Earth and Space Science最新文献

Satellite column formaldehyde (HCHO) is an indicator of regional volatile organic compounds (VOC) emissions as HCHO is a short-lived intermediate oxidation product. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in 2020, is the first geostationary satellite to monitor hourly HCHO. GEMS offers unprecedented potential to reveal the diurnal variations of VOC emissions in Asia. Here, we present the first study to evaluate year-round GEMS HCHO retrievals using TROPOMI satellite and ground-based Pandora spectrometers. Our study shows that GEMS HCHO aligns with TROPOMI (r = 0.59–0.85; differences within 20% for most areas). Moreover, GEMS captures monthly and diurnal HCHO variations observed by Pandora spectrometers across Asia with differences overall within 15% (r ∼ 0.85). Diurnally, we find strong HCHO variations over urban areas but not in forests. During the fire season of mainland Southeast Asia, GEMS HCHO increases in the afternoon, in line with diurnal emission estimates from the Global Fire Emissions Database Version 4 with small fires (GFED4s) and GEOS-Chem simulations. GEMS also captures the spatial patterns of fire emissions in GFED4s. GEMS HCHO shows negative bias when observing with a high (>60°) viewing zenith angle (VZA) and overly relies on model correction for observations to the north of 30°N.

Streamflow in the Colorado River Basin (CRB) is significantly altered by human activities including land use/cover alterations, reservoir operation, irrigation, and water exports. Climate is also highly varied across the CRB which contains snowpack-dominated watersheds and arid, precipitation-dominated basins. Recently, machine learning methods have improved the generalizability and accuracy of streamflow models. Previous successes with LSTM modeling have primarily focused on unimpacted basins, and few studies have included human impacted systems in either regional or single-basin modeling. We demonstrate that the diverse hydrological behavior of river basins in the CRB are too difficult to model with a single, regional model. We propose a method to delineate catchments into categories based on the level of predictability, hydrological characteristics, and the level of human influence. Lastly, we model streamflow in each category with climate and anthropogenic proxy data sets and use feature importance methods to assess whether model performance improves with additional relevant data. Overall, land use cover data at a low temporal resolution was not sufficient to capture the irregular patterns of reservoir releases, demonstrating the importance of having high-resolution reservoir release data sets at a global scale. On the other hand, the classification approach reduced the complexity of the data and has the potential to improve streamflow forecasts in human-altered regions.

Hurricane Nicholas was classified as a Category 1 tropical cyclone (TC) at 0000 UTC on 14 September 2021 and made landfall along the upper Texas Gulf Coast at 0530 UTC with maximum sustained winds of 33 m s⁻¹. Much of the electrical activity during Nicholas was monitored by the Houston Lightning Mapping Array (HLMA) network. Thunderstorm activity developed in the rainband at 1700 UTC on 13 September, diminished by 2030 UTC, and re-intensified after 2200 UTC. At 2004 UTC (13 September), a curved megaflash (∼220 km) was observed by the HLMA in the stratiform precipitation region of the outer rainband. By 0130 UTC on 14 September 2021, vigorous storm cells developed in the eastern eyewall region and propagated cyclonically to the western eyewall region. At least four “jet-like” transient luminous events (TLEs) were observed by the HLMA emanating from a storm cell in the western eyewall region between 0230 and 0300 UTC with VHF source points ranging from 30 to 45 km in altitude. Moreover, the TLEs occurred within a region of strong wind shear, upper-level graupel-ice crystal collisions (∼15 km), and strong cloud top divergence. Charge analysis of the thunderstorm activity during Nicholas revealed an overall normal dipole structure, while the megaflash and TLE cases exhibited inverted dipole charge structures. Dissipation of the upper-level screening charge layer resulting from cloud top divergence likely played a role in the observed TLE VHF sources escaping to altitudes exceeding 30 km.

The Tibetan Plateau (TP) is covered by numerous lakes, and lake surface water temperature (LSWT) is an essential indicator of climate change, while few observations hinder our understanding of LSWT variation and its causes over TP. This study aims to simulate the summer LSWT long-term trends of 81 TP lakes during 1980–2018 and quantify the impacts and contributions of atmospheric variables. Results show that TP lakes warmed with 0.32°C decade⁻¹ on average. Northern TP lakes warmed faster than the southern ones (0.44 vs. 0.16°C decade⁻¹) due to stronger trends of atmospheric variables and higher sensitive of colder lakes to atmospheric changes. 55 (67.9%) lakes of the total lakes studied in current work warmed slower than air due to weakened shortwave radiation (SW_↓). Attribution analysis suggests that the air warming and wetting over TP dominate lakes' warming. Regarding synthesis contributions, air warming contributed 79.3%, with increased surface air temperature (SAT) and downward longwave radiation (LW_↓) accounting for 41.6% and 37.7%, respectively, and air wetting indicated by increased surface specific humidity (SSH) contributed 39.0%, followed by a positive contribution (16.8%) from declined wind speed (WS). The negative contribution (−35.1%) from weakened SW_↓ nearly counterbalances the positive effects of increased LW_↓. 55.1% of the total synthesis contribution arises from the cross contribution through interactions among atmospheric variables and is mainly reflected in SAT and SSH, accounting for 26.8% and 24.8%, respectively. The findings enhance understanding of climate change impacts on lake systems and offer insights for lake resource management.

This study utilizes Interferometric Synthetic Aperture Radar (InSAR) to examine subsidence along the coastal strip of the Miami barrier islands from 2016 to 2023. Using Sentinel-1 data, we document vertical displacements ranging from 2 to 8 cm, affecting a total of 35 coastal buildings and their vicinity. About half of the subsiding structures are younger than 2014 and at the majority of them subsidence decays with time. This correlation suggests that the subsidence is related to construction activities. In northern and central Sunny Isles Beach, where 23% of coastal structures were built during the last decade, nearly 70% are experiencing subsidence. The majority of the older subsiding structures show sudden onset or sudden acceleration of subsidence, suggesting that this is due to construction activities in their vicinity; we have identified subsidence at distance of 200 m, possibly up to 320 m, from construction sites. We attribute the observed subsidence to load-induced, prolonged creep deformation of the sandy layers within the limestone, which is accelerated, if not instigated, by construction activities. Distant subsidence from a construction site could indicate extended sandy deposits. Anthropogenic and natural groundwater movements could also be driving the creep deformation. This study demonstrates that high-rise construction on karstic barrier islands can induce creep deformation in sandy layer within the limestone succession persisting for a decade or longer. It showcases the potential of InSAR technology for monitoring both building settlement and structural stability.

Previous 1-D spherically symmetric seismic modeling studies have shown that in the presence of a clathrate lid on Titan significant thermal profile differences result, particularly in comparison to a pure water ice shell. In turn, these thermal differences would lead to notable changes in the waveform amplitudes and seismic phase arrival times. In this study we investigate the feasibility of using surface waves dispersion to explore the structure of Titan's ice shell. We investigate the ability to measure and observe the frequency-dependent signals (0.003–0.100 Hz) and their utility in being able to detect existence of a methane-clathrate lid. We find that we are unlikely to resolve the clathrate-lid's existence using long-period techniques, and this could be a limitation for studying very thick ice shells ($��>�\approx �$ 20 km) of icy ocean worlds. We did resolve the frequency range of flexural waves transitioning to a Stoneley wave (mode) in the fundamental mode, and see a Rayleigh wave in the first overtone for a 100 km ice shell on Titan for a simulated quake.

Two years following the extreme rainfall event in Henan Province in July 2021, North China was struck by another significant rainfall episode in late July and early August 2023 (the “23.7” event). This recent event, surpassed only by the August 1963 deluge in Henan province, precipitated extensive disasters across the Beijing-Tianjin-Hebei region (BTH) over the North China Plain. Understanding the mechanisms underlying such extreme precipitation events, including moisture sources and atmospheric circulation patterns, in the context of synoptic-scale systems is crucial for accurate predictions and effective disaster mitigation in the future. To achieve this, this study utilized a vertically integrated water vapor transport method and a Water Accounting model to investigate the moisture sources and pathways of the “23.7” event. A systematic analysis of circulation patterns was also conducted based on the ERA5 reanalysis. The results showed that the western North Pacific and Indian Ocean contributed 38.1% and 18.6%, respectively, to the extreme rainfall over the BTH region. Additionally, terrestrial moisture sources contributed 16.59%, playing a significant role in the event. The stable and moisture-laden air was transported to the BTH due to the influence of binary tropical cyclones “Doksuri” and “Khanun,” as well as the western Pacific subtropical high-pressure system. Convergence and updraft dynamics trigger convective processes modulated by vortices and topography. The findings of this study help to build a deeper understanding of the formation processes and mechanisms behind such heavy rainfall, which provides insights for model predictions of similar high-impact low-frequency extreme rainfall events.

The exploration of multi-layer coupling mechanisms between earthquakes and the ionosphere is crucial for utilizing ionospheric precursors in earthquake prediction. A significant research task involves continuously tracking the spatio-temporal changes in ionospheric parameters, acquiring comprehensive seismic anomaly information, and capturing “deterministic” precursor anomalies. Based on data from the China Seismo-Electromagnetic Satellite (CSES), we enhance the Pattern Informatics (PI) Method and propose an Improved Pattern Informatics (IPI) Method. The IPI method enables the calculation of the spatio-temporal dynamics of electron density anomalies detected by the CSES satellite. The seismic signals in the electron density during earthquake on 2021 at Maduo are investigated in this work. The results show that: (a) Compared to original electron density images, the IPI method-derived models extract distinct electron density anomaly signals, regardless of the data whether are collected during descending (daytime) or ascending (nighttime) orbits, or across different time scales of change window. (b) The electron density anomalies appear about 40 days prior to the Maduo Mw7.3 earthquake. The evolution of these anomalies follows a pattern of appearance, persistence, disappearance, re-emergence, and final disappearance. Moreover, the evolution trends of the IPI hotspot images at daytime and nighttime are similar. These results suggest that the IPI method can capture the spatio-temporal trends of ionospheric parameters and effectively extract electronic precursors related to strong earthquakes.