Spaceborne remote sensing and airborne in situ observations of Arctic mixed-phase clouds

• Main Authors: Mioche, Guillaume, Jourdan, Olivier
• Other Authors: Laboratoire de Météorologie Physique (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Clermont Auvergne 2017-2020 (UCA 2017-2020 )-Centre National de la Recherche Scientifique (CNRS)
• Format: Book Part
• Language: English
• Published: HAL CCSD 2018
• Subjects: Arctic mixed-phase clouds; ice and liquid microphysical properties; in situ measurements; satellite remote sensing observations; [SDU.OCEAN]Sciences of the Universe [physics]/Ocean; Atmosphere; Arctic; Climate change; North Atlantic; Sea ice
• Online Access: https://hal.science/hal-03614464; https://hal.science/hal-03614464/document; https://hal.science/hal-03614464/file/Chapter_MPC_texte%20et%20figures.pdf; https://doi.org/10.1016/B978-0-12-810549-8.00006-4

International audience Our predictive capability of Arctic climate change is severely hampered by a lack of understanding about key processes, notably related to mixed-phase clouds (MPC). These cloud related processes are suspected to play a major role in the Arctic energy budget due to their persistence and peculiar microphysical properties. This chapter focuses on the characterization of MPC properties in the Arctic region from in situ and satellite observations. The frequency of occurrence of MPC over the Arctic region is determined from the CALIPSO and CloudSat satellite active remote sensing observations. Results highlight that the spatial, vertical and seasonal variability of MPC can be in part linked to the influence of the North Atlantic Ocean and the melting of sea ice. The microphysical and optical properties of the ice crystals and liquid droplets within MPC and the associated formation and growth processes responsible of the cloud life cycle are evaluated based on in situ airborne observations. Finally, the coupling of in situ MPC airborne measurements with the satellite active remote sensing is presented through a validation study to evaluate remote sensing retrieval algorithms and products such as the cloud detection or cloud phase.