The growth of the marine internal boundary layer (MIBL, height ℎ𝑖 ) with the shore-normal distance 𝑥, is a topic of continuing interest because of its applications in coastal dispersion, offshore wind farm siting, coastal air-sea fluxes and in evaporative ducting. Available data on MIBL are only scarce, given the difficulty to measurements and variability of coastal winds. During Coupled Air-Sea Processes and Electromagnetic Research (CASPER)-West campaign, from September 27 to October 27, 2017, an array of instrumentation was deployed on the Californian coast at Point-Mugu and on the research vessel Sally Ride. A state-of-art triple Doppler Lidar system was used to map the flow field up to 500 m in height above sea level and to a distance of ~ 4 kilometers from the coast with a spatial resolution of 30 m. Triple Doppler Lidar provides simultaneous vertical profiles of all three velocity components in the atmospheric boundary layer. A 20 m flux tower was used to characterize the atmospheric surface layer, especially its stability. The temporal variability of MIBL growth measured by the triple Doppler Lidar near the coast every 15 minutes were synthesized by its offshore wind direction and atmospheric stability. Over 5 unique case-studies of MIBL offshore development provided some useful general conclusions on the MIBL growth. Measurements also from a state-of-art motion-stabilized coherent Doppler Lidar and microwave radiometer on Sally Ride also showed the growth of offshore internal boundary layer several kilometers from the coast.

A series of survey protocol for deep sea polymetallic sulfides using not electromagnetic waves but acoustic, electromagnetic, gravity and magnetic, and geochemical methods has been proposedby Japanese national project, the Next-Generation Technology for Ocean Resources Exploration (Zipangu in the Ocean Program) launched in 2014, which enables effective and efficient explorations. The first version of the survey protocol has been made to determine the potential polymetallic sulfides areas using detailed scientific researches on their genesis. Deep sea polymetallic sulfides are produced beneath the sea floor because of the interaction between sea water and sub-bottom hydrothermal solutions driven from volcanic magma, indicating that they must be discovered at mid-ocean ridges, back-arc and arc regions, and hot spots. Recent studies further show that back-arc basins such as Okinawa Trough probably produce deep sea polymetallic sulfides bodies much larger than other regions (Tsuji et al., 2012). Some interesting topics on the survey protocol which further constrains the candidate areas, include acoustic, natural electric potential and seismic survey methods, that are 1) the shipboard Multi Beam Echo Sounding (MBES) survey that can acoustically detect hydrothermal plume including abundant CO2 for regional survey (100km2 <), 2) continuous self-potential measurements with tremendously low noise in the sea water that can identify individual sulfide deposit for semi-detailed survey (10km2- 100km2), and 3) state of the art vertical cable seismic (VCS) system which enables to delineate detailed structure of hydrothermal ore deposit body for detailed survey (< 10km2). These three methods, in combination with other geophysical and geochemical surveys, have been turned out to be effective and efficient for surveying deep sea polymetallic sulfides. Multiple types of data would be integrated into a single visualization to gain a clear view of the structure of the sulfides. Integrating core lithologies obtained via drilling with the seismic reflection structure data has been found to show the seismic velocity structure along with the extent of the polymetallic sulfides bodies.

Understanding the physical and chemical dynamics of caldera magma chambers prior to VEI 7+ eruptions is important for eruption forecasting and societal preparedness. The 1.26 Ma, 400 km3 Tshirege Member of the Bandelier Tuff is the later of two zoned rhyolitic ignimbrites erupted from the Valles caldera in the Jemez Mountains volcanic field, New Mexico, USA. To avoid effects of crystal-glass sorting, lithic contamination, and post-emplacement thermal alteration of glasses and mineral phases, we sampled whole pumices from non-welded tuff, including zones of otherwise welded tuff quenched against cold paleovalley walls. The tuff is broadly systematically chemically zoned from early-erupted high-silica rhyolite enriched in incompatible trace elements to late-erupted low-silica rhyolite. Whole-pumices indicate the upper portions of the Tshirege magma system were unaffected by convective stirring prior to the eruption, while some mixing and overturn is reflected by pumices from deeper in the system (i.e. stratigraphically higher in tuff sheet), likely closer to recharge sources. Analyses of well-preserved minerals, glasses and melt inclusions, and application of mineral thermometers and barometers, show a vertical stratification of temperature (710-840 °C), pressures of ~0.16 GPa, and variable [H2O] (~2.0-3.5 wt. %). Whole-pumice and melt inclusion chemistry supports crystal accumulation and subsequent melting and remobilization of the cumulate pile as a major contributor to the overall compositional zoning. 2-D thermal models indicate that the creation of the temperature gradient over ~10ka from mush development to mobilization would require volumetrically unreasonable influx of recharge magma (flux rate >30 km3/yr), suggesting that recharge heating is likely only affecting the lowest portions of the chamber. As a result, the thermal gradient likely existed prior to mobilization of the mush. Heating alone cannot affect thermal loosening of a mechanically locked mush to an eruptible crystallinity in reasonable time frames, and so input of volatiles such as H2O or CO2 from a second boiling of recharge magmas is required to melt and remobilize the crystal mush pile. The 1.26 Ma eruption was thus triggered by a final recharge event recorded as dacite pumice clasts distributed throughout the tuff.

The lateral size of sea ice floes is receiving increasing attention as an important variable for the polar climate system. We have developed a model for prognostic evolution of the floe size distribution, which emerges due to five key physical processes: new ice formation, welding of floes in freezing conditions, lateral growth and melt, and fracture of floes by ocean surface waves. As a result of the model’s foundation in the governing physics, free parameters occurring in the equations can be directly constrained by observations. Initial model experiments provided insight into the relative importance of various processes, showing floe freezing processes were particularly important for simulation of the floe size distribution. Previously, physical descriptions of lateral growth and welding together of floes had not been constrained by observations. This motivated an analysis of images obtained by drifting wave buoys (SWIFTs) deployed in the autumn Arctic Ocean to quantify these processes in-situ for the first time. We separated floe area growth due to welding from that due to lateral expansion, and compared observations to our physical descriptions of the individual processes. We also found a strong limitation on floe sizes imposed by the wave field. These results have been used to inform new physical descriptions of processes important for the sea ice floe size distribution.

Coastal communities, economy, and biodiversity are increasingly threatened by escalating environmental challenges. Addressing these necessitates multi-scale data-driven solutions. Digital Twins of the Ocean are emerging as a transformative approach, evolving into regional and local applications that integrate Earth observation (EO), in situ monitoring, numerical models, and Machine Learning (ML) into science-based and user-oriented solutions.  In this context, we present a portfolio of developments targeting key coastal challenges: (1) A ML method for rip current detection from beach imagery in support of emergency services. (2) An automated tool for seagrass wrack identification from coastal cameras, to assist local authorities in balancing tourism and conservation needs. (3) A multi-scale coastline monitoring, exploiting the synergies of fixed stations, crowd-sourced imagery, and satellite-derived shorelines, enabling high-resolution assessment of coastal state. (4) A Marine Heatwaves monitoring and forecasting system that integrates EU Copernicus Marine data for their operational assessment on  Marine Protected Areas. (5) A satellite-derived bathymetry mapping approach, lying on ML models trained on echosounder measurements, in support of coastal assessment and coastal interventions. (6) Benthic habitat mapping products, for sustainable marine planning, using EO, ground truth data, bio-optical models and ML to map benthic vegetation and density.  Through modular and problem-specific pipelines, this research integrates multi-platform data into contextualized, evidence-based intelligence for coastal planning, risk management, and environmental conservation. By ensuring citizen engagement and co-designing with stakeholders, this framework showcases the potential for coastal-to-ocean monitoring and forecasting with a user-oriented focus, prototyping a holistic information system.This research is part of the European Union (EU) funded projects FOCCUS (Grant Agreement 101133911) and iMagine (Grant Agreement 101058625). Views and opinions expressed are those of the authors only and do not necessarily reflect those of the EU or the European Health and Digital Executive Agency (HaDEA). Neither the EU nor the granting authority can be held responsible for them.

As already presented at previous conferences, we have developed an innovative technique for ocean wave observations from space: A dedicated reprocessing of spotlight-mode synthetic aperture radar (SAR) data enables us to produce a series of images covering a total time interval of a few seconds, in which moving wave patterns become visible. In most cases, the duration and quality of the image series is sufficient for computing a wavenumber-frequency spectrum and applying a dispersion relation filter to separate signatures of actual ocean waves from contributions of other physical phenomena and noise. Then the extracted wave signatures can be inverted into surface slope and displacement fields (in the space-time domain) and / or spectra (in the wavenumber-frequency domain) by applying relatively simple linear modulation transfer functions. Altogether this process is much more straightforward than traditional wave retrieval techniques for SAR images, and we think it produces more accurate results, although a full quantitative validation is still to be completed. This presentation at Ocean Sciences 2020 will not focus on the waves themselves, but on secondary information that can be retrieved from the moving wave patterns: Since the dispersion relation of ocean waves depends on water depth and surface current, these two parameters need to be tuned to fit the shape of the “dispersion shell” to the observed spectral energy distribution in each subwindow of a SAR image for which the wave field is analyzed. Accordingly, depth and surface current are obtained as additional outputs of the dispersion relation filter. This methodology is well established in the marine radar community, but has not been applied to satellite data before, where it presents a range of new opportunities as well as specific challenges. We will discuss the potential of the proposed method for practical applications and show first examples of retrieved nearshore wave, depth, and surface current fields.

The warm rain process is an important part of shallow cumulus convection and can influence both cloud microphysics and cloud radiative effects. Model studies suggest that as shallow cumulus grow in size, the likelihood of warm rain increases due to a decreasing impact of entrainment on cloud updrafts. This implies a reduction in evaporative effects near cloud center that may result in more efficient conversion from cloud water to precipitation as cloud size increases. While these findings have been illustrated with cloud resolving models, the likelihood of precipitation and the sensitivity of precipitation efficiency to cloud size has not yet been tested by global observations. A-Train satellite observations, with sensors sensitive to both cloud and precipitation water, can be used to examine shallow cumulus behavior with cloud size. We combine CloudSat and MODIS observations to create a warm cloud climatology by identifying warm oceanic contiguous cloud objects with top heights below the freezing level from August 2006 - December 2010. The characteristics of each cloud object, including cloud top height, along-track extent (size), vertical reflectivity gradients, integrated cloud and precipitation water, and column water vapor (CWV) environment, are calculated. As a proxy for warm rain efficiency, the ratio of precipitation to cloud water is also analyzed for varying cloud object sizes. For a fixed top height, our results show rain likelihood increases with cloud size. Our initial results support the hypothesis that as shallow cumulus size increases and/or environmental moisture increases, shallow cumulus updrafts are able to support larger droplets that are more likely to fall out as rain. Planned analysis will determine how our proxy for warm rain efficiency changes with cloud size.

Tropical convective organization and associated clusters of precipitation affect the global circulation and Earth’s energy budget, but many aspects such as the power-law distribution of precipitation clusters and the relation to convective self-aggregation remain poorly understood. Here, we present a physics-informed 2D conceptual model for tropical convective organization. The model is based on the budget equation of column moist static energy (CMSE) with terms that are parameterized based on diagnosing them in a high-resolution simulation with explicit convection. The conceptual model combines a reaction-diffusion equation, where the reaction term has memory, with a temporal red noise. We find that vertical advection has a strengthening effect on CMSE perturbations, whereas horizontal advection has a mitigating effect on CMSE perturbations. The CMSE tendencies from vertical and horizontal advection terms are larger in magnitude than those from radiation and surface fluxes. The strengthening effect of vertical advection corresponds to a negative gross moist stability (GMS) at short spatiotemporal scales, but the GMS becomes positive when the convection changes from shallow to deep, killing off the growth in CMSE. The conceptual model is faithful in simulating self-aggregation in that it shows a domain-size dependence of aggregation found in many prior works, and its CMSE power spectrum matches that of the high-resolution simulation except for a shallowing of the slope at high wavenumbers. Through analyzing the conceptual model equation, we show that 1) the domain-size dependence of self-aggregation is due to a competition between the strengthening effect of vertical advection and the smoothing effect of horizontal advection, and 2) the combination of temporal red noise and diffusive horizontal advection sets the shape of the CMSE power spectrum. Furthermore, the conceptual model also reproduces power-law distributions of precipitation clusters when precipitation clusters are viewed as thresholded islands on the CMSE topography. Thus, the simple conceptual model captures and helps to explain important aspects of convective self-aggregation and tropical convective organization.

Natural soil systems usually exhibit complex properties such as fractal geometry, resulting in complex dynamics for the movement of pollutants. This study developed a fractional advection-dispersion-reaction equation (fADRE) to quantify nitrate transport in soil systems. Applications showed that the fADRE model can quantify both hydrological and biogeochemical impacts on the fate and transport of nitrate in various saturated soils. The qualitative relationship between model parameters and the target system properties was also explored in detail.

We present an intercomparison and consistency study of aerosol optical depth (AOD) retrievals from the 1625 nm channel that has recently been added to the SURFRAD’s Multi-Filter Rotating Shadowband Radiometer (MFRSR) instruments. In addition, a Multi-Filter Radiometer (MFR) has been installed at the SURFRAD sites to measure upwelling radiation in the same wavelength bands. SURFRAD (Surface Radiation Budget Monitoring) is a NOAA measurement network with the prime directive to determine the surface radiative budget. It is composed of seven sites across the United States and two mobile facilities. Each site is equipped with an MFRSR which measures global and diffuse solar radiation in one broadband and six narrow band spectral channels. MFRSR retrivals include several aerosol optical properties including the spectrally resolved AOD at 415, 500, 673, 870, 940, and 1625 nm. With particular focus on the AOD from the 1625 nm channel we discuss measurement uncertainties based on instrument limitations, uncertainties from the retrieval algorithm, and statistical considerations. Some of the SURFRAD sites have a colocated CIMEL sunphotometer that in some instances is equipped with a 1625 nm channel. While the two datasets are highly correlated we observe various deviations. We furthermore present an aerosol particle size distribution retrieval based on the AOD from 5 narrow band MFRSR channels. Here we put particular emphasis on the 1625 nm channel and its potential to improve the retrieval of the coarse mode fraction of the size distribution.

Though spurious geomagnetic activity lead to terrestrial storms, which in turn impacts space weather as a result of interaction between Solar wind (SW) plasma carried by Solar wind moving towards Earth due to Coronal Mass Ejection (CME) and interplanetary magnetic field, the interplay linking the Solar plasma to the Earth’s magnetic field is yet to be understood thoroughly, and hence modelling the space weather is still perceived as a challenge. To address this issue, we resort to geometrical analysis of the phenomena using state-of-the-art Multi Fractal Analysis (MFA) techniques as well as Wavelet Transforms of SW and Earth’s magnetic field parameters during the period starting from few days before up to few days after the last Solar Eclipse on June 21, 2020, in order to predict abnormal behaviour in terrestrial environment, may or may not be leading to geomagnetic storms, well before the occurrence of the event.

Fast transients in the form of spiky radio bursts have been observed in solar flares events, emitting at different ranges in frequency. These dynamical phenomena show up as high brightness temperature increments with short durations of the order of milliseconds. In this work, we present results of the analysis of some properties of radio spike events observed at frequencies between 0.01 and 8.4 GHz, as reported in different studies. We analyze the relation of the duration, bandwidth, emitted flux, polarization and drift rate of the radio spikes with its observational frequency. Also, we analyze its correlation with other energetic solar events.

Climate change mitigation strategies increasingly focus on negative emission technologies, including enhanced weathering. This study investigates the relationship between cation release in soil and climate factors such as rainfall and temperature, as a method of modeling the dissolution of rock from a enhanced rock weathering deployment. We conducted a field experiment comparing basalt-amended plots with a control plot, measuring cation concentrations in soil porewater over time. Concurrently, we recorded rainfall and temperature data to assess environmental influences on cation release dynamics. Results show significant differences in cation release between basalt-amended and control plots. Statistical modeling reveals strong correlations between cation concentrations and both rainfall and temperature. Our findings demonstrate strong correlations with climatic factors which underscores the importance of considering environmental conditions when implementing enhanced weathering techniques. This research contributes to our understanding of the efficacy and dynamics of enhanced weathering in real-world conditions, informing future large-scale applications of this climate change mitigation approach. The predictive model developed from this study offers a valuable tool for estimating the potential effectiveness of enhanced weathering across diverse environmental settings.

In some “pressure-sensitive” rock formations, the variation of permeability with pore pressure is sufficiently large that it needs to be accounted for. Accounting for this variation of permeability renders the pressure diffusion equation nonlinear, and not amenable to exact analytical solutions. A constitutive model that fits many data sets is that of a permeability that varies exponentially with pressure. One-dimensional flow to a constant-pressure boundary in a medium whose permeability varies exponentially with pressure is investigated in this work, using numerical and approximate approaches. As part of the analysis, a dimensionless “pressure-sensitivity” parameter β is defined as the logarithm of the ratio of the far-field permeability to the permeability at the outflow boundary. The problem can be approached by applying a Boltzmann transformation to the governing PDE, and converting the resultant ODE into an integral equation, which can be solved by an iterative procedure. This numerical solution can serve as a benchmark against which to judge the accuracy of approximate solutions. One simple approximate model is based on the “sorptivity approximation” developed by Philip for unsaturated flow, which can be adapted to any nonlinear diffusion problem. This model linearizes the problem by defining an effective permeability as a drawdown-weighted average of the permeability as a function of pore pressure. The Philip approximation predicts that the flowrate, normalized against the case in which the permeability is constant, is 1–0.333β, to first-order in β. This problem can also be approached as perturbation problem, with β as the perturbation parameter. The zeroth-order solution is the classical error-function solution for a 1D diffusion problem with a constant-pressure boundary. The first-order correction is obtained in closed form, from which the flowrate at the outflow boundary is found. To first-order, the normalized flowrate is 1-0.318β. This solution is extended to higher values of β by defining an effective permeability such that, if inserted into the analytical solution for the mathematically linear problem, yields a flowrate that is exact to first order in β. When compared to the numerical solution, this new result has 5% accuracy out to values of β = 2, which probably covers most cases of interest.

Thunderstorms exhibiting anomalous charge structures (ACSs, i.e., anomalous storms) are comprised by more riming ice carrying net positive versus negative charge, thought to result from increased mixed-phase cloud liquid water content (LWC). Anomalous storms are rarely observed in the United States (US) outside of the Great Plains (GP) region, where environmental conditions that suppress warm precipitation efficiency and support robust updrafts are thought to favor increased mixed-phase LWC. Two rare anomalous supercells in the Southeastern (SE) US exhibited similar charge structure characteristics as observed in GP anomalous storms, including a deep positive (negative) charge layer associated with riming (non-riming) ice in the lower (upper) mixed-phase region. However, most characteristics associated with SE anomalous environments were not consistent with those in the GP. A more rigorous evaluation of hypotheses concerning ACS development and their observation in the SE compared electrical, kinematic, microphysical, and environmental properties between the two anomalous and two SE normal supercells (i.e., exhibiting normal charge structures). Similar metrics of warm precipitation efficiency were observed in each. However, lower relative humidity in the charging region of the SE anomalous storms uniquely matched environmental characteristics in GP anomalous storms and differentiated SE anomalous from normal environments, suggesting the relative importance of saturation ratio alongside LWC in positive charging of riming ice. Differences were also observed in charge region characteristics and flash locations between a SE anomalous and normal storm. As riming ice increased in the negative charge region of the ACS, flash initiation locations were increasingly observed in stronger updrafts and updraft gradients compared with the normal storm. The evolution of microphysical characteristics of the negative charge region in the anomalous storm suggested an increase in normal alongside anomalous charging, indicating that variability in charging polarity may impact spatial flash relationships with the updraft. Further work is needed to diagnose whether particle-scale charging variability influences flash rate relationships with convective parameters such as updraft or graupel volume.

Bioretention cells are a Low Impact Development (LID) technology that is being promoted as a green solution to attenuate urban stormwater nutrient loadings. Despite extensive implementation of bioretention cells in Canada, the mechanistic understanding of phosphorus (P) cycling in bioretention cells is still limited. We conducted detailed analyses of (geo)chemical and hydrological data coupled to numerical reactive transport modeling to simulate the fate and transport of P in a bioretention cell located in Mississauga (Ontario, Canada) within the Credit River watershed. Our objective is to utilize the model to predictively understand the accumulation and speciation of P in the bioretention cell under long-term field operation. Unlike existing bioretention models, our model incorporates a detailed representation of the biogeochemical processes that control P cycling in the bioretention cell. We further compare the model predictions with data from sequential chemical extractions of P from soil samples taken from the bioretention cell. The model correctly estimates the cumulative TP (total P) and SRP (soluble reactive P) outflow loadings from the bioretention cell, as well as the TP accumulation rate and observed partitioning of P over the different pools in the bioretention cell. The relative importance of various processes controlling P retention are assessed using mass balance calculations and sensitivity analyses of the model. The results show that filtration of fine P-containing particles and slow sorption are the main processes retaining P in the bioretention cell.

Most particle motions on Earth's surface are fundamentally stochastic and often occur under rarefied transport conditions. Every particle makes a unique path along the bed, similar but distinct from the paths of all other particles in motion, until it loses enough kinetic energy to become disentrained. The details of a particle's motion are determined by the amount of energy added and extracted during each moment of travel. Thus, particle motions physically reflect the complex energy dynamics at play and are a building block of morphodynamic theory. A full appreciation of this energy balance is needed to properly describe the motion of particles and associated disentrainment under different transport conditions. Often multidimensional behaviors occur during transport as both a result of and influence on these particle scale energy dynamics. One such phenomenon is that of particle-scale random walking during transport which results in diffusion over short timescales in both the downstream and transverse directions. We have adopted the Galton board as the fundamental conceptual model on which to create a mechanistic yet probabilistic formulation of particle diffusion. Here we provide a data set of two-dimensional particle travel distances supplemented with high-speed videos of particle-surface collisions collected during laboratory experiments to characterize the influence of shedding fluid vortices and angularity on collisional distances and two-dimensional travel for particles at low Reynolds numbers. Such a description is consistent with diffusion from the top-down and may be distinct from the bottom-up, or surface roughness, controlled random walking that other studies have explored. Preliminary analysis shows that spherical particles experience jiggling motions resulting in transverse displacement in the absence of surface roughness and this behavior is further exaggerated for particles of natural angularity. We hope to clarify the influence of the particle Reynolds number in top-down and bottom-up spreading.

Biosphere-atmosphere interactions in forest settings have a large impact on the budget and fate of nitrogen oxides (NOx) and ozone, as forests cover over 30% of Earth’s land surface area, where major sources and sinks of these key trace gases are located. Owing to their structure and biological activity, forests affect trace gas transport and chemistry both within and above the canopy. Factors such as turbulence, surface deposition, soil emission, and gas-phase oxidation chemistry must be considered when evaluating canopy-scale NOx and ozone fluxes. Interactions involving these processes result in canopy-scale bi-directional exchange of NOx. This might be further affected by leaf-level bi-directional NOx exchange characterized by the compensation point, the ambient NOx mixing ratio above which NOx is taken up by leaves and below which NOx is emitted by leaves. During the summer 2016 Program for Research on Oxidants: PHotochemistry, Emissions, and Transport campaign at the University of Michigan Biological Station, we conducted leaf-level gas exchange experiments on white pine (Pinus strobus), bigtooth aspen (Populus grandidentata), red maple (Acer rubrum), and red oak (Quercus rubra), all dominant tree species of the forest surrounding the campaign site. Known amounts of NO, NO2, or ozone were added to a pair of branch and blank enclosures. Measurements of these gases were made continuously in a sequence of inlet and outlet air from the branch enclosure followed by the blank enclosure. We also measured PAR, ambient and enclosure temperatures and moisture, leaf temperatures and wetness, and CO2 within the enclosure. Initial analyses show that the NOx mixing ratio differences before and after the enclosure have a small but clear correlation to the input NOx mixing ratio. Further analysis is required to examine the dependence of these differences on the micro-environment of the enclosures before conclusions can be made on the existence and magnitude of compensation points for each tree type. These results, combined with the concurrently observed NOx and ozone vertical gradients, will be further analyzed using a Multi-Layer Canopy Chemistry Exchange Model for assessing the effect of leaf-level exchange on the NOx and ozone dynamics at this forest site.