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Geophysical methods offer several key advantages over conventional subsurface measurement approaches, yet their use for hydrologic interpretation is often problematic. Here, we introduce theory and concepts of a novel Bayesian approach for…

Geophysics · Physics 2017-01-09 N. Linde , J. A. Vrugt

For objects in the low Earth orbit region, uncertainty in atmospheric density estimation is an important source of orbit prediction error, which is critical for space situational awareness activities such as the satellite conjunction…

Space Physics · Physics 2022-11-01 Smriti Nandan Paul , Richard J. Licata , Piyush M. Mehta

Dust clouds influence the atmospheric structure of brown dwarfs, and they affect the heat transfer and change the gas-phase chemistry. However, the physics of their formation and evolution is not well understood. In this letter, we predict…

Astrophysics · Physics 2016-08-30 CH. Helling , W. -F. Thi , P. Woitke , M. Fridlund

We aim to constrain the dust mass and grain sizes in the interaction regions between the stellar winds and the ISM around asymptotic giant branch stars. By describing the dust in these regions, we aim to shed light on the role of low mass…

Astrophysics of Galaxies · Physics 2022-09-21 M. Maercker , T. Khouri , M. Mecina , E. De Beck

The climate record preserved in polar glaciers, mountain glaciers, and widespread cave deposits shows repeated occurrence of abrupt global transitions between cold/dry stadial and warm/wet interstadial states during glacial periods. These…

Atmospheric and Oceanic Physics · Physics 2009-07-03 Brian F. Farrell , Dorian S. Abbot

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

This work is motivated by constructing a weather simulator for precipitation. Temperature and humidity are two of the most important driving forces of precipitation, and the strategy is to have a stochastic model for temperature and…

Applications · Statistics 2015-05-27 Xiangping Hu , Ingelin Steinsland , Daniel Simpson , Sara Martino , Håvard Rue

The transition from non-renewable to renewable energies represents a global societal challenge, and developing a sustainable energy portfolio is an especially daunting task for developing countries where little to no information is…

Applications · Statistics 2022-09-13 Jiachen Zhang , Paola Crippa , Marc G. Genton , Stefano Castruccio

Modern dune fields are valuable sources of information for the large-scale analysis of terrestrial and planetary environments and atmospheres, but their study relies on understanding the small-scale dynamics that constantly generate new…

Dust impacts on spacecraft are commonly detected by antenna instruments as transient voltage perturbations. The signal waveform is generated by the interaction between the impact-generated plasma cloud and the elements of the…

Space Physics · Physics 2023-04-04 Mitchell M. Shen , Zoltan Sternovsky , Alessandro Garzelli , David M. Malaspina

Dust storms may remarkably degrade the imaging quality of Martian orbiters and delay the progress of mapping the global topography and geomorphology. To address this issue, this paper presents an approach that reuses the image dehazing…

Computer Vision and Pattern Recognition · Computer Science 2022-06-22 Hongyu Li , Jia Li , Xin Ren , Long Xu

We employ the MarsWRF general circulation model (GCM) to test the predictions of a new physical hypothesis: a weak coupling of the orbital and rotational angular momenta of extended bodies is predicted to give rise to cycles of…

Earth and Planetary Astrophysics · Physics 2017-05-24 Michael A. Mischna , James H. Shirley

Stratospheric aerosols play an important role in the earth system and can affect the climate on timescales of months to years. However, estimating the characteristics of partially observed aerosol injections, such as those from volcanic…

Machine Learning · Computer Science 2024-09-12 J. Hart , I. Manickam , M. Gulian , L. Swiler , D. Bull , T. Ehrmann , H. Brown , B. Wagman , J. Watkins

Gaussian random field (GRF) models are widely used in spatial statistics to capture spatially correlated error. We investigate the results of replacing Gaussian processes with Laplace moving averages (LMAs) in spatial generalized linear…

Applications · Statistics 2019-07-26 Adam Walder , Ephraim M. Hanks

Nonsuspended sediment transport (NST) refers to the sediment transport regime in which the flow turbulence is unable to support the weight of transported grains. It occurs in fluvial environments (i.e., driven by a stream of liquid) and in…

Geophysics · Physics 2021-05-25 Thomas Pähtz , Yonghui Liu , Yuezhang Xia , Peng Hu , Zhiguo He , Katharina Tholen

Atmospheric trace-gas inversion refers to any technique used to predict spatial and temporal fluxes using mole-fraction measurements and atmospheric simulations obtained from computer models. Studies to date are most often of a…

Reliable and exact assessment of visibility is essential for safe air traffic. In order to overcome the drawbacks of the currently subjective reports from human observers, we present an approach to automatically derive visibility measures…

Computer Vision and Pattern Recognition · Computer Science 2015-05-21 Jean-Philippe Andreu , Stefan Mayer , Karlheinz Gutjahr , Harald Ganster

Understanding complex spatial dependency structures is a crucial consideration when attempting to build a modeling framework for wind speeds. Ideally, wind speed modeling should be very efficient since the wind speed can vary significantly…

Methodology · Statistics 2023-11-28 Matthew de Bie , Janet van Niekerk , Andriette Bekker

The martian atmosphere hosts dynamical phenomena ranging from planet-encircling dust storms to mesoscale orographic clouds and nocturnal low-level jets. General circulation model show capability to simulate these phenomena, but is…

Air pollution is a major driver of climate change. Anthropogenic emissions from the burning of fossil fuels for transportation and power generation emit large amounts of problematic air pollutants, including Greenhouse Gases (GHGs). Despite…

Machine Learning · Computer Science 2021-09-01 Linus Scheibenreif , Michael Mommert , Damian Borth