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At least 163 records · Page 9

A global database of dissolved organic matter (DOM) concentration measurements in coastal waters (CoastDOM v1)

Abstract. Measurements of dissolved organic carbon (DOC), nitrogen (DON), and phosphorus (DOP) concentrations are used to characterize the dissolved organic matter (DOM) pool and are important components of biogeochemical cycling in the coastal ocean. Here, we present the first edition of a global database (CoastDOM v1; available at https://doi.org/10.1594/PANGAEA.964012, Lønborg et al., 2023) compiling previously published and unpublished measurements of DOC, DON, and DOP in coastal waters. These data are complemented by hydrographic data such as temperature and salinity and, to the extent possible, other biogeochemical variables (e.g. chlorophyll a, inorganic nutrients) and the inorganic carbon system (e.g. dissolved inorganic carbon and total alkalinity). Overall, CoastDOM v1 includes observations of concentrations from all continents. However, most data were collected in the Northern Hemisphere, with a clear gap in DOM measurements from the Southern Hemisphere. The data included were collected from 1978 to 2022 and consist of 62 338 data points for DOC, 20 356 for DON, and 13 533 for DOP. The number of measurements decreases progressively in the sequence DOC > DON > DOP, reflecting both differences in the maturity of the analytical methods and the greater focus on carbon cycling by the aquatic science community. The global database shows that the average DOC concentration in coastal waters (average ± standard deviation (SD): 182±314 µmol C L−1; median: 103 µmol C L−1) is 13-fold higher than the average coastal DON concentration (13.6±30.4 µmol N L−1; median: 8.0 µmol N L−1), which is itself 39-fold higher than the average coastal DOP concentration (0.34±1.11 µmol P L−1; median: 0.18 µmol P L−1). This dataset will be useful for identifying global spatial and temporal patterns in DOM and will help facilitate the reuse of DOC, DON, and DOP data in studies aimed at better characterizing local biogeochemical processes; closing nutrient budgets; estimating carbon, nitrogen, and phosphorous pools; and establishing a baseline for modelling future changes in coastal waters.

54 ENVIRONMENTAL SCIENCES↗

Integrated Modeling and Optimal Operation of Multi-Energy System for Coastal Community

Focusing on remote, isolated, and underserved communities, a multi-energy system is designed in this research which is capable of utilizing different energy sources in a more coordinated and energy-efficient way to support various demands, such as fresh water, electricity, hydrogen, thermal demand, etc. The energy sources considered are renewables (wind, solar, marine) and natural gas. The energy conversion process includes water desalination, gas combustion, water electrolyzation, and different types of storage (hydrogen tank, electricity, thermal, etc.) are designed to serve as buffers in supply-demand balancing. Sets of experiments are designed to demonstrate the effectiveness of the proposed operating model and investigate the impact of uncertainties from renewable generations and demands.

Chen, Yang↗

ELM model simulations of Plum Island Ecosystems LTER low marsh site 2018-2020

Model simulations using the Department of Energy's Energy Exascale Earth System Model (E3SM) land model (ELM) with improved capabilities to represent vegetation response to salinity and inundation. The simulations were conducted for a tidal salt marsh at Plum Island Ecosystems Long Term Ecological Research (LTER) site near Rowley, Massachusetts, USA; the site is a low marsh dominated by Spartina alterniflora. The model was forced with site-specific meteorology, salinity and tidal cycles from 2018-2020. Four sets of model simulations are included and described below:1. Parameterization of the salinity response function. These simulations tested different combinations of values for optimal salinity and salinity tolerance.2. Model evaluation. This comparison conducted simulations using the default model, the salinity function only, the submergence function only, and both the salinity and submergence functions. 3. Salinity scenarios. These simulations used the 2018 salinity input data varied by -5 to +10 ppt salinity.4. Water level scenarios. These simulations used the tide height varied by -10 to +50 cm. These simulations were used to demonstrate how the salinity and submergence functions better represent carbon uptake by tidal salt marshes.The data package includes netCDF files used as forcing files for tide height and salinity, one for each year 2018-2020 at observed salinity concentrations, and an additional three forcing files in which salinity concentrations were varied 5 ppt lower, 5 ppt higher, and 10 ppt higher than the measured 2018 time series. Also included are python scripts for creating forcing files, plain text parameter and command files for running simulations, model outputs in netCDF format, and python scripts for visualizing outputs. Code for the modified E3SM model is archived in Sulman et al 2023 at doi:10.15485/1991625. More detail about files is provided in the README.md file.

54 ENVIRONMENTAL SCIENCES↗

Modeling Sea Ice Effects for Wave Energy Resource Assessments

Wave-generated power has potential as a valuable coastal resource, but the wave climate needs to be mapped for feasibility before wave energy converters are installed. Numerical models are used for wave resource assessments to quantify the amount of available power and its seasonality. Alaska is the U.S. state with the longest coastline and has extensive wave resources, but it is affected by seasonal sea ice that dampens the wave energy and the full extent of this dampening is unknown. To accurately characterize the wave resource in regions that experience seasonal sea ice, coastal wave models must account for these effects. The aim of this study is to determine how the dampening effects of sea ice change wave energy resource assessments in the nearshore. Here, we show that by combining high-resolution sea ice imagery with a sea ice/wave dampening parameterization in an unstructured grid, the Simulating Waves Nearshore (SWAN) model improves wave height predictions and demonstrates the extent to which wave power decreases when sea ice is present. The sea ice parametrization decreases the bias and root mean square errors of wave height comparisons with two wave buoys and predicts a decrease in the wave power of up to 100 kW/m in areas around Prince William Sound, Alaska. The magnitude of the improvement of the model/buoy comparison depends on the coefficients used to parameterize the wave–ice interaction.

16 TIDAL AND WAVE POWER↗

Geometry of Non-Diffusive Tracer Transport in Gridded Atmospheric Models

A first-order linear and numerically non-diffusive Eulerian transport algorithm, minVAR, was recently developed for preservation of correlations between interrelated tracers during advective transport. The present study extends this work by: (1) providing further investigation of several interesting geometric constructions found in contours of constant minVAR, short for minimum variance, through extension to three coordinate dimensions. These contours capture point-by-point representations of thousands of individual atmospheric aerosol and/or cloud particles as they evolve and are rendered on Eulerian grids at a level of sub-grid resolution limited only by numerical precision; and (2) exploration of geometric similarities between the Arakawa C-grid, used to obtain interpolated values of the wind field at grid scale and minVAR. In particular, we consider interpolation of the u and v horizontal components of wind velocity from grid to sub-grid scales. The last results are motivated by recent applications of the Weather Research and Forecasting (WRF) model applied in the coastal Houston region, where the recent TRacking Aerosol Convection Interactions ExpeRiment (TRACER) field campaign was organized. A unique and fully consistent mapping is obtained between particles moving along meteorological wind trajectories and the non-diffusive, non-dispersive representation of such trajectories on an Eulerian grid.

54 ENVIRONMENTAL SCIENCES↗

Impact of Coastal Marsh Eco‐Geomorphologic Change on Saltwater Intrusion Under Future Sea Level Rise

Abstract Coastal saltwater intrusion (SWI) is one key factor that affects the hydrology, ecology, and biogeochemistry of coastal ecosystems. Future climate change, especially intensified sea level rise (SLR), is expected to trigger SWI to encroach on coastal freshwater aquifers more intensively. Numerous studies have investigated decadal/century scale SWI under SLR by assuming a static coastal landscape topography. However, coastal landscapes are highly dynamic in response to SLR, and the impact of coastal landscape evolution on SWI has received very little attention. Thus, this study used a coastal marsh landscape as an example and investigated how coastal marsh evolution affects future SWI with a physically‐based coastal hydro‐eco‐geomorphologic model, Advanced Terrestrial Simulator. Our numerical experiments showed that it is very likely that the marsh elevation increases with future SLR due to sediment deposition, and a depression zone is formed due to different marsh accretion rates between the ocean boundary and the inland. We found that marsh accretion may significantly reduce the surface saltwater inflow at the ocean boundary, and the evolved topographic depression zone may prolong the residence time of surface ponded saltwater, affecting subsurface salinity distribution differently. We also predicted that marshlands may become more sensitive to upland freshwater supply under future SLR, compared with previous predictions without marsh evolution. This study demonstrates the importance of coastal evolution to coastal freshwater‐saltwater interaction. The eco‐geomorphologic effect may not be ignored when evaluating coastal SWI under SLR at decadal or century scales.

54 ENVIRONMENTAL SCIENCES↗

Automated Model for Improved Mapping of Country-Scale High-Resolution Coastal Bathymetry

Accurate and up-to-date maps of coastal bathymetry are critical for a variety of sectors from vessel navigation to port construction and are increasingly vital to inform coastal infrastructure management amid accelerating sea-level rise and more frequent and severe storm-surge events. The primary challenges to accurate and efficient bathymetric mapping from optical remote sensing are: accurately modeling light attenuation in both the atmosphere and water column; and inefficient data processing pipelines for highresolution satellite imagery. To address the effects of light attenuation within the water-column we have developed a novel physics-based bathymetry model that accounts for variations in water-column inherent optical properties on a pixel-by-pixel basis in optically-shallow aquatic environments, which represents a major advancement. For applications to satellite imagery, we have developed a software package that automatically applies the robust 6S atmospheric correction algorithm, estimates the bottom depth from the physics-based bathymetry model, which corrects for attenuation by suspended particulate matter and colored dissolved organic matter in the water column on a pixel-by-pixel basis, and leverages highperformance computing for rapid application to region-scale (e.g., CONUS) 2-meter resolution imagery datasets. Our approach is tailored to sensors that collect data at two-meter resolution with high return times for frequent updates. We mapped 591 WorldView satellite images for Florida, North Carolina, and Alaska and validated the maps against LiDAR-derived bathymetry data. Results show median RMSE of 1.75, 1.59, and 2.67 meters, respectively. By combining the strengths of Oak Ridge National Laboratory in high-performance computing and remote-sensing science with the water-column modeling expertise of Scripps Institution of Oceanography we advance the state of bathymetric mapping capability.

54 ENVIRONMENTAL SCIENCES↗

Unveiling Urban Pollution Patterns from a Bird’s-Eye View

Low-earth orbiting satellites have been observing the global distribution of nitrogen dioxide (NO2) since the 1990s and these observations have been used to identify pollution source regions, temporal trends, and links to health effects and community disparities. However, historically, space-based NO2 observations have been coarse in spatial and temporal resolution resulting in challenges in data interpretation and product validation; therefore, NASA developed airborne capabilities and measurements strategies to observe ultraviolet-visible (UV-VIS) trace gases at high temporal and spatial resolutions to unveiling never before seen spatiotemporal patterns over major urban hubs during recent air quality field studies. In this talk, Dr. Judd will share the story of these field studies with datasets collected from NASA’s airborne spectrometers, GeoTASO and GCAS, and how they integrate in with other space- and ground-based instrumentation to illustrate the conceptual model of air quality episodes in coastal urban environments, contribute to satellite validation and regional chemical transport model evaluation. These imagers have the capability to observe UV-VIS absorbing species, typically NO2 and HCHO, at spatial resolutions as fine as 250 m when observing from the upper-troposphere. Flight strategies allowed for the collection of repeated raster samples over urban areas multiple times per flight day in cities like Chicago, Los Angeles, and New York City, capturing never before seen pictures of the diurnal evolution of emissions, chemistry, and meteorology associated with NO2 heterogeneity. These airborne efforts help local air quality management better understand their air quality challenges as well as benefit the larger air quality community in preparation for geostationary air quality observations and the development of the global air quality observing system.

Laura Judd↗

Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem

Coastal terrestrial-aquatic interfaces (TAIs) are crucial contributors to global biogeochemical cycles and carbon exchange. A systematic evaluation of the interaction between coastal catchment properties and carbon dioxide (CO2) emission by soil respiration is significant for assessing carbon dynamics and predicting the future trajectory of atmospheric CO2 concentrations in coastal TAIs. The soil CO2 efflux in these transition zones is however poorly understood due to the high spatiotemporal dynamics of TAIs, as various sub-ecosystems in this region are compressed and expanded by complex influences of tides, changes in river levels, climate, and land use. We focus on the Chesapeake Bay region to (i) investigate the spatial heterogeneity of the coastal ecosystem and identify spatial zones with similar environmental characteristics based on the spatial data layers, including vegetation index (kNDVI), climate, landcover, diversity, topography, soil property, and relative tidal elevation; (ii) understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. Specifically, we employed hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, followed by the determination of main driving factors using Random Forest regression and SHapley Additive exPlanations. Maximum and minimum temperature are the main drivers common to all sub-ecosystems, while each region also has additional unique major drivers that differentiate them from one another. Precipitation exerts an influence on vegetated lands, while soil pH value holds importance specifically in forested lands. In croplands characterized by high clay content and low sand content, the significant role is attributed to bulk density. Wetlands demonstrate the importance of both elevation and sand content, with clay content being more relevant in non-inundated wetlands than in inundated wetlands. The topographic wetness index significantly contributes to the mixed vegetation areas, including shrub, grass, pasture, and forest. Additionally, our research reveals that dense vegetation land covers and urban/developed areas exhibit distinct soil property drivers. Overall, there is no one-size-fits-all approach to modeling carbon fluxes in coastal TAIs, and our study highlights the importance of further research and monitoring practices to improve our understanding of carbon dynamics and promote the sustainable management of coastal TAIs.

54 ENVIRONMENTAL SCIENCES↗

Diurnal cycle of precipitation over global monsoon systems in CMIP6 simulations

Accurate simulation of the diurnal cycle of precipitation over different climate regimes, including global monsoon systems, is an ongoing challenge for current state-of-the-art climate models. Here, in this study, the diurnal cycles of summertime precipitation from 21 CMIP6 historical simulations are evaluated with the NASA IMERG data via the diurnal harmonic amplitude and phase from the Fourier analysis in seven regional monsoon systems: Northern and Southern Africa monsoons, South Asia monsoon, East Asia monsoon, Australia monsoon, and North and South America monsoons. Particularly, we focus on four subregions including ocean, coastal ocean, land, and coastal land considering the different underlying physical processes. It is found that the CMIP6 historical simulations perform fairly well on reproducing the diurnal cycle of precipitation over ocean and coastal ocean, while the simulated diurnal harmonic phase and amplitude over land and coastal land show larger biases and model spread compared to biases over ocean and coastal ocean. The simulation of precipitation diurnal cycle is substantially improved in the multi-model mean of both CMIP6 historical and CMIP6 AMIP simulations compared with that of CMIP5 historical simulations. But the model bias of precipitation diurnal cycle is in general similar between CMIP6 AMIP and CMIP6 historical simulations, which suggests that the impact of the interactive ocean on the simulated diurnal precipitation averaged over a large domain is generally minor. The influence of model resolution on the diurnal cycle is shown in mixed directions across various subregions, and significant improvement from the low- to high-resolution models is only notable over coastal ocean.

54 ENVIRONMENTAL SCIENCES↗

Block-structured, equal-workload, multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Total Variation Diminishing)

Abstract. We describe the development of a block-structured, equal-CPU-load (central processing unit), multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Fully Nonlinear Boussinesq Wave Model with Total Variation Diminishing Solver). The new model framework does not interfere with the core solver, and thus the core program, FUNWAVE-TVD, is still a standalone model used for a single grid. The nesting interface manages the time sequencing and two-way nesting processes between the parent grid and child grid with grid refinement in a hierarchical manner. Workload balance in the MPI-based (message passing interface) parallelization is handled by an equal-load scheme. A strategy of shared array allocation is applied for data management that allows for a large number of nested grids without creating additional memory allocations. Four model tests are conducted to verify the nesting algorithm with assessments of model accuracy and the robustness in the application in modeling transoceanic tsunamis and coastal effects.

Choi, Young-Kwang↗

Freshening of the Labrador Sea Surface Waters in the 1990s: Another Great Salinity Anomaly

Both the observed and simulated time series of the Labrador Sea surface salinities show a major freshening event since the middles. It continues the series of decoder events of the 1970s and 1980s from which the freshening in the early 1970's was named as the Great Salinity Anomaly (GSA). These events are especially distinguishable in the late summer (August and September) time series. The observed data suggests that the 1990's freshening may equal the GSA in magnitude. This recent event is associated with a large reduction in the overturning rate between the early and latter part of the 1990s. Both the observations and model results indicate that the surface salinity conditions appear to be returning towards normal daring 1999 and 2000 in the coastal area, but offshore, the model predicts the freshening to linger on after peaking 1997.

Hakkinen, Sirpa↗

NASA Satellite Data for Seagrass Health Modeling and Monitoring

Time series derived information for coastal waters will be used to provide input data for the Fong and Harwell model. The current MODIS land mask limits where the model can be applied; this project will: a) Apply MODIS data with resolution higher than the standard products (250-m vs. 1-km). b) Seek to refine the land mask. c) Explore nearby areas to use as proxies for time series directly over the beds. Novel processing approaches will be leveraged from other NASA projects and customized as inputs for seagrass productivity modeling

Spiering, Bruce A.↗

Generalised Primal-Dual Grids for Unstructured Co-Volume Schemes

The generation of high-quality staggered unstructured grids is considered, leading to the development of a new optimisation-based strategy designed to construct weighted 'Regular-Power' tessellations appropriate for co-volume type numerical discretisation techniques. This new framework aims to extend the conventional Delaunay-Voronoi primal-dual structure; seeking to assemble generalised orthogonal tessellations with enhanced geometric quality. The construction of these grids is motivated by the desire to improve the performance and accuracy of numerical methods based on unstructured co-volume type schemes, including various staggered grid techniques for the simulation of fluid dynamics and hyperbolic transport. In this study, a new hybrid optimisation strategy is proposed; seeking to optimise the geometry, topology and weights associated with general, two-dimensional Regular-Power tessellations using a combination of gradient-ascent and energy-based techniques. The performance of this new method is tested experimentally, with a range of complex, multi-resolution primal-dual grids generated for various coastal and regional ocean modelling applications.

power diagrams↗

Securing Our Water Future: NREL's Research in Desalination of Nontraditional Water Sources

Today's water supply is built on a 20th century model of fresh water sources, centralized treatment, and wastewater discharge. But that model - especially in remote coastal communities or in disaster relief scenarios - is quickly becoming unsustainable. That's why researchers are looking to non-traditional water sources and new desalination technologies to provide our nation's industries and communities with a resilient, cost-effective water supply for the 21st century.

desalination↗

New Aerosol Models for the Retrieval of Aerosol Optical Thickness and Normalized Water-Leaving Radiances from the SeaWiFS and MODIS Sensors Over Coastal Regions and Open Oceans

We describe the development of a new suite of aerosol models for the retrieval of atmospheric and oceanic optical properties from the SeaWiFs and MODIS sensors, including aerosol optical thickness (tau), angstrom coefficient (alpha), and water-leaving radiance (L(sub w)). The new aerosol models are derived from Aerosol Robotic Network (AERONET) observations and have bimodal lognormal distributions that are narrower than previous models used by the Ocean Biology Processing Group. We analyzed AERONET data over open ocean and coastal regions and found that the seasonal variability in the modal radii, particularly in the coastal region, was related to the relative humidity, These findings were incorporated into the models by making the modal radii, as well as the refractive indices, explicitly dependent on relative humidity, From those findings, we constructed a new suite of aerosol models. We considered eight relative humidity values (30%, 50%, 70%, 75%, 80%, 85%, 90%. and 95%) and, for each relative humidity value, we constructed ten distributions by varying the fine-mode fraction from zero to 1. In all. 80 distributions (8Rh x 10 fine-mode fractions) were created to process the satellite data. We. also assumed that the coarse-mode particles were nonabsorbing (sea salt) and that all observed absorptions were entirely due to fine-mode particles. The composition of fine mode was varied to ensure that the new models exhibited the same spectral dependence of single scattering albedo as observed in the AERONET data,

Ahmad, Ziauddin↗

Advancing representations of turbulence in Earth System Models [Slides]

We have created a suite of coastally focused Large Eddy Simulation (LES), including a first ever investigation of the influence of the ocean bottom on turbulence. We have added important forcing not previously considered in LES models. We have evaluated a new more physically realistic and advanced closure against our LES database of simulations. Test cases will constrain constants in the new model and help us transition the mixing model from the deep ocean to the coastal ocean for the first time.

58 GEOSCIENCES↗

From tides to seasons: How cyclic tidal drivers and plant physiology interact to affect carbon cycling at the terrestrial-estuarine boundary (Final technical report)

Coastal ecosystems are among the most biologically and biogeochemically active and diverse systems on Earth. Because they act as important linkages between terrestrial ecosystems and the open ocean, their incorporation in Earth system models (ESMs) is critical to predict coastal and global responses to environmental changes. However, they vary greatly in the magnitude of tides and the volume and timing of freshwater input from land, making it challenging to model the major biogeochemical reactions that control productivity and greenhouse gas emissions across coastal terrestrial aquatic interfaces (TAIs). Our overall objective was to improve mechanistic process understanding and modeling of tidal wetland hydro-biogeochemistry in coastal TAIs. We established a new flux tower site (Ameriflux US-PLo) in the oligohaline part of the Parker River to continuously monitor ecosystem-scale carbon fluxes under temporally varying salinity conditions. The site is co-located with long-term monitoring plots of the Plum Island Ecosystems LTER project. We installed wells and redox sensors in the marsh interior and creek bank, established biomass monitoring plots and deployed novel optode sensors in both locations. We used this data to parameterize plant-mediated transport in PFLOTRAN and tested the impact of soil heterogeneity on porewater constituents and gas fluxes. We collected observations of root oxygen release with a novel planar optode system in the field. Flux data collected during the measurement period encompasses a large variation in salinity ranging from drought to record precipitation years. We developed a method to extract functional relationships from the flux data using artificial neural networks, identifying salinity thresholds for CH 4 fluxes. Finally, we are using the coupled ELM-PFLOTRAN model to test the impact of antecedent hydrological conditions on the salinity-CH 4 flux relationship. This grant contributed to the professional development of one postdoc, three research assistants and one graduate student. The sensor data has been shared with external collaborators.

54 ENVIRONMENTAL SCIENCES↗