A Hard Sphere Model for Bimolecular Recombination of Heavy Ions

We propose a hard sphere model of bimolecular recombination RM+ + X– → MX + R, where M+ is an alkali ion, X– is a halide ion, and R is a neutral rare gas or mercury atom. Calculations are carried out for M+ = Cs+, X– = Br–, R = Ar, Kr, Xe, Hg, for collision energies in the range from 1 to 10 eV, and for distributions of the RM+ complex internal energy corresponding to temperatures of 500, 1000, and 2000 K. The excitation functions and opacity functions of bimolecular recombination in the hard sphere approximation are found, and the classification of the collisions according to the sequences of pairwise encounters of the particles is considered. In more than half of all the cases, recombination occurs due to a single impact of the Br– ion with the R atom. For the recombination XeCs+ + Br–, the hard sphere model enables one to reproduce the most important characteristics of the collision energy dependence of the recombination probability obtained within the framework of quasiclassical trajectory calculations.

Massive-Parallel Trajectory Calculations version 2.2 (MPTRAC-2.2): Lagrangian transport simulations on Graphics Processing Units (GPUs)

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 numerically rather 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 MPI/OpenMP/OpenACC hybrid parallelization of MPTRAC were conducted on the 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. 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' ERA5 reanalysis, the performance evaluation showed a maximum speedup 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.

Massive-Parallel Trajectory Calculations version 2.2 (MPTRAC-2.2): Lagrangian transport simulations on Graphics Processing Units (GPUs)

Lagrangian models are powerful tools to study atmospheric transport processes. However, conducting large-scaleLagrangian transport simulations with many air parcels can become numerically rather 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 have been 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 MPI/OpenMP/OpenACC hybrid parallelization of MPTRAC have been conducted on the JUWELS Booster supercomputer operated by the Jülich Supercomputing Centre, Germany. The JUWELS Booster comprises 3744 NVIDIA A100 Tensor CoreGPUs, providing a peak performance of 71.0 PFlop/s. 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 100 million particles driven by the European Centre for Medium-Range Weather Forecasts’ ERA5 reanalysis, the performance evaluation showed a maximum speedup 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, being conducted on the GPUs. Another 15 % of the runtime is required for file-I/O, mostly to read the ERA5 data 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 to be 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

Contribution of Asian emissions to upper tropospheric CO over the remote Pacific

We use CO data from the MOPITT satellite instrument from 2000–2019 to compose a climatology of severe pollution events in the mid- and upper troposphere over the northern-hemispheric (NH-) Pacific. To link each individual pollution event detected by MOPITT with a CO source region, we performed trajectory calculations using MPTRAC, a lagrangian transport model. To analyse transport pathways and uplift mechanisms we combine MOPITT data, the trajectory calculations and ERA-Interim reanalysis data. Events of elevated CO which we detect at level between 500 hPa and 300 hPa over the NH-Pacific throughout the year, occur with a surprisingly high regularity and frequency (70 % of all days during winter, 80 % respectively during spring). Our study further indicates, that the spatial coverage of individual upper tropospheric pollution cluster increased in spring time during the 20 years we analysed. The position of upper tropospheric pollution plumes show a strong seasonal cycle. During winter, most pollution events are detected over the north-eastern and central NH-Pacific, during spring over the central NH-Pacific and during summer over the western NH-Pacific. We detect most pollution episodes during spring. Trajectory simulations reveal China as the major CO-source region throughout the year. The contribution of other source regions shows a strong seasonal cycle: NE-Asia is a significant CO-source region during winter and summer while India and SE-Asia are important source regions mainly during spring.

Sensitivity of stratospheric water vapour to variability in tropical tropopause temperatures and large-scale transport

Concentrations of water vapour entering the tropical lower stratosphere are primarily determined by conditions that air parcels encounter as they are transported through the tropical tropopause layer (TTL). Here we quantify the relative roles of variations in TTL temperatures and transport in determining seasonal and interannual variations of stratospheric water vapour. Following previous studies, we use trajectory calculations with the water vapour concentration set by the Lagrangian dry point (LDP) along trajectories. To assess the separate roles of transport and temperatures, the LDP calculations are modified by replacing either the winds or the temperatures with those from different years to investigate the wind or temperature sensitivity of water vapour to interannual variations and, correspondingly, with those from different months to investigate the wind or temperature sensitivity to seasonal variations. Both ERA-Interim reanalysis data for the 1999–2009 period and data generated by a chemistry–climate model (UM-UKCA) are investigated. Variations in temperatures, rather than transport, dominate interannual variability, typically explaining more than 70 % of variability, including individual events such as the 2000 stratospheric water vapour drop. Similarly seasonal variation of temperatures, rather than transport, is shown to be the dominant driver of the annual cycle in lower stratospheric water vapour concentrations in both the model and reanalysis, but it is also shown that seasonal variation of transport plays an important role in reducing the seasonal cycle maximum (reducing the annual range by about 30 %). The quantitative role in dehydration of sub-seasonal and sub-monthly Eulerian temperature variability is also examined by using time-filtered temperature fields in the trajectory calculations. Sub-monthly temperature variability reduces annual mean water vapour concentrations by 40 % in the reanalysis calculation and 30 % in the model calculation. As with other aspects of dehydration, simple Eulerian measures of variability are not sufficient to quantify the implications for dehydration, and the Lagrangian sampling of the variability must be taken into account. These results indicate that, whilst capturing seasonal and interannual variation of temperature is a major factor in modelling realistic stratospheric water vapour concentrations, simulation of seasonal variation of transport and of sub-seasonal and sub-monthly temperature variability are also important and cannot be ignored.

Dependence of the ROT effect on the energy of different light charged particles and on the incident neutron energy

The shift of the angular distribution of different light charged particles in ternary fission of 235U induced by polarized neutrons, the so-called ROT effect, was estimated by modified trajectory calculations, which take into account the rotation of the compound nucleus. In previous publications only α-particles were considered. It is shown here that inclusion of tritons significantly improves the agreement of the energy dependence of the ROT effect with experiment while the inclusion of 5He particles practically does not influence this dependence. In particular, the change in the magnitude of the ROT effect depending on the energy of incident neutrons is correctly predicted. Also, the ROT effect for gamma quanta and neutrons in binary fission is discussed along the same lines, because all mentioned effects are proportional to the effective angular velocity of the compound nucleus at the moment of scission.