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NASA NTRS1986

Experimental forecasts of El Nino

A deterministic numerical model of the coupled evolution of the tropical ocean and atmosphere was used to forecast all El Nino/Southern Oscillation (ENSO) events from 1970 to 1986. More particularly, the model, originally developed for studying large-scale ocean-atmosphere interactions in the tropics, successfully predicted the characteristics of the spatial and temporal structure of ENSO observed in the study interval. The model indicated that rainfall moving eastward over the Pacific slackens the surface winds that would otherwise cool the eastern Pacific by drawing up cooler subsurface waters. The oceanic thermocline increases, a poleward flow of westerly flowing warn waters deplets the equatorial warm water reservoir, and sea surface temperatures decline. These ENSO conditions are statistically tractable with the model several months in advance, provided upper ocean layer thermal data are available.

Cane, M. A.↗
NASA NTRS2010

Fiber Optic Thermal Health Monitoring of Composites

A recently developed technique is presented for thermographic detection of flaws in composite materials by performing temperature measurements with fiber optic Bragg gratings. Individual optical fibers with multiple Bragg gratings employed as surface temperature sensors were bonded to the surfaces of composites with subsurface defects. The investigated structures included a 10-ply composite specimen with subsurface delaminations of various sizes and depths. Both during and following the application of a thermal heat flux to the surface, the individual Bragg grating sensors measured the temporal and spatial temperature variations. The data obtained from grating sensors were analyzed with thermal modeling techniques of conventional thermography to reveal particular characteristics of the interested areas. Results were compared with the calculations using numerical simulation techniques. Methods and limitations for performing in-situ structural health monitoring are discussed.

Wu, Meng-Chou↗
DOE OSTI2023

Estimation of hydraulic conductivity in a watershed using sparse multi-source data via Gaussian process regression and Bayesian experimental design

Enhanced water management systems depend on accurate estimation of subsurface hydraulic properties. However, geologic formations can vary significantly, so information from a single source (e.g., widely spaced boreholes) is insufficient in characterizing subsurface aquifer properties. Therefore, multiple sources of information are needed to complement the hydrogeology understanding of a region. Here, this study presents a numerical framework in which information from different measurement sources is combined to characterize the 3D random field in a multi-fidelity prediction model. Coupled with the model, a Bayesian experimental design was used to determine the best future sampling locations. The Upper Sangamon watershed in east-central Illinois was selected as the case study site, where the multi-fidelity Gaussian process model was used to estimate the hydraulic conductivity in the region of interest. Multi-source observation data were obtained from electrical resistivity and borehole pumping tests. The accuracy of the model prediction is dependent on the locations and the distribution of both high- and low-fidelity data. Furthermore, the multi-fidelity model was compared with the single-fidelity model. The uncertainties and confidence in the measurements and parameter estimates were quantified and used to design future cycles of data collection to further improve the confidence intervals.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Constraining Oceanic Sources and Sinks of CO2 by Inverse Modeling: A First Step Toward Assimilation of In Situ and Remote Data

The primary goal of this collaborative project, lead by Nicholas Gruber at UCLA, is to better quantify the air-sea fluxes of pre-industrial and anthropogenic carbon dioxide CO2 for the global ocean with a newly developed inverse method. The method involves using ocean general circulation models (OGCMs) to characterize the subsurface distribution of tracers injected for different regions of the ocean surface. By linearly combining a series of these basis (or Greens) functions, one should be able to recreate any arbitrary ocean tracer field. In our case, we are using the global database of ocean dissolved inorganic carbon (DIC) from the WOCE/JGOFS global CO2 survey from the 1990s. The observed DIC field has been partitioned into pre-industrial and anthropogenic components using the empirical C* technique. We then solve for an optimal combination of the regional basis functions that best match the two sets observations in a least-squares sense with singular value decomposition. This in turn provides solutions for the regional air-sea CO2 fluxes (pre-industrial and anthropogenic) that are independent of more traditional estimates derived from surface water disequilibria in the partial pressure of CO2 and wind speed gas exchange parameterizations. We are apply the method to a suite of nine different OGCMs to test the robustness of the derived surface fluxes fields to differences in ocean circulation. Together with a collegue Keith Lindsay at NCAR, S. Doney's role in this project was to create the appropriate steady-state and temporally evolving basis functions from the NCAR CSM-1 ocean circulation model. Because of a slow start across the project in defining a common set of experimental protocols, we requested and were given a one year, no cost extension. Both the steady-state and temporally evolving basis functions were delivered to the UCLA group for further analysis. Additional information is included in the original extended abstract.

Doney, Scott↗
DOE OSTI2020

3-D Radiological Data Acquisition, Visualization and Modeling - 20211

The U.S. Army Corps of Engineers (USACE) was tasked to investigate and remediate low activity radiological contamination from research and production of the nation's first nuclear weapons at the former DuPont Chambers Works Formerly Utilized Sites Remedial Action Program (FUSRAP) site (DuPont). The DuPont site had several buildings used for the Manhattan project that were demolished in the 1940's and 1950's apparently using heavy earthmoving equipment. Some of the contaminated rubble from the demolition appears to have been spread out by this equipment resulting in somewhat random scattering of radiologically contaminated soil and debris along with aqueous spills. Traditional investigative methods such as soil borings, test pits and 2-dimensional gamma walkovers were only partially successful in delineating the radiological contamination at the site. It was feared that even 'chasing' the contamination during remediation would miss contamination if the demolition resulted in discontinuous trails of radiologically contaminated soils. In evaluating the data generated over the interceding decades, the USACE determined that a better method to collect and process the remedial action radiological data was needed to enable the project team to optimize predictive planning and meet documentation expectations. The purpose of this paper is to provide an overview of the effort and progress to combine and organize radiological survey methods into a highly flexible sampling, modeling, and decision analysis approach that emphasizes the quality of decision-making during remediation. This innovative system blends multiple tools to develop a methodology that can extend MARRSIM [1] into the subsurface and provide tools that can be applied to other sites. (authors)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

3D hydrogeophysical characterization of managed aquifer recharge basins

Aquifers are increasingly stressed. Managed aquifer recharge provides a potential solution to mitigate this stress and provide sustainable groundwater resources. Subsurface properties are known to have a strong control on the infiltration rates that can be achieved. However, these properties are often highly heterogeneous and difficult to assess with conventional probing techniques. Here, we show the application of 3D geophysical imaging to assess the recharge potential and its variation across several basins used for managed aquifer recharge. We link in-situ measurements of saturated hydraulic conductivity with the electrical resistivity of the subsurface to establish petrophysical relationships and use those relationships to estimate the distribution of hydraulic conductivity throughout the five recharge basins. Our results show a considerable variability in the hydraulic properties, i.e., soil texture and saturated hydraulic conductivity, that have a direct impact on potential infiltration rates. We use the 3D hydraulic property distributions to model groundwater recharge and provide estimates for infiltration rates and volumes, and use this approach to assess the impact of management activities on groundwater recharge performance. Having such data not only enables us to predict infiltration rates, but also provides means for optimizing such water infrastructure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses

Abstract Lateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Improving evapotranspiration computation with electrical resistivity tomography in a maize field

Abstract Hydrogeophysical methods have been increasingly used to study subsurface soil–water dynamics, yet their application beyond the soil compartment or the quantitative link to soil hydraulic properties remains limited. To examine how these methods can inform model‐based evapotranspiration (ET) calculation under varying soil water conditions, we conducted a pilot‐scale field study at an experimental maize plot with manipulated irrigation treatments. Our goal was to develop a workflow for (1) acquiring and inverting field electrical resistivity tomography (ERT) data, (2) correlating ERT to soil hydraulic properties, (3) spatially characterizing soil water stress that feeds into ET modeling (the FAO‐56 model), and (4) evaluating the performance of ERT‐based ET computation. Our results showed that ERT was able to capture decimeter‐scale soil water content (SWC) dynamics from root water uptake and irrigation manipulation and the contrast of soil water stress between deficiently and fully irrigated maize. We also demonstrated the flexibility of using ERT to spatially integrate soil water stress in the soil volume of interest, which could be adjusted based on different crops and plot layouts. The integration of the ERT datasets into ET modeling provided insights into the spatial heterogeneity of the subsurface that has been challenging for point‐based sensing, which can further our understanding of the hydraulic dynamics in the soil‐plant‐atmosphere continuum.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data-model files associated with the manuscript "The Effects of Spatial and Temporal Resolution of Gridded Meteorological Forcing on Watershed Hydrological Responses" (Shuai et al., 2022 HESS)

This data package contains the model inputs and outputs used in "The Effects of Spatial and Temporal Resolution of Gridded Meteorological Forcing on Watershed Hydrological Responses" (Shuai et al., 2022 HESS). The data.zip file contains the data used to drive the model simulations. The model.zip file contains the XML input file for ATS. The notebook.zip file contains the Jupyter notebooks for pre- and post- processing model results. The figures.zip file contains the raw figures associated with the manuscript.Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (10s of meters) has become efficient and computationally affordable. These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. In this study, we utilized the Advanced Terrestrial Simulator (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado). We compared simulated watershed hydrologic responses including streamflow, and distributed variables such as evapotranspiration, snow water equivalent (SWE), and groundwater table driven by three publicly available, gridded meteorological forcings (GMFs) -- Daily Surface Weather and Climatological Summaries (Daymet), Parameter-elevation Regressions on Independent Slopes Model (PRISM), and North American Land Data Assimilation System (NLDAS). By comparing various spatial resolutions (ranging from 400 m to 4 km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4 km (or 30% of the watershed area). However, the 4 km resolution has much worse performance than finer resolution in spatially distributed variables such as SWE. Using temporally disaggregated PRISM, we compared models forced by different temporal resolutions (hourly to daily), sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications on model calibration and watershed management decisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Computational Tools and Workflows for Quantitative Risk Assessment and Decision Support for Geologic Carbon Storage Sites: Progress and Insights from the U.S. DOE’s National Risk Assessment Partnership

The 2005 Intergovernmental Panel on Climate Change (IPCC) Special Report on CCS raised the profile of CO2 capture and storage (CCS) as an important technology for reducing greenhouse gas (GHG) emissions. CCS is now recognized as a key component of most climate change mitigation scenarios. Since publication of that report the international research, development, and deployment (RD&D) community has advanced key technical aspects, clarified regulatory requirements, explored value chain and infrastructure solutions, and developed incentive paradigms to enable and promote large-scale deployment of CCS. These efforts have included research to better characterize geologic storage resources, to improve injection performance and storage efficiency, to assess and manage subsurface environmental risks, and to advance monitoring technologies to assure system conformance. These efforts have helped to build confidence in the viability of geologic carbon storage (GCS), but stakeholder concerns about long-term risks and liability associated with GCS remain a hurdle to broad acceptance and large-scale deployment of CCS. Since 2010, the U.S. DOE’s National Risk Assessment Partnership (NRAP) – a research collaboration between five contributing national laboratories – has worked to establish and demonstrate methods and tools to quantify and manage the subsurface environmental risks associated with GCS, amidst uncertainty. This work supports the Office of Fossil Energy and Carbon Management Carbon Transport and Storage Program’s goal of advancing safe and secure commercial-scale GCS deployment. To address the technical challenge of simulating the physical response of the GCS site to large-scale CO2 injection, NRAP has adopted an approach that relies on coupling computationally efficient reduced-order and/or data-driven proxy models of important system components (i.e., storage reservoir, sealing caprock, leakage pathways, intermediate formations, overlying groundwater aquifers, and the atmosphere) in integrated assessment framework. That integrated model of the physical system is complemented with fit-for purpose functionality to support site characterization and risk-related decisions. The recently released NRAP Phase II toolset includes the Open-Source Integrated Assessment Model (NRAP-Open-IAM) for evaluation of trends in leakage risk and potential impact, tools to support monitoring design optimization (Designs for Risk Evaluation and Management – DREAM v3.0 and Passive Seismic Monitoring Tool - PSMT), and tools for state of stress evaluation (State-of-Stress Analysis Tool - SOSAT) and forecasting induced seismicity risk. The NRAP team has also released a pair of reports describing conceptual workflows to incorporate physics-based, quantitative risk assessment into many of the design, planning, operation, and closure decisions for GCS projects. An online catalogue highlights published studies where these tools and methods are demonstrated. In this presentation, the utility of these products to assess risks and address key stakeholder questions will be highlighted through examples, and related insights about the safety and security of geologic carbon storage in qualified storage sites will be discussed. The prospect of rapid, large-scale deployment of GCS technology to aggressively reduce anthropogenic CO2 emissions requires careful consideration of interference between multiple commercial-scale storage projects within a basin. Going forward, NRAP is expanding and adapting site-scale risk quantification tools and methods to enable assessment of risks and inform management decisions for basin-scale deployment. Increasingly, this work will leverage next-generation approaches for surrogate modelling, fast prediction, and advanced visualization enabled by machine learning and artificial intelligence to promote virtual learning, scenario evaluation, and augment risk-based decision making.

quantitative risk assessment, geologic carbon stor↗
DOE OSTI2023

Localized keyhole pore prediction during laser powder bed fusion via multimodal process monitoring and X-ray radiography

Systematic fault detection and control during laser powder bed fusion (L-PBF) has been a long-standing objective for system manufacturers and researchers in the additive manufacturing (AM) industry. This manuscript investigates a data fusion approach for detection of keyhole porosity formation during laser irradiation of Ti-6Al-4V substrates by concurrent recording of thermally induced optical emission measured using both off-axis and coaxial photodiode sensors, and acoustic emission. Subsurface defect formation was monitored via high-speed synchrotron X-ray imaging at 20,000 frames per second, enabling temporal registration of keyhole pore formation events to the monitoring signals at a resolution of 50 µs. We developed data fusion machine learning (ML) models for localized prediction of keyhole pore formation at various time scales ranging from 0.5 ms to 2 ms. The signal segments were featurized using two independent approaches: (1) power spectral density (PSD) and (2) highly comparative time series analysis (HCTSA) framework. The extracted features from different sensor modalities were fused together to construct a multimodal feature space and sequential feature selection was used to determine the most informative features for training the ML models. The predictive performance was evaluated for three classifying algorithms: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Gaussian Naive Bayes (GNB). As a result, pore formation events were predicted with up to 0.95 F1-score, 1.0 recall and 0.94 accuracy. The most heavily weighted features indicate that model performance is chiefly governed by the acoustic monitoring signal, with a secondary contribution from the optical emission sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Time–series Analysis of Volume Change at Brady Hot Springs, Nevada, USA using Geodetic Data from 2003 – 2018

Brady Hot Springs geothermal field has exhibited subsidence, as measured by interferometric synthetic aperture radar (InSAR). Previous studies have examined both the temporal evolution of the deformation from 2004 through 2016 and the spatial extent of the deformation, directly relating the observed subsidence to volumetric changes below the surface. We extend the modeling at Brady to analyze a data set of interferometric pairs spanning from the end of 2003 through 2018. We examine spatial and temporal trends in the observed deformation by time–series analysis of each of the 1656 cubic voxels in a parameterized elastic dislocation model to identify areas where the subsurface volume changes as a function of time. Joint time–series analysis of Global Positioning System and InSAR pairs confirm significant changes in rates of volume change during time intervals when well operations were varied. Here, the rate of subsidence increases with increased injection, consistent with the identification of thermal contraction of the rock matrix as the dominant driving mechanism. Conversely, the modeled volume increases when pumping ceases, suggesting thermal expansion of the rock matrix.

58 GEOSCIENCES↗
NASA NTRS2003

Martian Plains Volcanism in Syria Planum and Tempe Mareotis as Analogs to the Eastern Snake River Plains, Idaho: Similarities and Possible Petrologic Contributions to Topography

Prior to the Mars Global Surveyor (MGS) and Mars Odyssey (MO) missions, The Syria Planum region of Mars was noted for several clusters of small (5-100 km) shield volcanoes and collapse craters, long tube and fissure-fed lava flows, and possible volcanic vents that were thought to be nearly contemporaneous with the volcanism in the Tempe- Mareotis province, which has long been known for volcanic shields and vents analogous to those of the Eastern Snake River Plains (ESRP) in Idaho. Recent MGS-based work on regional and global populations of martian small shields has revealed significant global trends in edifice attributes that are well-explained by eruption models with latitudinal variations in subsurface water/ice abundance, consistent with recent MO evidence for significant amounts of subsurface water that varies in latitude abundance s, and topographic and morphologic evidence for more geologically recent lava-ice relationships. However, while the global trends in small volcano data can be at least partially explained by volatile interactions with volcanism, some global and regional characteristics appear to be perhaps better explained by possible compositional, crystallinity or eruption style variations. This study expands the sampling of shields done in martian initial global studies for the Syria Planum and Tempe-Mareotis regions, which display a newly visible breadth and number of features in image and topography data. We compare these features to a similar range of features visible in the ESRP where both compositional and eruption style variations can quantitatively be shown to contribute to morphologic and topographic differences.

Sakimoto, S. E. H.↗
DOE OSTI2026

Model data for infrastructure-aware simulation of compound flooding at Alligator Bayou Watershed, southeast Texas

This dataset supports infrastructure-aware hydrologic modeling and flood scenario analysis for the Alligator Bayou Watershed, a highly managed urban watershed in Southeast Texas. It includes Jupyter notebooks for figure reproduction, model configuration files, simulation outputs, and derived products used to quantify the influence of engineered stormwater infrastructure on flood behavior across multiple spatial scales. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations on a channel-aligned mesh with explicit representations of pump stations, gate structures, detention basins, and impervious surfaces. Outputs include time series of gate and pump flows, stage observations, and water balance components, as well as spatially explicit fields of peak ponded depth and flood duration across multiple infrastructure scenarios spanning a single-location detention basin expansion, distributed drainage limitations, and compound coastal flooding. These data facilitate full reproducibility of the manuscript figures and support further research on urban flood dynamics and the role of stormwater infrastructure in shaping watershed-scale flood response.

EARTH SCIENCE > OCEANS > COASTAL PROCESSES↗
DOE OSTI2025

Changes in soil water content and lateral flow exert large effects on soil thermal dynamics across Alaskan landscapes

Both lateral surface and subsurface water flow affect soil moisture dynamics, yet most land surface models only solve subsurface water movement vertically. Here, we use a 3D ecosystem model that considers both land surface and subsurface hydrologic processes to simulate soil moisture, which is then used to drive a 1-D vertical soil thermal model to simulate the soil moisture effects on soil thermal dynamics in central Alaska. Our coupled model improves soil temperature (ST) estimates by 43.5% in comparison with observational data. Soil moisture has little effect on ST during the wet season (-1.5%) and a substantial influence during the dry season (60%). Spatially, water lateral flow has significant impacts on both soil moisture and ST, causing model estimates for thawed areas in the transition season to increase by ~10% in the study area. Our results highlight the importance of considering dynamical soil moisture, as well as lateral flow effects, on soil thermal dynamics in permafrost regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Faulting and folding in the formation of planetary wrinkle ridges

Topographic profiles for planetary wrinkle ridges compiled from high-resolution Lunar Topographic Orthophoto maps for the moon and from monoscopic photoclinometry data for Mars reveal that many of these ridges are characterized by an elevation offset between one side of a ridge and the other. To investigate the relative importance of faulting and folding in the formation of planetary wrinkle ridges, this paper develops a model of subsurface structure, based on observations and measurements of surface physiography and topography by Golombek and Franklin (1987) and Plescia (1990), and assumptions of subsurface structure, which makes it possible to estimate shortening across wrinkle ridges on Moon and Mars. According to this model, total ridge shortening is on the order of 100 m; shortening due to faulting exceeds shortening due to folding for fault dips up to 60-80 deg, implying that faults beneath many wrinkle ridges break the surface to accomodate the greater displacement along the fault than is accomodated in the fold.

Golombek, M. P.↗
NASA NTRS1995

Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System: Dynamical Considerations - Part 1

The dynamical consequences of constraining a numerical model with sea surface height data have been investigated. The model used for this study is a quasigeostrophic model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. The assimilation of the surface data is thus equivalent to the prescription of a surface pressure boundary condition. The authors analyzed the mechanisms of the model adjustment and the characteristics of the resultant equilibrium state when the surface data are assimilated. Since the surface data are the superposition of a mean component and an eddy component, in order to understand the relative role of these two components in determining the characteristics of the final equilibrium state, two different experiments have been considered: in the first experiment only the climatological mean field is assimilated, while in the second experiment the total surface streamfunction field (mean plus eddies) has been used. It is shown that the model behavior in the presence of the surface data constraint can be conveniently described in terms of baroclinic Fofonoff modes. The prescribed mean component of the surface data acts as a 'surface topography' in this problem. Its presence determines a distortion of the geostrophic contours in the subsurface layers, thus constraining the mean circulation in those layers. The intensity of the mean flow is determined by the inflow/outflow conditions at the open boundaries, as well as by eddy forcing and dissipation.

Capotondi, Antonietta↗
NASA NTRS2019

Saildrone Baja Field Campaign: A Comparison of Surface Meteorology with GEOS Products

The Saildrone Baja field campaign was an international effort to collect measurements across the air-sea interface for a 62-day period between April 11-June 11, 2018. The field campaign was executed using a saildrone, an unmanned surface vehicle (USV) carrying a comprehensive suite of instruments to measure meteorological, ocean surface, and subsurface data. We use these data to validate near-surface meteorology and ocean surface temperature fields in theGlobal Earth Observing System (GEOS). This is the first study using Saildrone data to validate GEOS products. As these USV platforms become more prevalent, they could be used to improve model representation of the air-sea interface variables.

Akella, Santha↗