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Abstract

Interplanetary (IP) shocks are one of the dominant solar wind structures that can significantly impact the Geospace when impinge on the Earth's magnetosphere. IP shocks severely distort the magnetosphere and induce dramatic changes in the magnetospheric currents, often leading to large disturbances in the geomagnetic field. Sudden enhancements in the solar wind dynamic pressure (P Dyn) during IP shocks cause enhanced high-latitude convection electric fields which penetrate promptly to equatorial latitudes. In response, the equatorial electrojet (EEJ) current exhibits sharp changes of magnitudes primarily controlled by the change in P Dyn and the local time. In this paper, we further investigated the influence of shock impact angle on the EEJ response to a large number (306) of IP shocks that occurred during 2001–2021. The results consistently show that the EEJ exhibits a heightened response to the shocks that head-on impact the magnetosphere (frontal shocks) than those with inclined impact (inclined shocks). The greater EEJ response during the frontal shocks could be due to a more intensified high-latitude convection electric field resulting from the symmetric compression of the magnetosphere. Finally, an existing empirical relation involving P Dyn and local time is improved by including the effects of impact angle, which can quantitatively better predict the EEJ response to IP shocks.

Abstract

Removing stripe noise from the GRACE (Gravity Recovery and Climate Experiment) monthly gravity field model is crucial for accurately interpreting temporal gravity variations. The conventional parameter filtering (CPF) approach expresses the signal components with a harmonic model while neglecting non-periodic and interannual signals. To address this issue, we improve the CPF approach by incorporating those ignored signals using a first-order Gauss–Markov process. The improved parameter filtering (IPF) approach is used to filter the monthly spherical harmonic coefficients (SHCs) of the Tongji-Grace2018 model from April 2002 to December 2016. Compared to the CPF approach, the IPF approach exhibits stronger signals in low-degree SHCs (i.e., degrees below 20) and lower noise in high-order SHCs (i.e., orders above 40), alongside higher signal-to-noise ratios and better agreement with CSR mascon product and NOAH model in global and basin analysis. Across the 22 largest basins worldwide, the average Nash–Sutcliffe coefficients of latitude-weighted terrestrial water storage anomalies filtered by the IPF approach relative to those derived from CSR mascon product and NOAH model are 0.90 and 0.21, significantly higher than 0.17 and − 0.71, filtered by the CPF approach. Simulation experiments further demonstrate that the IPF approach yields the filtered results closest to the actual signals, reducing root-mean-square errors by 30.1%, 25.9%, 45.3%, 30.9%, 46.6%, 32.7%, 39.6%, and 38.2% over land, and 2.8%, 54.4%, 70.1%, 15.3%, 69.2%, 46.5%, 40.4%, and 23.6% over the ocean, compared to CPF, DDK3, least square, RMS, Gaussian 300, Fan 300, Gaussian 300 with P4M6, and Fan 300 with P4M6 filtering approaches, respectively

Abstract

The issue of outliers has been a research focus in the field of geodesy. Based on a statistical testing method known as the w-test, data snooping along with its iterative form, iterative data snooping (IDS), is commonly used to diagnose outliers in linear models. However, in the case of multiple outliers, it may suffer from the masking and swamping effects, thereby limiting the detection and identification capabilities. This contribution is to investigate the cause of masking and swamping effects and propose a new method to mitigate these phenomena. First, based on the data division, an extended form of the w-test with its reliability measure is presented, and a theoretical reinterpretation of data snooping and IDS is provided. Then, to alleviate the effects of masking and swamping, a new outlier diagnostic method and its iterative form are proposed, namely data refining and iterative data refining (IDR). In general, if the total observations are initially divided into an inlying set and an outlying set, data snooping can be considered a process of selecting outliers from the inlying set to the outlying set. Conversely, data refining is then a reverse process to transfer inliers from the outlying set to the inlying one. Both theoretical analysis and practical examples show that IDR would keep stronger robustness than IDS due to the alleviation of masking and swamping effect, although it may pose a higher risk of precision loss when dealing with insufficient data.

Abstract

Carrier-to-noise ratio ( \(C/{N}_{0}\) ) represents the ratio of signal power and noise power density, and it is of great significance in many applications of Global Navigation Satellite System (GNSS), such as satellite signal quality monitoring, spoofing detection, position accuracy estimation, etc. Accurate \(C/{N}_{0}\) estimation results will benefit a lot for short data situations like snapshot receivers, fast spoofing detection, adjusting tracking loop parameters based on fast \(C/{N}_{0}\) estimation and so on. However, most classical \(C/{N}_{0}\) estimation methods rely on the tracking stage of a GNSS receiver, which requires at least seconds of data to get an accurate estimation and further limits the application of \(C/{N}_{0}\) for such situations. To address the limitations of \(C/{N}_{0}\) estimation for short GNSS data, we introduce a \(C/{N}_{0}\) estimation method based on the Acquisition Correlation Ratio (ACR) that estimates \(C/{N}_{0}\) within only a few milliseconds signals. We derive the theoretical performance of ACR and three classical \(C/{N}_{0}\) estimation methods. It can be proved that the proposed ACR method has lower theoretical RMSE than the other three methods. Monte Carlo simulations are consistent with the theoretical analysis, which indicates that the accuracy of ACR method can approach the theoretical bound. Experiment results of signal simulator test and real-world test both indicate that the proposed method can enhance the estimation accuracy of \(C/{N}_{0}\) under short data conditions, achieving an estimation RMSE improvement of 0.8 dB-Hz on average with 20 ms data.

SummaryThe northwestern margin of the Ordos block is structurally separated by the Yinchuan–Hetao graben system. As one of the most active intracontinental graben systems within the Eurasian continent, its kinematic pattern of crustal extension is crucial for unraveling the ongoing processes of intracontinental graben formation, while it remains unclear principally due to a lack of geological constraints on crustal deformation. We obtained and analyzed a densified GNSS (Global Navigation Satellite System) velocity field in this region. Our results suggest that the western margin of the Hetao graben exhibits the NW-directed crustal extension (∼ 1.1 mm/yr), which can be attributed to the conjugate transtension resulting from the left-lateral motion along the E–W-trending northern boundaries of the Alashan and Ordos blocks, as well as the right-lateral motion along the N–S-trending western margin of the Ordos block. Additionally, in response to the NE-directed extrusion of the Tibetan Plateau, the Alashan block undergoes approximately NE-directed contraction (4.9 ± 1.1 nanostrain/yr) and NW-directed extrusion (2.8 ± 0.8 nanostrain/yr), which vacates space for the crustal extension of the Yinchuan graben with a rate of 0.9±0.1 mm/yr. Although it is challenging to determine whether the left-lateral motion (approximately 1 mm/yr) along the E–W-trending Hetao graben is the far-field effect of western Pacific subduction, the gradual decrease in right-lateral motion from the N–S-trending western margin of the Ordos block toward the north side of the Yinshan Orogen manifests the far-field effect of the Indo-Eurasian plate convergence extending into the Mongolian Plateau.

Acoustic waves generated by seismic waves contain information on the internal structure of planets, and can be sensed by pressure sensors onboard high-altitude balloons. To identify the various contributions (...

In coal-rock formations, many micro-fractures exist, and the expansion of these micro-fractures is the internal catalyst for the macroscopic destruction of coal-rock. Moreover, the occurrence state of gas changes with the expansion of micro-fractures. In engineering practice, most coal-rock mass needs cyclic operation in the blasting excavation or mechanical drilling, and the dynamic load of coal-rock mass is cyclic impact load.

Nano and microplastics are a well-known menace, found practically everywhere in nature, including soil, oceans, drinking water, air, and even the human body. Studies show that soils in particular hold a significant portion of N/MPs.

Abrupt shifts within complex systems such as the Earth's climate system are extremely hard to predict. Researchers at the Technical University of Munich (TUM) and the Potsdam Institute for Climate Impact Research (PIK) have now succeeded in developing a new method to anticipate such tipping points in advance.

With ESA's Arctic Weather Satellite due to launch in a few weeks, the satellite is now at the Vandenberg Space Force Base in California being readied for its big day. Once in orbit, this new mission will show how short-term weather forecasts in the Arctic and beyond could be improved.

Record snowfall in recent years has not been enough to offset long-term drying conditions and increasing groundwater demands in the U.S. Southwest, according to a new analysis of NASA satellite data.

DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, 2024
We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.

Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator
Maria Rosa Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-73,2024
Preprint under review for GMD (discussion: open, 0 comments)
Observational data and modelling capabilities are expanding in recent years, but there are still barriers preventing these two data sources to be used in synergy. Proper comparison requires generating, storing and handling a large amount of data. This manuscript describes the first step in the development of a new set of software tools, the ‘VISION toolkit’, which can enable the easy and efficient integration of observational and model data required for model evaluation.

ETH researchers are using radar to scan the snow and ice on the Jungfraujoch. Sometimes, scaling an icy peak is the only way for scientists to fully understand satellite data.

In the final decades of the 20th century, stratospheric ozone depletion—often called, not quite accurately, the ozone hole—was a widespread concern. Halocarbons, including chlorofluorocarbons used as coolants in refrigerators and aerosol spray cans, were linked, beginning in the mid-1970s, to a severely thinning ozone layer. However, global efforts to reduce halocarbon use have since led to a slow but steady recovery of the stratospheric ozone layer.

As the world struggles to decarbonize, it's becoming increasingly clear we'll need to both rapidly reduce emissions and actively remove carbon dioxide (CO2) from the atmosphere. The latest Intergovernmental Panel on Climate Change report considered 230 pathways to keep global warming below 1.5°C. All require CO2 removal.

Detecting marine debris from space is now a reality, according to a new study led by the Institut de Ciències del Mar (ICM-CSIC) and the University of Cadiz recently published in the journal Nature Communications.

Abstract

The orographic effect on the spatial structure of precipitation is a fundamental problem in hydrometeorology that still requires a better understanding of the physical processes involved in the emergence of rainfall patterns and their complex statistical structure. In tropical regions, where meteorological measurements are notoriously sparse and data quality control is often poor or missing, the study of precipitation modeling and prediction is challenging. This research aims to show an innovative approach based on a random cascade downscaling method to generate high-resolution precipitation products from coarse-scale precipitation products. This approach also includes a topographic enhancement function for describing the altitudinal variability of precipitation and a numerical diffusion filter to lessen the blockiness problem of random cascades. The suggested approach was applied to analyze some long-term precipitation statistics in the metropolitan area of Mexico City. The model result agrees closely with the temporal statistics of the selected precipitation products and reflects complex orographic constraints. The proposed downscaling approach becomes an alternative to expensive computational methods and allows urban hydrology applications and analysis of small watersheds to incorporate the effects of complex orography.

Abstract

Fog processing has a significant impact on sulfur chemistry in the atmosphere. This study analyzed three winter fog events in Hong Kong using single-particle aerosol mass spectrometry (SPAMS) and a Monitor for AeRosols and GAses in ambient air (MARGA). Black carbon (BC)-related carbonaceous particles with substantial sulfate amounts comprised the largest particle number fraction (56.7%). Sulfate mass concentration decreased during fog due to the cloud's effective scavenging, but fog processing notably promoted sulfate formation at the single-particle level (average peak area increases of 31.2%). Hydroxymethanesulfonate (HMS), an important S(IV) compound and fog tracer, was identified accounting for up to 12% by particle number fraction. Although pH showed a positive correlation (r = 0.53–0.69) with HMS particles in each fog scenario, a negative overall correlation (r = −0.51) was observed. Further analysis revealed that the higher aerosol acidity (pH 0.65–3.11), promoted Fe dissolution, leading to 49% of HMS particles being mixed with Fe, which potentially facilitated sulfate formation via the Fenton reaction. Additionally, around 40% of HMS-Fe particles are mixed with oxalate, thereby warranting further attention for their potential to cause more intricate sulfur oxidation processes. This study reveals the initial identification of a high mixed-state of HMS-Fe, which could potentially serve as a crucial avenue for the formation of sulfate on individual particulate matter. Considering the persistent augmentation of aerosol acidity in the Asian region, this phenomenon necessitates further investigation and attention.