The significant wave height (SWH) is of great importance in industries such as ocean engineering, marine resource development, shipping and transportation. Haiyang-2C (HY-2C), the 2nd operational satellite of China’s marine dynamic exploration series, can provide all-weather, all-day, global observations of wave height, wind, and temperature. The altimeter can only measure the nadir wave height and other information, and the scatterometer can obtain the wind field with a wide swath. In this paper, a deep learning approach is applied to produce a wide swath SWH data through the wind field from the scatterometer and the nadir wave height from altimeter. Two validation sets, 1-month data at 6-minute intervals and 1-day data with an interval of 10 s, are fed into the trained model. Experiments indicate that the extending nadir SWH yields a real-time wide swath grid product along track, which can be offered as support for oceanographic study, and it is superior to take the swell characteristics of ERA5 into account as the input of wide swath SWH model. In conclusion, the verification results demonstrate the effectiveness and feasibility of the wide swath SWH model.

The Earth’s mantle transition zone (MTZ) plays a key role in the thermal and compositional interactions between the upper and lower mantle. Seismic anisotropy provides useful information about mantle deformation and dynamics across the MTZ. However, seismic anisotropy in the MTZ is difficult to obtain from surface wave or shear wave splitting measurements. Here, we investigate the sensitivity to anisotropy of a body wave method, SS precursors, through 3-D synthetic modeling. Our study shows that the SS precursors can distinguish the anisotropy originating from three depths: shallow upper mantle (80-220 km), deep upper mantle above 410-km, and MTZ (410-660 km). Synthetic resolution tests indicate that SS precursors can resolve 3% azimuthal anisotropy where data have an average signal to noise ratio (SNR=7) when azimuthal coverage is sufficient. To investigate regional sensitivity, we apply the stacking and inversion methods to two densely sampled areas: Japan subduction zone and a central Pacific region around the Hawaiian hotspot. We find evidence for a trench-perpendicular fast direction (Θ=87°) of MTZ anisotropy in Japan, but the strength of anisotropy is poorly constrained due to limited azimuthal coverage. We attribute the azimuthal anisotropy to lattice-preferred orientation of wadsleyite induced by trench-parallel mantle flow near the stagnant slab. In the central Pacific study region, there is a non-detection of MTZ anisotropy, although modeling suggests the data coverage should allow us to resolve up to 3% anisotropy. Therefore, the Hawaiian mantle plume does not produce detectable azimuthal anisotropy in the MTZ.

Ocean sediment records document abrupt changes in glacial-to-deglacial circulation and mixing of the ocean, recorded as changes in 14C reservoir ages of surface waters. Here we present 14C-based high-resolution age records of four sediment cores derived by means of 14C plateau tuning. This provides a detailed and precise stratigraphic correlation between the western and eastern South Pacific and paleoclimate records of Antarctic ice cores as well as 14C reservoir ages. The accuracy and precision of plateau tuning are confirmed in two sediment cores off Chile; in one core by independent land-based age control of four tephra layers, in a second core by a suite of glacial sediment varves. During glacial times, high reservoir ages reaching up to ~1500 yr may reflect seasonal sea ice and/or a melt water lid at high latitudes both east of New Zealand and off southern Chile and may be linked to northward advection of upwelled old subsurface waters from the Polar Frontal Zone. Our results support the model of a bipolar seesaw at the onset of rapid deglacial Antarctic warming, moreover, they show that the Antarctic Cold Reversal immediately preceded the onset of the Younger Dryas cold spell.

• The energy sector is intertwined with water, food, public health, and gender matters. Hence a nexus perspective increases understanding of these interdependencies, enhancing efficiency, balancing trade-offs, building synergies, and improving governance. Energy helps to achieve secure and equal access to productive resources and inputs, helps to sustain food production systems, and helps to boost investment in rural infrastructure and technology. It also facilitates access to safe drinking water and sanitation, improvement of water quality, and expansion of wastewater treatment. Energy can help reduce death and illness from air, water, and soil pollution and contamination. It can also support women’s equal rights to economic and natural resources, enhance use of enabling technology, and help prevent violence against women and girls in public and private places. • The three objectives of Sustainable Energy for All (SE4All) are closely interwoven into the four nexus areas-water, food, health, and gender. Providing universal access to modern energy services, increasing the share of renewable energy (RE), and improving energy efficiency will greatly influence them. • The SE4All objectives generate multiple nexus opportunities and challenges. Water security may be increased if water-related risks are managed well and contamination risks minimized. Similarly, food security may improve, and RE sources may help decouple food prices from energy prices, while managing production of energy crops. Global health may improve further as efforts focus on reducing air pollution and strengthening health services delivery. Finally, gender equality can be enhanced as time poverty decreases through better energy services and as women participate more actively in the energy value chain. • Although existing data capture part of the nexus approach , improvements are needed in all four sectors to accurately monitor intersectoral impacts, supporting policymakers in developing integrated policies.

The first demonstration of rocket exhaust driven amplification (REDA) of whistler mode waves occurred on 26 May 2020 by transferring energy from pickup ions in a rocket exhaust plume to EM waves. The source of coherent VLF waves was the Navy NML Transmitter at 25.2 kHz located in LaMoure, North Dakota. The topside ionosphere at 480 km altitude became an amplifying medium with a 60 second firing of the Cygnus BT-4 engine. The rocket engine injected exhaust as a neutral cloud moving perpendicular to field lines that connected the NML transmitter to the VLF Radio Receiver Instrument (RRI) on e-POP/SWARM-E. Charge exchange between the ambient O+ ions and the hypersonic water molecules in the exhaust produced H2O+ ions in a ring-beam velocity distribution. The 25.2 kHz VLF signal from NML was amplified by 30 dB for a period 77 seconds as observed by the RRI. Simultaneously, preexisting coherent ELF waves at 300 Hz were amplified by 50 dB during and after the Cygnus burn. Extremely strong coherent emissions and quasi-periodic bursts in the 300 to 310 Hz frequency range lasted for 200 seconds after the release. The excitation of an ELF whistler cavity may have lasted even longer, but the orbit of the SWARM-E/e-POP moved the RRI sensor away from the wave emission region. The amplified 300 Hz ELF waves may have gained even more energy by cyclotron resonance with radiation belt electrons as they were ducted between geomagnetic-conjugate hemispheres.

Gas hydrates have been reported to exist in marine sediments from various parts of the world ocean. The hydrates start decomposing soon after recovery of the sediments through coring operations due to changes in ambient pressure and temperature. This decomposition leads to changes in sedimentary structures, and thus complicates physical property related measurements of the sediments by conventional methods. In this study, we used a medical X-ray CT scanner to quickly scan the recovered cores, and then used raw data from the CT, and thus avoided image processing steps, to estimate porosity and density of the sediments. The raw data were in terms of CT numbers, which were obtained by drawing a circular region of interest (ROI) to cover most of the sediments visible in a cross section XCT image of the sediments. The data were weighted for relative contribution of liquid and solid in sediments before estimating porosity. On the other hand, density was estimated by using an average CT number that was automatically calculated by the Osirix software used for drawing the ROI on an XCT image, and by using a calibration equation based on a set of standards. Although some uncertainty in estimation of relative volumes of solid, liquid and gas could not be avoided, the results obtained by this new procedure were in good agreement with those obtained by conventional methods. Since porosity and density estimates by the new procedure can be made in a matter of minutes after core recovery, it can guide progress of coring operation and further processing of hydrate-bearing sediments.

The shape of earthquake source spectra, traditionally fit by physics-based models, contains important parameters to constrain rupture dimension, duration, and geometry. Here we apply machine learning (ML) to derive single-variable and double-variable data-driven models of source spectra from 3675 Mw>5.5 global earthquakes, assuming that the Fourier transform of source time functions well represent earthquake source spectra below 1 Hz. The single-variable ML model, in the same degree of freedom as the Brune model, improves the goodness of fit by 8.5%. Specifically, the ML model fits the data without systematic bias, whereas the Brune model tends to underestimate at intermediate frequencies and overestimate at high frequencies. The latter discrepancy cannot be modelled by increasing the fall-off exponent in the Brune-type or the Boatwright-type models. The double-variable ML model is compared to existing double-corner-frequency models and is found to capture the second-order features such as the subtle curvature differences around the corner. Our results demonstrate that unsupervised machine learning can extract hidden global characteristics of high-dimensional data and provide observational evidence to amend existing physical models.

Rupture directivity and its potential frequency dependence is an open issue within the seismological community, especially for small-to-moderate events. Here we provide a statistical overview based on empirical evidence of seismological observations, thanks to the large amount of high-quality seismic recordings (more than 30’000 waveforms) from Central Italy, which represents an excellent and almost unique natural laboratory of normal faulting earthquakes in the magnitude range of 3.4 and 6.5 within the time frame 2008-2018. In order to detect an anisotropic distribution of ground motion amplitudes due to the rupture directivity, we fit the smoothed Fourier Amplitude Spectra (FAS) cleared of source-, site- and path- effects. According to our criteria, about 36% of the analyzed events (162 out of 456) are directive and the distribution of rupture direction is aligned with the strikes of the major faults of the Central Apennines. We find that the directivity is strongest, up to approximately 5 times the event’s corner frequencies. The results of this research provide useful insights to parameterize directivity as a frequency-dependent band-limited phenomenon, to be explicitly implemented in future ground motion modeling and scenario predictions.

During the mid-Holocene (MH, 6,000 years BP), precessional forcing drove enhanced monsoon rainfall, expanded vegetation cover, and reduced dust emissions throughout the African Sahara. The orbital forcing and feedback of vegetation albedo have been widely studied with climate models, but are found to be insufficient to explain the magnitude and location of rainfall anomalies suggested from proxy reconstructions. The feedback of reduced Saharan dust loading has been less-studied because Paleoclimate Modelling Intercomparison Project (PMIP) Phase 2/3 models did not incorporate the decreased MH Saharan dust emissions. Several recent modeling studies investigated the MH Saharan hydroclimate response to reduced dust loading; however, their models only resolved the direct effect from dust aerosols (i.e. direct radiative forcing), which leaves the contribution from indirect dust aerosol effects (i.e. dust aerosol-cloud interactions) largely unknown. Here we investigate the hydroclimate response due to Saharan dust using CESM CAM5-chem, which includes both the direct and indirect dust aerosol effects. In the simulations, reduced Saharan dust directly increases monsoon season (JJAS) net shortwave radiative flux at the surface, which drives continental warming. Convective clouds and convective precipitation are subsequently enhanced and, due to the overwhelming convective nature of this monsoonal region, total Saharan (20–31°N, 20°W–30°E) precipitation increases by 11.9%. However, indirect dust aerosol effects counteract the increase from convection precipitation. A reduction in Saharan dust decreases cloud nuclei number concentration and increases cloud droplet size, which in turn reduces stratus cloud cover and large-scale stable rainfall. Overall, the decrease in large-scale stable rainfall due to indirect dust effects reduces total precipitation by 12.5%. The total rainfall increase of 0.27 mm/day from reduced dust is significant but smaller than the response to changes in vegetation cover (1.19 mm/day). While these results indicate that less Saharan dust during the MH likely enhanced Saharan rainfall, they also suggest that a reduction in the indirect effects of dust likely dampened the overall response of rainfall to the MH dust forcing.

Induced seismicity due to fluid injection, including hydraulic fracturing, is an increasingly common phenomenon worldwide. Yet, the mechanisms by which hydraulic fracturing causes fault activation remain unclear. Here we show that pre-existing fracture networks are instrumental in transferring fluid pressures to larger faults on which dynamic rupture occurs. To date, studies of hydraulic fracturing-induced seismicity have used observations from regional seismograph networks at distances of 10's km, and as such lack the resolution to answer some of the key questions currently in the field. A high-quality dataset acquired at a hydraulic fracturing site in Alberta, Canada that experienced several events over MW 2.0 is presented for the purpose of analysing detailed mechanisms of fault activation. Both event hypocentres and measurements of seismic anisotropy reveal the presence of pre-existing fracture corridors that allowed communication of fluid-pressure perturbations to larger faults, over distances of up to a km or more. The presence of pre-existing permeable fracture networks can significantly increase the volume of rock affected by the pore pressure pulse, thereby increasing the probability of induced seismicity. This study demonstrates the importance of understanding the connectivity of pre-existing fracture networks as a tool for assessing potential seismic hazards associated with hydraulic fracturing of shale formations, and offers a conceptual understanding of induced seismicity due to hydraulic fracturing.

Linear elastic fracture mechanics (LEFM) suggests that short-lived flow accelerations, such as the one observed in the 2006 Byrd Glacier, East Antarctica, subglacial flooding event, can initiate abnormally large basal crevasses at the grounding line. Airborne radar measurements acquired in 2011 reveal hundreds of basal crevasses ranging in height ~40—335 m. Particle tracking results show that the formation of the largest basal crevasse occurred at the grounding line during the 2006 flooding event. Very large basal crevasses form distinctive surface depressions directly overhead, which are observed along the Byrd Glacier flowline to the terminus of the Ross Ice Shelf. By using these surface depressions as proxy for abnormally large basal crevasses, we create a timeline of past subglacial flooding events on Byrd Glacier. Understanding the frequency of flooding events and their effect on glacier dynamics will help inform subglacial hydrology models and models of ice sheet stability.

The magnetopause standoff distance characterizes global magnetospheric compression and deformation in response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation. We cannot derive this parameter from in-situ spacecraft measurements. However, time-series of the magnetopause standoff distance can be obtained in the near future using observations by soft X-ray imagers. In two companion papers, we describe methods of finding the standoff distance from X-ray images. In Part 1, we present the results of MHD simulations which we use for the calculation of the X-ray emissivity in the magnetosheath and cusps. Some MHD models predict relatively high density in the magnetosphere, larger than observed in the data. Correcting this, we develop magnetospheric masking methods to separate the magnetosphere from the magnetosheath and cusps. We simulate the X-ray emissivity in the magnetosheath for different solar wind conditions and dipole tilts.

Estuaries are dynamic coastal features that support industry, food production, and recreation, and provide habitat for numerous animal species. Their typically low surface gradients make estuaries vulnerable to sea level rise, storms, and high river water discharge. This vulnerability combined with the large number of people who often live near estuaries has led to increasing efforts over recent decades to improve our understanding of how to minimize flooding and protect people and property. Despite these efforts, however, we still lack the tools to quantify the relationship between changes in estuarine morphology and flood risks. In particular, the interplay between bathymetric changes and water levels during storm conditions remains poorly quantified. To address this knowledge gap, we present a general enthalpy framework for modeling the evolution of estuaries that couples a low gradient subaerial topset and a subaqueous offshore region or foreset. Sediment transport in both the subaerial and subaqueous domains includes a non-linear term that relates sediment flux, local slope, and a threshold of motion. With this approach, we describe the evolution of the bathymetric profile and sediment partitioning between topset and foreset under a range of sea-level variations scenarios. We find that in some cases upstream sections of the topset can undergo erosion during periods of sea-level rise and deposition during sea-level fall, contradicting traditional stratigraphic models. These counterintuitive bathymetric changes could potentially lead to shifts in the location of maximum water levels along the estuary not accounted for by models of storm inundation.

A document by Grace Guryan. Click on the document to view its contents.

Using a three-dimensional coupled physical-biological model, this paper explores the creation of phytoplankton blooms around tropical islands in the presence of ambient currents and short-lived (~4 days) wind events. The ambient flow creates a retention zone of weak flows in the lee of the island, which is a typical feature of island wakes. Findings reveal that wind-induced upwelling effects are essential for the initial nutrient enrichment and phytoplankton growth that occur mainly in this retention zone. Oscillating flow, typical of island wakes, occasionally releases mesoscale patches of upwelled water and its phytoplankton load into the ambient ocean. The phytoplankton continues to grow within floating structures that are of up to 20 km in diameter. This mechanism complements the plankton growth associated with the formation of mesoscale eddies.

High-resolution sea surface temperature (SST) estimates are dependent on satellite-based infrared radiometers, which are proven to be highly accurate in the past decades. However, the presence of clouds is a big stumbling block when physical approaches are used to derive SST. This problem is more prominent across tropical regions such as Arabian Sea(AS) and Bay of Bengal(BoB), restricting the availability of high-resolution SST data for ocean applications. The previous studies for developing daily high-resolution cloud-free SST products mainly focus on fusion of multiple satellites and in-situ data products that are computationally expensive and often time consuming. At the same time, it was observed that the capabilities of data-driven approaches are not yet fully explored in the estimation of cloud-free high-resolution SST data. Hence, in this study an attempt has been made for the first time to estimate daily cloud free SST from a single sensor (MODIS Aqua) dataset using advanced machine learning techniques. Here, three distinct machine learning techniques such as Artificial Neural Networks (ANN), Support Vector Regression (SVR) and Random Forest (RF)-based algorithms were developed and evaluated over two different study areas within the AS and BoB using 10 years of MODIS data and in-situ reference data. Among the developed algorithms, the SVR-based algorithm performs consistently better. In AS region, while testing, the SVR-based SST estimates was able to achieve an adjusted coefficient of determination (R_adj^2) of 0.82 and root mean square error (RMSE) of 0.71°C with respect to the in situ data. Similarly, in BoB too, the SVR algorithm outperforms the other algorithms with R_adj^2 of 0.78 with RMSE of 0.88ºC. Further, a spatio-temporal and visual analysis of the results as well as an inter-comparision with NOAA AVHRR daily optimally interpolated global SST (a standard SST product available in practice) the suggest that the proposed SVR-based algorithm has huge potential to produce operational high-resolution cloud-free SST estimates, even if there is cloud cover in the image.

Magnetic reconnection occurs in turbulent plasmas like shock transition regions, while its exact role in energy dissipation therein is not yet clear. We perform a 2D particle-in-cell simulation for foreshock waves and study electron heating associated with reconnection. The probability distribution of Te exhibits a shift to higher values near reconnection X-lines compared to elsewhere. By examining the Te evolution using the superposed epoch analysis, we find that Te is higher in reconnection than in non-reconnecting current sheets, and Te increases over the ion cyclotron time scale. The heating rate of Te is 10%-40% miVA2, where VA is the average ion Alfvén speed in reconnection regions, which demonstrates the importance of reconnection in heating electrons. We further investigate the bulk electron energization mechanisms by decomposing under guiding center approximations. Around the reconnection onset, E|| dominates the total energization partly contributed by electron holes, and the perpendicular energization is dominant by the magnetization term associated with the gyro-motion in the inhomogeneous fields. The Fermi mechanism contributes negative energization at early time mainly due to the Hall effect, and later the outflow in the reconnection plane contributes more dominant positive values. After a couple of ion cyclotron periods from reconnection onset, the Fermi mechanism dominates the energization. A critical factor for initiating reconnection is to drive current sheets to the de-scale thickness. The reconnection structures can be complicated due to flows originated from the ion-scale waves, and interactions between multiple reconnection sites. These features may assist future analysis of observation data.

Quantifying sector-resolved methane fluxes in complex emissions environments is challenging yet necessary to improve emissions inventories and guide policy.  Here, we separate energy and agriculture sector emissions using a dynamic linear model analysis of methane, ethane, and ammonia data measured at a Northern Colorado site from November 2021 to January 2022. By combining these sector-apportioned observations with spatially resolved inventories and Bayesian inverse methods, energy and agriculture methane fluxes are optimized across the study’s ~850 km2 sensitivity area. Energy sector fluxes are synthesized with previous literature to evaluate trends in energy-sector methane emissions. Optimized agriculture fluxes in the study area were 3× larger than inventory estimates; we demonstrate this discrepancy is consistent with differences in the modeled vs. real-world spatial distribution of agricultural sources. These results highlight how sector-apportioned methane observations can yield multi-sector inventory optimizations in complex environments.