Seismic anisotropy, observed in the lowermost mantle near Large Low-Shear-Velocity Provinces (LLSVPs), is likely caused by strong deformation from mantle flow interacting with these regions or plume formation. This study explores slab-induced plume generation from thermochemical piles (LLSVPs) and resulting flow behavior using 3-D regional-scale mantle convection models in ASPECT, coupled with mantle fabric simulations in ECOMAN. Various models with different LLSVP density and viscosity were tested. The modeling of the lattice preferred orientation with predominant activity of the slip system [001](100) for Bridgmanite and [100](001) for post-Perovskite reveals that the lower mantle is generally isotropic, except (i) in regions of plume conduits where vertically polarized shear waves (Vsv) are faster, and (ii) in the lowermost mantle characterized by fast horizontally polarized shear waves (Vsh) that transition to fast Vsv at the margins of the rheologically stiffer LLSVP piles where deformation and upwelling of the surrounding mantle take place.

On January 18, 2021, a blind mid-crustal Mw ~6.4 earthquake occured near San Juán, Argentina. The observation of associated ground deformation with InSAR is hidden by strong tropospheric signals. We properly correct the data and reconstruct the deformation field through InSAR timeseries approach. We show it is possible to retrieve such signal with sufficient quality to invert the fault parameters. The ground deformation can be explained by uniform slip of a single NW dipping fault plane at a depth of 19km, and the geometry of such fault supports the reactivation of inherited structures on top of the Cuyania Terrane, insinuating a direct connection and strain transfer to the active east-vergent Precordillera front.

Safe and efficient storage of CO2 in saline aquifers requires mobility control to prevent CO2 from accumulation and rapid spreading at the formation top below the caprock. In the past, we have demonstrated the effectiveness of two engineered olefinic-based oligomers for viscosification of sc-CO2 and the significant improvement in residual trapping of sc-CO2 in brine-saturated homogeneous sandstone cores. The objective of this work is to examine the sweep efficiency and residual brine saturation in the layered cores by effective viscosification with two engineered molecules, providing the implications for CO2 trapping in layered porous media by effective viscosification. In neat CO2 injection, the CO2channels through the high permeability layer, causing rapid breakthrough and high residual brine saturation. This results in an inefficient process for CO2 storage in saline aquifers. In viscosified CO2 injection, we observe significant improvements in crossflow at the interface between the two-permeability layer, partly due to the mobility control and residual brine saturation reduction. In comparison to the neat CO2 injection, the synergistic effect of the mobility control and increases in interfacial elasticity by injection of vis-CO2 results in delay in breakthrough by a factor of 2 and about 95% higher brine production. Compared to our previous work on displacement experiments in homogeneous sandstone core, there is a more significant reduction of residual brine saturation in layered cores by viscosified CO2 injection. Increases in injection rate is also demonstrated to improve the CO2 storage in layered cores. Both the CO2 viscosification and increases in injection rate may promote the injection pressure to overcome the capillary entry pressure, leading to CO2 displacement of brine in the low-permeability layer. CT-imaging data advances understanding of boundary conditions, brine production, and local residual brine saturation in layered cores. 

A document by Wang Mudan. Click on the document to view its contents.

We look for repeating earthquakes at Shishaldin volcano (Alaska) by a multi-stage clustering of the waveforms of a large catalog of Long-Period (LP) earthquakes (about 330,000 events) occurring between October 2003 and July 2004, that includes a minor eruption. We find about 5,550 LP earthquakes with at least on repeater in the catalog; they mostly occur in the interval December 2003 - March 2004. Repeaters are composed of two ∼5-s wave packets. The first packet is a direct source effect and its polarization dip angle points towards the nucleation depth of the pressurization phenomenon triggering the conduit resonance. The second packet is in the coda of the first one and is dominated by scattered waves. Repeaters are LP events with common pressurization position and triggering mechanism. The nucleation depths of the overall LP seismicity and of the repeaters (inferred by the polarization dip angle) show a sharp increase in January 2004 that temporary matches the onset of the eruptive crisis, followed by a slow nucleation depth increase in January-May 2004, that we interpret as a fast pressure drop followed by a slow pressure build up in the feeding system. During the latter stage, coda wave interferometry applied to pairs of repeaters indicates a medium velocity increase. By simple macroscopic modelling of the feeding system as a homogeneous porous medium and a velocity increase as due to squeezing of fluid-filled cracks, we estimate a pressure increase of 40 MPa in Dec 2003 - Apr 2004.

The state of the near-surface atmosphere, especially air temperature and specific humidity, has profound effects on human health, ecosystem function, and global energy flows. The accuracy of these products is important for weather forecasting, climate modeling, data assimilation, and trend assessment. The Atmospheric Infrared Sounder (AIRS) provides global products of near-surface air temperature and specific humidity estimates. These products have seen continuous improvements in accuracy, resulting in significant reductions in error rates. Despite these improvements, existing studies have not systematically validated AIRS near-surface products in both temporal and spatial perspectives, especially over oceans. This study aims to fill this gap by using the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) as a ground-based reference to evaluate AIRS near-surface air temperature and specific humidity over the ocean from the V7 Level 2 product. Our results show an overall underestimation of near-surface air temperature and specific humidity, with pronounced spatial patterns in the estimation errors. In addition, we observed higher uncertainties near land and found that the products perform better during winter and at night on a global scale, although there are regional exceptions. In terms of time scale, the estimation errors show remarkable stability over a 20-year period, demonstrating the ability of AIRS to capture general temporal characteristics. These findings underline the importance of validating and understanding the retrieval uncertainties of AIRS near-surface products, paving the way for improved climatological applications.

Oxygen Deficient Zones (ODZs) are key areas of N loss, a process dependent on organic matter. Understanding the sources of organic matter to the ODZ is necessary to predict how biogeochemical cycles will respond to ocean changes. Size fractionated (5-20, 20-53, 53-180, 180-500, >500 µm) particulate organic C and N (POM) concentration and isotopic composition depth profiles from three stations in the offshore Eastern Tropical North Pacific (ETNP) ODZ were used to create previously missing ETNP specific particle size to carbon and nitrogen relationships for models, while gaining insights into the origins of POM in the ODZ. Since the within-ODZ Prochlorococcus assimilate nitrite, we used the resulting highly depleted d15N signal to trace organic matter of cyanobacterial origin to medium sized particles at the secondary chlorophyll maximum (SCM), and to >500 µm particles directly below the SCM. This organic nitrogen was consumed in the upper ODZ. Other POM maxima were seen at the zooplankton vertical migration maxima with the increase in POM marked in the 5-20 µm fraction. In the deep ODZ, below the zooplankton migration depth, POM concentrations in the 5-20 µm fraction were unusually small, the C:N ratios were extremely high (>20), and d15N was enriched (8-12‰), indicating degraded material. In deep samples, d13C was more depleted in larger particle size and correlated with enriched d15N, indicating increased degradation in 53-500 µm particles. This trend suggests an additional source of small particles, such as from in situ production, rather than just the fragmentation of large particles.

The rotational reorientation of the Moon, a phenomenon that has left its mark on the Moon’s geological configuration, has been studied in light of the large impacts that occurred on its surface during its early evolution. This work investigates the possibility that a single impact from a massive object, similar to those described on other celestial bodies in the solar system, may have caused a significant redistribution of lunar mass at an early stage in its history. This redistribution would have led to and promoted its rotational reorientation and its current state of tidal locking with Earth. Such an event would not only have altered the Moon’s rotational orientation but also affected the distribution of craters and tectonic structures on its surface

Ground level enhancements (GLEs), which occur when high energy solar protons reach Earth, are a considerable space weather hazard for aviation activities. Neutron monitor (NM) observations of these events are the key input to operational models of ionising radiation at aviation altitudes. Similarly, the NM data is key to techniques for deriving anisotropic solar proton spectra during GLEs. A higher density of observations is desirable for both purposes. In this paper, a simple way of improving the density of observations is presented: the compact neutron monitor (CNM). This monitor uses the same detectors as soil moisture sensing networks. Three years of data from the CNM located in Guildford, UK, is shown presented. The solar cycle variation in cosmic rays is observed, alongside 4 Forbush decreases of varying magnitude. No GLEs were observed during this time, due to a lack of any events of sufficient magnitude to be observed. A future CNM station near Lerwick, UK is briefly described in addition to the Guildford station. The implications of the observations to date are discussed in the context of GLE detection. The CNM is complimentary to existing and emerging NM designs, and may be suitable for use as a reference point for the soil moisture monitoring networks. The suitability of the CNM to GLE detection can be extrapolated to the soil moisture networks in the case of large GLEs; in the event of one occurring, the data may provide unprecedented spatial resolution.

We applied an unsupervised clustering algorithm, initially trained on data from Magnetospheric Multiscale (MMS) mission at Earth, to MESSENGER observations at Mercury to identify three distinct plasma regions: magnetosphere, magnetosheath, and solar wind. This demonstrates the applicability of transfer learning for heliophysics, a machine learning technique where knowledge learned from one task is reused to perform a similar task, for an unsupervised learning task. We find that 72% of bow shock crossings and 84% of magnetopause crossings identified by the clustering algorithm using MESSENGER data are in agreement with published magnetopause and bow shock lists. These findings highlight the potential for utilizing a clustering algorithm across multiple planetary environments.

In the summer of 2021, devastating river floods occurred in Western Europe as a result of extreme rainfall. At numerous bridges, debris accumulations were observed, exacerbating flooding upstream by impeding waterflow and sometimes contributing to bridge failure. Due to widespread building damage and flooding of settlements along the rivers, these accumulations differed markedly from classic logjams, with substantial amounts of man-made objects. A new database of clogged bridges in Belgium and Germany – described in a separate data descriptor – was analysed to characterise bridge clogging and determine the effect of bridge design, bridge location and hydraulic conditions. Nearly half of the debris volume consisted of man-made materials, including building rubble, anthropogenic wood and vehicles. This created remarkably dense accumulations, highlighting the importance of further studying debris accumulations of mixed composition. Examination of the relations between bridge design and accumulation volumes found bridges with narrow pier spacing (≤10 metres) more susceptible to forming large accumulations. Blocking by the deck and railing also played a prominent role, in conjunction with blocking by the piers, as peak water levels at most bridges (85%) reached or exceeded the deck. These findings can help to better understand bridge clogging effects on flood conditions, to design bridges with lower debris accumulation risks, and to inform future flood hazard assessments, flood risk mapping, and disaster response strategies, especially in urbanised regions.

The directional derivative approach (DDA) has the potential to rapidly and accurately quantify emission distributions based on the directional derivative of satellite-observed column amounts with respect to the horizontal wind. From the first principles, this paper derives the DDA emission estimators with a range of complexity by vertically integrating the 3D continuity equation and simplifying the results under several assumptions and approximations. The connection and difference between the DDA and a widely used divergence method for emission estimation are highlighted. A key difference is that the DDA integrates from the surface to an intermediate altitude instead of to the top of the observed column. This leads to the inherent background removal of the DDA, in contrast to the explicit background removal necessitated by the divergence method theory. Linear fittings are used to account for the effects of topography, chemical reactions, and retrieval biases. Realistic estimators of NOx emissions using satellite-observed NO2 column amounts are proposed, leveraging external climatology of the NOx:NO2 ratio and its directional derivative. These estimators are evaluated within a WRF-CMAQ simulation of NOx by comparisons with the model NOx emissions. The DDA estimators consistently outperform the divergence method estimator, and the DDA estimator that considers both topography and chemistry features the lowest root mean square error (RMSE). Lessons learned from this study using synthetic model data can be readily applied to the usage of actual satellite observations for emission estimation.

We demonstrate the effectiveness of long-term continuous interferometric Synthetic Aperture Radar (InSAR) monitoring for local resource management. Sustainable yield is a key concept in groundwater management to ensure sustainable, low-impact groundwater extraction. This study proposes to estimate sustainable yield using InSAR, combined with local groundwater production data. We apply this method to the Hollywood Basin in Los Angeles, California, leveraging nearly 30 years of InSAR data (1992–2023) to investigate ground deformation linked to groundwater extraction. High spatial InSAR measurements reveal deforming regions linked to anthropogenic activities previously not well-characterized by in-situ observation networks. By integrating InSAR data with production records, we estimate the sustainable yield for the basin to be 1,211 to 1,394 acre-feet per year, significantly lower than the current operating safe yield of 3,000 acre-feet per year. Utilizing Independent Component Analysis (ICA), we are able to distinguish hydrological signals originating from the deep and shallow aquifers in the Hollywood Basin. Our findings demonstrate the effectiveness of InSAR for long-term monitoring of anthropogenic deformation and for supporting urban planning and resource management.

Incoherent scatter radar measurements rely on the application of a priori parameters from empirical models to initialize the analysis of incoherent scatter spectra. Currently, there is a need to transform ionosphere models to enable reliable space weather predictions through data assimilation of observations. Very often the data assimilation relies on electron densities measured with incoherent scatter radars. Erroneous a priori parameters would lead to the assimilation of flawed and physically inconsistent data depending on the ionospheric model. It might therefore be beneficial to assimilate the entire radar spectrum and infer the plasma parameters from the assimilated spectrum by applying the a priori parameters as given by the model. To assess the potential assimilation of incoherent scatter spectra into models, we investigate synthetic EISCAT incoherent scatter spectra calculated from TIE-GCM results. At F1 region altitudes, the atomic-to-molecular ion ratio strongly affects the shape of the incoherent scatter spectrum. Since the vertical profiles of the atomic-to-molecular ion ratio are distinctly different in the EISCAT a priori model and TIE-GCM, the assimilation of single plasma parameters induces additional, unbalanced forces into the model. A similar problem arises in the E region due to different ion-neutral collision frequency profiles. These problems could be solved by assimilation of the entire incoherent scatter spectrum followed by an in-model evaluation of the plasma parameters. We demonstrate the effect of different a priori profiles on the spectral analysis and how the derived plasma parameters are changing when leveraging a more comprehensive approach of using forward modeling with TIE-GCM.

 The absolute values of VLM and VCM are mostly from +1mm/yr to-1mm/yr. The area of Poland can be considered tectonically stable.  The developed VCM model correlates with the geological and tectonic structure of the region.  The method of combining WAV sets based on different computational strategies yielded good results.

Accurate hourly precipitation forecasting is essential for local socioeconomic activities. Here, a U-shaped neural network (U-Net) with a customized loss function for precipitation is proposed to enhance 1–24-hour precipitation post-processing over Beijing, China. 36 precipitation-related predictors, informed by local forecasters’ expertise and grounded in physical constraints, are utilized as inputs. Permutation importance (PI) and saliency maps are used to evaluate the average and specific influence of selected predictors on U-Net predictions. The findings indicate the inclusion of additional predictors is crucial for bias correction, resulting in improvements of ~14.3\% in critical success index for precipitation exceeding 10mm/h. PI analysis reveals that associated atmospheric variables function as important supplementary indicators, and saliency maps visualizations suggest that key region influencing a given grid-point extends to ~30 kilometers for 1–24-hour precipitation forecasting. It demonstrates that integrating knowledge-based predictors is promise in advancing precipitation post-processing, and further understanding and interpretation of model is crucial.

Root zone water storage capacity (SR) plays a fundamental role in determining the magnitude of evapotranspiration (ET) during both average and extreme climatic conditions. While methods exist to estimate SR globally at relatively fine spatial scales, the effects of uncertainty in these broad-scale estimates on evapotranspiration are largely unknown. We present a new method to efficiently describe the relationships between SR and evapotranspiration across all possible values of SR, for a given climate. This approach replaces computationally expensive model sensitivity analyses and provides a means for characterizing the importance of uncertainty and spatial variability in SR across various climates and timescales. To demonstrate the utility of our framework, we apply our approach to nine sites across the United States that vary in their seasonal climatology. In doing so, we show that evapotranspiration can be dramatically different between sites even with the same SR. For example, a very shallow SR (15 mm) would limit evapotranspiration to 27% of its maximum value (given no storage limitation) in some sites but to only 68% in others. Furthermore, if SR was estimated to be 250 mm with an uncertainty of +- 20%, the effect on estimated evapotranspiration in Eel (a site in Northern California) would be significant (+- 10%) but negligible in Boulder (a site in the Colorado Rockies). Furthermore, we find distinct site-specific SR–ET relationships that substantially impact how uncertainty and spatial variability in landscape distributions of SRaffect evapotranspiration patterns.

To better understand the landscape dynamics and changes in habitat connectivity influenced by glacial and interglacial oscillations over the biodiversity-rich Hengduan Mountains (HM) region, high-resolution climate data for past periods are essential. We apply the non-hydrostatic limited-area model COSMO, with a resolution of 12 km over East Asia, to simulate the Last Glacial Maximum (LGM), a period characterized by a generally colder and drier climate compared to present-day conditions. We perform the downscaling with a novel approach for paleoclimate modelling, the Pseudo-Global Warming (PGW) method. The COSMO PGW simulation for the LGM shows that COSMO generally replicates the large-scale dynamics of the driving global climate model simulation in the colder climate. Both models suggest weaker Asian summer monsoon systems during this period. Consequently, regions such as the Bay of Bengal, and the South China Sea, which typically receive substantial monsoon rainfall, experience significantly reduced precipitation. However, despite these model similarities, the high-resolution COSMO simulation exhibits distinctive differences on a smaller scale—particularly over land. For instance, COSMO suggests a more pronounced southward shift of the jet stream during the LGM winter, with cooler conditions in southern China. Moreover, the COSMO simulation, despite the overall weaker summer monsoon circulation, features increased precipitation amounts for much of the HM. Additionally, COSMO suggests a more extensive increase in snowfall over the High Mountain Asia region. Our study suggests that the resource-saving PGW approach is a suitable method to bridge the gap between large-scale projections and regional climate impacts—also for past periods like the LGM.