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A 29-year variable resolution climate simulation is conducted from January 1988 to December 2016 using the Model for Prediction Across Scale-Atmosphere (MPAS-A), with prescribed sea surface temperatures obtained from ERA-Interim reanalysis. The global variable resolution configuration employs a mesh refinement of 92–25 km centered over East Asia. Model validations against combined observed datasets highlight that MPAS-A demonstrated advantages over three selected Regional Climate Models (RCMs) in terms of the spatial distribution of precipitation and spatial variability of the near-surface air temperature but struggled with accurately depicting temporal precipitation patterns. MPAS-A's anomalies in mid-latitude circulation and wave activity fluxes explained the weaker cold air activities during winter in eastern China and the northward shift of the Meiyu rain belt. Common issues with reference RCMs exist in MPAS-A, such as excessive zonal moisture transport over the ocean and unrealistic interannual variability over the northwest Pacific Ocean. The wet biases over the ocean are associated with systematically higher Convective Available Potential Energy (CAPE) for MPAS-A. However, the extreme rainfall indices such as R95pTOT and R99pTOT are not completely dominated by these wet biases and still exhibit reasonable results. This finding underscores the robustness and potential of the variable resolution (VR) approach in obtaining regional information within a single model framework. Key Points: • A global variable resolution simulation is conducted from 1988 to 2016 following CORDEX-East Asia framework. • MPAS-A demonstrates superior spatial correlation in precipitation and better spatial variability in near-surface air temperature compared to three RCMs from CORDEX-EA-II. • MPAS-A and RCMs exhibit similar anomalies in moisture transport, but MPAS-A performs better over the northwest Pacific Ocean. [ABSTRACT FROM AUTHOR]

South America is a large continent situated mostly in the Southern Hemisphere (SH) with complex topography and diverse emissions sources. However, the atmospheric chemistry of this region has been historically understudied. Here, we employ the Multi‐Scale Infrastructure for Chemistry and Aerosols, a novel global circulation model with regional refinement capabilities and full chemistry, to explore the sources and distribution of the carbon monoxide (CO) tropospheric column in South America during 2019, and also to assess the effect that South American primary emissions have over the rest of the world. Most of the CO over South America can be explained either by non‐methane volatile organic compounds (NMVOC) secondary chemical production or by biomass burning emissions, with biomass burning as the main explanation for the variability in CO. Biomass burning in Central Africa is a relevant contributor to CO in all of the continent, including the southern tip. Biogenic emissions play a dual role in CO concentrations: they provide volatile organic compounds that contribute to the secondary CO production, but they also destroy OH, which limits the chemical production and destruction of CO. As a net effect, the lifetime of CO is extended to ∼120 days on average over the Amazon, while still being in the range of 30–60 days in the rest of South America. Plain Language Summary: We use the Multi‐Scale Infrastructure for Chemistry and Aerosols, a global model with regional refinement, to study the origins of carbon monoxide (CO) in South America during 2019. The main sources of CO are the secondary production from non‐volatile organic compounds and the biomass burning primary emissions. The main source of temporal variability in the whole are the biomass burning emissions. We show that biomass burning in central Africa is a relevant source of South American CO during all year in all of the continent, including the furthermost south. Key Points: We employ the Multi‐Scale infrastructure for Chemistry and Aerosols to quantify the budget of CO in South America during 2019Most of the variability in the CO burden is explained by the variability in biomass burning emissionsBiomass burning in Central Africa is a relevant contributor to CO in all of the continent, including the southern region [ABSTRACT FROM AUTHOR]

Model intercomparison studies often report a large spread in simulation results, but quantifying the causes of these differences is hindered by the fact that several processes contribute to the model spread simultaneously. Here we use the Multi‐Scale Infrastructure for Chemistry and Aerosols (MUSICA) version 0 to investigate the model resolution dependencies of simulated chemical species, with a focus on the differences between global uniform grid and regional refinement grid simulations with the same modeling framework. We construct two global (ne30 [∼112 km] and ne60 [∼56 km]) and two regional refinement grids over Korea (ne30x8 [∼14 km] and ne30x16 [∼7 km]). The grid resolution can change chemical concentrations by an order of magnitude in the boundary layer, and the importance increases as the species' reactivity increases (e.g., up to 50% and 1,000% changes for ethane and xylenes, respectively). The diurnal cycle of oxidants (OH, O3, and NO3) also varies with the grid resolution, which leads to different oxidation pathways of volatile organic compounds (e.g., the fraction of monoterpenes reacting with NO3 in Seoul around midnight is 90% for ne30, but 65% for ne30x16). The models with high‐resolution grids usually do a better job at reproducing aircraft observations during the KORUS‐AQ campaign, but not always, implying compensating errors in the coarse grid simulations. For example, ozone is better reproduced by the coarse grid due to the artificial mixing of NOx. When developing new chemical mechanisms and evaluating models over urban areas, the uncertainties associated with model resolution should be considered. Plain Language Summary: A new model framework, the Multi‐Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0), has been developed at NCAR to enable a computationally feasible global modeling framework while still resolving chemistry at urban scales. Using the MUSICAv0 framework with different horizontal grid resolutions (∼112, ∼56, ∼14, and ∼7 km), this work examines how much horizontal grid resolution can affect simulated chemical concentrations in 3D chemistry models. Model concentrations can vary up to 10 times between ∼112 and ∼7 km grids over urban areas at the surface. On the other hand, a region‐specific emission inventory with detailed local information is essential for some chemical species, although it is generally less important than the grid resolution for many chemical species. The model with a high‐resolution grid better reproduces observations in general, but in some cases compensating errors result in better comparisons for the coarse grid. This work suggests that the effects of grid resolution should not be ignored when evaluating new chemical mechanisms and chemistry models in future studies, and high grid resolution in 3D models is needed to simulate air pollutants over urban and downwind regions. Key Points: The dependence of simulated chemical species on model resolution is quantified in a single modeling frameworkModel evaluations can be substantially affected by grid resolution, especially for urban surface and aircraft measurements at low altitudesGrid resolution strongly impacts the oxidation of volatile organic compounds through differences in diurnal variation of oxidants [ABSTRACT FROM AUTHOR]

Abstract Model intercomparison studies often report a large spread in simulation results, but quantifying the causes of these differences is hindered by the fact that several processes contribute to the model spread simultaneously. Here we use the Multi‐Scale Infrastructure for Chemistry and Aerosols (MUSICA) version 0 to investigate the model resolution dependencies of simulated chemical species, with a focus on the differences between global uniform grid and regional refinement grid simulations with the same modeling framework. We construct two global (ne30 [∼112 km] and ne60 [∼56 km]) and two regional refinement grids over Korea (ne30x8 [∼14 km] and ne30x16 [∼7 km]). The grid resolution can change chemical concentrations by an order of magnitude in the boundary layer, and the importance increases as the species' reactivity increases (e.g., up to 50% and 1,000% changes for ethane and xylenes, respectively). The diurnal cycle of oxidants (OH, O3, and NO3) also varies with the grid resolution, which leads to different oxidation pathways of volatile organic compounds (e.g., the fraction of monoterpenes reacting with NO3 in Seoul around midnight is 90% for ne30, but 65% for ne30x16). The models with high‐resolution grids usually do a better job at reproducing aircraft observations during the KORUS‐AQ campaign, but not always, implying compensating errors in the coarse grid simulations. For example, ozone is better reproduced by the coarse grid due to the artificial mixing of NOx. When developing new chemical mechanisms and evaluating models over urban areas, the uncertainties associated with model resolution should be considered.

Explicit Runge–Kutta methods and implicit multistep methods utilizing a Newton–Krylov nonlinear solver are evaluated for a range of configurations of the shallow-water dynamical core of the spectral element community atmosphere model to evaluate their computational performance. These configurations are designed to explore the attributes of each method under different but relevant model usage scenarios including varied spectral order within an element, static regional refinement, and scaling to the largest problem sizes. This analysis is performed within the shallow-water dynamical core option of a full climate model code base to enable a wealth of simulations for study, with the aim of informing solver development within the more complete hydrostatic dynamical core used for climate research. The limitations and benefits to using explicit versus implicit methods, with different parameters and settings, are discussed in light of the trade-offs with Message Passing Interface (MPI) communication and memory and their inherent efficiency bottlenecks. Given the performance behavior across the configurations analyzed here, the recommendation for future work using the implicit solvers is conditional based on scale separation and the stiffness of the problem. For the regionally refined configurations, the implicit method has about the same efficiency as the explicit method, without considering efficiency gains from a preconditioner. The potential for improvement using a preconditioner is greatest for higher spectral order configurations, where more work is shifted to the linear solver. Initial simulations with OpenACC directives to utilize a Graphics Processing Unit (GPU) when performing function evaluations show improvements locally, and that overall gains are possible with adjustments to data exchanges. [ABSTRACT FROM AUTHOR]

Macromolecular crystallographic refinement relies on sometimes dubious stereochemical restraints and rudimentary energy functionals to ensure the correct geometry of the model of the macromolecule and any covalently bound ligand(s). The ligand stereochemical restraint file (CIF) requires a priori understanding of the ligand geometry within the active site, and creation of the CIF is often an error-prone process owing to the great variety of potential ligand chemistry and structure. Stereochemical restraints have been replaced with more robust functionals through the integration of the linear-scaling, semiempirical quantum-mechanics (SE-QM) program DivCon with the PHENIX X-ray refinement engine. The PHENIX/DivCon package has been thoroughly validated on a population of 50 protein-ligand Protein Data Bank (PDB) structures with a range of resolutions and chemistry. The PDB structures used for the validation were originally refined utilizing various refinement packages and were published within the past five years. PHENIX/DivCon does not utilize CIF(s), link restraints and other parameters for refinement and hence it does not make as many a priori assumptions about the model. Across the entire population, the method results in reasonable ligand geometries and low ligand strains, even when the original refinement exhibited difficulties, indicating that PHENIX/DivCon is applicable to both single-structure and high-throughput crystallography.