Changes in the thermospheric wind originating in storm-time transients in high-latitude Joule heating and ion circulation are effective in modifying conditions throughout Earth’s upper atmosphere and ionosphere. Among the effects these drivers can produce are large-scale gravity waves (GWs), characterized by significant wind transients that propagate away from the auroral zone, driving transient ion motion during their 1-2 hour passage. Longer period changes in mean winds can develop over the following hours to days, depending on the duration and magnitude of the high latitude heating, and also extend globally. The effectiveness of these processes in modifying the mean density of the daytime ionosphere likely depends on the extent to which these disturbances reach the daytime equatorial region and downward into the E-region wind dynamo (below $\sim$180 km). A study of a month of observations made during the ICON mission reveals the variety of behaviors with both transient effects and longer-term changes in mean winds. The duration of auroral inputs, as opposed to the average input over time, is identified as important to the development of dynamo-modifying zonal disturbance winds. During geomagnetic disturbances, we find that the predictive capability of a general circulation model (TIEGCM) for meridional wind transport is good (R$>$.8) while the storm-time zonal wind transport is harder to predict (R$>$.5). This study is the first of its kind, measuring winds and storm responses continously for a month in both the daytime E- and F- regions simultaneously with $\sim$97 minute cadence.

We investigate details of the interaction of subaqueous barchans with dune-size obstacles by carrying out numerical simulations where the fluid is solved at the grain scale and the motions of individual grains are computed at all time steps. With the outputs, we analyze the disturbances of the fluid flow, the trajectories of grains, and the resultant force on each grain, the latter being unfeasible from experiments and field measurements. We show that in some cases particles pass over the obstacle, while in others they completely circumvent it (without touching it), or are even blocked. For the circumvention and blocking cases, which we call bypass and trapped, respectively, we show the existence of a strong vortex between the lee face of the dune and the obstacle. This vortex results from the interactions of recirculation regions and horseshoe vortices, and has enough strength to deviate the main flow and carry grains around the obstacle in those cases. Our results shed light on the reasons for passing over, circumventing, and blocking, and contribute to our understanding of dunes in the presence of large obstacles such as hills, crater rims, and human constructions.

We resolve the low-frequency earthquake (LFE) activity within tremor from a compact area beneath southern Vancouver Island. Using LFE templates made from stacking thousands of nearly co-located LFEs as empirical Green’s functions, we detect LFEs using time-domain iterative deconvolution of the ”optimal” horizontal component (the dominant particle motion direction) of tremor velocity seismograms. The deconvolution is guided by the correlation between seismic stations. During identified tremor bursts, our 3-station catalog yields more than one detection per second. 60% of these are validated at a fourth station, but judging from the consistency of their migration patterns, many of those rejected are also legitimate. Waveforms predicted from these detections simultaneously reduce the residual on the unused vertical and ”orthogonal” horizontal components of the seismograms. The unresolved portions of the seismograms are likely times of significant tremor activity outside the target area. Deconvolution reveals clear LFE migrations with speeds near 5-6 m/s during 20% of the bursts, consistent with contemporaneous 4-s tremor detections in the same region. Given the number of consecutive seismogram peaks with detections, it is doubtful that each detection represents just one LFE. More likely, tremor is usually saturated in time with LFEs that are on average separated by less than the characteristic LFE duration. Such time saturation is consistent with stochastic models of tremor generation designed to explain tremor spectra, and also disguises the real number of LFEs within tremor, making it difficult to constrain the seismic moment and duration of individual LFEs.

The Magnetospheric Multiscale (MMS) mission is a groundbreaking mission that provides data of unprecedented quality. During the extended phase, an “unbiased campaign’ in the terrestrial magnetosheath was planned, to collect data in the turbulent magnetosheath with a uniform coverage never attained before. The strategy, to collect 3 minutes of high-resolution burst data every 9 minutes, provides an “unsupervised’ selection of data containing the first homogeneous sampling of the magnetosheath. This provides a first opportunity to study this environment broadly and without selection bias. We present an overview of properties observed in this data set that can be further exploited in numerous ways.

A document by Tianning Su. Click on the document to view its contents.

Sulfate burden over the North Atlantic (NATL) exhibits strong seasonality despite no seasonality in anthropogenic sulfur dioxide (SO2) emissions. However, the seasonality of sulfate aerosols over NATL has decreased over the past five decades, likely due to a reduction in the United States (U.S.) SO2 emissions following the Clean Air Act of 1976. We performed atmospheric chemistry and transport model simulations to assess the impact of changing U.S. SO2 emissions between 1970 and 2010 on NATL sulfate burden and radiative forcing. U.S. SO2 emission reductions weakened the North Atlantic sulfate burden’s seasonality by ~20%, primarily due to decreased chemical production and transport in summer. These emission reductions caused a summertime radiative forcing (~2 Wm-2) twice as large as the wintertime forcing. Our findings highlight the complex, season-dependent responses of sulfate burden and radiative effects to regional emission changes.

A document by Jose Roberto Miranda. Click on the document to view its contents.

Accurate characterization of surface meteorological distributions over coastal areas and complex terrain, especially the relationship between temperature and altitude, is essential for simulating snowpack dynamics. This is challenging at spatial resolutions smaller than common gridded meteorological datasets (e.g., resolutions smaller than 5 to 250 km) due to sparse long-term temperature measurements at those resolutions and local factors like cool air pooling and inversions. Near-surface air temperatures (Ta) are often assumed to decrease with elevation at a constant rate of 6.5°C km-1, leading to significant model errors in snow evolution and other key processes. This study evaluated the impact of local dynamical adjustments to downscaled Ta on snow simulations over two coastal mountainous terrains using the Noah-MultiParameterization land surface model. Forcings were derived from remote sensing and reanalysis precipitation products and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) atmospheric products at the downscaled 1-km resolution. Hourly lapse rates at each grid cell were calculated by applying linear regression to Ta and elevation from neighbor grids (one grid length in the x or y direction) at the native MERRA-2 resolution and applied to the downscaled 1-km Ta product. We assessed the impact on simulated snow cover and depth across simulations forced with the downscaled Ta (1) without lapse rate correction, (2) corrected with a static lapse rate (6.5°C km-1), and (3) corrected with the dynamic hourly lapse rate. We evaluated model skill improvement with dynamic or static lapse rate correction, and no correction against satellite-derived products. Both lapse rate correction methods led to similar improvements on average, relative to no correction. However, dynamic lapse rate correction showed more pronounced improvements in simulating perennial snowpacks at mid-elevations and in deficit years, indicating the method can better resolve heterogeneous snowpack conditions that are key for water resource management.

From maintaining biodiversity to protecting coastlines, mangroves are crucial to the environment. However, due to increasing water pollution from humans, mangrove species have suffered significantly. In 2021, 14 out of 70 mangrove plant species were classified as endangered to different degrees in China (Fu et al., 2021). Heavy metals, like cadmium, and lead are extremely harmful to mangroves (Angulo-Bejarano, Puente-Rivera and Rocío Cruz-Ortega, 2021). The metals contain malondialdehyde compounds that cause stress to the plants resulting in increased mortality, inhibition of photosynthesis and growth (Nguyen et al., 2020). Heavy metal resistance bacteria can better utilise the metals in the environment to improve plant growth (Wu et al., 2018). This can be done as some plant growth promoting bacteria have characteristics like the production of indole-3-acetic acid and siderophores, nitrogen fixation and others (Derya Efe, 2020). Thus, different levels of heavy metal resistance bacteria in the water near mangroves may be able to help the growth. Water samples were collected from different locations in Hong Kong near mangrove growth. The samples were diluted into different concentrations and spread onto different functional plates and further tested on heavy metal resistance. The water samples were also sent to ALS company for testing heavy metals, especially: mercury, cadmium, manganese, lead, and copper. The amount of heavy metal in water samples will be compared against isolated bacteria that have heavy metal resistance. This will give us an idea of the effect of pollution on plants. Heavy metals are only one aspect of it. Although the environment is adapting and finding ways to cope with the changes, it is vital for humans to recognise the amount of damage caused and to save planet Earth. 

Seamounts, generally formed by volcanic activity, play a crucial role in marine ecosystems, ocean circulation, and plate tectonics. Cataloguing the world´s seamounts has usually relied on analysing vertical gravity gradient (VGG) data, in which edifices smaller than 2 km generally produce no signal, leaving a significant gap in our understanding of ocean floor topography. Most of the seamounts identified in VGG data have been picked by hand, in view of the >40.000 features presently identified, a very time-consuming process. With the Seabed 2030 initiative making ever-increasing amounts of multibeam data publicly accessible, it has become extremely important to leverage this detailed bathymetry data for seamount detection and combine it with computer-aided detection methods. We present a novel framework that automatically detects and catalogs seamounts in multibeam data, enhancing comprehensive mapping of seamount distribution across a range of edifice sizes.Our framework initially segments the multibeam data into 128x128 sized images, allowing it to manage large datasets. It then uses Convolutional Neural Networks (CNNs) to calculate feature vectors. These vectors are used to cluster segmented images, distinguishing flat seafloor areas from those with potential seamounts. Potential summits are flagged and then evaluated by calculating features such as slope, shape, and summit area, resulting in a detailed catalog of seamounts with information on their characteristics and sizes.The framework´s capability to automatically scan large datasets in a short time enhances efficiency of seamount detection. The framework is also extendable, allowing additional seafloor features, such as ridges or trenches, to be included. It holds significant potential for improving our understanding of ocean floor topography and seamount distribution and for analysing the terabytes of bathymetric data held in international repositories.The resulting catalogues allow us, among others, to address questions of the diverse causes of magmatism in the ocean basins, potentially quantify the influence of seamounts on deep ocean mixing and provide important fundamental data on the distribution of habitat types on the deep sea.

Each year, Earth experiences new record-breaking temperatures, highlighting the urgent need to transition to less carbon-intensive energy systems and expand carbon storage operations in the subsurface. Shales and tight formations stand out as a crucial player in large scale storage operations and as a source for low-carbon energy carriers such as methane

A document by Tasfia Tasnim. Click on the document to view its contents.

Airborne maritime lidars are widely used for measuring coastal bathymetry. However, these lidars require manned aircraft for operation and are expensive to build and field. Additionally, Alaska’s remoteness, inclement weather, and limited personnel capacity provide unique challenges to data gathering with traditional maritime lidar not seen in the contiguous United States. Droneborne maritime lidar is a promising solution to address these challenges and enhance the data gathering capability in the Arctic.Here, we report on the ongoing development of a droneborne maritime lidar at the University of Alaska-Fairbanks (UAF) Geophysical Institute. This lidar is designed to fly on a fixed-wing unmanned aerial vehicle (UAV) owned by the Alaska Center for Unmanned Aerial System Integration. This UAV has a 25 m/s cruise speed and a flight endurance of 900 km. The current status of the design will be reported, as well as modeling results showing the signal-to-noise ratio and expected depth performance. We also determine the optimal spot diameter for bathymetric profiling in Alaskan waters where this system will be fielded.

Soil inorganic carbon (SIC) constitutes a major carbon (C) source on Earth, playing a crucial role in CO2 sequestration and climate regulation. While plant growth and microbial activity primarily influence the soil organic C (SOC) pool through the release of dissolved organic C (DOC), their indirect effects on dissolved inorganic C (DIC), and SIC, require further exploration. This study investigates the impact of plant growth on DIC and SIC dynamics in a carbonate-poor soil planted with either C3 (Silphium perfoliatum L.) or C4 (Zea mays L.) plants. Lysimeter leachates were analysed to assess DIC and DOC concentrations, pH, CO2 efflux, and δ13C isotopes over two weeks under varying drought and irrigation conditions. Findings revealed significantly higher DIC concentrations compared to DOC in leachates of both plant types, alongside increased CO2 efflux and pH, indicative of increased root respiration dynamics. Interestingly, the δ13C values of DOC were nearly uniform across C3 and C4 plots (-29 ± 0.7‰), while DIC values displayed greater variability, ranging from ~-7 to -20‰. A mass balance approach further identified that C4 plant contributions could account for up to ~62% of the DIC pool. These results challenge the traditional viewpoint that plant growth primarily influences the DOC rather than the DIC pool, thus, underscoring the role of root and rhizomicrobial respiration in enhancing DIC contributions and the dynamics of soil inorganic C. These new insights into the complex interactions between plant growth, microbial activity, and soil inorganic carbon, emphasize their importance in climate change mitigation strategies.

A document by DARSHAN MEHTA. Click on the document to view its contents.

This study characterizes the changes produced by tropical cyclones (TCs) over the North West shelf of Australia on the ocean structure and ocean thermal energy budget using a 20-year composite of cyclone data (1996-2016) created from Bluelink ReANalysis data (BRAN). Part 2 focuses on assessing the effects of season and TC intensity and translation speed on the development of temperature anomalies and the associated ocean heat content (OHC) changes. Stronger cold anomalies develop at the surface over locations with a shallow barrier layer, for strong and slow-moving TCs. The period of the year influences the recovery of the surface anomalies, which happens faster between December and February. The warm anomalies in the subsurface are stronger for more intense TCs and over locations with a shallow barrier layer, as the vertical mixing processes are more efficient. During the passage of the TC the majority of the OHC losses are located beneath the TC core and in the surface layer, while the OHC increases in the subsurface layer between 500 and 1000 km from the TC centre. When the temperature anomalies start to recover, the OHC increases at a stronger rate in the surface layer due to the air-sea heat fluxes and in the TC core region where the strong upwelling relaxes to downwelling. A month after the TC passage there is an overall increase in the OHC of the region after strong TCs and TCs that happen later in the season, while weak TCs cause an overall decrease in the OHC.

INTRODUCTIONThe mesozooplankton community represents an important link in energy transfer from lower to higher trophic levels in the marine environment, both as grazers of primary producers and as a food source for a variety of consumers from pelagic forage fish to baleen whales. Therefore, observing and assessing changes in mesozooplankton diversity and biomass provides a means for understanding broader changes in marine ecosystems and informing management decisions. The Gulf of Maine is a semi-enclosed shelf sea within the broader North Atlantic biome (Pershing and Stamieskin, 2020). Its mesozooplankton community is largely comprised of copepods, with Calanus finmarchicus the historically dominant species (Bigelow, 1924; Johnson et al., 2011; Melle et al., 2014). Because of its rich lipid stores, C. finmarchicus is a valuable energy source for the North Atlantic right whale and many planktivorous pelagic fish such as sand lance and Atlantic herring (Meyer Gutbrod et al. 2021; Suca et al., 2022; Becker et al., 2020). Other copepods commonly found in the Gulf of Maine, including species the generaCentropages , Pseudocalanus , Metridia , andOithona, are also a food source for planktivores, but have a smaller body size and lipid stores compared to C. finmarchicus (e.g., Lee et al., 2006; Carlowicz et al., 2024).Climate scenario models applying statistical relationships indicate thatC. finmarchicus abundance will disappear or decline substantially in this region in the next five decades as surface and bottom waters in the Gulf of Maine continue to warm (Reygondeau and Beaugrand, 2011; Chust et al., 2014; Grieve et al., 2017). While these projections simplify the complex dynamic processes controlling circulation and production in the Gulf of Maine (e.g. Runge et al., 2015), there is nevertheless the possibility of the loss of C. finmarchicus and consequently the subarctic character of the Gulf of Maine’s ecosystem function (Pershing et al., 2021).Populations of the common resident mesozooplankton exhibit strong seasonal cycles. For example, C. finmarchicus andPseudocalanus spp. reach peak abundance in late spring and early summer, whereas Centropages typicus attains peak abundance in late summer and autumn (Durbin and Kane 2007; Ji et al. 2009; Melle et al. 2014). In addition to seasonal variations, interannual and decadal variations in abundance, diversity, and evenness have been reported (e.g., Pershing et al., 2005, Record et al., 2010, Johnson et al., 2011, Kane 2007, Pershing and Kemberling 2023). Most notably, the annual abundance of late-stage C. finmarchicus (CV-adult) was relatively high in the 1980s, decreased for much of the 1990s, and then increased again between 2000-2010 (Ji et al. 2022: autumn data; Pershing and Kemberling 2023). A reverse pattern of interdecadal increase and decrease is evident in Gulf of Maine populations of Centropages typicus , Pseudocalanus spp. and Oithona spp., as well asC. finmarchicus stages CI-CIV (Pershing and Kemberling, 2023).In or around 2010, a likely climate-driven shift in the oceanographic regime in the Gulf of Maine occurred, characterized by a marked increase in sea surface temperature (GMRI 2022) and a change in the external sources of deep water (Record et al., 2019, Meyer-Gutbrod et al., 2021, Townsend et al., 2023 ). Importantly, an increased influence of Warm Slope Water driven by a northward shift in the Gulf Stream is considered to have supplanted the flow of Labrador Slope Water into the Gulf of Maine via the Northeast Channel (Thibodeau et al., 2018, Seidov et al., 2021; Neto et al. , 2021: see Fig. 1). In addition, Townsend et al. (2023) report variability in the strength of Scotian Shelf Water inflow during winter through spring, which sets up a seasonal barrier to intrusions of Warm Slope Water and modified Gulf Stream water into the Gulf of Maine the following summer and autumn. This increase in influence from Warm Slope Water in the Gulf of Maine is consistent with observations of weakening of the Atlantic Meridional Overturning Circulation (Saba et al., 2016, Caesar et al., 2021, Seidov et al., 2021; Meyer Gutbrod et al., 2021).Correlated with the 2010 shift in in oceanographic conditions is a marked decline in summer through winter late- stage C. finmarchicus (Record et al., 2019; Meyer-Gutbrod et al., 2021; Pershing and Kemberling 2023; Shank et al. 2024; Runge et al. in review). Concurrently, there is evidence of an increase since 2010 of smaller copepods, including Centropages, Pseudocalanus andMetridia species (Pershing and Kemberling 2023,) and an increase in early-stage C. finmarchicus copepodid stages in spring and early summer (Ji et al., 2022; Honda et al., 2024; Runge et al., in review). These changes in the mesozooplankton community drew interest because of their potential link to declines in the populations of endangered and commercially important species (Record et al., 2019, Richards and Hunter, 2021, Meyer-Gutbrod et al., 2021). Notably, the foraging behavior of the critically endangered North Atlantic right whale (NARW) population has shifted in the past decade, moving from their traditional summer feeding grounds in the eastern Gulf of Maine and Bay of Fundy to the Gulf of St. Lawrence (Meyer-Gutbrod et al., 2021). Recent declining trends in lobster recruitment were also shown to correlate with C. finmarchicus abundance and phenology (Carloni et al., 2024; Shank et al. 2024). These oceanographic and ecosystem changes occurring in the Gulf of Maine around 2010 have been called a regime shift in a number of studies (Meyer Gutbrod et al. 2021; Pershing and Kemberling, 2023; Shank et al. 2024). To explain the shift in the mesozooplankton community in 2010, Pershing and Kemberling (2023) proposed that decadal variations in community structure are driven by external physical forcings that enhance water column stratification in the Gulf of Maine, due to freshening (in decades prior to 2010) or surface warming (since 2010), in either case favoring ‘summer-time communities’ of the smaller mesozooplankton taxa (e.g.,Centropages , Pseudocalanus , Metridia , andOithona ). In addition, shifts in phenology, increased predation pressure and the resulting lower autumn-winter abundance of C. finmarchicus (as predators on early copepod life stages and competitive grazers), are recognized to play a role in shaping the mesozooplankton community (Ji et al, 2022; Wiebe et al., 2022; Pershing and Kemberling, 2023; Honda et al., 2024).The effects of the 2010 shift in oceanographic conditions and the mechanisms underlying change in the Gulf of Maine mesozooplankton community merit further investigation, not only to better understand how the western Gulf of Maine ecosystem will respond to future oceanographic change, but also to provide insight into mechanisms driving mesozooplankton dynamics across the margin of the North Atlantic biome. Here we use data from two time series stations in the western Gulf of Maine to document change in the periods immediately before and after the 2010 oceanographic shift. Recent studies indicate the importance of seasonal drivers in regulating the abundance of C. finmarchicus , such that the decadal scale patterns of abundance of C. finmarchicus stages CI-CIV (driven by processes occurring between late winter through mid summer) are in many ways opposite to the pattern of abundance of stages CV-CVI (Pershing and Kemberling, 2023; Honda et al.,2024; Runge et al., in review). We apply the lens of seasonality in drivers to examine how C. finmarchicus and other species and the overall diversity of the mesozoplankton community responded at subannual to annual scales, and whether the integration of responses across species sustained or changed total mesozooplankton biomass. We examine the evidence for the hypothesis that the oceanographic shift led to an expansion of the summertime mesozooplankton community adapted to more stratified, oligotrophic conditions with higher abundance and diversity of predators (Pershing and Kemberling, 2023). We find that the observations from these two time series stations provide insight into the complex interactions among changes in external advective supply, atmospheric forcing and local production in the western Gulf of Maine, where the direct socioeconomic impacts of a pelagic ecosystems shift are particularly important.

The Isocon method is a widely used and efficient approach for mass-transfer calculations. However, it faces significant challenges, including the reliable identification of immobile elements, selection of parental source compositions, and effective visualization. This paper aims to establish a general principle for selecting reference immobile elements. It demonstrates that the Isocon diagram cannot guarantee the accurate identification of real immobile elements and clarifies the meanings of ∆𝐶𝐶 𝑚𝑚 and ∆𝐶𝐶 𝑚𝑚 𝐶𝐶 𝑚𝑚 𝑂𝑂. Importantly, mobile elements with identical mobility align along the same line in an Isocon plot, complicating the selection of immobile elements. For immobile elements, ∆𝐶𝐶 𝑚𝑚 and ∆𝐶𝐶 𝑚𝑚 𝐶𝐶 𝑚𝑚 𝑂𝑂 both equal zero, and their partition coefficients approach infinity. This study provides alternative masstransfer calculation methods without requiring knowledge of original concentrations, based on the equation ∆𝐶𝐶 𝑚𝑚 = (𝜀𝜀 − 1) 𝐶𝐶 𝑚𝑚 𝐴𝐴 𝐷𝐷 𝐴𝐴 dis = (𝜀𝜀 − 1)𝐶𝐶 𝑚𝑚 𝑑𝑑𝑑𝑑𝑑𝑑 = (𝜀𝜀 − 1)𝐶𝐶 𝑚𝑚 𝐴𝐴 𝐷𝐷 𝑑𝑑𝑑𝑑𝑑𝑑/𝐴𝐴. The principle for selecting immobile elements is to prioritize those with partition coefficients closest to infinity. To validate the proposed approach, datasets from magmatic, metamorphic, ore-forming, and theoretical environments were analyzed. The results confirm the approach's reliability and emphasize the critical role of high-quality chemical analyses in mass-transfer studies.