https://hdl.handle.net/20.500.14178/909 2026-09-14T16:54:32Z 2026-09-14T16:54:32Z Brabec, Matyáš Klepl, Jiří Kruliš, Martin https://hdl.handle.net/20.500.14178/3922 2026-09-05T01:00:19Z 2026-01-01T00:00:00Z

Cellato: a DSL for Cellular Automata based on C++ Template Meta-programming Brabec, Matyáš; Klepl, Jiří; Kruliš, Martin Cellato is a tool with embedded DSL in C++ that leverages template meta-programming to define and execute cellular automata (CA) via concise type-level expressions that are specialized into efficient kernels at compile time. Its modular architecture decouples the Algorithm (rules), Evaluator (per-cell update), Layout (memory representation), and Traverser (grid iterator), allowing users to mix and match components without altering rule definitions. We demonstrate Cellato on Conway's Game of Life, Forest Fire, Wireworld, and the Greenberg-Hastings excitable medium, which cover binary as well as multi-state models and Moore to von Neumann neighborhoods. We experimented with three memory layouts (standard arrays, bit-packed arrays, and bit-planes) for transparent bit-level encodings and data-parallel optimizations. Targeting both CPU and GPU back-ends, Cellato delivers performance on par with hand-tuned code, while its zero-overhead abstractions, flexible scheduling, and portable optimizations provide a robust foundation for high-performance CA computations.

2026-01-01T00:00:00Z Huszár, Peter Bartík, Lukáš Karlický, Jan Prieto Perez, Alvaro Patricio https://hdl.handle.net/20.500.14178/3917 2026-09-04T01:00:26Z 2026-01-01T00:00:00Z

Emitted yesterday, polluting today: temporal source apportionment of fine particulate matter pollution over Central Europe Huszár, Peter; Bartík, Lukáš; Karlický, Jan; Prieto Perez, Alvaro Patricio Fine particulate matter (PM2.5) pollution remains a critical health issue in Europe. While numerous studies have quantified the spatio-sectoral sources of urban PM, the temporal origin has received minimum attention. This study addresses this gap by developing a Temporal Source Apportionment approach within the CAMx chemical transport model to quantify the long-term contributions of emissions from the preceding 14 d to PM concentrations, focusing on the 2010-2019 period and Central Europe. The novelty of the study lies in a long term and continuous adoption of TSA unlike previous attempts to quantify the age distribution of polluting aerosol that focused on selected air pollution periods.The results show that current-day emissions dominate winter PM2.5, contributing 30 %-60 % on average, while day-1 emissions add further 20 %-30 %. Contributions decrease with emission age, falling below 5 % after 3 d and becoming negligible beyond 7 d. Secondary inorganic aerosols and primary organic aerosols exhibit similar patterns, although for winter nitrate levels, the highest contribution comes from day-1 emissions, reflecting the time needed for chemical formation. Summer contributions are smaller due to enhanced mixing and faster removal, whereas biogenic emissions also contribute largely, giving anthropogenic emissions a smaller role.Importantly, while the average contribution of older emissions is low, occasional episodes show substantial impacts: day-4 emissions can contribute up to 10 %, and even week-old emissions can add 2 % in winter. These findings emphasize that adverse air quality episodes are influenced not only by same-day emissions but also by pollution accumulated from previous days resulting from past emissions. Effective mitigation policies on PM pollution must therefore consider reducing emissions several days in advance of predicted pollution episodes, rather than relying solely on same-day interventions.

2026-01-01T00:00:00Z Peiker, Jan Karlický, Jan Huszár, Peter https://hdl.handle.net/20.500.14178/3916 2026-09-04T01:00:37Z 2026-01-01T00:00:00Z

Interpolating station quantile biases for tropospheric ozone MDA8 bias correction Peiker, Jan; Karlický, Jan; Huszár, Peter Chemistry transport models (CTMs) consistently exhibit systematic errors in ozone concentrations, which can be partly compensated by bias correction. There are several bias correction strategies suitable for using station data, but they are likely to introduce statistical artifacts when applied at high resolution. We propose a new bias correction strategy based on parametric interpolation of quantile biases (PIQB) suitable for high resolution simulations, which is designed to avoid such artifacts. In this study, we evaluate and compare the performance of our strategy with other older strategies with a focus on ambient maximum daily 8 h average ozone concentrations (MDA8). Our experimental setup consisted of two simulations from the CTMs WRF-Chem and CAMx at horizontal resolution of 9 km within the time period of 2007-2016 and 165 ground-based stations in central Europe. Our results show that each strategy brings the simulated MDA8 closer to observations, but PIQB performs the best in terms of mitigating systematic errors while retaining the modeled fine resolution structure of spatial variability. We conclude that out of the considered strategies, PIQB is the most suitable one for bias correction at high resolution, suggesting its possible applications for correcting climate projections of ozone MDA8.

2026-01-01T00:00:00Z Karlický, Jan Bareš, Jáchym Huszár, Peter https://hdl.handle.net/20.500.14178/3915 2026-09-04T01:00:14Z 2026-01-01T00:00:00Z

Sensitivity of modeled urban climate to urban canopy parameters over central Europe Karlický, Jan; Bareš, Jáchym; Huszár, Peter Urban areas are characterized by modifications of the local climate, leading to so-called urban meteorology islands (UMIs). A UMI is the result of the different physical properties of surfaces in cities compared to their rural surroundings. In this study, we performed a set of multi-year simulations with the Weather Research and Forecasting model and two urban schemes to investigate the sensitivity of urban climate modifications (i.e. UMIs) to changes in characteristics of the urban environment, described in models by so-called urban canopy parameters (UCPs). Our results reveal a high sensitivity of urban-induced changes in all mentioned meteorological variables to alterations in UCPs. Temperatures in urban areas are mainly influenced by changes in urban fraction (UF), roof albedo, green roofs with irrigation, and also by anthropogenic heat in winter, with a magnitude around 0.5 degrees C. On the contrary, urban wind speed is impacted by parameters that describe the urban morphology, about 0.1 m s-1. Our study also shows substantial differences between both urban models used, mainly in urban-induced temperatures in winter, with a difference of around 1.5 degrees C. The results of the study can also be used as a primary evaluation of different mitigation strategies represented by changes in UCP values. The decrease of UF and the increase in roof albedo seem to be the most suitable possibilities to reduce the intensity of urban heat islands in summer; vegetation-covered roofs have a noticeable impact only if they are also irrigated.

2026-01-01T00:00:00Z