16 citations · 18 across the 5 of their papers we have counts for
5 papers
JAX-SCM v1.0: a modern atmospheric single-column model for boundary layer research
Maximilian Pierzyna
We present JAX-SCM v1.0, an open-source atmospheric single-column model for boundary layer research, implemented in Python using the JAX computing library. The model solves for hor…
OTProf: estimating high-resolution profiles of optical turbulence () from reanalysis using deep learning
Maximilian Pierzyna, Sukanta Basu, Rudolf Saathof
Accurate, high-resolution vertical profiles of optical turbulence (), which reflect local meteorology and topography, are crucial for ground-based optical astronomy and free…
Assessing the Geographic Generalization and Physical Consistency of Generative Models for Climate Downscaling
Carlo Saccardi, Maximilian Pierzyna, Haitz Sáez de Ocáriz Borde +6
Kilometer-scale weather data is crucial for real-world applications but remains computationally intensive to produce using traditional weather simulations. An emerging solution is…
OTCliM: generating a near-surface climatology of optical turbulence strength () using gradient boosting
Maximilian Pierzyna, Sukanta Basu, Rudolf Saathof
This study introduces OTCliM (Optical Turbulence Climatology using Machine learning), a novel approach for deriving comprehensive climatologies of atmospheric optical turbulence st…
Π-ML: A dimensional analysis-based machine learning parameterization of optical turbulence in the atmospheric surface layer
Maximilian Pierzyna, Rudolf Saathof, Sukanta Basu
Turbulent fluctuations of the atmospheric refraction index, so-called optical turbulence, can significantly distort propagating laser beams. Therefore, modeling the strength of the…