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SummaryNumerical models of geothermal reservoirs typically depend on hundreds or thousands of unknown parameters, which must be estimated using sparse, noisy data. However, these models capture complex physical processes, which frequently results in long run-times and simulation failures, making the process of estimating the unknown parameters a challenging task. Conventional techniques for parameter estimation and uncertainty quantification, such as Markov chain Monte Carlo (MCMC), can require tens of thousands of simulations to provide accurate results and are therefore challenging to apply in this context. In this paper, we study the ensemble Kalman inversion (EKI) algorithm as an alternative technique for approximate parameter estimation and uncertainty quantification for geothermal reservoir models. EKI possesses several characteristics that make it well-suited to a geothermal setting; it is derivative-free, parallelisable, robust to simulation failures, and in many cases requires far fewer simulations to provide an accurate characterisation of the posterior than conventional uncertainty quantification techniques such as MCMC. We illustrate the use of EKI in a reservoir modelling context using a combination of synthetic and real-world case studies. Through these case studies, we also demonstrate how EKI can be paired with flexible parametrisation techniques capable of accurately representing prior knowledge of the characteristics of a reservoir and adhering to geological constraints, and how the algorithm can be made robust to simulation failures. Our results demonstrate that EKI provides a reliable and efficient means of obtaining accurate parameter estimates for large-scale, two-phase geothermal reservoir models, with appropriate characterisation of uncertainty.

Abstract

Magnetic reconnection converts magnetic field energy into particle energy by breaking and reconnecting magnetic field lines. Magnetic reconnection is a kinetic process that generates a wide variety of kinetic waves via wave-particle interactions. Kinetic waves have been proposed to play an important role in magnetic reconnection in collisionless plasmas by, for example, contributing to anomalous resistivity and diffusion, particle heating, and transfer of energy between different particle populations. These waves range from below the ion cyclotron frequency to above the electron plasma frequency and from ion kinetic scales down to electron Debye length scales. This review aims to describe the progress made in understanding the relationship between magnetic reconnection and kinetic waves. We focus on the waves in different parts of the reconnection region, namely, the diffusion region, separatrices, outflow regions, and jet fronts. Particular emphasis is placed on the recent observations from the Magnetospheric Multiscale (MMS) spacecraft and numerical simulations, which have substantially increased the understanding of the interplay between kinetic waves and reconnection. Some of the ongoing questions related to waves and reconnection are discussed.

Abstract

The Analyzer for Cusp Electrons (ACE) instruments on the Tandem Reconnection and Cusp Electrodynamics Reconnaissance Satellites (TRACERS) mission provide measurements of electron velocity distribution functions from two closely spaced spacecraft in a low Earth orbit that passes through the magnetospheric cusp. The precipitating and upward-going electrons provide a sensitive probe of the magnetic field line topology and electrostatic potential structure, as well as revealing dynamic processes. ACE measurements contribute to the top-level TRACERS goals of characterizing the spatial and temporal variation of magnetic reconnection at the terrestrial magnetopause and its relationship to dynamic structures in the cusp. ACE utilizes a classic hemispheric electrostatic analyzer on a spinning platform to provide full angular coverage with 10 degree by 7 degree resolution. ACE can measure electrons over an energy range of 20-13,500 electron volts, with fractional energy resolution of 19%. ACE provides 50 ms cadence measurements of the electron velocity distribution, enabling sub-kilometer spatial resolution of cusp boundaries and other structures.

Abstract

The Europa Clipper mission will explore Europa and investigate its habitability utilizing a set of five remote-sensing instruments that cover the electromagnetic spectrum from thermal infrared to ultraviolet wavelength, four in-situ fields and particles instruments, a dual-frequency radar, and a gravity and radio science investigation. Key mission objectives include to produce high-resolution images of Europa’s surface, determine its composition, look for signs of recent or ongoing activity, measure the thickness of the icy shell, search for subsurface lakes, and determine the depth and salinity of Europa’s ocean. The Europa Clipper Mission Plan integrates the above investigations in a way that allows for the simultaneous acquisition of complimentary datasets (i.e., datasets at the regional scale, distributed globally across Europa) utilizing a complex network of flybys while in Jupiter orbit. About 50 flybys of Europa—with closest-approach altitudes varying from several thousand kilometers to as low as 25 kilometers—will be executed over an approximately 4.3-year prime mission. We present an overview of the mission design, which is driven by the complex scientific goals of the mission but also influenced by launch vehicle capabilities, the intense Jovian radiation environment, varying thermal environment, and dependency on precise planet and moon flybys to manage the orbit. We describe the interplanetary and Jovian orbit design, Mission Plan, and Navigation Plan, and forecast performance against mission requirements to date.

In the race to combat global climate change, much attention has been given to natural carbon sinks: those primarily terrestrial areas of the globe that absorb and sequester more carbon than they release. While scientists have long known that coastal salt marshes are just such a sink for "blue carbon," or carbon stored in the ocean and coastal ecosystems, it has been difficult to get an accurate estimate of just how much they store, and so most of the focus has been on terrestrial sinks such as forests and grasslands.

The greater Los Angeles area has long been the subject of intense seismographic monitoring. A network of highly sensitive seismometers peppers the region on a constant vigil for earthquakes.

Regional pollution is speeding up snow melt in the Indian Himalayas. That's according to a new study from an international group of scientists including Indian Institute of Technology Madras civil engineering Ph.D. student Amit Singh Chandel and Karl Rittger, research associate at the Institute of Arctic and Alpine Research (INSTAAR) at the University of Colorado Boulder.

A volcano near Alaska's most populous city is showing signs it could be headed toward an eruption, officials said.

Author(s): S. Iseni, G. B. Sretenović, V. V. Kovačević, N. Bonifaci, C. Pichard, C. Cachoncinlle, and A. Khacef

Gas discharge physics is particularly helpful to study many spectacular aspects of atmospheric electricity, e.g., lightning and sprite streamers. However, the observations of double-headed streamers (DHS) in nature—formed after the breakdown—remain an open question. Considering that the topic of DHS…

[Phys. Rev. E 111, L023202] Published Thu Feb 13, 2025

Abstract

The stochastic representation of an uncertain shape model allows the dynamic evaluation of its induced gravity signal. This can be also applied for representing a time variable gravity field to model mass changes. The algorithm for estimating variations in gravitational potential is extended for the case of second-order derivatives. Two different harmonic synthesis formulas are used to derive the sought variations: one expressed in spherical coordinates using the traditional associated Legendre functions (ALF) and their derivatives up to the second order, while the other expressed in Cartesian coordinates by including the derived Legendre functions (DLF). The obtained variations are compared in terms of convergence with gravity signal differences referring to the specific shape changes using the line integral analytical approach for three asteroid shape models. Both approaches provide results that differ from the analytical method at a 1E−1 level, while the differences between them are at the 1E−15 level. The obtained results are highly influenced by the geometry of the examined shape model, with the ALF approach providing variations with closer agreement with the analytical method only for the almost spherical shape. Both harmonic synthesis expressions can be used to derive accurate results, as they differ at a very low level, and one can choose based on the convenience of their algorithmic characteristics.

Abstract

Effective angular momentum (EAM) forecasts are widely used as an important input for predicting both polar motion and dUT1. So far, model predictions for atmosphere, ocean, and terrestrial hydrosphere utilized in Earth rotation research reach only 6-days into the future. GFZ’s oceanic and land-surface model forecasts are forced with operational 6-day high-resolution deterministic numerical weather predictions provided by the European Centre for Medium-range Weather Forecasts. Those atmospheric forecasts extend also further into the future with a reduced sampling rate of just 6 h but the prediction skill decreases rapidly after roughly one week. To decide about publishing 10-day instead of 6-day model-based EAM forecasts, we generated a test set of 454 individual 10-day forecasts and used it with GFZ’s EAM Predictor method to calculate Earth rotation predictions. Using 10-day instead of 6-day EAM forecasts leads to slight improvements in y-pole and dUT1 predictions for 10 to 30 days ahead. By introducing additional neural network models trained on the errors of the EAM forecasts when compared to their subsequently available analysis runs, Earth rotation prediction can be enhanced even further. A reduction of the mean absolute errors for polar motion and length-of-day prediction at a forecast horizon of 10 days of 26.8% in x-pole, 15.5% in y-pole, 27.6% in dUT1, and 47.1% in \(\Delta \) LOD is achieved. This test application successfully demonstrates the potential of the extended EAM forecasts for Earth rotation prediction although the success rate has to be further improved to arrive at robust routine predictions. GFZ publishes from October 2024 onwards raw uncorrected 10-day instead of 6-day EAM forecasts at www.gfz-potsdam.de/en/esmdata for the individual contributions of atmosphere, ocean, and terrestrial hydrosphere. Users interested in the summarized effect of all subsystems are advised to use the 90-day combined EAM forecast product that also makes use of the presented corrections to the EAM forecasts.

Abstract

GPS flex power can improve anti-jamming capability by enhancing the transmitting power of individual signals. However, during the active periods of GPS flex power in 2020, it was found that the accuracy of kinematic orbit for GRACE-FO satellites is decreased. In this paper, the impact of flex power on kinematic orbit determination of GRACE-FO is investigated. With the analysis of 30-day epoch-differenced geometry-free combinations of phase, i.e., \(\:\varDelta\:{{\Phi\:}}_{\text{G}\text{F}}\) and signal-to-noise ratio (SNR) for GRACE-FO satellites, a new strategy which considers the impact of flex power on the continuity of ambiguity is put forward to improve the kinematic orbit of GRACE-FO. After considering flex power, the 3D root-mean-square (RMS) of GRACE-C and GRACE-D are reduced to 4.10 and 4.42 cm, with improvements of 36% and 21%, respectively. The improvements of SLR validation are 34% and 14% for GRACE-C and GRACE-D. The above results prove the effectiveness of the proposed strategy.

Abstract

Signal anti-jamming has always been a difficult problem in GNSS (global navigation satellite system) signal processing. There are many GNSS anti-jamming techniques in the existing research, which can achieve good results if the interferences are sparsely distinguishable in some signal feature domains. Specifically, the single antenna based anti-jamming techniques cannot deal with wideband Gaussian noise interference because it is not sparse in time or frequency domain, while the only effective method currently is using multiple antennas to apply the space array processing (SAP) technique since the wideband Gaussian noise interference is sparse in the spatial domain. However, when the incoming directions of the different interferences are not less than that of antennas, the interferences are not sparse to the array anymore, and the SAP anti-jamming performance would decrease drastically. In this paper, a LSTM (long short-term memory) deep neural network (DNN) based algorithm is proposed to enhance the array anti-jamming performance in this situation. The proposed network estimates the interferences as an integrity by exploring the non-linear relationship of the array data received by antennas. Especially, a new loss function is designed exclusively for GNSS anti-jamming problem. The proposed DNN method is verified in the simulation that two wideband Gaussian interferences with JSR (jamming to signal ratio) 50 dB can be eliminated by using two antennas’ data, and the interference cancellation ratio improvement is about 24 dB compared to some other widely used classical SAP algorithms.

SummaryWe present new numerical tools for geophysical inversion and uncertainty quantification (UQ), with an emphasis on blocky (piecewise-constant) layered models that can reproduce sharp contrasts in geophysical or geological properties. The new tools are inspired by an “old” and very successful inversion tool: regularized, nonlinear inversion. We combine Occam’s inversion with total variation (TV) regularization and a split Bregman method to obtain an inversion algorithm that we call blocky Occam, because it determines the blockiest model that fits the data adequately. To generate a UQ, we use a modified randomize-then-optimize approach (RTO) and call the resulting algorithm RamBO (randomized blocky Occam), because it essentially amounts to running blocky Occam in a randomized parallel for-loop. Blocky Occam and RamBO inherit computational advantages and stability from the combination of Occam’s inversion, split Bregman and RTO, and, therefore, can be expected to be robustly applicable across geophysics.

Extreme fire seasons in recent years highlight the urgent need to better understand wildfires within the broader context of climate change. Under climate change, many drivers of wildfires are expected to change, such as the amount of carbon stored in vegetation, rainfall, and lightning strikes.

Publication date: February 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 267

Author(s):

Publication date: February 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 267

Author(s): Guowen Han, Bowen Zhang, Lixia Wang, Hongshuo Yan, Guowei Xin, Xiaobin Zhang

Publication date: February 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 267

Author(s): Fei Liu, Chenggang Lu, Yizhen Tang, Yaru Pan

Publication date: February 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 267

Author(s): E. Romashets, M. Vandas, T. Weaver, C. Bahrim

Publication date: February 2025

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 267

Author(s): Swati, Priya Gupta, Nitin Dubey, Sparsh Agarwal, Dhananjali Singh, Devbrat Pundhir