Chemistry Across Multiple Phases (CAMP) version 1.0: an integrated multiphase chemistry model

A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an “abstracted aerosol representation” that allows a given chemical mechanism to be solved in atmospheric models with different aerosol representations (e.g., sectional, modal, or particle-resolved). This is accomplished by treating aerosols as a collection of condensed phases that are implemented according to the aerosol representation of the host model. The framework also allows multiple chemical processes (e.g., gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass transfer) to be solved simultaneously as a single system. The flexibility of the model is achieved by (1) using an object-oriented design that facilitates extensibility to new types of chemical processes and to new ways of representing aerosol systems, (2) runtime model configuration using JSON input files that permits making changes to any part of the chemical mechanism without recompiling the model (this widely used, human-readable format allows entire gas- and aerosol-phase chemical mechanisms to be described with as much complexity as necessary), and (3) automated comprehensive testing that ensures stability of the code as new functionality is introduced. Together, these design choices enable users to build a customized multiphase mechanism without having to handle preprocessors, solvers, or compilers. Removing these hurdles makes this type of modeling accessible to a much wider community, including modelers, experimentalists, and educators. This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the Multiscale Online AtmospheRe CHemistry (MONARCH) chemical weather prediction system for use at regional and global scales. Results from the initial deployment to box models of different complexity and MONARCH will be discussed, along with future extension to more complex gas–aerosol systems and the integration of GPU-based solvers.Matthew L. Dawson has received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. 747048. Matthew L. Dawson, Oriol Jorba, and Christian Guzman have been supported by the Ministerio de Ciencia, Innovación y Universidades (grant no. RTI2018-099894-BI00). Christian Guzman acknowledges funding from the AXA Research Fund. Nicole Riemer, Matthew West, and Jeffrey H. Curtis acknowledge funding from the National Science Foundation (grant no. AGS 19-41110). This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under cooperative agreement no. 1852977.Peer ReviewedPostprint (published version

Chemistry Across Multiple Phases (CAMP) version 1.0: an integrated multiphase chemistry model

A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an “abstracted aerosol representation” that allows a given chemical mechanism to be solved in atmospheric models with different aerosol representations (e.g., sectional, modal, or particle-resolved). This is accomplished by treating aerosols as a collection of condensed phases that are implemented according to the aerosol representation of the host model. The framework also allows multiple chemical processes (e.g., gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass transfer) to be solved simultaneously as a single system. The flexibility of the model is achieved by (1) using an object-oriented design that facilitates extensibility to new types of chemical processes and to new ways of representing aerosol systems, (2) runtime model configuration using JSON input files that permits making changes to any part of the chemical mechanism without recompiling the model (this widely used, human-readable format allows entire gas- and aerosol-phase chemical mechanisms to be described with as much complexity as necessary), and (3) automated comprehensive testing that ensures stability of the code as new functionality is introduced. Together, these design choices enable users to build a customized multiphase mechanism without having to handle preprocessors, solvers, or compilers. Removing these hurdles makes this type of modeling accessible to a much wider community, including modelers, experimentalists, and educators. This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the Multiscale Online AtmospheRe CHemistry (MONARCH) chemical weather prediction system for use at regional and global scales. Results from the initial deployment to box models of different complexity and MONARCH will be discussed, along with future extension to more complex gas–aerosol systems and the integration of GPU-based solvers.Matthew L. Dawson has received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. 747048. Matthew L. Dawson, Oriol Jorba, and Christian Guzman have been supported by the Ministerio de Ciencia, Innovación y Universidades (grant no. RTI2018-099894-BI00). Christian Guzman acknowledges funding from the AXA Research Fund. Nicole Riemer, Matthew West, and Jeffrey H. Curtis acknowledge funding from the National Science Foundation (grant no. AGS 19-41110). This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under cooperative agreement no. 1852977.Peer ReviewedPostprint (published version

High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems

This is the final technical report for the project entitled: "High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems", funded at NPAC by the DAO at NASA/GSFC. First, the motivation for the project is given in the introductory section, followed by the executive summary of major accomplishments and the list of project-related publications. Detailed analysis and description of research results is given in subsequent chapters and in the Appendix

CityFFD – City Fast Fluid Dynamics Model for Urban Microclimate Simulations

In recent years, due to the rapid population growth and the preference to live in urban areas, urbanization has intensely increased. Currently, based on a United Nation report, 55% of the population live in the cities and the number is expected to reach about 68% by 2050. Urban microclimate has significant impacts on human life and health, and building energy performance. Urban microclimate information, such as wind velocity, temperature, humidity, pollutant dispersion levels, and local precipitation, are often important for accurate evaluations of building energy performance, indoor and outdoor human comfort, extreme events, and emergency situations. For example, it was reported that indoor temperature estimated with the microclimate information could be at least 5 °C different from that without it, which could be significant for the evaluations of indoor thermal comfort. The study of urban microclimate includes both observational and numerical approaches. The observational study is often related to field measurements, satellite imagery, and laboratory tests, e.g. in wind tunnels. The numerical approach is often based on computer models, such as CFD (computational fluid dynamics), for high-resolution and relatively small computing domains, compared to larger scale regional climate models, such as WRF and GEM-SURF. The latter two models are mostly used to model the domain size of 1~10 km with the resolution more than 100 m so they are not developed for urban microclimate and building-level simulations. In comparison, CFD has been applied to the urban microclimate of less than 1 km with a resolution less than 10 m down to the building level. However, conventional CFD solvers often perform unsatisfactorily for microscale and complicated problems because of numerical constraints such as stability issues associated with CFL condition, which is a necessary condition for convergence while solving certain partial differential equations (usually hyperbolic PDEs) numerically. Thus, conventional tools are often computationally expensive for modeling microclimates and consequently impractical for urban-scale problems. Recently, there are an increasing amount of efforts focusing on developing faster and accurate CFD techniques such as based on Fast Fluid Dynamics (FFD) methods. A FFD method relies on semi-Lagrangian and fractional step methods. FFD methods is fundamentally an explicit method without the CFL constraint so it is unconditionally stable even under large time steps and coarse grid resolutions, which are common for urban microclimate problems. In the meantime, the conventional FFD methods are often dependent on low-order interpolation schemes and thus with high numerical errors, which are the main drawbacks of this approach. The main objective of this thesis is to develop a fast and accurate CFD solver with a series of new computing algorithms based on semi-Lagrangian approach for modeling urban/city scale microclimates. The new solver with the name of CityFFD (city Fast Fluid Dynamics), is designed for tackling the challenges of large domain, coarse grid, and/or large time step, which are typical for urban microclimate simulations, without a heavy reliance on computer resources, such as the possibility of running on personal computers. First, a novel high-order interpolation scheme is proposed to significantly reduce the numerical errors of conventional semi-Lagrangian solvers. The new interpolation scheme enables the possibility of obtaining fast and accurate results even on coarse grids. The second algorithm focuses on the simulation accuracy associated with the time step of the semi-Lagrangian method. A new scheme of an adaptive time step is developed to adjust the time step dynamically according to local truncation errors. To improve the estimation of the characteristic curves, a new algorithm is proposed by considering the acceleration of the flow particles inside the computational domain which can provide highly accurate results and capture the complicated flow fields even by using a large time step. The fourth algorithm is to speed up the simulation by eliminating the need for solving the Poisson equation, which is often the most time-consuming operation of conventional semi-Lagrangian models. The new scheme is based on the concept of the artificial compressibility of solving incompressible flows and makes it easier to implement parallel computing techniques, such as the NVIDIA GPU CUDA and the OpenMP. The last feature of CityFFD is adding Large Eddy Simulation (LES) model to capture the turbulence behavior of the flow in urban environments. In this section, a parallel OpenMP geometry reader is developed to read the city scale geometries in a fast manner. At the end, the proposed CityFFD model is demonstrated by a case study: the modeling of an extreme weather event, the snow-storm of the century in Montreal, for evaluating building resilience during the storm, to show the importance of urban microclimate and its impact on human health and indoor environment

Computational Methods in Science and Engineering : Proceedings of the Workshop SimLabs@KIT, November 29 - 30, 2010, Karlsruhe, Germany

In this proceedings volume we provide a compilation of article contributions equally covering applications from different research fields and ranging from capacity up to capability computing. Besides classical computing aspects such as parallelization, the focus of these proceedings is on multi-scale approaches and methods for tackling algorithm and data complexity. Also practical aspects regarding the usage of the HPC infrastructure and available tools and software at the SCC are presented

Tropospheric Chemical State Estimation by Four-Dimensional Variational Data Assimilation on Nested Grids

The University of Cologne chemistry transport model EURAD and its four-dimensional variational data assimilation implementation is applied to a suite of measurement campaigns for analysing optimal chemical state evolution and flux estimates by inversion. In BERLIOZ and VERTIKO, interest is placed on atmospheric boundary layer processes, while for CONTRACE and SPURT upper troposphere and tropopause height levels are focussed. In order to achieve a high analysis skill, some new key features needed to be developed and added to the model setup. The spatial spreading of introduced observational information can now be conducted by means of a generalised background error covariance matrix. It has been made available as a flexible operator, allowing for anisotropic and inhomogeneous correlations. To estimate surface fluxes with high precision, the facility of emission rate optimisation using scaling factors is extended by a tailored error covariance matrix. Additionally, using these covariance matrices, a suitable preconditioning of the optimisation problem is made available. Furthermore, a module of adjoint nesting was developed and implemented, which enables the system to operate from the regional down to the local scale. The data flow from mother to daughter grid permits to accomplish nested simulations with both optimised boundary and initial values and emission rates. This facilitates to analyse constituents with strong spatial gradients, which have not been amenable to inversion yet. Finally, an observation operator is implemented to get to assimilate heterogeneous sources of information like ground-based measurements, airplane measuring data, Lidar and tethered balloon soundings, as well as retrieval products of satellite observations. In general, quality control of the assimilation procedure is obtained by comparison with independent observations. The case study analyses show considerable improvement of the forecast quality both by the joint optimisation of initial values and emission rates and by the increase of the horizontal resolutions by means of nesting. Moreover, simulation results for the two airplane campaigns exhibit outstanding characteristics of the assimilation system also in the middle and upper troposphere region

In-Time Parallelization Of Atmospheric Chemical Kinetics

This work investigates the potential of an in-time parallelization of atmospheric chemical ki- netics. Its numerical calculation is one time-consuming step within the numerical prediction of the air quality. The widely used parallelization strategies only allow a limited potential level of parallelism. A higher level of parallelism within the codes will be necessary to enable benefits from future exa-scale computing architectures. In air quality prediction codes, chem- ical kinetics is typically considered to react in isolated boxes over short splitting intervals. This allows their trivial parallelization in space, which however is limited by the number of grid entities. This work pursues a parallelization beyond this trivial potential and investigates a parallelization across time using the so called “parareal algorithm”. The latter is an iterative prediction-correction scheme, whose efficiency strongly depends on the choice of the predictor. For that purpose, different options are being investigate and compared: Time-stepping schemes with fixed step size, adaptive time-stepping schemes and repro-models, functional representations, that map a given state to a later state in time. Only the choice of repromodels leads to a speed-up through parallelism, compared to the sequential reference for the scenarios considered here

Process based Modelling of Chemical and Physical Aerosol Properties Relevant for Climate and Health

Atmospheric aerosol particles have substantial influence on climate and air quality. However, the anthropogenic influence on the atmospheric aerosol is still poorly known. This limits the understanding of past and future climate changes. Additionally, both epidemiological and toxicological studies indicate adverse health effects of inhaled aerosol particles. In order to study the effect of atmospheric processes on the particle properties relevant for climate and health, two models were developed and implemented. The first is a 2D-Lagrangian model for Aerosol Dynamics, gas phase CHEMistry and radiative transfer (ADCHEM), which treats the dispersion in the vertical and horizontal direction perpendicular to air mass trajectories. The second model is a kinetic multilayer model for Aerosol Dynamics, gas and particle phase chemistry in laboratory CHAMber environments (ADCHAM). With ADCHAM it is possible to study process based formation and evaporation of secondary organic aerosol particles, and mass transfer limitations and reactions within the particle phase. ADCHEM was used to quantify the anthropogenic influence from the city of Malmö (280 000 inhabitants) in southern Sweden. In Malmö and a few tens of kilometres downwind, the primary particle emissions have a large influence on the particle number concentration. However, more than 2 hours downwind Malmö, the anthropogenic particle mass contribution is dominated by secondary ammonium nitrate. To quantify the direct and indirect climate impact of urban aerosol emissions, the secondary aerosol formation which changes the optical and hygroscopic properties of the primary soot particles, needs to be addressed in future measurements and process modelling. ADCHAM was used to simulate different laboratory chamber experiment, with focus on potential influential but poorly known processes for secondary organic aerosol properties, formation and evaporation rates in the atmosphere (i.e. oligomerization, organic salt formation, salting-out effects, oxidation of organic compounds in the particle phase and mass transfer limitations in the particle phase). The model results reveal that formation of small amounts of low-volatile and long lived oligomers, which accumulate in the particle surface layers, can effectively prevent the evaporation of more volatile compounds. This can significantly prolong the lifetime of SOA in the atmosphere

Towards large eddy simulation of dispersed gas -liquid two-phase turbulent flows

This study presents a detailed investigation of all essential components of computational and modeling issues necessary for a successful large-eddy simulation (LES) of dispersed two-phase turbulent flows. In particular, a two-layer concept is proposed to enable the LES capability in two-phase flows involving dispersed bubbles that are relatively large compared to the mesh size. The work comprises three major parts.;Part I focuses on the development and verification of a transient, three-dimensional, finite-volume-method (FVM) based accurate Navier-Stokes solver, named DREAM II (second generation of the DREAM code). Several high-order schemes are implemented for both the spatial and temporal discretization. Solution of the coupled partial differential equations is attacked with a fractional step (projection) method. The developed solver is verified against various benchmarks including Taylor\u27s vortex, free-shear layer, backward-facing step flow and square cavity. A second-order overall accuracy is achieved in both space and time.;Part II concerns the modeling and LES of single-phase turbulent flows. A review of the LES theory and subgrid-scale (SGS) models is presented. Three SGS models, namely, Smagorinsky model, dynamic model and implicit model, are implemented and investigated. Then turbulent channel flow, plane mixing layer, and flow past a square cylinder are simulated, and comparisons of the first-, second-order statistics, and characteristic flow structures are made with direct numerical simulation (DNS) and/or benchmark experiments. The test results show superior quality of the present LES.;Part III delves into the theory, modeling and simulation of dispersed two-phase flow systems. A conceptual review of the characteristics and description of such system is made, considering both Eulerian-Eulerian (E-E) and Eulerian-Lagrangian (E-L) approaches, but with an emphasis on the latter. Various hydrodynamic forces acting on particles or bubbles are summarized and interpreted. Formulations regarding interphase coupling is discussed in depth. Typical computational treatments of modeled two-way couplings in an E-L DNS/LES are reviewed. Issues related to the interpolation are addressed. A general Lagrangian particle-tracking (LPT) program, named PART, is developed and verified using analytical solutions. (Abstract shortened by UMI.)