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Abstract

Glaciers and ice streams flowing over sediment beds commonly have a layer of ice-rich debris adhered to their base, known as a “frozen fringe,” but its impact on basal friction is unknown. We simulated basal slip over granular beds with a cryogenic ring shear device while ice infiltrated the bed to grow a fringe, and measured the frictional response under different effective stresses and slip speeds. Frictional resistance increased with increasing slip speed until it plateaued at the frictional strength of the till, closely resembling the regularized Coulomb slip law associated with clean ice over deformable beds. We hypothesize that this arises from deformation in a previously unidentified zone of weakly frozen sediments at the fringe's base, which is highly sensitive to temperature and stress gradients. We show how a rheologic model for ice-rich debris coupled with the thermomechanics of fringe growth can account for the regularized Coulomb behavior.

Abstract

Using 9  years of full-depth profiles from 55 Deep Argo floats in the Southwest Pacific Basin collected between 2014 and 2023, we find consistent warm anomalies compared to a long-term climatology below 2,000 m ranging between 11 ± 2 to 34 ± 2 m°C, most pronounced between 3,500 and 5,000 m. Over this period, a cooling trend is found between 2,000 and 4,000 m and a significant warming trend below 4,000 m with a maximum rate of 4.1 ± 0.31 m°C yr−1 near 5,000 m, with a possible acceleration over the second half of the period. The integrated Steric Sea Level expansion below 2,000 m was 7.9 ± 1 mm compared to the climatology with a trend of 1.3 ± 1.6 mm dec−1 over the Deep Argo era, contributing significantly to the local sea level budget. We assess the ability to close a full Sea Level Budget, further demonstrating the value of a full-depth Argo array.

Abstract

In this work, we address the computational challenge of large-scale physics-based simulation models for the ring current. Reduced computational cost allows for significantly faster than real-time forecasting, enhancing our ability to predict and respond to dynamic changes in the ring current, valuable for space weather monitoring and mitigation efforts. Additionally, it can also be used for a comprehensive investigation of the system. Thus, we aim to create an emulator for the Ring current-Atmosphere interactions Model with Self-Consistent magnetic field (RAM-SCB) particle flux that not only improves efficiency but also facilitates forecasting with reliable estimates of prediction uncertainties. The probabilistic emulator is built upon the methodology developed by Licata and Mehta (2023), https://doi.org/10.1029/2022sw003345. A novel discrete sampling is used to identify 30 simulation periods over 20 years of solar and geomagnetic activity. Focusing on a subset of particle flux, we use Principal Component Analysis for dimensionality reduction and Long Short-Term Memory (LSTM) neural networks to perform dynamic modeling. Hyperparameter space was explored extensively resulting in about 5% median symmetric accuracy across all data sets for one-step dynamic prediction. Using a hierarchical ensemble of LSTMs, we have developed a reduced-order probabilistic emulator (ROPE) tailored for time-series forecasting of particle flux in the ring current. This ROPE offers accurate predictions of omnidirectional flux at a single energy with no pitch angle information, providing robust predictions on the test set with an error score below 11% and calibration scores under 8% with bias under 2% providing a significant speed up as compared to the full RAM-SCB run.

Abstract

In this study, the error of total electron content (TEC) derived from the global ionospheric map (GIM) (GIM-TEC) during equatorial plasma bubble (EPB) event is investigated for the first time. The frequently-used assessment parameter of ionospheric TEC model, namely difference of Slant TEC (difference of slant total electron content (dSTEC)) is checked and employed based on eight global navigation satellite system (GNSS) stations distributed around the geomagnetic equator during the high solar activity year of 2014. The international GNSS service final GIM products are exemplified. The results present several interesting findings: (a) The observed dSTEC series is biased when an EPB is observed at the highest satellite elevation, leading to a fake bias in GIM-TEC; (b) When an EPB occurred, the error of GIM-TEC can increases or decreases and its variation sign is unrelated to the magnitude of EPB; (c) The average of the EPB-induced GIM-TEC errors is mainly at −5 to 5 TECU with 76% (24%) of positive (negative) values, and the maximum (minimum) is close to 10 TECU (−10 TECU); (d) The structure of EPB is unable to be captured by the GIM-TEC series.

Abstract

Zenith tropospheric delay (ZTD) is an important atmospheric parameter in radio-space-geodetic techniques such as Global Navigation Satellite System (GNSS), which is pivotal for GNSS positioning, navigation and meteorology. The Vienna Mapping Function (VMF) data server is a widely utilized source for implementing ZTD, offering two types of models, that is, the empirical one and the discrete one with Grid-wise and Site-wise models. Therefore, to evaluate the accuracy of these models becomes the focus of this article. Specifically, this study investigates their performances in terms of calculation of ZTD, using the hourly values derived from the International GNSS Service data as references. The results show that the root mean square err (RMSE) of the Site-wise, Grid-wise and global pressure and temperature 3 model are 11.71/13.03/38.56 mm, respectively, indicating the discrete model performs generally better than the empirical model, and the Site-wise model is the better of the two discrete models. From the perspective of spatial resolution, the performance of these three models in ZTD calculation shows obvious influences of latitude changes and elevation differences. From the temporal analysis, the accuracy of the discrete model shows differences over different UTC epochs, while the empirical model can only express the seasonal ZTD characteristics with the average RMSE at different epochs being similar, the specifically values are 39.67, 39.26, 39.38 and 39.18 mm at UTC 0:00, 6:00, 12:00 and 18:00, respectively. The histogram and boxplot well indicate the accuracy differences of the three models in different seasons. Additionally, the time series of three models at different latitudes were also explored in this research. These explorations are conducive to the selection of appropriate models for calculating ZTD based on specific requirements.

Abstract

Uranus is one of the least explored planets in our solar system, it exhibits a unique magnetic field structure which was observed by NASA's Voyager 2 mission nearly 50 years ago. Notably, Uranus displays extreme magnetic field asymmetry, a feature exclusive to the icy giants. We use the Boris algorithm to investigate how high energy protons behave within this unusual magnetic field, which is motivated by Voyager 2's observation of lower-than-expected high energy proton radiation belt intensities at Uranus. When considering full drift motions of high energy protons around Uranus, the azimuthal drift velocity can vary by as much as 15% around the planet. This results in areas around Uranus where particles will be more depleted (faster drift) and other regions where there is a surplus of particles (slower drift). This could provide a partial explanation for the “weak” proton radiation belts observed by Voyager 2.

Abstract

The plasma density is one of the most fundamental quantities of any plasma yet measuring it in space is exceptionally difficult when the density is low. Measurements from particle detectors are contaminated by spacecraft photoelectrons and methods using plasma wave emissions are hampered by natural plasma instabilities which dominate the wave spectrum. Here we present a new method which calculates the density from magnetosonic waves near the lower hybrid resonance frequency. The method works most effectively when the ratio of the plasma to cyclotron frequency is fpe/fce < 3.5. The method provides a lower bound on the plasma density. Using the new method we show that wave acceleration of electrons to relativistic energies is increased by orders of magnitude. The method enables years of satellite data to be re-analyzed for the Earth and the effectiveness of wave acceleration at the Earth, Jupiter and Saturn to be re-assessed.

Abstract

The evolution of gas hydrates influenced by the seawater environment is unknown. We present a model of structural transformation from sI hydrate to sII hydrate due to the influence of seawater environment and vent fluid in nature through in situ experiments of gas hydrate formation in the Haima cold seep area. The in situ experimental results indicate that gas hydrates preferentially form as sI hydrates even in cold seep environments where C2+ hydrocarbons are present. During subsequent evolution, the sI hydrates could restructured at the effect of seawater environment and vent fluid, causing transformation to sII hydrates under the influence of hydrate stability. The supply of gas and direct contact with seawater environment are critical factors for structural transformation. Such structural transformation is the result of gas hydrates seeking thermodynamic stability and may be common in active cold seep areas.

Abstract

Understanding the generation of damaging, high-frequency ground motions during earthquakes is essential both for fundamental science and for effective hazard preparation. Various theories exist regarding the origin of high-frequency ground motions, including the standard paradigm linked to slip heterogeneity on the rupture plane, and alternative perspectives associated with fault complexity. To assess these competing hypotheses, we measure ground motion amplitudes in different frequency bands for 3 ≤ M ≤ 5.8 earthquakes in Southern California and compare them to empirical ground motion models. We utilize a Bayesian inference technique called the Integrated Nested Laplace Approximation (INLA) to identify earthquake source regions that produce higher or lower ground motions than expected. Our analysis reveals a strong correlation between fault complexity measurements and the high-frequency ground motion event terms identified by INLA. These findings suggest that earthquakes on complex faults (or fault networks) lead to stronger-than-expected ground motions at high frequencies.

Abstract

Leveraging Gravity Recovery and Climate Experiment mascon products spanning from April 2002 to September 2023, we, for the first time, ascertain the substantial influence of cryospheric mass variations on Earth's Chandler wobble (CW). Further, in contrast to traditional analysis conducted in the excitation domain, this study focuses on the polar motion domain and incorporates the wavelet analysis technique. Our findings reveal some intriguing phenomena: Between 2006 and 2020, the cryosphere contributed an average amplitude of approximately 4.85 mas to CW, equivalent to 5.05%, with its impact escalating to about 11 mas from 2018 to 2022, representing a fourfold rise in its contribution ratio to approximately 20%. This marked surge can be attributed to the more erratic glacier mass balance results from ongoing climate change. Moreover, there is a pronounced decrease in the CW signal post-2018, which starkly contrasts with cryospheric contribution, suggesting a potential linkage to climate change yet warrants further investigation.

Abstract

The interdecadal variability of tropical cyclone precipitation (TCP) over the western North Pacific (WNP) has not been thoroughly explored in previous studies. Here, we show that the TCP variations are modulated by both the Atlantic Multidecadal Oscillation (AMO) and Interdecadal Pacific Oscillation (IPO) as evidenced by reanalysis data and model experiments. A clustering analysis of tropical cyclone tracks shows that the AMO dominates a dipole pattern of TCP anomalies in the South China Sea and along the coastal eastern China. Meanwhile, the IPO dominates TCP over the southeastern WNP. Further analyses show that the AMO, particularly its extratropical component, affects TCP over the WNP by triggering an eastward-propagating Rossby-wave train, resulting in a pair of anomalous gyres over the WNP. Contrastly, the IPO modulates TCP by stimulating tropical circulation anomalies via the tropical pathway. These findings shed light on improving near-term TCP forecast and its regional influence on East Asia.

Abstract

A minequake of magnitude M L 4.1 occurred on 18 May 2020 early in the morning at the LKAB underground iron ore mine in Kiruna, Sweden. This is the largest mining-induced earthquake in Scandinavia. It generated acoustic signals observed at three infrasound arrays at 9.3 (KRIS, Sweden), 155 (IS37, Norway), and 286 km (ARCI, Norway) distance. We perform full-waveform focal mechanism inversion based on regional seismic data and local infrasound data. These independently highlight that this event was dominated by a shallow-depth collapse in agreement with in-mine seismic station data. However, regional infrasound data cannot inform the inversion process without an accurate model of atmospheric winds and temperatures. Yet, our numerical simulations demonstrate a potential of using local and regional infrasound data to constrain an event's focal mechanism and depth.

Abstract

The MMS satellites traversed a ∼6 di-wide and ∼500 km/s southward reconnection exhaust at the dayside magnetopause on 6 December 2015 and ∼29 di from the associated X-line region. A narrow ∼0.26–0.34 di layer of enhanced ±3.5 nW/m3 oscillating energy conversion perpendicular to the magnetic field resides in this exhaust. It contained two regions of diverging in-plane electric fields in general agreement with two clockwise electron flow vortices and a proposed increase of the electron vorticity ∇ × V e. The layer developed sunward of a unipolar Hall magnetic field for a duskward BM/BL ∼ 0.9 guide field. Each electron flow vortex supported a local ∆BM ∼ 10 nT strengthening of this Hall field. The presence of this electron-scale layer in a southward exhaust for a duskward guide field is consistent with a two-dimensional simulation of a similar structure that evolved from an X-line into a northward exhaust for a similar strength dawnward guide field.

Abstract

We obtain three-dimensional models of crustal shear-wave velocity and radial anisotropy in the Bohai Bay basin (BBB), revealing distinct radial anisotropy patterns. The western region of the basin exhibits pronounced positive crustal radial anisotropies, attributed to upper mantle convection driven by the subduction of the Pacific plate during the early Tertiary. Conversely, the eastern region of the basin demonstrates weak to negative radial anisotropies, indicating a compression shear rupture system influenced by the far-field India-Eurasian collision during the Neogene-Quaternary. These differences suggest that the formation of the BBB is associated with the dynamic transition from Pacific subduction to India-Eurasian collision during the Cenozoic. Moreover, the Luxi uplift, with its stable upper-middle crustal structures, acts as a barrier hindering the eastward extension of the BBB.

Quantitative study of storm surge risk assessment in an undeveloped coastal area of China based on deep learning and geographic information system techniques: a case study of Double Moon Bay
Lichen Yu, Hao Qin, Shining Huang, Wei Wei, Haoyu Jiang, and Lin Mu
Nat. Hazards Earth Syst. Sci., 24, 2003–2024, https://doi.org/10.5194/nhess-24-2003-2024, 2024
This paper proposes a quantitative storm surge risk assessment method for data-deficient regions. A coupled model is used to simulate five storm surge scenarios. Deep learning is used to extract building footprints. Economic losses are calculated by combining adjusted depth–damage functions with inundation simulation results. Zoning maps illustrate risk levels based on economic losses, aiding in disaster prevention measures to reduce losses in coastal areas.

Simulation of a lithosphere-atmosphere-ionosphere electromagnetic coupling prior to the Wenchuan MS8.0 earthquake
Mei Li, Zhuangkai Wang, Chen Zhou, Handong Tan, and Meng Cao
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-94,2024
Preprint under review for NHESS (discussion: open, 0 comments)
In order to check the relationship between ground-based electromagnetic anomaly and ionospheric effect before the famous Wenchuan MS 8.0 earthquake, three physical models have been established to simulate the communication process of electromagnetic energy from the Wenchuan hypocenter to the Earth’s surface, via the atmosphere to the ionosphere to cause ionospheric variations.

Abstract

Despite intensified efforts to better quantify Internal Tide dynamics over past decades, large uncertainties remain regarding their distribution and lifecycle in the ocean. In particular, internal tide incoherence (loss of time-regularity) has limited our ability to characterize, understand, and predict internal tides, challenging the exploitation of new-generation wide-swath satellite altimeters. Based on a realistic high-resolution numerical simulation, we quantify the internal tide distribution and incoherence properties in the North Atlantic. We quantify IT incoherence for sea level and surface currents, and for different vertical modes independently. Our results show that typical decorrelation timescale induced by the mesoscale turbulence are rather short—below 25 days for the first vertical mode. It further exhibits a strong dependence of the internal tide incoherence with location, reflecting regions of enhanced eddy activity, and with vertical mode number—higher baroclinic modes being much more incoherent with shorter decorrelation timescale.

Abstract

Surface, aircraft, and satellite measurements indicate pervasive early cold season (Augut–September) CO2 emissions across Arctic regions, consistent with increased ecosystem metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink-to-source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season.

Abstract

Machine Learning (ML) is having a profound impact in the domain of Weather and Climate Prediction. A recent development in this area has been the emergence of fully data-driven ML prediction models which routinely claim superior performance to that of traditional physics-based models. We examine some aspects of the forecasts produced by three of the leading current ML models, Pangu-Weather, FourCastNet and GraphCast, with a focus on their fidelity and physical consistency. The main conclusion is that these ML models are not able to properly reproduce sub-synoptic and mesoscale weather phenomena and lack the fidelity and physical consistency of physics-based models and this has impacts on the interpretation of their forecasts and their perceived skill. Balancing forecast skill and physical realism will be an important consideration for future ML models.

Abstract

Accurate wildfire forecasting can inform regional management and mitigation strategies in advance of fire occurrence. Existing systems typically use fire danger indices to predict landscape flammability, based on meteorological forecasts alone, often using little or no direct information on land surface or vegetation state. Here, we use a vegetation characteristic model, weather forecasts and a data-driven machine learning approach to construct a global daily ∼9 km resolution Probability of Fire (PoF) model operating at multiple lead times. The PoF model outperforms existing indices, providing accurate forecasts of fire activity up to 10 days in advance, and in some cases up to 30 days. The model can also be used to investigate historical shifts in regional fire patterns. Furthermore, the underlying data driven approach allows PoF to be used for fire attribution, isolating key variables for specific fire events or for looking at the relationships between variables and fire occurrence.