modelinG-sateLlite-Aircraft approaCh for cIrrus Advanced characTErisation – GLACIATE

Cirrus are pure ice clouds at high altitudes that remain largely unknown due to the variability and complexity of their composition. These unknowns lead to high uncertainties in their representation in global climate models and the ability to estimate their radiative effects and contribution to future climate change.

Led by a scientific consortium from the University of Lille (ULi), Johannes Gutenberg University of Mainz (JGU) and Research Center Jülich (FZJ), GLACIATE will significantly improve our understanding of the global variability of cirrus formation mechanisms, microphysical properties and radiative effects. The complementary expertise of the consortium will allow us to develop an innovative framework bridging the gaps between modeling, satellite observations, and in-situ measurements.

Four main scientific objectives will be achieved. First, GLACIATE will develop enhanced satellite retrievals of cirrus properties, based on existing IASI and DARDAR algorithms, that make use of relevant cloud history information (e.g. cirrus origin, dominant ice formation pathways) provided by the advanced Lagrangian model CLaMS-Ice. Second, it will construct an innovative joint in-situ / satellite / modeling framework, set around selected campaign case studies, and used for rigorous testing of satellite / modeling developments and for further process analyses. Third, GLACIATE will establish and analyze global and regional cirrus property distributions, including cloud radiative effects, from both satellite observations and modeling. Lastly, GLACIATE will identify the cirrus formation and evolution pathways that are responsible for the variability of cirrus microphysical and radiative properties.

Thereby GLACIATE will have a significant scientific impact in the field of cloud research. It will deepen the current knowledge about cirrus cloud processes and help to better understand the spatio-temporal variability of global cirrus cloud fields. Insights gained on driving mechanisms of cirrus properties will help evaluate potential future changes in cirrus clouds, particularly relevant for weather, climate and geo-ingeneering applications. Additionally, GLACIATE will provide novel dataset of enhanced satellite retrieval algorithm and products associated with ice origin and history information to the wider scientific community, as well as well-constrained case studies that include regional high-resolution modeling and observational cirrus cloud datasets (in-situ and satellite). All these dataset will be made freely available.

Overall, GLACIATE's contributions will significantly improve our understanding of ice cloud radiative effects and provide an array of novel tools and datasets to the climate research community, thereby contributing to the future of climate studies.