scale. This work is based on the synergy of spaceborne active remote sensing (CALIPSO/CloudSat) and airborne in situ observations.

We will present results about the time and space variability and vertical distribution of MPC over the entire Arctic region, with a focus on the Svalbard region. The influence of the seasonal cycle as well as surface type (open sea, sea ice, land) on the MPC occurrences will also be investigated.

Then, this study will focus on a statistical analysis of MPC clouds properties based on in situ measurements carried out during several airborne campaigns in Svalbard region (14 flights corresponding to 54 vertical profiles). This will provide a detailed characterization of microphysical and optical properties of MPC, discriminating liquid and ice phases. Small scale processes occurring in arctic clouds will be also studied.

Finally, accurate profiles of relevant clouds parameters (optical depth, liquid/water fraction, ice crystals morphology, ice and liquid water contents…) will be assessed to contribute to the improvement of clouds representation in global and mesoscale models and to improve airborne and spatial remote sensing retrievals algorithms.