Earth and Space Science最新文献

The transport medium, mode, energy, and distance are recorded in the grain-size and grain-shape distributions in a sedimentary deposit. While grain-size analysis has long been used in sedimentology, grain-shape analysis is increasingly recognized as a valuable tool for reconstructing sedimentary processes and palaeoenvironments. Using Dynamic Image Analysis, this study focuses on endmember modeling of combined grain-size-shape distributions as an additional and robust sedimentological tool. To refine the technique, the topmost 10 m of a sedimentary section from the Mangshan Loess Plateau, China, was analyzed. Endmember modeling of the size-shape distributions revealed three sediment populations indicating different transport modes: sandy silt via short-term modified saltation (decreasing convexity with increasing grain-size), coarse silt via short-term suspension (decreasing aspect ratio and Cox circularity with grain-size), and coarse silt via long-term suspension (relatively low decreasing aspect ratio with grain-size, relatively high Cox circularity and convexity). A strong negative correlation was found between the finest endmember and a loess microcodium oxygen isotope record (precipitation proxy) from a nearby site, indicating that analyzing shape of the particles may help distinguish between dry and wet deposition. The nature of shape sorting seems to change with grain-size, transport mode and transport distance. For silt-sized sediments, shape sorting mainly occurs during deposition and is dominated by overall shape of the particles, whereas for the sand-sized sediments predominant shape sorting occurs already during entrainment based on grain regularity. These findings highlight the significance of integrating grain-shape with grain-size analyses to better resolve sediment transport processes.

The radar surface echo can be separated into coherent and incoherent components by statistical approaches, and the coherent component can be described by a backscattering model related to the RMS height. According to backscattering models for fractal surfaces, the coherent power in decibels decreases with RMS height on a scale independent of the wavelength at a rate depending on the Hurst exponent and the roughness scale. We extract the coherent power in four research areas by fitting the amplitude distribution of the Martian surface echoes recorded by the SHARAD radar, and compare the coherent power with the RMS height derived from pulse width of the MOLA laser altimeter. Scatter plots of squared MOLA-derived RMS height-coherent power are drawn to estimate the rates of coherent power fall-off by linear fitting, and the fitting power fall-off rates are compared to the Hurst exponents derived from digital terrain models in those areas. The fitting rates decrease with the Hurst exponent, similar to the theoretical rates. However, the fitting rates decrease with the Hurst exponent more sharply than the theoretical prediction. We explain the mismatch with a linear assumption between different roughness parameters, which helps to estimate the Hurst exponent, and a significant discrepancy between the wavelength and the roughness scale might influence the estimation results due to the scaling dependence of the Hurst exponent. This paper offers an opportunity to learn about the Hurst exponent at a tens-of-meter scale.

Geomagnetic storms, intense disturbances in the Earth's magnetosphere, pose risks to both technology and human activity in space. In this study, we analyzed geomagnetic field measurements from the Dusheti Observatory in Georgia during the intense geomagnetic storms of March 3, March 24, and 11 May 2024. Using cross-correlation, wavelet coherence, and detrended fluctuation analysis, we investigated the relationship between the $��B_z�$ component of interplanetary magnetic field, dynamic pressure, plasma $��{\beta }_p�$ in the upstream solar wind, and the H-component of the geomagnetic field. Our results reveal significant correlations with $��B_z�$ and $��P�$, characterized by distinct time lags of the order of 200 min, compatible with timescales observed in the literature. Wavelet coherence on both shorter and longer temporal scales revealed complex, multiscale characteristics of solar wind-magnetosphere coupling dynamics. Plasma $��{\beta }_p�$ showed an increase in coherence when a time shift is introduced, with maximal coherence for a shift of 12.5 hr, which may be related to the structure of the impinging coronal mass ejection and to the state of the magnetosphere. Detrended Fluctuation Analysis highlights regime changes in the Hurst exponent, indicating an increase in self-organization prior to storms. These findings emphasize the importance of localized studies in understanding the impacts of geomagnetic storms in Georgia.

Revealing the characteristics of moisture transport in heavy rainfall events in eastern China under the Northeast China Cold Vortex (NCCV) background holds important scientific and practical value for improving precipitation prediction accuracy. This study uses reanalysis data, surface observations, and a Lagrangian trajectory model to compare the characteristics and moisture transport mechanisms of NCCV and non-NCCV (NNCCV) rainstorms in Northeast China (NEC), North China (NC), and the Yangtze-Huaihe River basin (YHR). The results show that: (a) The high-value area of NCCV rainstorm intensity in NEC is located along the southern coast; in NC, rainstorms are in the southeast, with NNCCV rainstorms being more intense. In YHR, NCCV rainstorms are distributed along the Yangtze River, while NNCCV rainstorms are concentrated in the central-north and southeastern coast. NCCV rainstorm frequency peaks in July in NEC and NC, and in June in YHR. The NCCV significantly changes the rainstorm distribution in YHR in June and August. All three regions show an upward trend in NCCV rainstorm frequency, with the fastest increase in YHR. (b) For NCCV rainstorms in NEC, the southwest pathway moisture contributes the most (40%), while NNCCV rainstorms are dominated by the southeast pathway (48%). In NC, both NCCV and NNCCV rainstorms are primarily influenced by the southwest pathway moisture (45% and 42%, respectively). In YHR, the southeast pathway moisture accounts for 62% of NCCV rainstorms, compared to 46% for NNCCV rainstorms. (c) In NEC, the NCCV easily triggers strong local cyclonic convergence, with more moisture from the eastern coast than usual. In NC, the NCCV introduces dry and cold air during rainstorms, reducing moisture but enhancing dynamic uplift through north-south wind convergence. In YHR, the southward shift of the NCCV interacts with the western Pacific subtropical high, leading to collisions between dry easterly currents and warm moist southwesterly jets, triggering convective instability and intensified precipitation.

Revealing the characteristics of moisture transport in heavy rainfall events in eastern China under the Northeast China Cold Vortex (NCCV) background holds important scientific and practical value for improving precipitation prediction accuracy. This study uses reanalysis data, surface observations, and a Lagrangian trajectory model to compare the characteristics and moisture transport mechanisms of NCCV and non-NCCV (NNCCV) rainstorms in Northeast China (NEC), North China (NC), and the Yangtze-Huaihe River basin (YHR). The results show that: (a) The high-value area of NCCV rainstorm intensity in NEC is located along the southern coast; in NC, rainstorms are in the southeast, with NNCCV rainstorms being more intense. In YHR, NCCV rainstorms are distributed along the Yangtze River, while NNCCV rainstorms are concentrated in the central-north and southeastern coast. NCCV rainstorm frequency peaks in July in NEC and NC, and in June in YHR. The NCCV significantly changes the rainstorm distribution in YHR in June and August. All three regions show an upward trend in NCCV rainstorm frequency, with the fastest increase in YHR. (b) For NCCV rainstorms in NEC, the southwest pathway moisture contributes the most (40%), while NNCCV rainstorms are dominated by the southeast pathway (48%). In NC, both NCCV and NNCCV rainstorms are primarily influenced by the southwest pathway moisture (45% and 42%, respectively). In YHR, the southeast pathway moisture accounts for 62% of NCCV rainstorms, compared to 46% for NNCCV rainstorms. (c) In NEC, the NCCV easily triggers strong local cyclonic convergence, with more moisture from the eastern coast than usual. In NC, the NCCV introduces dry and cold air during rainstorms, reducing moisture but enhancing dynamic uplift through north-south wind convergence. In YHR, the southward shift of the NCCV interacts with the western Pacific subtropical high, leading to collisions between dry easterly currents and warm moist southwesterly jets, triggering convective instability and intensified precipitation.

Do systematic differences in cloud-to-ground (CG) lightning properties—particularly return stroke number and current intensity—exist across different thunderstorm types? This question is foundational not only to the atmospheric electricity but also to advancing lightning risk prediction, which crucially depends on a robust understanding of how these physical attributes vary among thunderstorm types. This study compares CG lightning characteristics between frontal (FR) and warm-sector heavy rainfall (WR) events in Guangdong, China, using data from the Guangdong Lightning Location System from 2003 to 2014. Results show that WR events feature a higher positive CG (PCG) lightning percentage, more return strokes (RSs) of negative CG (NCG) lightning, and stronger NCG lightning currents, but lower CG lightning frequency compared to FR events. FR events exhibit higher peak currents in PCG compared to NCG lightning, while WR events show the opposite pattern. These differences remain consistent across the varying precipitation intensity bins used to classify the events. Additionally, WR events develop secondary peaks in the distributions of PCG lightning percentage, NCG RS number, and NCG lightning current as precipitation intensity increases, gradually approaching the decreasing peaks in FR events at higher precipitation intensities, leading to more similar CG lightning properties between the two event types. It is demonstrated that different types of thunderstorms can produce lightning discharges with distinct physical properties. Specifically, weaker convection may correlate with more RSs and greater current in NCG lightning. This finding offers valuable insights for the construction of future lightning risk predication.

The Surface Water and Ocean Topography (SWOT) mission provides unprecedented high-resolution simultaneous observations of both sea surface height anomalies and sea surface roughness. Specifically, it enables more precise analysis of strong internal waves. Off the Amazon Shelf, in the Indonesian Seas, and near the Mascarene Ridge, internal wave signatures range from 3 to 50 km in wavelength. Using a three-layer model to describe upper ocean stratification, SWOT measurements of sea surface heights are converted into thermocline displacements, which can reach amplitudes of up to 80 m. Simultaneous measurements of changes in sea surface roughness and height offer new insights into the mechanisms behind internal wave detection through precise radar intensity measurements. In fact, SWOT data can be analyzed with a modulation transfer function that connects radar intensity contrasts to the divergence of surface currents derived from sea surface height measurements. Based on these observations, a SWOT-based modulation transfer function is developed as a function of the amplitude and wavenumber of internal waves, as well as local wind conditions. The highest radar intensity contrasts occur when internal waves propagate in the same direction as the wind, indicating resonant conditions between short wind waves and internal waves. These findings open new possibilities for extracting valuable information about Brunt–Väisälä frequency profiles from satellite observations of internal waves.

Differences in satellite sampling affect their ability to resolve small-scale features over Arctic sea ice. For CryoSat-2 (CS2) and ICESat-2 (IS2) these differences are driven by geometric (footprint resolution) and radiometric (radar or laser) sampling. Here we compare growth season (October-April) surface type densities (the detected densities of lead, floe, and ambiguous targets) from CS2 and IS2 products, Arctic-wide over a common mission period. We develop these products using standard and fully-focused CS2 sea ice processing, IS2 ATL07 sea ice height data, and IS2 ATL10 sea ice freeboard data. Our analysis shows agreement in the spatial distributions of lead and floe densities between products, but significant variations in magnitude. Average floe densities from CS2 standard and fully-focused processing are 40% and 41% respectively, but 91% for all IS2 products. The average lead density from CS2 standard processing is 45%, and below 10% for all other products. The factors causing ambiguous classifications and misclassifications differ between satellites; while CS2 is more susceptible to off-nadir ranging to leads, IS2 retrievals are complicated by variable apparent lead brightness at nadir, and the presence of ridged ice. We also investigate the impact of sampling on sea ice floe length estimates, which average 1.8–2.9 km. Finally, we assess the performance of CS2 and IS2 surface type classification along near-coincident CRYO2ICE orbits. Based on our results we encourage CS2 and IS2 data users to consider how satellite sampling impacts true geophysical retrievals, and to utilize both missions simultaneously to benefit from their complementary strengths.

Earth's primary accretion was followed by a protracted flux of interplanetary collisions by leftover planetesimals. The effects of the largest collisions—with bodies possibly exceeding 1,000 km diameter—would have been devastating for terrestrial near-surface environments. While our understanding of these events is hampered by the lack of terrestrial geological record, modeling provides useful insights on their consequences. In this paper we quantify impact-generated melting and vaporization of the early Earth via a comprehensive suite of state-of-the-art shock physics numerical models. We consider a wide range of impact scenarios (impactor sizes and velocities) as well as target conditions chosen to encompass early Earth conditions (i.e., geothermal gradients, crustal thickness and composition). We find that impact-generated melting of the Hadean (4–4.5 Ga) near-surface was widespread, and that the largest impacts would have effectively dredged-up mantle melts and redistributed them at the surface. Similarly, large scale vaporization of target and impactor materials would have altered atmospheric chemistry and its redox state well into the Mesoarchean (∼3 Ga). Altogether, these impact-related processes would have had a profound consequence on the early Earth, and our results will provide a valuable resource for further studies devoted to addressing their environmental consequences.

Accurate atmospheric drag modeling is essential for precise orbit determination and prediction of Low Earth Orbit satellites. A key component is the thermospheric density, typically estimated using empirical models driven by geomagnetic activity indices such as the 3-hr Kp or ap. However, the coarse temporal resolution and fixed upper bounds of Kp/ap indices limit their ability to reflect rapid geomagnetic variations, especially during storms, leading to underestimated thermospheric density. In this study, we investigated the usefulness of replacing Kp/ap with the higher-frequency and open-ended Hpo/apo indices during geomagnetic storms. The correlation between Kp/ap and Hpo/apo indices over 126 geomagnetic storms was analyzed, and strong correlations (correlation coefficients > 0.93) were found. Using satellite-derived density as a reference, we evaluated the performance of four empirical thermospheric models, including JB2008, NRLMSIS2.1, DTM2020 Operational, and DTM2020 Research, when driven by Hpo/apo. Results show that the performance of the JB2008 and DTM2020 Operational models is improved during moderate and intense geomagnetic storms but deteriorates under super storm conditions. The improvements are approximately 3%–9% for computed to observed (C/O) means and 4%–11% for C/O RMSEs with the JB2008 model, respectively, and less significant with the DTM2020 Operational model. For NRLMSIS2.1, only slight differences (<1% in means and <2% in RMSEs) were found in the model performance after index substitutions. Under super storm conditions, the impacts of index substitutions are statistically insignificant at the 95% confidence level. Additionally, increasing Hpo/apo temporal resolution from 60 to 30 min yields limited benefits (<1% improvement) for all models.