Earth and Space Science最新文献

The north-south seismic belt of China poses a high risk of earthquakes, necessitating the need for accurate and rapid prediction of intensity measures (IMs) to prevent and mitigate potential damage. We have developed a new multi-task model, CRAQuake, to predict IMs for the north-south seismic belt of China. Using initial arrival seismic waves recorded at a single station as input, CRAQuake simultaneously predicts six IMs without relying on pre-configured parameters such as earthquake source, path, and location. The model was trained on 4,281 sets of strong motion records data sets at 822 stations and tested to show highly correlated results with the target IMs. The prediction performance continues to improve as the input initial arrival seismic wave time window increases. CRAQuake promises to enhance the accuracy and timeliness of IMs prediction in the north-south seismic belt of China.

The stochastic Green's function method (SGFM), which simulates the source spectra of small earthquakes based on the ω⁻² model and follows the scaling law of earthquakes to synthesize into a large earthquake, is a practical ground motion simulation method in areas lacking suitable small earthquake records. However, one of the problems in the application of the SGFM is that the source spectrum synthesized from small earthquakes shows a fall-off in the mid-frequency band, as the number of fault divisions of the large earthquake increases. To solve this problem, this study proposes an improved method, which introduces a correction coefficient for the source spectrum according to the ω⁻² model and considers the variation of subfault rise time with the rupture process. Taking the 1994 Northridge earthquake as an example, the ground motion simulation results of the improved method are compared with observed records. The results show that only introducing the correction coefficient causes larger amplitude of simulation results than observed records. Only considering the variation of subfault rise time can improve the fall-off problem to some extent, but the accuracy of ground motion simulation at observation points has no significant improvement. By simultaneously introducing the correction coefficient and considering the variation of subfault rise time, the simulation results are in good agreement with observed records and are able to reproduce the directivity effect at the forward observation points. Therefore, the improved SGFM proposed in this study is an effective and reliable tool for ground motion simulation.

In this paper we address two problems associated with data-limited dynamic spacecraft exploration: data-prioritization for transmission, and data-reduction for interpretation, in the context of ESA ExoMars rover multispectral imaging. We present and explore a strategy for selecting and combining subsets of spectral channels captured from the ExoMars Panoramic Camera, and attempt to seek hematite against a background of phyllosilicates and basalts as a test case scenario, anticipated from orbital studies of the rover landing site. We compute all available dimension reductions on the material reflectance spectra afforded by 4 spectral parameter types, and consider all possible paired combinations of these. We then find the optimal linear combination of each pair whilst evaluating the resultant target-vs.-background separation in terms of the Fisher Ratio and classification accuracy, using Linear Discriminant Analysis. We find ∼50,000 spectral parameter combinations with a classification accuracy >95% that use 6-or-less filters, and that the highest accuracy score is 99.6% using 6 filters, but that an accuracy of >99% can still be achieved with 2 filters. We find that when the more computationally efficient Fisher Ratio is used to rank the combinations, the highest accuracy is 99.1% using 4 filters, and 95.1% when limited to 2 filters. These findings are applicable to the task of time-constrained planning of multispectral observations, and to the evaluation and cross-comparison of multispectral imaging systems at specific material discrimination tasks.

A dense network of GNSS receivers is employed to study temporal and spatial characteristics of large-scale traveling ionospheric disturbances (LSTIDs) in Iran. Three geomagnetic storms in 2021 are selected. To determine LSTID propagation, an eighth-order Butterworth bandpass filter was applied to the data to remove the diurnal variability of the total electron content (TEC). Moreover, two-dimensional TEC perturbation maps are provided to explore the meridional and zonal structures of the LSTIDs. Analysis of a major storm on November 4 (Kp = 7, Dst = −99 nT) revealed two single LSTIDs and three groups of multiple LSTIDs. The phase velocity and wavelength of LSTIDs in this event varied between 190 and 930 m/s and 1,030–5,022 km, respectively. Southward propagating LSTIDs appeared to be more frequent than northward. The complex propagation of two simultaneous LSTIDs is resolved. A large-amplitude mixed front showing broadening both latitudinally and meridionally is revealed. No nighttime propagating LSTID is reported. In addition, global differential TEC data are explored to examine the detection of LSTID propagation. The global data validates the timing, direction of propagation, and strength of LSTIDs detected over Iran. The auroral oval extension is consistent with generating and propagating reported LSTIDs. The second storm studied occurred on August 27 (Kp = 4, Dst = −82 nT). This storm exhibited weaker LSTIDs in terms of both observed numbers and amplitude. Finally, the storm case of May 12 (Kp = 7, Dst = −61 nT) was examined. The results underscores the vital role of the Dst index in studying LSTIDs.

Understanding the interaction between Mars and the solar wind is crucial for comprehending the atmospheric evolution and climate change on Mars. To gain a comprehensive understanding of the Martian plasma environment, global numerical simulations are essential in addition to spacecraft observations. However, there are still discrepancies among different simulation models. This study investigates how these discrepancies stem from the considered physical processes and numerical implementations. We compare two global multispecies MHD models: the “Sun model” based on the BATS-R-US code and the “Sakata model” based on a newly developed multifluid model MAESTRO. By employing the same typical upstream conditions and the same neutral atmosphere for current Mars, along with similar numerical implementations such as inner boundary conditions, we obtain simulation results that exhibit unprecedented agreement between the two models. The dayside results are nearly identical, especially along the subsolar line, indicating the robustness of MHD models to predict dayside interaction under given upstream conditions and ionosphere assumptions. The escape rates of planetary ions are also in good agreement. However, discrepancies remain in the terminator and nightside regions. Detailed numerical implementations, including inner boundary conditions, magnetic field divergence control methods, and radial resolutions, are shown to influence certain aspects of the results greatly, such as magnetotail configuration and ion diffusion.

Previous studies that intercompared global Level-4 (L4) sea surface temperature (SST) analyses were centered on the assessment of the accuracy and bias of SST by comparing them with independent near-surface Argo profile temperature data. This type of assessment is centered on the absolute value of SST rather than on SST spatial properties (gradients), which is more relevant to the study of oceanographic features (e.g., fronts, eddies, etc.) and ocean dynamics. Here, we use, for the first time, the spectrum of singularity exponents to assess the structural and dynamical quality of different L4 gap-filled products based on the multifractal theory of turbulence. Singularity exponents represent the geometrical projection of the turbulence cascade, and its singular spectrum can be related to the probability density function of the singularity exponents normalized by the scale. Our results reveal that the different schemes used to produce the L4 SST products generate different singularity spectra, which are then used to identify a potential loss of dynamical information or structural coherence. This new diagnostic constitutes a valuable tool to assess the structural quality of SST products and can support data satellite SST producers efforts to improve the interpolation schemes used to generate gap-filled SST products.

The application of high-frequency radar as an instrument for assimilating tsunami-induced current fields is garnering increasing interest. The performance of surface current velocity measurements depends on the azimuthal differences between the crossing radar beams at the measurement points. This study aimed to incorporate the measurement error distributions of the east-west and north-south velocity components into tsunami data assimilation based on an optimal interpolation method, assuming Gaussian noise with the time-invariant and a uniform standard deviation (STD = 5 cm/s) of radial velocity measurements. Through the empirical orthogonal function (EOF) analysis of radar-derived surface currents in the Kii Channel, Japan, the velocities reconstructed using higher modes (EOFs 16–274) were associated with measurement errors, portraying nonuniform distribution depending on the crossing beam angle of two radar beams. Based on independent fifteen-time assimilation experiments for two different tsunami scenarios, for a uniform water depth of 500 m, we observed a significant improvement of up to 29% and 0.9% in the assimilation performance (on average) over the along-coast stations for scenarios with 1- and 5-m maximum initial sea surface heights, respectively. The measurement errors dependent on the crossing beam angle reduced the error-induced tsunamis, resulting in stable assimilations, with lower STDs in the fifteen-time assimilation performances. When the STD of Gaussian noise varies with time, it is important to consider the temporal change in the radial velocity measurement errors and/or noise-filtering techniques, to maintain a certain level of noise intensity.

The Dynamic Albedo of Neutrons (DAN) instrument on the Mars Science Laboratory Curiosity rover primarily measures neutrons that have undergone interactions with rocks and materials in the rover's local environment. As the rover ascends Aeolis Mons, it may encounter more extreme local topography (e.g., cliffs, gullies, canyons). We present three parts of the rover's traverse in which local topography, expressed as the average local relief relative to the rover, is moderately to strongly correlated with an increase in passive thermal neutron count rates. These increases in count rates are consistent with results from radiation transport models of the instrument's performance near simulated topographic features. Additional DAN measurements in areas of high average local relief (>0.25 m) within 5 m of the instrument could bolster this correlation. DAN's sensitivity to topography in its passive mode could be utilized as a new measurement capability and has implications for the operation of future landed missions carrying neutron spectrometers (e.g., VIPER, MoonRanger, Lunar-VISE).

We calculate focal mechanisms and centroid depths for deep-focus earthquakes (DFEs) along the Peru-Brazil border. We obtained a total of 28 focal solutions for events with magnitudes between 4.2 and 7.5 Mw and occurring between 2014 and 2022. Focal mechanisms indicate predominance of normal faulting, demonstrating a rather uniform down-dip compression (DDC) regime within the plate. The orientations of the nodal planes suggest that earthquakes tend to occur along faults parallel to the local slab strike, although other fault types are documented. Stress orientations derived from the focal mechanisms agree with patterns expected if faulting were initiated by transformational faulting on a metastable olivine wedge (MOW) under DDC. Centroid depths range between 557 and 659 km, defining a narrow seismic zone within the lower portion of the subducting plate and an aseismic upper portion. We suggest that DFEs nucleate through transformational faulting within a narrow MOW preserved at a colder slab segment right above the lower mantle and juxtaposed to a shallower, warmer segment at around 500 km depth. This thermal complexity was possibly produced through flat subduction initiated by the subduction of the Nazca Ridge. We speculate that subduction of other aseismic ridges is possibly controlling the thermal state of the Nazca slab as a whole and, consequently, the depth distribution of DFEs along the South America subduction front.

After its successful implementation on the surface of Mars, laser-induced breakdown spectroscopy (LIBS) is likely to be employed on a diverse array of other solid bodies in our Solar System. Here we address the accuracy and quantification limits of LIBS under the vacuum conditions found on the Moon relative to what is known about its geochemistry. The interplay among accuracy as represented by root mean-squared errors (RMSE), the median concentration, and quantification limits (LOQ) of LIBS analyses for each of 69 elements is evaluated. This comparison shows that several key elements in lunar geochemistry cannot be well-studied with LIBS, including K₂O, S, Rb, Br, and C. Conversely, highly accurate analyses of SiO₂, CaO, and many minor and trace elements such as Mn, Yb, and Zn are possible under conditions found on the Moon. Use of LIBS must always be considered in the context of the geochemistry and geology of the target materials.