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Atmospheric modeling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their…

Applications · Statistics 2021-07-08 Javier Rubio-Herrero , Carlos Ortiz Marrero , Wai-Tong Louis Fan

Our understanding of physical processes in Photodissociation regions or Photon Dominated Regions (PDRs) largely depends on the ability of spectral synthesis codes to reproduce the observed infrared emission-line spectrum. In this paper, we…

Astrophysics · Physics 2009-11-13 N. P. Abel , P. A. M. van Hoof , G. Shaw , G. J. Ferland , T. Elwert

This study introduces and validates a cloud condensation model on insoluble nuclei using a novel comparative analysis of simultaneous radiosonde and ceilometer data. A transformation of the radiosonde's temperature and relative humidity…

Atmospheric and Oceanic Physics · Physics 2026-01-27 Rani Arielly , Adva Baratz , Ran Aharoni , Ofir Shoshanim

Cloud Computing has established itself as an efficient and cost-effective paradigm for the execution of web-based applications, and scientific workloads, that need elasticity and on-demand scalability capabilities. However, the evaluation…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-22 Remo Andreoli , Jie Zhao , Tommaso Cucinotta , Rajkumar Buyya

The Dark Sky Simulations are an ongoing series of cosmological N-body simulations designed to provide a quantitative and accessible model of the evolution of the large-scale Universe. Such models are essential for many aspects of the study…

Cosmology and Nongalactic Astrophysics · Physics 2014-07-10 Samuel W. Skillman , Michael S. Warren , Matthew J. Turk , Risa H. Wechsler , Daniel E. Holz , P. M. Sutter

Multi-wavelength surveys place cloud dispersal at 1-5 Myr after massive stars emerge, before the first supernovae. Whether a cloud disperses, re-collapses, or leaks Lyman-continuum (LyC) photons depends on how pre-supernova winds, radiation…

Astrophysics of Galaxies · Physics 2026-05-28 Jia Wei Teh , Ralf S. Klessen , Simon C. O. Glover , Kathryn Kreckel

One of the greatest sources of uncertainty in future climate projections comes from limitations in modelling clouds and in understanding how different cloud types interact with the climate system. A key first step in reducing this…

Atmospheric and Oceanic Physics · Physics 2022-10-17 Valentina Zantedeschi , Fabrizio Falasca , Alyson Douglas , Richard Strange , Matt J. Kusner , Duncan Watson-Parris

We have extensively mapped a sample of dense molecular clouds (L1512, TMC-1C, L1262, Per 7, L1389, L1251E) in lines of HC3N, CH3OH, SO and C^{18}O. We demonstrate that a high degree of chemical differentiation is present in all of the…

Several data analysis techniques employ similarity relationships between data points to uncover the intrinsic dimension and geometric structure of the underlying data-generating mechanism. In this paper we work under the model assumption…

Machine Learning · Statistics 2019-04-09 Nicolas Garcia Trillos , Daniel Sanz-Alonso , Ruiyi Yang

Precipitation plays a critical role in the Earth's hydrological cycle, directly affecting ecosystems, agriculture, and water resource management. Accurate precipitation estimation and prediction are crucial for understanding climate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Zhenyu Yu , Hanqing Chen , Mohd Yamani Idna Idris , Pei Wang

Determining the behaviour of convection and clouds is one of the biggest challenges in our understanding of exoplanetary climates. Given the lack of in situ observations, one of the most preferable approaches is to use cloud-resolving or…

Earth and Planetary Astrophysics · Physics 2023-06-22 Jun Yang , Yixiao Zhang , Zuntao Fu , Mingyu Yan , Xinyi Song , Mengyu Wei , Jiachen Liu , Feng Ding , Zhihong Tan

In general, large datasets enable deep learning models to perform with good accuracy and generalizability. However, massive high-fidelity simulation datasets (from molecular chemistry, astrophysics, computational fluid dynamics (CFD), etc.…

Machine Learning · Computer Science 2022-07-27 Wai Tong Chung , Ki Sung Jung , Jacqueline H. Chen , Matthias Ihme

Numerical weather prediction requires initial estimates of the atmospheric state. Since the atmospheric density field is intricately woven into the atmosphere's governing equations, advancing atmospheric density estimation will improve…

Atmospheric and Oceanic Physics · Physics 2025-09-08 William Luszczak , Man-Yau Chan

Bright active galaxies show a range of properties but many of these properties are correlated which has led to the concept of the Quasar Main Sequence. We test whether our current understanding of the quasar structure allows to reproduce…

High Energy Astrophysical Phenomena · Physics 2019-04-25 Swayamtrupta Panda , Bożena Czerny , Chris Done , Aya Kubota

I describe DESPOTIC, a code to Derive the Energetics and SPectra of Optically Thick Interstellar Clouds. DESPOTIC represents such clouds using a one-zone model, and can calculate line luminosities, line cooling rates, and in restricted…

Instrumentation and Methods for Astrophysics · Physics 2015-06-15 Mark R. Krumholz

Forecasting the formation and development of clouds is a central element of modern weather forecasting systems. Incorrect clouds forecasts can lead to major uncertainty in the overall accuracy of weather forecasts due to their intrinsic…

Computer Vision and Pattern Recognition · Computer Science 2021-06-17 A. H. Nielsen , A. Iosifidis , H. Karstoft

We compute a new generation of standard solar models (SSMs) that includes recent updates on some important nuclear reaction rates and a more consistent treatment of the equation of state. Models also include a novel and flexible treatment…

We introduce new functionality to treat fractal aggregate aerosol particles within the Virga cloud modeling framework. Previously, the open source cloud modeling code Virga (Batalha et al. 2025), the Python version of EddySed (Ackerman &…

Because of the vast volume of data being produced by today's scientific simulations, lossy compression allowing user-controlled information loss can significantly reduce the data size and the I/O burden. However, for large-scale cosmology…

Information Theory · Computer Science 2017-08-08 Dingewn Tao , Sheng Di , Zizhong Chen , Franck Cappello

Atmospheric aerosols influence the Earth's climate, primarily by affecting cloud formation and scattering visible radiation. However, aerosol-related physical processes in climate simulations are highly uncertain. Constraining these…