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SummaryThe Epidemic-Type Aftershock Sequence (ETAS) model is currently the most powerful statistical seismicity model that reproduces the general characteristics of earthquake clustering in space and time. However, its application can be hampered by biased parameter estimations related to earthquake catalog deficiencies, particularly in regions where the spatial coverage of local recording networks is relatively poor. Here, we systematically investigate the possible influences of the effect introduced by data truncation through the choice of the cutoff magnitude (${m}_{cut})$ and missing events due to heterogeneity of the seismic network on ETAS parameter estimates along the East African Rift System (EARS). After dividing the region into six source zones based on rheological and mechanical behaviors, the ETAS model is fitted to the earthquakes within each zone using the Davidon-Fletcher-Powell optimization algorithm. The fits and variations in parameter estimates are compared for each zone to the others and the seismological implications are discussed. We found that some parameters vary as a function of ${m}_{cut}$ primarily driven by changes in catalog size. Additionally, a systematic regional dependency of ETAS parameters is found across source zones. Furthermore, a median heat flow value for each analyzed source zone in the EARS is calculated. In contrast to previous findings in other tectonic settings, the results reveal no significant correlations between the crustal heat flows and the ETAS parameters describing earthquake productivity (${K}_0$) and the relative efficiency of an earthquake with magnitude M to produce aftershocks ($\alpha $). Our findings have significant implications for understanding the mechanisms of earthquake interaction and, therefore, provide tight constraints on the model's parameters that may serve as a testbed for existing earthquake forecasting models in this region where the vulnerability of local buildings and structures exacerbate seismic risk.

SummaryTo what extent mechanical anisotropy is required to explain the dynamics of the lithosphere is an important yet unresolved question. If anisotropy affects stress and deformation, and hence processes such as fault loading, how can we quantify its role from observations? Here, we derive analytical solutions and build a theoretical framework to explore how a shear zone with linear anisotropic viscosity can lead to deviatoric stress heterogeneity, strain-rate enhancement, as well as non-coaxial principal stress and strain rate. We develop an open-source finite-element software based on FEniCS for more complicated scenarios in both 2-D and 3-D. Mechanics of shear zones with transversely isotropic and orthorhombic anisotropy subjected to misoriented shortening and simple shearing are explored. A simple regional example for potential non-coaxiality for the Leech River Schist above the Cascadia subduction zone is presented. Our findings and these tools may help to better understand, detect, and evaluate mechanical anisotropy in natural settings, with potential implications including the transfer of lithospheric stress and deformation through fault loading.

SummaryThe columnar-flow approximation allows the development of computationally efficient numerical models tailored to the study of the rapidly rotating dynamics of Earth’s fluid outer core. In this paper we extend a novel columnar-flow formulation, called Plesio-Geostrophy (PG) by including thermal effects and viscous boundary conditions. The effect of both no-slip and stress-free boundaries, the latter being a novelty for columnar-flow models, are included. We obtain a set of fully 2D evolution equations for fluid flows and temperature where no assumption is made regarding the geometry of the latter, except in the derivation of an approximate thermal diffusion operator. To test the new PG implementation, we calculated the critical parameters for onset of thermal convection in a spherical domain. We found that the PG model prediction is in better agreement with unapproximated, 3D calculations in rapidly rotating regimes, compared to another state-of-the-art columnar-flow model.

SummaryDownward flow of surface-derived water deep into the upper crust is investigated using two dimensional coupled hydrothermal numerical models. In the models, downward flow is driven by either topographic gradients or seismic pumping, while it is facilitated by large episodic variations in fault permeability, intended to mimic fracturing and healing on a fault over repeated seismic cycles. The models show that both forcing scenarios are equally capable of driving surface-derived fluid to the base of faults at 10 km depth in several tens of thousands of years under certain conditions. Downward flow of cold fluid occurs almost exclusively during and shortly after earthquakes, while during the remaining portion of the seismic cycle fluids remain relatively stationary while they undergo thermal relaxation (i.e., heating). Rapid downward flow is favoured by a large coseismic permeability, long permeability healing time scale, and large coseismic dilatancy or high topographic relief above the fault at the surface. However, downward fluid flow is completely inhibited if fluid pressures exceeds the hydrostatic gradient, even by modest amounts, which suggests that deep fluid infiltration is unlikely to occur in every region.

Abstract

Low-cost single-frequency receivers are increasingly applied to high-precision positioning in support of high-performance GNSS market applications. However, frequent and multiple small cycle slips (CS) detection and repair is a limiting factor for single-frequency receiver-based high-precision positioning techniques, particularly in challenging environments. In this contribution, a single-frequency CS detection and repair method for a standalone GNSS receiver is proposed by using a common-antenna-based dual-board design. This design can produce two independent phase measurements received from the two boards at the same frequency for each satellite. The proposed method can construct between-board, between-epoch, and between-satellite triple differences by using these measurements to eliminate interference errors as statistics for detecting and repairing CS. If the reference satellite has a CS, the CS is transferred among the statistics caused by the between-satellite difference operation, which inevitably leads to incorrect CS detection. To solve this problem, the proposed method further considers adding a common clock design between the dual boards sharing one antenna. In this way, the between-board difference operation can directly eliminate receiver clock errors without performing the between-satellite difference operation, thereby avoiding the problem of the reference satellite. A real-world static and kinematic experiment was conducted to test the proposed method. Compared with traditional methods, the proposed method can achieve better CS detection and repair performance in terms of different multipath effects, dynamics, and sampling intervals, making it possible to obtain better positioning performance in carrier phased-based positioning techniques.

Abstract

Zenith Tropospheric Delay (ZTD) is one of the main atmospheric errors in the Global Navigation Satellite System (GNSS). In this study, we propose a novel ZTD forecasting model based on the deep-learning method named Informer-based ZTD (IBZTD) forecasting model using the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth generation reanalysis data (ERA5) from 2011 to 2021. With 72-hour historical GNSS-derived ZTDs as prior information, the subsequent 24-hour ZTDs can be forecasted. The IBZTD forecasting model achieves the best regression fit with post GNSS-derived ZTDs compared with GPT3 (Global Pressure and Temperature 3) and HGPT2 (Hourly Global Pressure and Temperature 2) models, especially in winter with a Root Mean Square Error (RMSE) of 1.51 cm and a Mean Absolute Error (MAE) of 1.15 cm. With the post GNSS-derived ZTDs as reference, in terms of the overall 24-hour forecasting accuracy for 9 GNSS stations in 2022, IBZTD forecasting model achieves a MAE of 1.66 cm and a RMSE of 2.21 cm, significantly outperforming the GPT3 model (MAE: 2.60 cm, RMSE: 3.37 cm), HGPT2 model (MAE: 3.23 cm, RMSE: 4.03 cm) and Long Short-Term Memory (LSTM) model (MAE: 2.65 cm, RMSE: 3.65 cm). An average time improvement of 17.8% and comparable forecasting precisions are achieved in the IBZTD forecasting model compared with the Transformer-based ZTD (TBZTD) forecasting model. Using predicted ZTD as prior constraints in Precise Point Positioning (PPP), the vertical convergence speed exhibits a significant improvement of 14.20%, 20.24%, 18.48%, and 19.39% in four seasons.

Abstract

Uranus distinguishes itself from other planets in the Solar System with a range of remarkable attributes, including a magnetosphere with a unique configuration, its quiescent atmosphere, its heating imbalance, its dense and narrow rings, and its unusually dark and tectonically processed icy satellites. Yet no mission to date has investigated either this ice giant or Neptune from up close. A Uranus Orbiter and Probe has thus been identified as the highest-priority new NASA Flagship mission for initiation in the decade 2023–2032. One invaluable instrument on a Uranus probe is a mass spectrometer experiment that analyzes the planet’s chemical composition in situ in real-time during the probe’s descent through the atmosphere. The selection of a mass spectrometer experiment is profoundly driven by the scientific questions the mission seeks to address and necessitates the accurate measurements of crucial elements including their isotope ratios. In addition to fulfilling the posed science requirements, the chosen experiment must adhere to stringent constraints such as mass, power, and size limitations while also prioritizing speed, simplicity of operation, a high level of reliability, and a completely autonomous operation. Here, we offer a succinct overview of the scientific rationale driving the Uranus probe mission, exploring various potential configurations for the mass spectrometer experiment, detailing instruments that complement a mass spectrometer, and discussing key factors that influence the mission’s profile. We also address the possibility of a collaborative effort between NASA and ESA, which could play a pivotal role in ensuring the successful development of this groundbreaking mission.

Abstract

European Space Agency’s Mars Express (MEX) has been orbiting Mars for 20 years and its instruments have provided a plethora of observations of atmospheric dust and clouds. These observations have been analysed to produce many unique views of the processes leading to dust lifting and cloud formation, and a full picture of the climatologies of dust and clouds has emerged. Moreover, the orbit of MEX enables viewing the planet at many local times, giving a unique access to the diurnal variations of the atmosphere. This article provides an overview of the observations of dust and clouds on Mars by MEX, complemented by the Trace Gas Orbiter that has been accompanying MEX on orbit for some years.

Abstract

Weather features, such as extratropical cyclones, atmospheric rivers (ARs), and fronts, contribute to substantial amounts of precipitation globally and are associated with different precipitation characteristics. However, future changes in these characteristics, as well as their representation in climate models, remain uncertain. We attribute 6-hourly accumulated precipitation to cyclones, moisture transport axes (AR-like features), fronts, and cold air outbreaks, and the combinations thereof in 10 ensemble members of the CESM2-LE between 1960 and 2100 under the SSP3-7.0 scenario. We find that, despite some biases in both precipitation and weather features, CESM2-LE adeptly represents the precipitation characteristics associated with the different combinations of weather features. The combinations of weather features that contribute most to precipitation in the present climate also contribute the most to future changes, both due to changes in intensity as well as frequency. While the increase in precipitation intensity dominates the overall response for total precipitation in the storm track regions, the precipitation intensity for the individual weather features does not necessarily change significantly. Instead, approximately half of the increase in precipitation intensity in the storm track regions can be attributed to a higher occurrence of the more intensely precipitating combinations of weather features, such as the co-occurrence of extratropical cyclones, fronts, and moisture transport axes.

Abstract

The Atacama Desert is amongst the driest places on Earth yet large dust outbreaks seem rare. We present the first quantitative assessment of dust events in the Atacama for 1950–2021 based on station observations. A total of 1920 dust days were recorded with less than 10% being classified as dust storms. We calculated the wind speeds at 5%, 25% and 50% of the dust-event frequency distribution. The mean wind speed for the threshold of 5% is 10.9 ± 1.6 ms−1 which is twice as large as the values in the Taklamakan, Western Sahel, and Sudan, and consistent with the perceptually infrequent dust activity despite the exceptional aridity. We see no overall long-term trend but increased dust activity for 1970–1978, 1984–1988 and 2013–2017. A combination of changes in the wind speed statistics and soil conditions, possibly including anthropogenic land-use changes have led to the variability in dust activity.

Once upon a time, the Teton Range, a 40-mile-long mountain range in the northern Rocky Mountains, may have extended much longer than it does now.

Abstract

Religious burning (RB) has been identified as a major source of atmospheric aerosols on the Qinghai-Tibet Plateau. However, there is limited understanding of the detailed chemical composition, size distribution, and optical properties of RB aerosols in this region. To characterize these important aerosol properties, ambient PM2.5 and size resolved aerosols from RB emissions in Lhasa were collected during summer 2019. Organic functional group (OFG) and inorganic ion composition was measured using Fourier transform infrared spectroscopy and ion chromatography, respectively. The ambient PM2.5 was dominated by organic components, with the OFG concentrations significantly higher during religious events, reflecting the substantial impact of RB emissions on local air quality. The RB aerosols were characterized by high fractions of alkane (34%), hydroxyl (29%), and carboxylic acid (13%) groups, with peak mass in the accumulation mode (0.56–1.00 μm). The high abundance of hydroxyl group and the size distribution pattern suggested that the RB aerosols were formed from volatilization of fuel materials followed by unaltered condensation, a process that may be unique to the low-temperature, low-oxygen burning in the scattered burners at the temples. The absorption coefficient of RB aerosols showed similar size distribution to the mass size distribution, but the absorption Ångström exponent displayed the lowest value in the 0.56–1.00 μm size mode. This specific size distribution aligned with the mass fraction of carboxylic acids and mirrored the mass proportion of alkanes, suggesting that smaller and larger particles were enriched with substances that have higher light-absorbing capabilities.

Abstract

We investigate the synoptic and mesoscale dynamics of two wet and two dry cold surges in January 2021 using a combination of observations, reanalysis, and convective-scale model forecasts from the Met Office Unified Model (MetUM). We focus on the wet surges, and particularly the wettest days which are locally extreme over Singapore and the surrounding region (i.e., the daily mean and area-averaged rainfall over 20 years exceeds the 99th percentile). On the large scale, the wet surges are characterized by an anomalously strong anticyclone over Siberia prior to their onset. The anticyclone and resultant surge winds are stronger than those of the dry surges. There is also a relatively moist (dry) environment prior to the onset of the wet (dry) surges, with the Madden-Julian Oscillation (MJO) being in Phase 3 (Phase 6). On the mesoscale, the combination of the cold surge and a local tropical low produce strong, moist north-easterly winds and convection over the Singapore region. The equatorward advection of positive anomalies of equivalent potential temperature resembles a weak gravity-current-like structure at its head, although the spatial scale is much too large for a gravity current. There is a moist bias in the model forecasts, although the precipitation is underestimated regionally during the wet surges and particularly on the extreme rainfall days. Overall, the model forecasts perform well synoptically but not in the details of mesoscale convection.

Researchers at Stanford and Colorado State University have developed a rapid, low-cost approach for studying how individual extreme weather events have been affected by global warming. Their method, detailed on Aug. 21 in Science Advances, uses machine learning to determine how much global warming has contributed to heat waves in the U.S. and elsewhere in recent years.

In recent years, the news about Earth's climate—from raging wildfires and stronger hurricanes, to devastating floods and searing heat waves—has provided little good news.

New research by the University of Liverpool has revealed how an underwater avalanche grew more than 100 times in size, causing a huge trail of destruction as it traveled 2,000km across the Atlantic Ocean seafloor off the North West coast of Africa.

Abstract

Over the past 30 years, the Arctic Dipole Anomaly (DA) has repeatedly led to record lows in summer sea ice extent, with cloud radiative effects (CRE) playing a crucial regulatory role. Here, we reveal the CRE variations between positive and negative DA events and elucidate the slowing impacts of CRE on sea ice thickness (SIT) changes. The DA triggers robust meridional winds and transpolar drift, markedly reducing SIT in the Beaufort Sea (BeS), Chukchi Sea (CS), and East Siberian Sea (ESS), while increasing it in the Greenland Sea (GS). CRE significantly slow SIT changes, contributing +14.4, +4.4, +16.4, and −26.7 cm to changes from June to August, against total changes of −55.9, −29.4, −39.8, and +42.8 cm in September over BeS, CS, ESS, and GS, respectively. This study underscores the key impacts of CRE on sea ice variation, emphasizing their significance in the polar climate system.

Time is of the essence in tropical cyclone prediction: The more warning time a community has, the better prepared its members will be when a storm makes landfall. Currently, the path and nature of tropical cyclones can be predicted up to only five days in advance.

Interactions between neighboring tectonic plates can push parts of Earth's surface up or down to form notable features, such as the Andes and the Himalayas. The forces that sculpt the Earth's surface far from plate edges are less well understood. For instance, multiple hypotheses compete to explain the uplift of the Colorado Plateau in the interior of the North American plate.

Abstract

The impact of the boreal summer intraseasonal oscillation (BSISO) on rainfall anomalies in the Yangtze–Huaihe River Basin (YHRB) was found to be modulated by the stratospheric quasi-biennial oscillation (QBO), which is reasonable for the close associations between the QBO and summer extreme precipitation in the YHRB. It was found that the extreme precipitation preferentially occurred in the YHRB during the easterly phase of the QBO (EQBO) compared to the westerly phase of the QBO (WQBO). This was primarily because the BSISO was more prone to cause rainfall extremes in the YHRB during the EQBO summers than during the WQBO summers. The EQBO can induce the background stratospheric easterly wind to arch downward into the troposphere, which enhanced the BSISO-associated moisture transport and moisture convergence and thus resulted in stronger rainfall extremes in the YHRB.