Volcanic ash detection is important for effective emergency management. Ash emitted by volcanoes is injected at high altitudes into the atmosphere, dispersed and driven by wind and extended for kilometres away from volcanoes. It can affect communities in different ways including health, agriculture, the environment and air traffic. Thus, detecting and tracking the volcanic ash clouds using satellite images can help civil protection authorities and volcanic ash advisory centres respond rapidly to a volcanic event. Satellite based detection of volcanic ash has traditionally entailed the implementation of radiances, reflectances, brightness temperatures (BT), brightness temperature differences (BTD), beta ratios and cloud objects tracking tools. The aim of this study is to test machine learning algorithms on satellite data in order to identify volcanic ash in the atmosphere as an attempt to enhance the space-borne ash detection capabilities especially in ambiguous cases, where image classification is hard, such as when ash, clear land and cirrus clouds coexist within a scene. We used a set of 10 satellite images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the satellites Terra and Aqua just after the 4 June 2011 eruption of the Puyehue Cordon Caulle Volcanic Complex to train and test two supervised classification algorithms: K-Nearest Neighbours and Support Vector Machine, for volcanic ash detection in the atmosphere. We first built a database that consists of 217,859 pixels identified and labelled, on the basis of visual interpretation of color composites, according to seven classes: volcanic ash above the emission centre, land and sea, meteorological clouds above land and sea, and clear sky above land and sea. For each of the seven classes, sample pixel values were retrieved for six features, which are given by the BT at 11𝝁m and the BTDs between 11 and 12 𝝁m, 11 and 3.9 𝝁m, 11 and 6.7 𝝁m, 11 and 8.5 𝝁m and a BTD that combines the BTs measured at 11, 12 and 8.5 𝝁m. We show preliminary results on statistical analysis of the training datasets and performance of both algorithms for volcanic ash detection above land and sea including verification tests with MODIS datasets that cover the April 2015 eruption of Volcan Calbuco (Chile).

Numerous studies have indicated that mesoscale eddies play an important role in diapycnal mixing and drive global water circulation. Although the relationships between eddy surface features and turbulent mixing have been discussed for individual cases of typical eddies, global studies cannot rely on ship-based microstructural measurements. Fine-scale methods have been developed, wherein either the vertical shear of velocity or density strain is used to estimate turbulent mixing. In this study, the turbulent dissipation rate was estimated using strain information from Argo floats trapped in eddies. Spatially averaged estimates revealed the global distribution patterns of the dissipation rates inside the eddies. In addition, the relationships between eddy features (polarity, radius, vertical extent, and aspect ratio) and turbulent dissipation rates were analyzed. Three main conclusions were made from this study. First, turbulent dissipation rates inside anticyclones were generally larger than those inside cyclones. Second, turbulent dissipation rates inside eddies are related to their vertical extent but not to their horizontal scale. For shallow eddies (with a vertical extent less than 250 m for cyclones and 300 m for anticyclones), the deeper the vertical extent, the larger the turbulent dissipation rate. Finally, the relationship between the eddy aspect ratio and turbulent dissipation rate was characterized by skewness. The average turbulent dissipation rate reached a maximum value when the cyclone aspect ratio was approximately 0.007; conversely, no maximum value was reached for anticyclones. This work establishes a correlation between eddy features and turbulent dissipation rates, which will help guide numerical simulations of mesoscale eddies.

The Southern Ocean is responsible for the majority of the global oceanic heat uptake that contributes to global sea level rise. At the same time, ocean temperatures do not change at the same rate in all regions and sea level variability is also affected by changes in salinity. This study investigates ten years of steric height variability (2008 to 2017) in the Southern Ocean (30°S to 70°S) by analysing temperature and salinity variations obtained from the GLORYS-031 model provided by the European Copernicus Marine Environment Monitoring Service (CMEMS). The thermohaline variability is decomposed into thermohaline modes using a functional Principal Component Analysis (fPCA). Thermohaline modes provide a natural basis to decompose the joint temperature-salinity vertical profiles into a sum of vertical modes weighted by their respective principal components (PCs) that can be related to steric height variability. Interannual steric height trends are found to differ significantly between subtropical and subpolar regions, simultaneously with a shift from a thermohaline stratification dominated by the first ‘thermal’ mode in the north to the second ‘saline’ mode in the South. The Polar Front appears as a natural boundary between the two regions, where steric height variations are minimized. Despite higher melt rates and atmospheric temperatures, steric height in Antarctic waters (0-2000 m) has dropped since 2008 due to higher salt content in the surface and upper intermediate layer and partially colder waters, while subtropical waters farther north have mostly risen due to increased heat storage.

In this study we identify a global seasonal bias in ocean color remote sensing reflectances (R rs , λ) using data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instrument aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder) satellite, in addition to Argo floats and in-water reflectance from the Marine Optical BuoY (MOBY) site. The seasonal bias in R rs is present in the VIIRS (Visible Infrared Imaging Radiometer Suite), SeaWIFS (Sea-viewing Wide Field-of-view sensor), and MODIS (Moderate resolution imaging spectrometer) satellites at all visible wavelengths and is larger at longer wavelengths. Products derived from Rrs are affected by the bias to varying degrees, with particulate backscattering varying up to 50% over a year, chlorophyll varying up to 25% over a year, and absorption from phytoplankton or dissolved material varying by up to 15%. The seasonal bias is prominent in areas of low biomass (i.e., gyres) and is not easily discernable in areas of high biomass. We found that the seasonal bias in Rrs is not caused by Raman scattering choice or implementation, nor is it due to differences with satellite viewing angle. Biases in particulate backscattering are not affected by specific assumptions used within Rrs inversion models. Changing the specific space/time averaging window in different processing levels of remote sensing data and matchups were not the cause either. While we have eliminated several candidates which could cause the bias, there are still outstanding questions about the role atmospheric correction plays. We provide evidence that the Bidirectional Reflectance Distribution Function correction factor may control the observed seasonal bias to some extent, but does not preclude the effect of the aerosol correction. We provide recommendations for work to be conducted in the near-future. In particular, the use of CALIOP aerosol data may help improve the aerosol model used in atmospheric correction and the execution of more simulations to discern the relative influence of atmospheric correction parameters. Community efforts are needed to find the root cause of the seasonal bias because all past, present, and future data will be affected until a solution is implemented.

Long-duration, continuous geodetic timeseries suggest that volcanoes exhibit a wide range of deformation patterns that vary between episodes of unrest. Viscoelastic deformation around crustal magma storage zones is an expected contributor to such observations, but is challenging to characterize robustly. Here we present an analytic approach for modeling crustal deformation around magma reservoirs that highlights frequency-domain signatures of viscoelastic response for temperature-dependent crustal rheology. We develop a transfer function that links frequency spectra of chamber pressure to surface displacement, finding that properties of the magmatic system are encoded at periods where geodetic observations are routinely made. Inhomogeneous viscoelastic response is characterized by a frequency-dependent elastic-viscous transition around the reservoir. We explore the consequences of this frequency dependence by examining broadband forcing consisting of multiple impulsive pressurization episodes, and identify a history dependence of volcano deformation in which past activity influences the stress state and surface deformation of future episodes.

The 15 January 2022 eruption of the Hunga Tonga-Hunga Ha'apai underwater volcano injected a record amount of water directly into the stratosphere. This study attempts to quantify this impact on the temperature, as well as the subsequent changes to the stratospheric circulation, during the months following the eruption based on reanalysis fields. The extreme nature of the temperature, wind, and circulation changes are tracked through comparisons of the first six months of 2022 with the past 42 years. Examination of the data assimilation process shows that at 20 hPa the thermal observations are forcing temperatures to cool significantly, compensating for the absence of the excess stratospheric moisture in the model used for the reanalysis, resulting in unusually low temperatures. In response to this cooling the atmosphere adjusts by creating strong westerly winds above the temperature anomaly and large changes to the downward and poleward mean meridional circulation.

A large earthquake unlocks a fault-zone via dynamic rupture while releasing part of the elastic energy stored during the interseismic stage. As earthquakes occur at depth, the analyses of earthquake physics rely primarily on experimental observations and conceptual models. A common view is that the earthquake instability is necessarily related to the frictional weakening that is commonly observed in shear experiments under seismic slip velocities. However, recent experiments with frictional interfaces in brittle acrylics and rocks have explicitly demonstrated that no characteristic frictional strength exists; a wide range of stresses (‘overstresses’) are sustained prior to rupture nucleation. Moreover, the experimentally observed singular stress-fields and rupture dynamics are precisely those predicted by fracture mechanics. We therefore argue here that earthquake dynamics are best understood in terms of dynamic fracture mechanics: rupture dynamics are driven by overstresses, but not directly related to the fault frictional properties.

The signature extraction and processing are the key aspects of enhancing recognition ability for radar target characteristics. In this paper, to reveal the intrinsic property of the target and improve the accuracy of radar cross section(RCS), we proposed RCS diagnostic imaging technique, extracting the parameters of scattering center model by state space method(SSM), to analyze the signature of GTD-based returns. Comparison with estimating signal parameter via rotational invariance techniques(ESPRIT) method, reconstructing the RCS profile through original and recovery signal, and employing SSM to the PEC sphere simulation, both the signature of specular and creeping wave extraction, the validation of SSM completely achieved the diagnostic imaging by means of parameter extraction.

Snowpack ecosystem studies are primarily derived from research on snow-on-soil ecosystems. Greater research attention needs to be directed to the study of glacial snow covers as most snow cover lies on glaciers and ice sheets. With rising temperatures, snowpacks are getting wetter, which can potentially give rise to biologically productive snowpacks. The present study set out to determine the linkage between the thermal evolution of a snowpack and the seasonal microbial ecology of snow. We present the first comprehensive study of the seasonal microbial activity and biogeochemistry within a melting glacial snowpack on a High Arctic ice cap, Foxfonna, in Svalbard. Nutrients from winter atmospheric bulk deposition were supplemented by dust fertilisation and weathering processes. NH4+ and PO43- resources in the snow therefore reached their highest values during late June and early July, at 22 and 13.9 mg m-2, respectively. However, primary production did not respond to this nutrient resource due to an absence of autotrophs in the snowpack. The average autotrophic abundance on the ice cap throughout the melt season was 0.5 {plus minus} 2.7 cells mL-1. Instead, the microbial cell abundance was dominated by bacterial cells that increased from an average of (39 {plus minus} 19 cells mL-1) in June to (363 {plus minus} 595 cells mL-1) in early July. Thus, the total seasonal biological production on Foxfonna was estimated at 153 mg C m-2, and the glacial snowpack microbial ecosystem was identified as net-heterotrophic. This work presents a seasonal ‘album’ documenting the bacterial ecology of glacial snowpacks.

The Mg/Ca and oxygen isotope ratios (δ18O) of multiple species of planktic foraminifers provide information on the hydrological conditions between the surface and the thermocline. Knowledge of the apparent calcification depth (ACD) of planktic foraminifers is key to reconstructing paleoenvironments; however, ACDs exhibit seasonal variations and differ over regional scales. We obtained the ACDs of Globigerinoides ruber, Trilobatus sacculifer, and Neogloboquadrina dutertrei in the Bay of Bengal using multiyear sediment-trap samples collected at approximately 900 m depth. The sediment traps were moored in the southwestern Bay of Bengal, with sampling intervals of 17-42 days. The temperature estimates obtained from the δ18O and Mg/Ca patterns of G. ruber, T. sacculifer, and N. dutertrei indicate that G. ruber reflects the temperature within the mixed layer, whereas N. dutertrei precipitates its test in the upper thermocline and T. sacculifer calcifies between these depths. The rapidly attenuating photosynthetically active radiation constrains the living depths of these symbiont-bearing species to within the upper 60 m of the euphotic zone in the southwestern Bay of Bengal. Although G. ruber and N. dutertrei calcify at different depths, as demonstrated by the different δ18O values of the two species (Δ18Or-d), large Δ18Or-d values were not obtained just in spring and summer when stratification is developed . The flux-weighted δ18O value of a species corresponds to the mean annual δ18O value of that species. Seasonal variations in species-specific test fluxes can be averaged out because of recurring flux peaks during the northeast and southwest monsoon seasons.

Fine and ultrafine ambient particulate matter (PM) has major health and climate impacts. Chemical composition of PM is required for better estimation of these impacts but is considerably expensive to measure as compared to the total PM mass concentrations. We explore the indirect estimation of PM chemical composition by analysing the temporal variation of, relatively inexpensively measured, total PM.

A potential risk of injecting CO2 into storage reservoirs with marginal permeability (≲ 10-14 m2) is that commercial injection rates could induce fracturing of the reservoir and/or the caprock. Such fracturing is essentially fluid-driven fracturing in the leakoff-dominated regime. Recent studies suggested that fracturing, if contained within the lower portion of the caprock complex, could substantially improve the injectivity without compromising the overall seal integrity. Modeling this phenomenon entails complex coupled interactions among the fluids, the fracture, the reservoir, and the caprock. We develop a simple method to capture all these interplays in high fidelity by sequentially coupling a hydraulic fracturing module with a coupled thermal-hydrological-mechanical (THM) model for nonisothermal multiphase flow. The model was made numerically tractable by taking advantage of self-stabilizing features of leakoff-dominated fracturing. The model is validated against the PKN solution in the leakoff-dominated regime. Moreover, we employ the model to study thermo-poromechanical responses of a fluid-driven fracture in a field-scale carbon storage reservoir that is loosely based on the In Salah project’s Krechba reservoir. The model reveals complex yet intriguing behaviors of the reservoir-caprock-fluid system with fracturing induced by cold CO2 injection. We also study the effects of the in situ stress contrast between the reservoir and caprock and thermal contraction on the vertical containment of the fracture. The proposed model proves effective in simulating practical problems on length and time scales relevant to geological carbon storage.

How lightning initiates inside thunderclouds remains a major puzzle of atmospheric electricity. By monitoring optical emissions from thunderstorms, the Atmosphere-Space Interactions Monitor (ASIM) onboard the International Space Station is providing new clues about lightning initiation by detecting Blue LUminous Events (BLUEs), which are manifestations of an enigmatic type of electrical discharge that sometimes precedes lightning and is named “fast breakdown”. Here we combine optical and radio observations from a thunderstorm near Malaysia to uncover a new type of event containing multiple optical and radio pulses. We find that the first optical pulse coincides with a strong radio signal in the form of a Narrow Bipolar Event (NBE) but subsequent optical pulses, delayed some milliseconds, have weaker radio signals, possibly because they emanate from a horizontally oriented fast breakdown which does not trigger full-fledged lightning. Our results cast light on the differences between isolated and lightning-initiating fast breakdown.

We use UAVSAR interferograms to characterize fault slip, triggered by the Mw 7.2 El Mayor-Cucapah earthquake on the southernmost San Andreas Fault in the Coachella Valley providing comprehensive maps of landscape change that complement in situ measurements. Creepmeters and geological mapping of fault offsets on Durmid Hill recorded 4 mm and 8 mm of average triggered slip respectively on the fault, in contrast to radar views that reveal significant off-fault dextral deformation averaging 20 mm. Unlike slip in previous triggered slip events on the southernmost San Andreas fault, dextral shear in 2010 is not confined to transpressional hills in the Coachella valley. Edge detection and gradient estimation applied to the 50-m-sampled interferogram data identify the location (to 20 m) and local strike (to < 4°) of secondary surface ruptures. Transverse curve fitting applied to these local detections provides local estimates of the radar-projected dextral slip and a parameter indicating the transverse width of the slip, which we equate with the depth of subsurface shear. These estimates are partially validated by fault-transverse interferogram profiles generated using the web-based UAVSAR tool of GeoGateway, and appear consistent for radar-projected slip greater than about 5 mm. An unexpected finding is that creep and triggered slip on the San Andreas fault terminate in the shallow subsurface below a surface shear zone that resists the simple expression of aseismic fault slip. We introduce the notion of a surface locking depth above which fault slip is manifest as distributed shear, and evaluate its depth as 6-27 m.

To understand long term variability of solar activity, homogeneous time series are required. However, proxies like the Zurich sunspot number or cosmogenic isotopes suffer from discontinuities. Naked eye observations of aurorae, however, might be used to bridge discontinuities in solar activity indices in order to approach a homogeneous solar activity record. With information derived from aurora observations like observing site, time of aurora sighting and position on sky we can reconstruct the auroral oval. Since aurorae are correlated with geomagnetic indices like the Kp index, it is possible to obtain information about the terrestrial magnetic field in the form of the position of the magnetic poles as well as the magnetic disturbance level. \\ Here we present a Bayesian approach to reconstruct the auroral oval from ground-based observations by using two different auroral oval models. With this method we can estimate the position of the magnetic poles in corrected geomagnetic coordinates as well as the Kp index. The method is first validated on synthetic observations before it is applied to four modern geomagnetic storms between 2003 and 2017 where ground-based reports and photographs were used to obtain the necessary information. We have shown that we are able the reconstruct the pole location with an accuracy of $\approx 2^{\circ}$ in latitude and $\approx 11^{\circ}$ in longitude. The Kp index can be inferred with a precision of one class. \\ The future goal is to employ the method to historical observations.

The Indian Ocean Geoid Low (IOGL) appears as a prominent feature if the geoid is, as usual, shown with respect to the Earth’s reference shape. However, if it is shown relative to hydrostatic equilibrium, i.e. including excess flattening, it appears as merely a regional low on a north-south trending belt of low geoid. For a mantle viscosity structure with an increase of 2-3 orders of magnitude from asthenosphere to lower mantle, which is suitable to explain the long-wavelength geoid, a geoid low can result from both positive density anomalies in the upper mantle and negative anomalies in the lower mantle. Here we propose that the IOGL can be explained due to a linear, approximately north-south-trending high-density anomaly in the lower mantle, which is crossed by a linear, approximately West-Southwest-East-Northeast trending anomaly low-density anomaly in the upper mantle. While the former can be explained due to its location in a region of former subduction and inbetween the two Large Low Shear Velocity Provinces (LLSVPs), we propose here that the latter is due to an eastward outflow from the Kenya plume rising above the eastern edge of the African LLSVP. We show that, with realistic assumptions we can approximately match the size, shape and magnitude of the geoid low.

South China(SC) is characterized by large-area multistage magmatism.There are five large-scale metallogenic belts in SC, multiple world-class deposits have been discovered, showing great prospecting potential. What led to the difference in the type and metal association of the deposits? What controls the distribution of the different types of metallogenic belts? Where can we find new deposits? To address these concerns, it is necessary to consider the metallogenic factors based on mineral system. Firstly,the satellite gravity was converted into Bouguer gravity under spherical coordinates. Then the reduction-to-the pole (RTP) magnetic anomalies in SC were obtained using the moving window with different geomagnetic parameter respectively.Further to that, inversion of gravity and magnetic data was applied to calculate the vertical lithospheric interfaces,and then the possible metallogenic source zones of the five metallogenic belts were analyzed. The distribution of main faults were determined and the boundaries among Yangtze Block (YB), Cathaysia Block (CB) and Jiangnan Orogenic belt (JNO) were redefined by multiscale edge detection of gravity and magnetic data,then the ore-forming pathways in the main metallogenic belts were explored. 3D spatial distribution of intrusions qualitatively identified by inverted susceptibility and density model , and hence the depositing site of Cu, Fe, Au, W and Sn deposits were inferred. The metallogenic source zones, pathways, and sites of the deposits of the mineral system in SC were qualitatively identified according to the gravity and magnetic data analysis , providing indications for future prospecting exploration in SC.

In this study, we revisit the role of curvature in modifying frontal stability. We first consider the statement “fq < 0 implies potential for instability”, where f is the Coriolis parameter and q is the Ertel potential vorticity (PV). This is true for any inviscid baroclinic flow. It is also evident in the transition of a governing equation for circulation within a front from elliptic to hyperbolic form as the discriminant changes sign. However, for curved fronts, an additional scale factor enters the discriminant owing to conservation of absolute angular momentum, L, leading to Solberg’s (1936) generalization of the Rayleigh criterion. In non-dimensional form, this expression also generalizes the classical instability criterion of Hoskins (1974) by accounting for centrifugal forces: modification of the front’s vertical shear and stratification owing to curvature tilts the absolute vorticity vector away from its thermal wind state and, in an effort to conserve the product of non-dimensional PV (q’) and absolute angular momentum (L’), this alters Rossby and Richardson numbers permitted for stable flow. The criterion, Φ’=L’q’ < 0, is then investigated in non-dimensional parameter space representative of low-Richardson-number vortices. An interesting outcome is that, for Richardson numbers near one, anticyclonic flows increase in q’, while cyclonic flows decrease in q’. Though stabilization is muted for anticyclones (owing to multiplication by L’), the de-stabilization of cyclones is robust, and may help to explain an observed asymmetry in the distribution of submesoscale coherent vortices in the global ocean.