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Publication date: March 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 268

Author(s): Xuecheng Wang, Peiran Xie, Yiyi Xie, Hou Jiang

Publication date: March 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 268

Author(s): Ce Zhang, Shuaimin Wang, Yuling Zhao, Yujing Xu, Jiajia Zhang, Yanhan Mo, Hong Yu

Publication date: March 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 268

Author(s): Mikhail L. Shmatov

Publication date: March 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 268

Author(s): B. Abida Choudhury, M.I.R. Tinmaker

Publication date: Available online 4 March 2025

Source: Advances in Space Research

Author(s): Nikolas Pfaffenzeller, Roland Pail, Thomas Gruber

Publication date: Available online 4 March 2025

Source: Advances in Space Research

Author(s): Jin Liu, Zijun Zhang, Xiaolin Ning, Xin Ma

Publication date: Available online 3 March 2025

Source: Advances in Space Research

Author(s): Tongtong Wan, Keke Xu, Shuanggen Jin, Shuaipeng Wang, Yifu Liu, Wenhang Zhu

Publication date: Available online 3 March 2025

Source: Advances in Space Research

Author(s): M.J.A. Bolzan, E.A. Barbosa, P.R. da Silva

Publication date: Available online 3 March 2025

Source: Advances in Space Research

Author(s): Hanying Xu, Min Li, Yunbin Yuan, Ting Zhang, Wenyao Zhang

Publication date: Available online 1 March 2025

Source: Advances in Space Research

Author(s): Lingyu Bi, Chengzhi Sun, Xinying Wu, Shen Qiao, Zihao Li, Hongzhou Li

Publication date: Available online 28 February 2025

Source: Advances in Space Research

Author(s): Carlo Calatroni, Gilles Métris, Clément Courde, Duy-Hà Phung, Julien Chabé, Mourad Aimar, Nicolas Maurice, Hervé Mariey

Publication date: Available online 27 February 2025

Source: Advances in Space Research

Author(s): He Ren, Haichao Gui, Rui Zhong

Publication date: Available online 27 February 2025

Source: Advances in Space Research

Author(s): Guo Chen, Jun Tao, Na Wei, Qile Zhao

An extraordinary jump in ocean temperatures in 2023 and 2024 was at the extreme end of expectations from global warming and would have been "practically impossible" without climate change, new research said Wednesday.

As climate change continues to drive global sea level rise, many people living in coastal areas are already seeing the effects. Coastal erosion is accelerating and shifting coastlines inland, and storm surges are getting worse. But lurking beneath the surface is another major consequence that is thus far poorly understood: rising groundwater.

Critical minerals such as lithium, cobalt and copper are essential for an energy transition away from fossil fuels—but America's perception of their importance isn't fully understood, which can slow progress.

A recent swarm of small shallow earthquakes in Mexico City in 2019 and 2023 caused surprisingly strong ground shaking, prompting researchers to wonder how shaking from a moderate-sized earthquake might impact buildings across the city.

Princeton University and Xiamen University researchers report that in tropical and subtropical oligotrophic waters, ocean acidification reduces primary production, the process of photosynthesis in phytoplankton, where they take in carbon dioxide (CO2), sunlight, and nutrients to produce organic matter (food and energy).

SummaryIn recent years, Full-Waveform Inversion (FWI) has been extensively used to derive high-resolution subsurface velocity models from seismic data. However, due to the nonlinearity and ill-posed nature of the problem, FWI requires a good starting model to avoid producing non-physical solutions (i.e., being trapped in local minima). Moreover, traditional optimization methods often struggle to effectively quantify the uncertainty associated with the recovered solution, which is critical for decision-making processes. Bayesian inference offers an alternative approach as it directly or indirectly evaluates the posterior probability density function using Bayes’ theorem. For example, Markov Chain Monte Carlo (MCMC) methods generate multiple sample chains to characterize the solution’s uncertainty. Despite their ability to theoretically handle any form of distribution, MCMC methods require many sampling steps; this limits their usage in high-dimensional problems with computationally intensive forward modeling, as is the FWI case. Variational Inference (VI), on the other hand, approximates the posterior distribution in the form of a parametric or non-parametric proposal distribution. Among the various algorithms used in VI, Stein Variational Gradient Descent (SVGD) is characterized for its ability to iteratively refine a set of samples (commonly referred to as particles) to approximate the target distribution through an optimization process. However, mode and variance-collapse issues affect SVGD in high-dimensional inverse problems. In this study, we propose to improve the performance of SVGD within the context of FWI by combining an annealed variant of the SVGD algorithm with a multi-scale strategy, a common practice in deterministic FWI settings. Additionally, we demonstrate that Principal Component Analysis (PCA) can help to evaluate the performance of the optimization process and gain insights into the behavior of the output particles and their overall distribution. Clustering techniques are also employed to provide more rigorous and meaningful statistical analysis of the particles in the presence of multi-modal distributions (as is usually the case in FWI). Numerical tests, performed on a portion of the acoustic Marmousi model using both single and multiple frequency ranges, reveal the benefits of annealed SVGD compared to vanilla SVGD to enhance uncertainty estimation using a limited number of particles and thus address the challenges of dimensionality and computational constraints.

SummaryThe ability to detect low frequency sounds from distant energetic events depends on the temperature and wind structure of the atmosphere. Thus, from time to time surface-based acoustic detectors may not be able to capture sounds arriving from certain directions. However, the temperature minimum at the tropopause may create an acoustic duct called the “AtmoSOFAR” channel that could transmit acoustic waves laterally – but perhaps not to the ground. If true, then elevated sensors such as those borne aloft by balloons would record the signatures even in regions where ground based sensors cannot. This has been difficult to prove because high altitude acoustic sources are rare and balloon deployments are sporadic. This work describes the detection and characterization of powerful acoustic waves generated during the launch and terminal explosion of the SpaceX Starship rocket on 20 April 2023 using a pair of microbarometers on a stratospheric balloon. The signals traveled through the AtmoSOFAR channel, carrying information about the size and nature of their source. This channel also appears to leak some acoustic energy to the ground, in agreement with previous studies. The acoustic yield of the Starship terminal explosion was on the order of 103 tons TNT equivalent, which agrees with the estimated fuel load of the vehicle to about a factor of 2, but is two orders of magnitude larger than optical estimates. These results support an earlier study that claimed lateral transmission of sound from a smaller rocket through the AtmoSOFAR channel. The transmission of source information through the AtmoSOFAR channel motivates its use for monitoring other natural and anthropogenic events using balloon-borne sensors. This may become increasingly important as more and more private and government entities conduct spacecraft launches and reentries. It may also provide a means of monitoring clear air turbulence and other sound-generating atmospheric phenomena at a distance.