Since pilots generally avoid intense convective areas, ice crystals icing (ICI) is an aeronautical weather incident that mainly occurs in the anvil of tropical deep convective clouds. Samples of favorable conditions for the occurrence of ICI and data from the High Altitude Ice Crystals (HAIC) 2015 field campaign in French Guiana are investigated and compared with simulations of the French operational mesoscale forecast system Application of Research to Operations at Mesoscales (AROME). To this end, a contextualization of convective systems into convective, stratiform, and cirriform regions is employed for both observations and AROME. General features of the microphysics of deep tropical convective systems are identified. The number concentration of crystals larger than 125 μm and total water content (TWC) are strongly correlated at each temperature level, and both decrease with increasing distance from convective cores. AROME can reproduce the general behavior of the observed microphysics, especially TWC, but seems unable to simulate extreme ICI events. Reasons are sought in the assumptions performed in the microphysical scheme ICE3, and guidelines are proposed to enhance its skills in the context of ICI. In particular, the representation of the snow particle size distribution is adjusted across observations using a generalized gamma shape. This shape is found to outperform the usual Marshall–Palmer and gamma shapes. Additionally, a temperature and snow content dependence of generalized gamma parameters is found. These changes are found to significantly improve the snow concentration diagnostic of ICE3, and these modifications open the way for improvements in the ICE3 scheme.

Ice crystal icing (ICI) poses a threat nowadays for airplane pilots crossing the anvils of tropical mesoscale convective systems (MCSs). The use of fine‐scale operational numerical weather predictions as provided by the French limited‐area model AROME could help to better understand this phenomenon and to help its anticipation. To enable AROME to simulate ICI‐prone conditions, modifications of its single‐moment microphysical scheme Intercity‐Express 3 (ICE3) are tested. Using a temperature‐dependent snow particle distribution deeply impacts the organization and the ice phase of the simulated MCS. Notably, while the size of convective regions decreases, the size of anvil clouds increases and the low stratiform rain increases as well. As a result, by increasing the quantity of snow and decreasing the quantity of graupel, the simulation of ICI‐prone conditions in the anvils of convective systems is enabled. Using this parametrization, further modifications fine‐tune the representation of snow and further increase the size of the anvil cloud. The Marshall–Palmer snow distribution is replaced by a generalized gamma and the terminal fall velocities of snow hydrometeors are parametrized so that they are in closer agreement with observations.

<p>The Paris region (France) is increasingly the focus of urban atmospheric research. Numerous national and international research projects have chosen Europe’s largest metropolitan region as their study area to better understand and predict critical hazards (incl. heat, air pollution, thunderstorms) in the context of a changing climate. Located on rather flat terrain in continental, mid-latitude climates, the densely populated Paris region is very suitable for the evaluation of urban processes in numerical simulations at different scales. The European research infrastructures ACTRIS and ICOS are developing strategies for the improved operational monitoring of air pollution and greenhouse gas budgets, respectively. Various research projects are conducting fundamental process studies and model developments to investigate the dynamics and chemistry of the urban atmosphere and its interactions with the rural surroundings and regional-scale flow to better quantify associated health risks and inform sustainable planning.</p> <p>In addition to numerous modelling activities (chemistry-transport, numerical weather prediction, climate projections), diverse atmospheric observations are collected. These include dense surface station networks, turbulent flux towers, and ground-based atmospheric remote sensing to monitor the atmospheric boundary layer. This multi-project context motivates the pooling of resources.</p> <p>To facilitate efficient project synergy and to optimise the coordination of the individual experimental campaigns, the <strong>PANAME initiative </strong>(https://paname.aeris-data.fr/) was established. PANAME provides a framework to optimise the design of the Paris region measurement network and helps to standardise the operations. A professional, multi-disciplinary data portal is developed at the French AERIS atmospheric data centre to host the PANAME observations and model results. Here, data are collected and formatted, standardised advanced products are derived from the diverse sensor networks and high-quality visualisations are generated in near real-time. The presentation will provide an overview on the scientific objectives of the on-going projects, the deployment of measurements and simulation tools, and the data portal design.</p> <div> </div>