The European Centre for Medium-Range Weather Forecasts' (ECMWF's) next-generation reanalysis ERA5 provides many improvements, but it also confronts the community with a “big data” challenge. Data storage requirements for ERA5 increase by a factor of ∼80 compared with the ERA-Interim reanalysis, introduced a decade ago. Considering the significant increase in resources required for working with the new ERA5 data set, it is important to assess its impact on Lagrangian transport simulations. To quantify the differences between transport simulations using ERA5 and ERA-Interim data, we analyzed comprehensive global sets of 10-day forward trajectories for the free troposphere and the stratosphere for the year 2017. The new ERA5 data have a considerable impact on the simulations. Spatial transport deviations between ERA5 and ERA-Interim trajectories are up to an order of magnitude larger than those caused by parameterized diffusion and subgrid-scale wind fluctuations after 1 day and still up to a factor of 2–3 larger after 10 days. Depending on the height range, the spatial differences between the trajectories map into deviations as large as 3 K in temperature, 30 % in specific humidity, 1.8 % in potential temperature, and 50 % in potential vorticity after 1 day. Part of the differences between ERA5 and ERA-Interim is attributed to the better spatial and temporal resolution of the ERA5 reanalysis, which allows for a better representation of convective updrafts, gravity waves, tropical cyclones, and other meso- to synoptic-scale features of the atmosphere. Another important finding is that ERA5 trajectories exhibit significantly improved conservation of potential temperature in the stratosphere, pointing to an improved consistency of ECMWF's forecast model and observations that leads to smaller data assimilation increments. We conducted a number of downsampling experiments with the ERA5 data, in which we reduced the numbers of meteorological time steps, vertical levels, and horizontal grid points. Significant differences remain present in the transport simulations, if we downsample the ERA5 data to a resolution similar to ERA-Interim. This points to substantial changes of the forecast model, observations, and assimilation system of ERA5 in addition to improved resolution. A comparison of two Lagrangian trajectory models allowed us to assess the readiness of the codes and workflows to handle the comprehensive ERA5 data and to demonstrate the consistency of the simulation results. Our results will help to guide future Lagrangian transport studies attempting to navigate the increased computational complexity and leverage the considerable benefits and improvements of ECMWF's new ERA5 data set.

The Asian summer monsoon provides an important pathway of tropospheric source gases and pollution into the lower stratosphere. This transport is characterized by deep convection and steady upwelling, combined with confinement inside a large-scale anticyclonic circulation in the upper troposphere and lower stratosphere (UTLS). In this paper, we show that a barrier to horizontal transport along the 380 K isentrope in the monsoon anticyclone can be determined from a local maximum in the gradient of potential vorticity (PV), following methods developed for the polar vortex (e.g., Nash et al., 1996). The monsoon anticyclone is dynamically highly variable and the maximum in the PV gradient is weak, such that additional constraints are needed (e.g., time averaging). Nevertheless, PV contours in the monsoon anticyclone agree well with contours of trace gas mixing ratios (CO, O₃) and mean age from model simulations with a Lagrangian chemistry transport model (CLaMS) and satellite observations from the Microwave Limb Sounder (MLS) instrument. Hence, the PV-based transport barrier reflects the separation between air inside the core of the anticyclone and the background atmosphere well. For the summer season 2011 we find an average PV value of 3.6 PVU for the transport barrier in the anticyclone on the 380 K isentrope.

The international research project RECONCILE has addressed central questions regarding polar ozone depletion, with the objective to quantify some of the most relevant yet still uncertain physical and chemical processes and thereby improve prognostic modelling capabilities to realistically predict the response of the ozone layer to climate change. This overview paper outlines the scope and the general approach of RECONCILE, and it provides a summary of observations and modelling in 2010 and 2011 that have generated an in many respects unprecedented dataset to study processes in the Arctic winter stratosphere. Principally, it summarises important outcomes of RECONCILE including (i) better constraints and enhanced consistency on the set of parameters governing catalytic ozone destruction cycles, (ii) a better understanding of the role of cold binary aerosols in heterogeneous chlorine activation, (iii) an improved scheme of polar stratospheric cloud (PSC) processes that includes heterogeneous nucleation of nitric acid trihydrate (NAT) and ice on non-volatile background aerosol leading to better model parameterisations with respect to denitrification, and (iv) long transient simulations with a chemistry-climate model (CCM) updated based on the results of RECONCILE that better reproduce past ozone trends in Antarctica and are deemed to produce more reliable predictions of future ozone trends. The process studies and the global simulations conducted in RECONCILE show that in the Arctic, ozone depletion uncertainties in the chemical and microphysical processes are now clearly smaller than the sensitivity to dynamic variability.

Sulfur dioxide (SO₂) emissions from strong volcanic eruptions are an important natural cause for climate variations. We applied our new Lagrangian transport model Massive‐Parallel Trajectory Calculations to perform simulations for three case studies of volcanic eruption events. The case studies cover the eruptions of Grímsvötn, Iceland, Puyehue‐Cordón Caulle, Chile, and Nabro, Eritrea, in May and June 2011. We used SO₂ observations of the Atmospheric Infrared Sounder (AIRS/Aqua) and a backward trajectory approach to initialize the simulations. Besides validation of the new model, the main goal of our study was a comparison of simulations with different meteorological data products. We considered three reanalyses, i.e., ERA‐Interim, Modern‐Era Retrospective Analysis for Research and Applications (MERRA), and National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) Reanalysis Project as well as the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational analysis. Qualitatively, the SO₂ distributions from the simulations compare well not only with the AIRS data but also with Cloud‐Aerosol Lidar with Orthogonal Polarization and Michelson Interferometer for Passive Atmospheric Sounding aerosol observations. Transport deviations and the critical success index (CSI) are analyzed to evaluate the simulations quantitatively. During the first 5 or 10 days after the eruptions we found the best performance for the ECMWF analysis (CSI range of 0.25–0.31), followed by ERA‐Interim (0.25–0.29), MERRA (0.23–0.27), and NCAR/NCEP (0.21–0.23). High temporal and spatial resolution of the meteorological data does lead to improved performance of Lagrangian transport simulations of volcanic emissions in the upper troposphere and lower stratosphere.

Lagrangian models are fundamental tools to study atmospheric transport processes and for practical applications such as dispersion modeling for anthropogenic and natural emission sources. However, conducting large-scale Lagrangian transport simulations with millions of air parcels or more can become rather numerically costly. In this study, we assessed the potential of exploiting graphics processing units (GPUs) to accelerate Lagrangian transport simulations. We ported the Massive-Parallel Trajectory Calculations (MPTRAC) model to GPUs using the open accelerator (OpenACC) programming model. The trajectory calculations conducted within the MPTRAC model were fully ported to GPUs, i.e., except for feeding in the meteorological input data and for extracting the particle output data, the code operates entirely on the GPU devices without frequent data transfers between CPU and GPU memory. Model verification, performance analyses, and scaling tests of the Message Passing Interface (MPI) – Open Multi-Processing (OpenMP) – OpenACC hybrid parallelization of MPTRAC were conducted on the Jülich Wizard for European Leadership Science (JUWELS) Booster supercomputer operated by the Jülich Supercomputing Centre, Germany. The JUWELS Booster comprises 3744 NVIDIA A100 Tensor Core GPUs, providing a peak performance of 71.0 PFlop s⁻¹. As of June 2021, it is the most powerful supercomputer in Europe and listed among the most energy-efficient systems internationally. For large-scale simulations comprising 10⁸ particles driven by the European Centre for Medium-Range Weather Forecasts' fifth-generation reanalysis (ERA5), the performance evaluation showed a maximum speed-up of a factor of 16 due to the utilization of GPUs compared to CPU-only runs on the JUWELS Booster. In the large-scale GPU run, about 67 % of the runtime is spent on the physics calculations, conducted on the GPUs. Another 15 % of the runtime is required for file I/O, mostly to read the large ERA5 data set from disk. Meteorological data preprocessing on the CPUs also requires about 15 % of the runtime. Although this study identified potential for further improvements of the GPU code, we consider the MPTRAC model ready for production runs on the JUWELS Booster in its present form. The GPU code provides a much faster time to solution than the CPU code, which is particularly relevant for near-real-time applications of a Lagrangian transport model.

Monitoring and modeling of volcanic plumes are important for understanding the impact of volcanic activity on climate and for practical concerns, such as aviation safety or public health. Here, we apply the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) to estimate the SO₂ injections into the upper troposphere and lower stratosphere by the eruption of the Raikoke volcano (48.29^∘ N, 153.25^∘ E) in June 2019 and its subsequent long-range transport and dispersion. First, we used SO₂ retrievals from the AIRS (Atmospheric Infrared Sounder) and TROPOMI (TROPOspheric Monitoring Instrument) satellite instruments together with a backward trajectory approach to estimate the altitude-resolved SO₂ injection time series. Second, we applied a scaling factor to the initial estimate of the SO₂ mass and added an exponential decay to simulate the time evolution of the total SO₂ mass. By comparing the estimated SO₂ mass and the mass from TROPOMI retrievals, we show that the volcano injected 2.1 ± 0.2 Tg SO₂, and the e-folding lifetime of the SO₂ was about 13 to 17 d. The reconstructed SO₂ injection time series are consistent between using the AIRS nighttime and the TROPOMI daytime products. Further, we compared forward transport simulations that were initialized by AIRS and TROPOMI SO₂ products with a constant SO₂ injection rate. The results show that the modeled SO₂ change, driven by chemical reactions, captures the SO₂ mass variations from TROPOMI retrievals. In addition, the forward simulations reproduce the SO₂ distributions in the first ∼10 d after the eruption. However, diffusion in the forward simulations is too strong to capture the internal structure of the SO₂ clouds, which is further quantified in the simulation of the compact SO₂ cloud from late July to early August. Our study demonstrates the potential of using combined nadir satellite retrievals and Lagrangian transport simulations to further improve SO₂ time- and height-resolved injection estimates of volcanic eruptions.