The Mediterranean region is frequently affected by heavy precipitation that produce flash-floods and landslides. They are the most damaging natural risk in Mediterranean that costs each year several billions euros of damages and fatalities. Mesoscale convective systems that stay over the same area during several hours are the main responsible for high rainfall totals that produce flash-flooding. These meteorological phenomena result from complex multiscale interactions between the ambient flow, topography and deep atmospheric convection that make difficult the forecast of the precise timing and location of the intense convective precipitation. The overarching objective of the MUSIC project is to provide a better understanding and modelling of intense convective precipitation events in Mediterranean in order to improve their forecast by state-of-art kilometric and sub-kilometric scale Numerical Weather Prediction (NWP) models. To reach this objective: (1) The project strongly relies on the observations collected during the HyMeX SOP1 field campaign that took place in northwestern Mediterranean (France, Italy, Spain) from 5 Sep. to 6 Nov. 2012. This major field campaign provides a novel and unique dataset of observations of the convective systems as well as of the ambient flow over the northwestern Mediterranean. (2) The project concentrates on the key physical parameterizations that strongly influence the forecasts of deep convection at kilometric and sub-kilometric scales: (i) the modelling of microphysical processes that is a leading order contributor to NWP precipitation forecast errors and (ii) the modelling of the turbulence in boundary layer and in and near convective clouds that influences the convection initiation and cloud growth. (3) The project makes use of the novel capabilities of large-grid simulations on massively-parallel scalar supercomputers to explicitly resolve (i) at sub-kilometric scale the multiscale interactions between convective and larger scale processes leading to heavy precipitation events in order to progress in their understanding and (ii) turbulence and microphysics within convective systems and in boundary layer through Large Eddy Simulations. The process studies led in MUSIC as well as these high-resolution large-grid simulations will supply references and guidelines for, in the future, improving and validating deep convection/microphysical/turbulence parameterizations of regional climate models, which are essential in the simulation of precipitation extremes.

The representation of clouds, aerosols and cloud-aerosol-radiation interaction remain the largest uncertainties in climate change, limiting our ability to accurately reconstruct and predict future climate change. The South East (SE) Atlantic is a region where high atmospheric aerosol loadings (from biomass burning, mineral dust, marine origin) and semi-permanent stratocumulus cloud are co-located. This area provides a unique natural laboratory for studying the full range of aerosol-radiation and aerosol-cloud interactions and their perturbations of the Earth’s radiation budget. Aside the fundamental knowledge that can be gained from the study of this environment, these perturbations of the radiative systems occurring in SE have a significant impact, not just locally but also via global teleconnections on wider changes in climate. There have never been detailed although measurements of the combined cloud-aerosol-radiation system over the SE Atlantic are crucial in constraining the current generation of large eddy simulation, numerical weather prediction and climate models. The AErosol RadiatiOn and CLOuds in Southern Africa (AEROCLO-SA) project proposes a break-through study focusing on the South East (SE) Atlantic off the western coast of southern Africa providing with a novel evaluation of the interactions between aerosols, clouds and radiation and their representation in global and regional models. AEROCLO-SA will deliver a wide range of airborne, surface-based and satellite measurements of clouds, aerosols, and their radiative impacts to 1) improve representation in models of absorbing and scattering aerosols 2) reduce uncertainty of the direct, semi-direct and indirect radiative effect, and their impact on stratocumulus clouds; 3) challenge satellite retrievals of cloud and aerosol and their radiative impacts to validate and improve algorithms; AEROCLO-SA is the French contribution in the framework of a very high level international, synergistic project. Aside the French contribution (5 leading laboratories from Universities and CNRS), it gathers partners - from the UK (Met Office, Univ. of Reading, Manchester, Oxford, …) within the CLARIFY-2016 project ); - from the USA within the NSF LASIC project (22 US universities and research labs) and within the US NASA ORACLES (5 NASA research centers and 8 Universities); - and from southern African Universities under the umbrella of the ARSAIO research initiative (CNRS/NRF). AEROCLO-SA includes ground-based and airborne measurements, and modelling. The present project aims at funding the airborne part of the French contribution 1/ to allow the French community who was part of the overall strategy from the very beginning to eventually participate to its implementation during the international field campaign 2/ to gather unique datasets 3/ to participate the valorization of the international dataset.

Black carbon (BC) contributes to global warming by absorbing sunlight. Current global climate models systematically underpredict the atmospheric aerosol absorption by a factor of three when compared to observations, which is often attributed to the underestimation of BC emissions [Bond et al. 2004, 2013; Textor et al. 2006]. Emission inventories of BC are traditionally constructed using a bottom-up approach based on activity data and emissions factors (EF). EF determination requires highly expensive (both in time and means) meticulous methodologies, which leads in practice to emission data with very heterogeneous quality in space and time [Lamarque et al. 2010; Granier et al. 2011]. Southeast Asia (SEA) hosts a multiplicity of combustion sources emitting large amounts of BC in the atmosphere: biomass burning including peatland and forest fires and domestic usage of biofuels, oil products for transportation, but it will be particularly affected by coal burning to meet the explosive energy demand over the next decades. This part of Asia also stands downstream the intense BC emissions from China in winter. As a result, all the trends quantitatively go upwards and point SEA as the top priority region of the world to be investigated. International programs have attempted to simulate the effects of BC on climate in SEA, all pointed out that better time and space resolved emissions inventories are the crucial point to improve forecast and climate models [Koch et al. 2009; Bond et al. 2013]. BLACKNET will lead to a new cost-effective operational system to monitor BC along with other combustion tracers, and subsequently identify, localise and characterise their sources. (1) The first objective is technical: the development and operational demonstration of a network of BC sensors deployed over the Indochinese Peninsula, providing continuously collected & computed data. (2) The second objective is scientific: the consecutive development of innovative atmospheric data products relying on inverse modelling based on communicating BC sensors, in order to improve and validate top-down BC emissions inventories. The consortium includes internationally recognized researchers and research groups in the fields of aerosol characterization, inverse modelling, emission inventories and regional/global modelling. The field work achievements are ensured by the strong involvement in the project of the Asian Institute of Technology in Bangkok and the Vietnamese Academy of Science and Technology, in the frame of an International Research Group (GDRI-Sud) dedicated to BC impacts in Southeast Asia, and funded over the period 2018-2021 by IRD and the leading laboratories, including LA – the coordinator of the present BLACKNET proposal. Impacts are expected on potential market development as new opportunities will emerge for the French Earth observation commercial sector, mainly technology/sensor and data treatment software providers and for downstream users - service providers - with the definition and demonstration of new services and the enablement of new science applications. The project outputs will fit into international frameworks like the Global Emissions InitiAtive (GEIA), the Copernicus Atmosphere Monitoring Service, particularly CAMS-43 about aerosols, from which data will be used for comparison, and the ASEAN Agreement on Transboundary Haze Pollution which binds the ten ASEAN Member Countries to tackle transboundary haze pollution.

The development of operational services dedicated to mitigate natural and anthropogenic risks is one of the objectives of this ANR call. In the frame of a previous project already led by SPE lab, IDEA (2010-2013 Forest-Fires, from combustion Emissions to Atmospheric transport), considered as a highlighted project by the ANR, several demonstrators dedicated to wildfire risk were developed (codes, approaches, services), aiming at proposing a new generation fire decision support system. Available thanks to recent technological advances in the field of meteorology, data assimilation, fire modeling and supercomputing these tools have only been tested and partially validated on a limited amount of case studies and over limited time periods. The goal of the FireCaster project is to extent the approaches at the national scale by prototyping a platform that allows to estimate upcoming fire risk (H+24 to H+48) and in case of crisis, to predict fire front position and local pollution (H+1 to H+12). The main challenge is here to deliver these new diagnostics immediately for any given territory and at any given forecast date. It requires to overcome a key issue: access to high resolution (50m) fuel models and data. In order to characterize these fuels and potential pollution products, it is planned to use new vegetation atlas and study smoke emissions for various fuel types and states of fuel. These models will then be generalized to the whole French territory, not by developing specific codes, but for the first time by linking them to surface models, which simulate energy exchanges and water cycle in meteorological models. Surface models recently had a strong increase in resolution and accuracy that makes this link possible (SURFEX model -CNRM- operational). In terms of risk, we propose a probabilistic approach, based on large sets of perturbed multi-model simulations (INRIA), to determine the distribution of potential fire sizes. This approach will provide a new diagnostic (fire burnt area) very different from the current indicator (risk of fire ignition with no indication on the potential size). Fire fighting tools should help to estimate the benefits and risks of each intervention scenario as planned by crisis management centres. They should also evaluate the impact of fires on air pollution and smoke for fire-fighters and population alert. Probability impact maps for each fire fighting scenario, showing areas where the passage of fire is highly expectable, will be obtained by ensemble simulations, taking into account interactively fire-fighting actions. Another, deterministic and more detailed coupled Fire/Meso-NH atmospheric crisis model will determine front position, smoke pollution and local micro-meteorology with data assimilation of aerial/spaceborne observation of fire contours; it will be implemented (CECI) to reduce the uncertainty of these deterministic predictions. Eventually, in order to link the resulting computations to innovative indicators, economic, human and environmental costs will be evaluated (LISA). At the national French level, Météo-France, responsible for this public service mission, will supervise and test the project and evaluate the products within a steering committee also composed of the European Forest Fire Information System (JRC), the National Forestry Services (ONF), the French government space agency (CNES) and Corsican fire brigades (to test crisis tools). While the project success first requires a successful application at national scale, there exists a strong potential of development at the European level. All codes will be Open-Science with French SMEs interested in selling the knowledge required to apply the platform to other countries or areas in the frame of SAFE Cluster (former Pôle Risques).

Allergy to pollen is an increasing human health problem with more than 20% of children sensitized. This problem is expected to be emphasized by climate change. One important tool for adaptation and prevention of risk is to be able to forecast the risk based on forecasting peak of airborne pollen concentration. This is helpful for sensitized population to limit their exposition and for medical and pharmacological system to anticipate needs. However only few attempts have been done to include pollen within air quality forecasting system. The project aims at addressing this question by developing a forecasting system of allergy risk to pollen in response to weather conditions at the French level to implement in French and European air quality forecasting systems. The project is based on a complementary and combined approach with data and model. A first objective of the project will be to improve the existing french aerobiological network by developing a new generation of automatic real time pollen sensors. The current measurement are indeed done by manual count of pollen grains. This limit the number of station that can be managed and induce delay between measurement and estimation of pollen load. These new automatic sensors will open a new era for aerobiological survey by allowing both real time informations and a better spatial coverage. A second objective of the project will be to develop a complete modeling chain to describe all the processes from production of pollen by plants to transport by the atmosphere. This model will include all the processes related to pollen emission including plant phenology and pollen production related to climate conditions. A method will also be developed to assimilate in-situ data by dynamic optimisation of parameters of the surface pollen emission model to obtain to most reliable pollen forecast. Finally a link will be done between pollen concentration and clinical symptoms by relating pollen to prescription of drugs and clinical index filled by a doctor’s network. This studies will allow to defined empirical relationships that will be included into the modeling system to assess a factor of risk. This system will be implemented into the French air quality system PREV’AIR and the proof of concept will be evaluated. The multidisciplinary consortium will be based on public research institute , operators for air quality monitoring and two private companies and the global leader in immunotherapy who will help to define user requirements