The Lagrangian particle dispersion model FLEX-PART in its original version in the mid-1990s was designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as those released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modeling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g., greenhouse gases, short-lived climate forcers like black carbon and volcanic ash, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to global. In particular, inverse modeling based on source-receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.4, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) and data from the United States National Cen-ters of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEX-PART description (version 6.2), the model has been improved in different aspects such as performance, physicochemical parameterizations, input/output formats, and available preprocessing and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes in runs with very large numbers of particles. The deviation from 100 % efficiency is almost entirely due to the remaining nonparallelized parts of the code, suggesting large potential for further speedup. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g., to quantify dispersion in the vicinity of a point source. The wet deposi-Published by Copernicus Publications on behalf of the European Geosciences Union. 4956 I. Pisso et al.: FLEXPART version 10.4tion scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option of running backward in time from atmospheric concentrations at receptor locations for many years, but this has now been extended to also work for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEX-PART is the only model with that capability. Furthermore, the temporal variation and temperature dependence of chemical reactions with ...

Abstract. Mineral dust is an important component of the climate system, interacting with radiation, clouds, and biogeochemical systems and impacting atmospheric circulation, air quality, aviation, and solar energy generation. These impacts are sensitive to dust particle size distribution (PSD), yet models struggle or even fail to represent coarse (diameter (d) >2.5 µm) and giant (d>20 µm) dust particles and the evolution of the PSD with transport. Here we examine three state-of-the-art airborne observational datasets, all of which measured the full size range of dust (d=0.1 to >100 µm) at different stages during transport with consistent instrumentation. We quantify the presence and evolution of coarse and giant particles and their contribution to optical properties using airborne observations over the Sahara (from the Fennec field campaign) and in the Saharan Air Layer (SAL) over the tropical eastern Atlantic (from the AER-D field campaign). Observations show significantly more abundant coarse and giant dust particles over the Sahara compared to the SAL: effective diameters of up to 20 µm were observed over the Sahara compared to 4 µm in the SAL. Excluding giant particles over the Sahara results in significant underestimation of mass concentration (40 %), as well as underestimates of both shortwave and longwave extinction (18 % and 26 %, respectively, from scattering calculations), while the effects in the SAL are smaller but non-negligible. The larger impact on longwave extinction compared to shortwave implies a bias towards a radiative cooling effect in dust models, which typically exclude giant particles and underestimate coarse-mode concentrations. A compilation of the new and published effective diameters against dust age since uplift time suggests that two regimes of dust transport exist. During the initial 1.5 d, both coarse and giant particles are rapidly deposited. During the subsequent 1.5 to 10 d, PSD barely changes with transport, and the coarse mode is retained to a much greater degree than expected from estimates of gravitational sedimentation alone. The reasons for this are unclear and warrant further investigation in order to improve dust transport schemes and the associated radiative effects of coarse and giant particles in models.

Mineral dust is an important component of the climate system, interacting with radiation, clouds and biogeochemical systems, and impacting atmospheric circulation, air quality, aviation and solar energy generation. These impacts are sensitive 10 to dust particle size distribution (PSD), yet models struggle or even fail to represent coarse (diameter (d) >2.5 µm) and giant (d>20 µm) dust particles and the evolution of the PSD with transport. Here we examine three state-of-the-art airborne observational datasets, all of which measured the full size range of dust (d=0.1 to >100 µm) at different stages during transport, with consistent instrumentation. We quantify the presence and evolution of coarse and giant particles and their contribution to optical properties. Observations are taken from the Fennec fieldwork over the Sahara and in the Saharan Air Layer (SAL) near 15 the Canary Islands, and from the AER-D fieldwork in the vicinity of the Cape Verde Islands in the SAL.Observations show significantly more abundant coarse and giant dust particles over the Sahara compared to the SAL: effective diameters of up to 20 µm were observed over the Sahara, compared to 4 µm in the SAL. Mass profiles show that over the Sahara 40% of dust mass was found in the giant mode, contrasting to 2 to 12% in the SAL. Size-resolved optical property 20 calculations show that in the shortwave (longwave) spectrum excluding the giant mode omits 18% (26%) of extinction over the Sahara, compared to 1-4% (2-6%) in the SAL. Excluding giant particles results in significant underestimation of both shortwave and longwave extinction over the Sahara, as well as of mass concentration, while the effects in the SAL are smaller but non-negligible. Omitting the giant mode results in a greater omission of dust longwave radiative effects compared to the shortwave, suggesting a bias towards a radiative cooling effect of dust when the giant mode is excluded and/or the coarse mode 25 is underestimated. This will be important in dust models, which typically exclude giant particles and underestimate coarse mode concentrations.A compilation of effective diameters against dust age since uplift time suggests that two regimes of dust transport exist. During the initial 1.5 days, both coarse and giant particles are rapidly deposited. During the subsequent 1.5 to 10 days, PSD barely 30 changes with transport, and the coarse mode is retained to a much greater degree than expected from estimates of gravitational

Abstract. The Lagrangian particle dispersion model FLEXPART was in its original version in the mid-1990s designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modelling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g. greenhouse gases, short-lived climate forcers like black carbon, or volcanic emissions, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to the global scale. In particular, inverse modelling based on source-receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.3, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts' (ECMWF) Integrated Forecast System (IFS), and data from the United States' National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physico-chemical parametrizations, input/output formats and available pre- and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes. The deviation from 100 % efficiency is almost entirely due to remaining non-parallelized parts of the code, suggesting large potential for further speed-up. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g. to quantify dispersion in the vicinity of a point source. The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option for running backward in time from atmospheric concentrations at receptor locations since many years, but this has now been extended to work also for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEXPART is the only model with that capability. Furthermore, temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane. Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART's customary binary format. In this paper, we describe these new developments. Moreover, we present some tools for the preparation of the meteorological input data and for processing of FLEXPART output data and briefly report on alternative FLEXPART versions.

Abstract. Lagrangian particle dispersion models require interpolation of all meteorological input variables to the position in space and time of computational particles. The widely used model FLEXPART uses linear interpolation for this purpose, implying that the discrete input fields contain point values. As this is not the case for precipitation (and other fluxes) which represent cell averages or integrals, a preprocessing scheme is applied which ensures the conservation of the integral quantity with the linear interpolation in FLEXPART, at least for the temporal dimension. However, this mass conservation is not ensured per grid cell, and the scheme thus has undesirable properties such as temporal smoothing of the precipitation rates. Therefore, a new reconstruction algorithm was developed, in two variants. It introduces additional supporting grid points in each time interval and is to be used with a piecewise linear interpolation to reconstruct the precipitation time series in FLEXPART. It fulfils the desired requirements by preserving the integral precipitation in each time interval, guaranteeing continuity at interval boundaries, and maintaining non-negativity. The function values of the reconstruction algorithm at the sub-grid and boundary grid points constitute the degrees of freedom, which can be prescribed in various ways. With the requirements mentioned it was possible to derive a suitable piecewise linear reconstruction. To improve the monotonicity behaviour, two versions of a filter were also developed that form a part of the final algorithm. Currently, the algorithm is meant primarily for the temporal dimension. It was shown to significantly improve the reconstruction of hourly precipitation time series from 3-hourly input data. Preliminary considerations for the extension to additional dimensions are also included as well as suggestions for a range of possible applications beyond the case of precipitation in a Lagrangian particle model. MotivationIn numerical models, extensive variables (those being proportional to the volume or area that they represent, e.g. mass and energy) are usually discretised as grid-cell integral values so that conservation properties can be fulfilled. A typical example is the precipitation flux in a meteorological forecasting model. Usually, one is interested in the precipitation at the surface, and thus the quantity of interest is a two-dimensional horizontal integral (coordinates x and y) over each grid cell. Furthermore, it is accumulated over time t during the model run and written out at distinct intervals together with other variables, such as wind and temperature. After the trivial postprocessing step of de-accumulation, each value thus represents an integral in x, y, t space -the total amount of precipitation which fell on a discrete grid cell during a discrete time interval.In Lagrangian particle dispersion models (LPDMs) (Lin et al., 2013), it is necessary to interpolate the field variables obtained from a meteorological model to particle positions in (three-dimen...