The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such that occurring after an accident in a nuclear power plant. In the meantime, FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. A need for further multiscale modeling and analysis has encouraged new developments in FLEXPART. In this paper, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run this new model and present special options and features that differ from those of the preceding versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization, and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format, both of which have efficient data compression. In addition, test case data and the source code are provided to the reader as a Supplement. This material and future developments will be accessible at http://www.flexpart.eu.Peer ReviewedPostprint (published version

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. Ozone and nitrous oxide are measured at high spatial and temporal resolution by instruments flying on the ER-2 NASA research aircraft. Comparing the airborne transects to reconstructions by ensemble of diffusive backward trajectories allows estimation of the average vertical Lagrangian turbulent diffusion experienced by the air parcels. The resulting estimates show large Lagrangian diffusion of the order of 0.1 m 2 s −1 in the surf zone outside the polar vortex and smaller values of the order of 0.01 m 2 s −1 inside. Locally, large variation of Lagrangian diffusion occurs over mesoscale distances. It is found that high temporal resolution (3 h or less) is required for off-line transport calculations and that the reconstructions are sensitive to spurious motion in standard analysed winds.

We find that summer methane (CH4) release from seabed sediments west of Svalbard substantially increases CH4 concentrations in the ocean but has limited influence on the atmospheric CH4 levels. Our conclusion stems from complementary measurements at the seafloor, in the ocean, and in the atmosphere from land‐based, ship and aircraft platforms during a summer campaign in 2014. We detected high concentrations of dissolved CH4 in the ocean above the seafloor with a sharp decrease above the pycnocline. Model approaches taking potential CH4 emissions from both dissolved and bubble‐released CH4 from a larger region into account reveal a maximum flux compatible with the observed atmospheric CH4 mixing ratios of 2.4–3.8 nmol m−2 s−1. This is too low to have an impact on the atmospheric summer CH4 budget in the year 2014. Long‐term ocean observatories may shed light on the complex variations of Arctic CH4 cycles throughout the year.

Atmospheric measurements show an increase in CH 4 from the 1980s to 1998 followed by a period of near-zero growth until 2007. However, from 2007, CH 4 has increased again. Understanding the variability in CH 4 is critical for climate prediction and climate change mitigation. We examine the role of CH 4 sources and the dominant CH 4 sink, oxidation by the hydroxyl radical (OH), in atmospheric CH 4 variability over the past three decades using observations of CH 4 , C 2 H 6 , and δ 13 C CH4 in an inversion. From 2006 to 2014, microbial and fossil fuel emissions increased by 36 ± 12 and 15 ± 8 Tg y À1 , respectively. Emission increases were partially offset by a decrease in biomass burning of 3 ± 2 Tg y À1 and increase in soil oxidation of 5 ± 6 Tg y À1 . A change in the atmospheric sink did not appear to be a significant factor in the recent growth of CH 4 .Plain Language Summary Methane is the second most important greenhouse gas and is responsible for approximately 17% of the direct radiative forcing from all long-lived greenhouse gases. Observations of methane in the atmosphere have shown a dramatic increase from 2007 after a period of relative stability between the late 1990s and early 2000s, but the cause of this increase is still under scientific debate. This study uses atmospheric observations of methane and two related tracers, the isotopic ratio of carbon in methane and ethane, to constrain the sources and sinks of methane over the past three decades. The increase in methane between 2007 and 2014 is likely due to an increase in microbial sources, of 24-48 Tg/y (predominantly natural wetlands and agricultural), as well as fossil fuel sources, of 7-23 Tg/y. In contrast to other recent studies, a reduction in the atmospheric sink of methane was found not to be a significant factor in explaining the recent atmospheric increase.