Wydział Fizyki UW > Badania > Seminaria i konwersatoria > Środowiskowe Seminarium Fizyki Atmosfery

Środowiskowe Seminarium Fizyki Atmosfery

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Zapraszamy do sali B4.58, ul. Pasteura 5 o godzinie 13:15

Dr Jun-Ichi Yano (Meteo-France, Toulouse)

Emergence of Self–Organization of Atmospheric Moist Convection, as Seen Through the Energy–Cycle in Wavelet Space

The energy cycle of a convectively–organized system, as realized by a convective–scale idealized simulation, is analyzed in wavelet space. In the equilibrium state, most of the available potential energy that is generated by convective heating is immediately converted into kinetic energy by means of buoyancy forcing, consistent with the free–ride principle. In turn, most of the generated convective kinetic energy is manifest as gravity waves propagating away from convective centers. The kinetic energy of these small–scale gravity waves is transferred upscale by their own advective nonlinearities. Finally, a large–scale circulation generated by this “inverse cascade” drives the formation of an organized structure in the precipitation field.
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Identyfikator spotkania: 983 9347 6526
Kod dostępu: 190038

Zapraszamy do sali B4.58, ul. Pasteura 5 o godzinie 13:15

prof. dr hab. Wojciech W. Grabowski (NSF NCAR, MMM Lab, Boulder CO USA)

Broadening of adiabatic droplet spectra through eddy hopping: Polluted versus pristine environments

The observed widths of cloud droplet spectra in adiabatic volumes of natural clouds have been a conundrum in cloud physics from the early days of in-situ cloud observations. Observed spectral widths are often in the range of 1 to 2 microns, whereas adiabatic parcel calculations suggest widths up to only a few tenths of 1 micron. We use a 1D Eulerian updraft model with Lagrangian particle–based microphysics (introduced in Grabowski et al. JAS 2025) to study the impact of cloud turbulence on droplet formation and diffusional growth. The model either includes or excludes effects of cloud turbulence. The impact of turbulence is simulated using a stochastic model of vertical velocity fluctuations that drive supersaturation fluctuations experienced separately by each superdroplet. The specific setup considers shallow cumulus clouds growing from a turbulent convective boundary layer and featuring cloud base updrafts between 1 and 4 m s-1. The focus is on contrasting adiabatic spectral broadening in pristine and polluted environments, and on comparing modeling results with cloud observations. Turbulence significantly impacts CCN activation and droplet diffusional growth above the cloud base and leads to an increased adiabatic spectral width aloft. The impact is moderate for polluted clouds, but spectral widths in pristine conditions are up to several times larger than those with no turbulence. In contrast, adiabatic simulations without turbulence typically feature wider droplet spectra in polluted clouds. The difference comes from a larger range of activated CCN and a larger magnitude of supersaturation fluctuations for the same vertical velocity fluctuations because of a larger phase relaxation time in pristine conditions.
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Meeting ID: 995 7689 0170
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Zapraszamy do sali 1.02, ul. Pasteura 5 o godzinie 13:15

prof. dr hab. Małgorzata Werner (Wydział Nauk o Ziemi i Kształtowania Środowiska, Uniwersytet Wrocławski)

Anthropogenic and natural aerosols in the atmosphere - examples of practical applications of modelling and measurements

This presentation will focus on the application of numerical modelling and measurement methods to assess air quality in Europe, with a focus on Poland. The modelling will include the state-of-the-art Eulerian chemical transport models dedicated for regional scale analysis as well as Gaussian type models used for city scale. In addition, the application of machine learning methods and the combination of chemical transport model results with observations to predict air pollution concentrations will be presented. The talk will cover the most problematic chemical pollutants such as PM2.5 (particulate matter with a diameter of less than 2.5 m), BaP (benzo(L)piren), NO2 (nitrogen dioxide) as well as biological particles such as allergenic pollen grains. Examples of the application of modelling to answer questions related to air quality management will be shown. The presentation will conclude with current challenges and opportunities for further development.
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Meeting ID: 981 6805 5999
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Zapraszamy do sali B4.58, ul. Pasteura 5 o godzinie 13:15

dr Mehri Davtalab (Department of Environmental Research, Center for Physical Sciences and Technology, Vilnius, Lithuania)

Integrating GIS and machine learning for urban air quality assessment

Rapid urbanization and industrial growth have intensified air quality challenges in cities worldwide. Understanding how urban structure influences air pollution requires analytical frameworks capable of handling complex spatial and temporal data. This seminar presents how the integration of Geographic Information Systems (GIS) and Machine Learning (ML) can enhance urban air quality research. GIS provides a spatial foundation for managing and visualizing environmental parameters such as land use, traffic density, meteorological conditions, and emission sources. ML techniques make it possible to identify complex relationships between urban structural characteristics such as urban built-up areas (UBAs) and urban green spaces (UGSs) and pollutant concentrations. Moreover, ML enables air quality assessment by predicting pollutant levels, estimating missing data, and determining the influence of environmental and urban factors. By integrating GIS-based spatial analysis with ML-based predictive modeling, it becomes possible to generate high-resolution air quality maps, identify pollution hotspots, and evaluate the role of urban morphology in pollutant dispersion. This integrated approach improves the interpretability of air quality assessments and informs strategies for sustainable urban and environmental management.
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Meeting ID: 978 4851 4361
Passcode: 005211

Zapraszamy do sali B4.58, ul. Pasteura 5 o godzinie 13:15

prof. Martin Oberlack (Department of Mechanical Engineering, Technical University of Darmstadt, Germany)

Recent progress in the symmetry based theory for near-surface shear flows

Zapraszamy do sali B4.58, ul. Pasteura 5 o godzinie 13:15

dr Simon Görtz (Technical University of Darmstadt)

Wave propagation and causality in atmospheric free shear layers

We investigate the reflection and transmission of waves through a shear layer. We use a hyperbolic tangent to model the shear layer, and reflection and transmission coefficients to quantify its interaction with pressure waves. Using causality arguments in the inverse Laplace transform, we demonstrate that the direction of the incident wave in relation to the mean velocity gradient is crucial. A wave that is incident from the upper far field and propagates in the opposite direction to the increasing velocity gradient is amplified during the reflection process, and a distinct resonance frequency exists. Conversely, waves incident from the lower far field propagate in the direction of the increasing velocity gradient. Causality reveals that these waves are damped during reflection and that a distinct total absorption frequency exists. Therefore, causality arguments underline the observation that the problem is not fully symmetric from the perspective of an incident wave, even if a symmetric mean flow profile is chosen.
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Meeting ID: 959 2988 8109
Passcode: 874810