Lagrangian Transport Research Articles

Estimating the spawning locations of the deep-sea red and blue shrimp Aristeus antennatus (Crustacea: Decapoda) in the northwestern Mediterranean Sea with a backtracking larval transport model

The deep-sea red and blue shrimp Aristeus antennatus is a commercially valuable species that occurs in the northwestern Mediterranean Sea where ripe females have been found in fishing areas. In the Palamós harbor, a local management plan restricts fishing in certain locations to sustain the resource. However, little is known about the dispersal of larvae; specifically, it is not known how far larvae are transported from spawning locations and if there could be mixing of larvae between different fishing areas. The objective of this study was to estimate the spawning sites of larvae collected at 35 sampling stations, evaluate uncertainty in the estimates, and determine if larvae could be exchanged between fishing areas. The spawning sites of larvae were estimated by backward simulation of larval trajectories using a 3-dimensional coupled hydrodynamic and Lagrangian transport model. The backtracked larvae were assigned temperature-dependent stage durations based on a literature review of similar species. Results of model simulations indicated that the median distances from sampling to spawning locations were 11 and 38 km when shortest and longest pelagic durations (PD) were implemented, respectively. Sensitivity studies of backward trajectories showed that distance estimates could vary by as much as 27, 3, and 8 km due to differences in simulated PD, sub-grid-scale turbulence, and advection, respectively. Larvae from 13 of the 35 sampling stations were tracked back to multiple fishing grounds, suggesting that mixing of larvae from different fishing areas could occur. For example, for the sampling stations within the restricted area of Palamós, 35% of simulated larvae came from the restricted area itself, and 0.9% and 10% of larvae came from neighboring areas to the north and south, respectively. These results suggest that larval transport may connect subpopulations of A. antennatus across different fishing areas, an idea that may help inform regional management plans.

Contrasting impacts of climate change on connectivity and larval recruitment to estuarine nursery areas

Connectivity between spawning grounds and recruitment areas of marine fish species drives population structure and dynamics, and may be affected by climate-induced changes in oceanographic processes. We analysed the variability in recruitment success of larvae to estuarine nursery areas along the Iberian Atlantic coast of four fish species with distinct spawning grounds and periods (Solea solea, Solea senegalensis, Platichthys flesus and Dicentrarchus labrax). Concomitantly, we explored the variations in connectivity patterns between “cold” and “warm” year archetypes. We used a three-dimensional Lagrangian transport particle-tracking model integrating time series of velocity, temperature and salinity fields archived from the Regional Ocean Modelling System. We simulated individual larval dispersal, over extended spawning periods, from multiple coastal spawning areas to estuarine recruitment areas over 20 years (1989–2008). Overall, high inter- and intra-annual variation were found for all species. Nonetheless, highest overall average recruitment estimates were obtained for S. solea and D. labrax (with 7.3% and 5.7% of the particles released in spawning areas reaching a recruitment area, respectively) compared to S. senegalensis and P. flesus (3.4% and 1.7%, respectively). Recruitment estimates were overall higher at earlier spawning dates but peak values occurred at later spawning events. Regarding spawning origin, particles that recruited to the northern part of the Iberian coast were mainly from southern source areas. For estuarine systems located in southern Portugal, the relative contributions of northern and southern coastal spawning areas were more balanced, or with a preponderance of northern spawning areas (namely for S. senegalensis and D. labrax). Recruitment was higher in “warm” years compared to “cold” years, except for P. flesus for which nil recruitment was registered in the southern Iberian coast during “warm” years. Larvae also travelled farther in “warm” years compared to “cold” years. Ultimately, understanding how oceanographic conditions govern larval recruitment to estuarine nursery areas is pivotal to forecast the potential impacts of climate change on species with segregated life histories, and will underpin long term management and safeguarding of estuarine nursery role.

Dissipation scaling and structural order in turbulent channel flows

Scaling and structural evolutions are contemplated in a new perspective for turbulent channel flows. The total integrated turbulence kinetic energy and the total dissipation can be viewed as global constraints on the turbulence structure, leading to predictable, ordered scaling for u′2 and v′2 through its first and second gradients, respectively. This self-similarity allows for profile reconstructions at any Reynolds numbers based on a common template through simple multiplicative operations. Using these scaled variables in the Lagrangian transport equation derives the Reynolds shear stress, which in turn computes the mean velocity profile through the Reynolds-averaged Navier–Stokes equation. The dissipation scaling along with the transport equations renders succinct views of the turbulence dynamics and its structural characteristics. In this way, variable profiles can be analytically reconstructed, which bears potential implications toward solvability and computability of turbulent flows in canonical and other geometries.

Lagrangian Transport and Chaotic Advection in Three-Dimensional Laminar Flows

AbstractTransport and mixing of scalar quantities in fluid flows is ubiquitous in industry and Nature. While the more familiar turbulent flows promote efficient transport and mixing by their inherent spatio-temporal disorder, laminar flows lack such a natural mixing mechanism and efficient transport is far more challenging. However, laminar flow is essential to many problems, and insight into its transport characteristics of great importance. Laminar transport, arguably, is best described by the Lagrangian fluid motion (“advection”) and the geometry, topology, and coherence of fluid trajectories. Efficient laminar transport being equivalent to “chaotic advection” is a key finding of this approach. The Lagrangian framework enables systematic analysis and design of laminar flows. However, the gap between scientific insights into Lagrangian transport and technological applications is formidable primarily for two reasons. First, many studies concern two-dimensional (2D) flows, yet the real world is three-dimensional (3D). Second, Lagrangian transport is typically investigated for idealized flows, yet practical relevance requires studies on realistic 3D flows. The present review aims to stimulate further development and utilization of know-how on 3D Lagrangian transport and its dissemination to practice. To this end, 3D practical flows are categorized into canonical problems. First, to expose the diversity of Lagrangian transport and create awareness of its broad relevance. Second, to enable knowledge transfer both within and between scientific disciplines. Third, to reconcile practical flows with fundamentals on Lagrangian transport and chaotic advection. This may be a first incentive to structurally integrate the “Lagrangian mindset” into the analysis and design of 3D practical flows.

Upscaling bimolecular reactive transport in highly heterogeneous porous media with the LAgrangian Transport Eulerian Reaction Spatial (LATERS) Markov model

The LAgrangian Transport Eulerian Reaction Spatial (LATERS) Markov model was developed to predict upscaled bimolecular reactive transport in a flow around an array of solid cylinders. This method combines the stochastic Lagrangian Spatial Markov model (SMM) to predict transport and a volume averaged reaction rate equation to predict reactions of the form $$A+B\rightarrow \emptyset$$ . Here, we extend the LATERS Markov model to upscale bimolecular reactive transport in a Darcy flow through an idealized heterogeneous porous medium. In agreement with previous literature, the accuracy of the prediction is a function of the Damkohler (Da) numbers, i.e., high Da are more challenging because of incomplete mixing. It was found that a key component which must be incorporated into the upscaled model in these high Da systems is the idea that nearby A and B particles should be more likely to react than those that are farther apart. This is here achieved by appropriately reducing the resolution of the spatial grid employed to resolve the reactive process.

Incorporating features from the Stochastic Time-Inverted Lagrangian Transport (STILT) model into the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model: a unified dispersion model for time-forward and time-reversed applications

AbstractThe Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model is a state-of-the-science atmospheric dispersion model that is developed and maintained at the National Oceanic Atmospheric Administration’s (NOAA) Air Resources Laboratory (ARL). In the early 2000s, HYSPLIT served as the starting point for development of the Stochastic Time-Inverted Lagrangian Transport (STILT) model that emphasizes backward-in-time dispersion simulations to determine source regions of receptors. STILT continued its separate development and gained a wide user base. Since STILT was built on a now outdated version of HYSPLIT and lacks long-term institutional support to maintain the model, incorporating STILT features into HYSPLIT allows these features to stay up to date. This paper describes the STILT features incorporated into HYSPLIT, which include: a new vertical interpolation algorithm for WRF derived meteorological input files, a detailed algorithm for estimating boundary layer height, a new turbulence parameterization, a vertical Lagrangian timescale that varies in time and space, a complex dispersion algorithm, and two new convection schemes. An evaluation of these new features was performed using tracer release data from the Cross Appalachian Tracer Experiment and the Across North America Tracer Experiment. Results show the dispersion module from STILT, which takes up to double the amount of time to run, is less dispersive in the vertical and in better agreement with observations than the existing HYSPLIT option. The other new modeling features from STILT were not consistently statistically different than existing HYSPLIT options. Forward-time simulations from the new model were also compared against backward-time equivalents and found to be statistically comparable to one another.

An Interpolation Method to Reduce the Computational Time in the Stochastic Lagrangian Particle Dispersion Modeling of Spatially Dense XCO2 Retrievals.

A growing constellation of satellites is providing near‐global coverage of column‐averaged CO2 observations. Launched in 2019, NASA’s OCO‐3 instrument is set to provide XCO2 observations at a high spatial and temporal resolution for regional domains (100 × 100 km). The atmospheric column version of the Stochastic Time‐Inverted Lagrangian Transport (X‐STILT) model is an established method of determining the influence of upwind sources on column measurements of the atmosphere, providing a means of analysis for current OCO‐3 observations and future space‐based column‐observing missions. However, OCO‐3 is expected to provide hundreds of soundings per targeted observation, straining this already computationally intensive technique. This work proposes a novel scheme to be used with the X‐STILT model to generate upwind influence footprints with less computational expense. The method uses X‐STILT generated influence footprints from a key subset of OCO‐3 soundings. A nonlinear weighted averaging is applied to these footprints to construct additional footprints for the remaining soundings. The effects of subset selection, meteorological data, and topography are investigated for two test sites: Los Angeles, California, and Salt Lake City, Utah. The computational time required to model the source sensitivities for OCO‐3 interpretation was reduced by 62% and 78% with errors smaller than other previously acknowledged uncertainties in the modeling system (OCO‐3 retrieval error, atmospheric transport error, prior emissions error, etc.). Limitations and future applications for future CO2 missions are also discussed.

Lagrangian heat transport in turbulent three-dimensional convection

Spatial regions that do not mix effectively with their surroundings and thus contribute less to the heat transport in fully turbulent three-dimensional Rayleigh-B\'{e}nard flows are identified by Lagrangian trajectories that stay together for a longer time. These trajectories probe Lagrangian coherent sets (CS) which we investigate here in direct numerical simulations in convection cells with square cross section of aspect ratio $\Gamma = 16$, Rayleigh number $Ra = 10^{5}$, and Prandtl numbers $Pr = 0.1, 0.7$ and $7$. The analysis is based on $N=524,288$ Lagrangian tracer particles which are advected in the time-dependent flow. Clusters of trajectories are identified by a graph Laplacian with a diffusion kernel, which quantifies the connectivity of trajectory segments, and a subsequent sparse eigenbasis approximation (SEBA) for cluster detection. The combination of graph Laplacian and SEBA leads to a significantly improved cluster identification that is compared with the large-scale patterns in the Eulerian frame of reference. We show that the detected CS contribute by a third less to the global turbulent heat transport for all investigated $Pr$ compared to the trajectories in the spatial complement. This is realized by monitoring Nusselt numbers along the tracer trajectory ensembles, a dimensionless local measure of heat transfer.

Simulation of reactive solute transport in the critical zone: a Lagrangian model for transient flow and preferential transport

Abstract. We present a method to simulate fluid flow with reactive solute transport in structured, partially saturated soils using a Lagrangian perspective. In this context, we extend the scope of the Lagrangian Soil Water and Solute Transport Model (LAST) (Sternagel et al., 2019) by implementing vertically variable, non-linear sorption and first-order degradation processes during transport of reactive substances through a partially saturated soil matrix and macropores. For sorption, we develop an explicit mass transfer approach based on Freundlich isotherms because the common method of using a retardation factor is not applicable in the particle-based approach of LAST. The reactive transport method is tested against data of plot- and field-scale irrigation experiments with the herbicides isoproturon and flufenacet at different flow conditions over various periods. Simulations with HYDRUS 1-D serve as an additional benchmark. At the plot scale, both models show equal performance at a matrix-flow-dominated site, but LAST better matches indicators of preferential flow at a macropore-flow-dominated site. Furthermore, LAST successfully simulates the effects of adsorption and degradation on the breakthrough behaviour of flufenacet with preferential leaching and remobilization. The results demonstrate the feasibility of the method to simulate reactive solute transport in a Lagrangian framework and highlight the advantage of the particle-based approach and the structural macropore domain to simulate solute transport as well as to cope with preferential bypassing of topsoil and subsequent re-infiltration into the subsoil matrix.

Assessment of the spawning habitat, spatial distribution, and Lagrangian dispersion of the European anchovy (Engraulis encrasicolus) early stages in the Gulf of Cadiz during an apparent anomalous episode in 2016

Modelling the environmental factors influencing the spatial variation of fish early life stages density and their drift history can identify the key biological and physical processes for the recruitment variability. Distance-based linear multivariate techniques were used to characterize the spawning areas of the European anchovy Engraulis encrasicolus in the Gulf of Cadiz (GoC). Chlorophyll is the environmental variable that best characterized its spawning areas with a time-lag of three days. The use of Lagrangian models to simulate the dispersal of small pelagic species more dependent on advection such as the European anchovy early life stages (early larvae and eggs) in the GoC could provide the degree of connectivity between spawning and nursery areas and identify the physical drivers of the recruitment variability. The larval final destination is critical for the survival of a marine species which is coastal-dependent during its early life stages. Simulations with a Lagrangian transport model in the Southwest Iberian Peninsula were performed during the most intense spawning peak of 2016, when a strong and persistent countercurrent event developed. Most of the simulated early life stages were transported to the western Portuguese coast and, to a lesser extent, to the Atlantic oligotrophic waters, suggesting an increase in the connectivity between the subdivision 9a South and West components. Although different environmental processes occurring during ontogenetic stages, as well as overfishing, among others, can explain part of the variability observed in recruitment, events such as the development of coastal countercurrents during the spawning season could partly account for an increase of anchovy on the western Portuguese coast and a decrease in the Gulf of Cadiz one year later.

Rapid assessment tool for oil spill planning and contingencies

The Rapid Oil Spill Hazard Assessment is presented as a demonstration of concept for a tool providing a framework for managers and planners to assess potential impact areas of oil spills. The tool consists of precomputed oil spill scenarios derived from the analysis of twenty years of modeled current data using Self-Organizing Maps to identify 16 representative patterns. These patterns were used to provide boundary conditions for hydrodynamic and wave models to generate higher resolution current fields, used to drive a Lagrangian oil particle transport model creating the most probable oil spill dispersion patterns. To demonstrate the concept, the tool is applied to the Perdido region in the western Gulf of Mexico. A total of 896 oil spill simulations were performed, considering surface and bottom spills, and were stored in a database for easy access to map arrival probabilities and times to be used in risk and vulnerability analysis.

On the model uncertainties in Bayesian source reconstruction using an ensemble of weather predictions, the emission inverse modelling system FREAR v1.0, and the Lagrangian transport and dispersion model Flexpart v9.0.2

Abstract. Bayesian source reconstruction is a powerful tool for determining atmospheric releases. It can be used, amongst other applications, to identify a point source releasing radioactive particles into the atmosphere. This is relevant for applications such as emergency response in case of a nuclear accident or Comprehensive Nuclear-Test-Ban treaty verification. The method involves solving an inverse problem using environmental radioactivity observations and atmospheric transport models. The Bayesian approach has the advantage of providing an uncertainty quantification on the inferred source parameters. However, it requires the specification of the inference input errors, such as the observation error and model error. The latter is particularly hard to provide as there is no straightforward way to determine the atmospheric transport and dispersion model error. Here, the importance of model error is illustrated for Bayesian source reconstruction using a recent and unique case where radionuclides were detected on several continents. A numerical weather prediction ensemble is used to create an ensemble of atmospheric transport and dispersion simulations, and a method is proposed to determine the model error.

The Facility Level and Area Methane Emissions inventory for the Greater Toronto Area (FLAME-GTA)

We present the Facility Level and Area Methane (CH4) Emissions inventory for the Greater Toronto Area (FLAME-GTA). We estimate that total emissions of CH4 in the GTA, the most populous metropolitan area in Canada, are about 86 ± 38 Gg/yr. The FLAME-GTA estimate is within uncertainty of, but lower in magnitude than the existing gridded inventories provided by the Emissions Database for Global Atmospheric Research (EDGAR v 5.0), and by Environment and Climate Change Canada's Air Quality Research Division (ECCC - AQRD) that estimate emissions of 96 ± 48 Gg/yr and 143 ± 71 Gg/yr in the GTA region, respectively. Using a Lagrangian transport model, we predict atmospheric mixing ratios based on different emission inventories and compare the predictions with in situ measurements available from an observatory within the GTA for January–March in both 2015 and 2016. Due to the strong influence of local sources on our observations only a subregion of our GTA inventory is evaluated. These results identify the need for a more extensive measurement network and an improved atmospheric transport modeling effort for further evaluation of the emission inventories.

Numerical study on blue mackerel larval transport in East China Sea

Abstract An Individual-based model (IBM) for studying the blue mackerel larval transport in East China Sea (ECS), for the first time, is developed based on Ichthyop model. Coastal and Regional Ocean Community model (CROCO), a typical hydrodynamic model, is configured as well to provide Ichthyop with the physical variables (e.g. temperature, salinity, current). Effects of physical environments (current and temperature), spawning ground/depth/time and diel vertical migration (DVM) on aspects of the early life stage of blue mackerel, including connectivity between spawning ground and nursery area, temperature-dependent mortality, transportation and dispersal distance, are discussed in detail for the first time based on IBM. Two transport scenarios are considered in our simulations: (1) passive Lagrangian transport and (2) DVM. The experimental results show that the transport of the blue mackerel in ECS is principally controlled by the Kuroshio Current (KC) and Tsushima Warm Current (TSWC). Most of the larvae that affected by TSWC are mainly remained in ECS stock, while those controlled by KC are generally confined in the Pacific stock. In passive Lagrangian transport, the larvae from the largest spawning ground do not only remain in ECS stock but also drift to the Pacific stock in February. In travelling to the Pacific stock, the larvae will experience a long-distance trip and may spread away from the suitable growth area, which is not conducive to their survival. Whereas in DVM scenario, cases with different vertical migration mechanisms all have shorter dispersal distances comparing to the first scenario, the long-distance movement is significantly reduced during the simulating period, particularly in February. DVM tends to prevent the larvae entering the Pacific stock from the largest spawning ground in ECS, thus could increase the recruitment and survival for ECS stock.

Effects of Wave-Induced Processes in a Coupled Wave–Ocean Model on Particle Transport Simulations

This study investigates the effects of wind–wave processes in a coupled wave–ocean circulation model on Lagrangian transport simulations. Drifters deployed in the southern North Sea from May to June 2015 are used. The Eulerian currents are obtained by simulation from the coupled circulation model (NEMO) and the wave model (WAM), as well as a stand-alone NEMO circulation model. The wave–current interaction processes are the momentum and energy sea state dependent fluxes, wave-induced mixing and Stokes–Coriolis forcing. The Lagrangian transport model sensitivity to these wave-induced processes in NEMO is quantified using a particle drift model. Wind waves act as a reservoir for energy and momentum. In the coupled wave–ocean circulation model, the momentum that is transferred into the ocean model is considered as a fraction of the total flux that goes directly to the currents plus the momentum lost from wave dissipation. Additional sensitivity studies are performed to assess the potential contribution of windage on the Lagrangian model performance. Wave-induced drift is found to significantly affect the particle transport in the upper ocean. The skill of particle transport simulations depends on wave–ocean circulation interaction processes. The model simulations were assessed using drifter and high-frequency (HF) radar observations. The analysis of the model reveals that Eulerian currents produced by introducing wave-induced parameterization into the ocean model are essential for improving particle transport simulations. The results show that coupled wave–circulation models may improve transport simulations of marine litter, oil spills, larval drift or transport of biological materials.

Persistent meanders and eddies lead to quasi-steady Lagrangian transport patterns in a weak western boundary current

The Brazil Current (BC) is a weak western boundary current flowing along the Southwestern Atlantic Ocean. It is frequently described as a flow with intense mesoscale activity and relatively low volume transport between 5.0 and 10.0 Sv. We use a 13-year eddy-resolving primitive-equation simulation to show that the presence of persistent meanders and eddies leads to characteristic quasi-steady Lagrangian transport patterns, aptly extracted through climatological Lagrangian Coherent Structures (cLCS). The cLCS position the surface expression of the BC core along the 2000-m isobath, in excellent visual agreement with high resolution satellite sea-surface temperature and the model Eulerian mean velocity. The cLCS deformation pattern also responds to zonally persistent cross-shelf SSH transition from positive (high) values near coastline to low (negative) values between 200- and 2000-m and back to positive (high) offshore from the 2000-m isobath. Zonally-paired cyclonic and anticyclonic structures are embedded in this transition, also causing the cLCS to deform into chevrons. An efficient transport barrier is identified close to the 200-m isobath confirmed by limited inshore movement of drogued drifters and accurately indicated by an along slope maxima of climatological strength of attraction. We also show that the persistent cyclonic and anticyclonic structures may induce localized cross-shelf transport. Regions of low climatological strength of attraction coincide with large shelves and with stagnant synthetic trajectories. We also show that cLCS accurately depict trajectories initiated at the location of Chevron’s spill (November 2011) as compared to synthetic and satellite-tracked trajectories, and the outline of the oil from that accident. There is also an agreement between the large-scale oil slicks reaching the Brazilian beaches (from August 2019 to February 2020) and the strength of climatological attraction at the coast. Our work also clarifies the influence of persistent mesoscale structures on the regional circulation. The identification and quantitative description of climatological Lagrangian coherent structures is expected to improve the effectiveness of future emergency response to oil spills, contingency planning, rescue operations, larval and fish connectivity assessment, drifter launch strategies, waste pollutant and marine debris dispersion and destination.

Lagrangian transport in two‐dimensional time‐periodic cavity flow

AbstractThe Lagrangian transport in a laminar incompressible flow in a two‐dimensional square cavity driven by a harmonic tangential oscillation of a single cavity wall is investigated numerically for a range of Reynolds (Re) and Strouhal (Str) numbers. The topology of fluid trajectories is described by means of stroboscopic projections, which reveal the co‐existence of chaotic trajectories and regular Kolmogorov‐Arnold‐Moser (KAM) tori. The higher the frequency of the lid oscillation the more regular the fluid motion becomes and the size of the KAM tori increases. For low frequencies the KAM tori are strongly stretched along instantaneous streamlines of the flow, while for high frequencies they resemble streamlines of a mean flow.

Stochastic Variational Formulations of Fluid Wave\u2013Current Interaction

We are modelling multiscale, multi-physics uncertainty in wave–current interaction (WCI). To model uncertainty in WCI, we introduce stochasticity into the wave dynamics of two classic models of WCI, namely the generalised Lagrangian mean (GLM) model and the Craik–Leibovich (CL) model. The key idea for the GLM approach is the separation of the Lagrangian (fluid) and Eulerian (wave) degrees of freedom in Hamilton’s principle. This is done by coupling an Euler–Poincaré reduced Lagrangian for the current flow and a phase-space Lagrangian for the wave field. WCI in the GLM model involves the nonlinear Doppler shift in frequency of the Hamiltonian wave subsystem, which arises because the waves propagate in the frame of motion of the Lagrangian-mean velocity of the current. In contrast, WCI in the CL model arises because the fluid velocity is defined relative to the frame of motion of the Stokes mean drift velocity, which is usually taken to be prescribed, time independent and driven externally. We compare the GLM and CL theories by placing them both into the general framework of a stochastic Hamilton’s principle for a 3D Euler–Boussinesq (EB) fluid in a rotating frame. In other examples, we also apply the GLM and CL methods to add wave physics and stochasticity to the familiar 1D and 2D shallow water flow models. The differences in the types of stochasticity which arise for GLM and CL models can be seen by comparing the Kelvin circulation theorems for the two models. The GLM model acquires stochasticity in its Lagrangian transport velocity for the currents and also in its group velocity for the waves. However, the CL model is based on defining the Eulerian velocity in the integrand of the Kelvin circulation relative to the Stokes drift velocity induced by waves driven externally. Thus, the Kelvin theorem for the stochastic CL model can accept stochasticity in its both its integrand and in the Lagrangian transport velocity of its circulation loop. In an “Appendix”, we also discuss dynamical systems analogues of WCI.

Impact of Lagrangian transport on lower-stratospheric transport timescales in a climate model

Abstract. We investigate the impact of model trace gas transport schemes on the representation of transport processes in the upper troposphere and lower stratosphere. Towards this end, the Chemical Lagrangian Model of the Stratosphere (CLaMS) was coupled to the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and results from the two transport schemes (Lagrangian critical Lyapunov scheme and flux-form semi-Lagrangian, respectively) were compared. Advection in CLaMS was driven by the EMAC simulation winds, and thereby the only differences in transport between the two sets of results were caused by differences in the transport schemes. To analyze the timescales of large-scale transport, multiple tropical-surface-emitted tracer pulses were performed to calculate age of air spectra, while smaller-scale transport was analyzed via idealized, radioactively decaying tracers emitted in smaller regions (nine grid cells) within the stratosphere. The results show that stratospheric transport barriers are significantly stronger for Lagrangian EMAC-CLaMS transport due to reduced numerical diffusion. In particular, stronger tracer gradients emerge around the polar vortex, at the subtropical jets, and at the edge of the tropical pipe. Inside the polar vortex, the more diffusive EMAC flux-form semi-Lagrangian transport scheme results in a substantially higher amount of air with ages from 0 to 2 years (up to a factor of 5 higher). In the lowermost stratosphere, mean age of air is much smaller in EMAC, owing to stronger diffusive cross-tropopause transport. Conversely, EMAC-CLaMS shows a summertime lowermost stratosphere age inversion – a layer of older air residing below younger air (an “eave”). This pattern is caused by strong poleward transport above the subtropical jet and is entirely blurred by diffusive cross-tropopause transport in EMAC. Potential consequences from the choice of the transport scheme on chemistry–climate and geoengineering simulations are discussed.

Investigating the Long-Range Transport of Aerosol Plumes Following the Amazon Fires (August 2019): A Multi-Instrumental Approach from Ground-Based and Satellite Observations

Despite a number of studies on biomass burning (BB) emissions in the atmosphere, observation of the associated aerosols and pollutants requires continuous efforts. Brazil, and more broadly Latin America, is one of the most important seasonal sources of BB, particularly in the Amazon region. Uncertainty about aerosol loading in the source regions is a limiting factor in terms of understanding the role of aerosols in climate modelling. In the present work, we investigated the Amazon BB episode that occurred during August 2019 and made the international headlines, especially when the smoke plumes plunged distant cities such as São Paulo into darkness. Here, we used satellite and ground-based observations at different locations to investigate the long-range transport of aerosol plumes generated by the Amazon fires during the study period. The monitoring of BB activity was carried out using fire related pixel count from the moderate resolution imaging spectroradiometer (MODIS) onboard the Aqua and Terra platforms, while the distribution of carbon monoxide (CO) concentrations and total columns were obtained from the infrared atmospheric sounding interferometer (IASI) onboard the METOP-A and METOP-B satellites. In addition, AERONET sun-photometers as well as the MODIS instrument made aerosol optical depth (AOD) measurements over the study region. Our datasets are consistent with each other and highlight AOD and CO variations and long-range transport of the fire plume from the source regions in the Amazon basin. We used the Lagrangian transport model FLEXPART (FLEXible PARTicle) to simulate backward dispersion, which showed good agreement with satellite and ground measurements observed over the study area. The increase in Rossby wave activity during the 2019 austral winter the Southern Hemisphere may have contributed to increasing the efficiency of large-scale transport of aerosol plumes generated by the Amazon fires during the study period.