Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ocean sciences”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

COMPASS-FME Synoptic Sites Level 2 Sensor Data v2-1

This is the version 2-1 Level 2 (L2) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems. Level 2 (L2) data consist of sensor observations from the COMPASS-FME synoptic sites, TEMPEST, and DELUGE. Compared to the L1 data, these are more consistent (always 15-minute timestamps for the entire year); better QA/QC’d (out of bounds, out of service, and extreme outlier values are removed); and more complete, with a gap-filled time series available alongside the main observations, and additional derived (calculated) variables. L2 data are intended to be rapidly and easily usable in analyses and simulations. However, algorithmic outlier identification always carries the risk of removing valid data, and Level 1 data may be more suitable for analyses that focus on variability or extreme events. This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific Parquet (a high performance, space efficient format; see https://parquet.apache.org) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are reported every 15 minutes. Data files are in Apache Parquet, a high performance, space efficient format for tabular data. These files can be read using R's `arrow` package (https://arrow.apache.org/docs/r/), with similar tools available in other languages. Please see v2-1 L2 Sensor Package QStart.pdf for detailed information on data package structure, temporal coverage, and versioning.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

Dataset for Cruz-O'Byrne et al (2026): "Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry"

Hydrologic disturbances from accelerated sea-level rise and the increasing frequency and intensity of storms and tidal flooding are altering biogeochemical processes in upland coastal forests, transforming these ecosystems into wetlands. However, the initial effects of flooding on belowground biogeochemistry and the mechanisms driving greenhouse gas dynamics and soil organic matter stability during the early stages of this transition remain poorly understood. This dataset presents the results of a mesocosm experiment conducted in a controlled, highly instrumented laboratory environment, in which freshwater and brackish water pulses were applied to intact soil monoliths from a temperate upland coastal forest to examine how floodwater chemistry influences soil biogeochemistry and organo-mineral interactions. All data files are plain-text CSV (comma-separated value), and no special software is required to read them. Details about the content of each file are available in the document “Dataset_readme”. The dataset consists of the following data: • rcruzobyrne_moisture: Soil volumetric water content (VWC) • rcruzobyrne_GHG: Headspace greenhouse gas (GHG) concentration and fluxes • rcruzobyrne_methane_isotopes: Headspace methane isotope signature • rcruzobyrne_porewater: Porewater chemistry • rcruzobyrne_CDOM: Porewater colored dissolved organic matter (CDOM) • rcruzobyrne_FTIR: Soil Fourier-transform infrared (FTIR) spectroscopy Details of the experimental setup, data collection, and data analysis are provided in the manuscript by Cruz-O’Byrne et al (2026) Divergent biogeochemical responses in upland coastal forest soils to repeated flooding and shifts in water chemistry. Biogeochemistry. https://doi.org/10.1007/s10533-026-01340-0

EARTH SCIENCE > ATMOSPHERE > GREENHOUSE GAS↗

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗

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↗

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗

Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.

54 ENVIRONMENTAL SCIENCES↗

EXCHANGE Campaign 1: A Community-Driven Baseline Characterization of Soils, Sediments, and Water Across Coastal Gradients

The EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) program is a consortium of scientists working together to improve our understanding of how the two-way exchange of water between estuaries or large lake lacustuaries and the terrestrial landscape influence the state and function of ecosystems across the coastal interface. EXCHANGE Campaign 1 (EC1) focuses on the spatial variation in biogeochemical structure and function at the coastal terrestrial-aquatic interface (TAI). In the Fall of 2021, the EXCHANGE Consortium gathered samples from 52 TAIs. Samples collected from EC1 were analyzed for bulk geochemical parameters, bulk physicochemical parameters, organic matter characteristics, and redox-sensitive elements.Please download ec1_README.pdf for a complete list of available data in each .zip folder, package version history, and detailed information about the project. This README will serve as the central place for EC1 Data Package updates. Experimental setup and v1 methods are documented in Myers-Pigg and Pennington et al., 2023 (https://doi.org/10.1038/s41597-023-02548-7).EC1 Data Package Structure:ec1_README.pdfec1_methods.pdfec1_metadata_v3.zip...ec1_dd.csv...ec1_flmd.csv...ec1_sample_catalog.csv...ec1_metadata_kitlevel.csv...ec1_metadata_collectionlevel.csv...ec1_data_collectionlevel.csv...ec1_igsn_metadata.csvec1_soil_v3.zipec1_sediment_v3.zipec1_water_v3.zipec1_processingscripts_v3.zipThis data package is on v3 and was originally published May 2023 (v1). Subsequent updates will be published here with new version numbers. Please see the Change History section in ec1_README.pdf for detailed changes.---Acknowledging EXCHANGE: General Support and Data Product UseWe ask that users of EXCHANGE data add the following acknowledgement when publishing data in scholarly articles and data repositories:"This research is based on work supported by COMPASS-FME, a multi-institutional project supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Environmental System Science Program."

54 ENVIRONMENTAL SCIENCES↗

CO2 and CH4 leaf-level fluxes and soil porewater concentrations from common vegetation patches in Louisiana’s coastal wetlands

This dataset contains leaf-level flux and soil porewater concentration measurements of carbon dioxide (CO2) and methane (CH4 ) in plots in the footprint of Ameriflux sites US-LA2 and US-LA3. Leaf fluxes in US-LA2 were measured on patches dominated by Sagittaria lancifolia and co-dominated by Sagittaria lancifolia and Typha latifolia. In US-LA3, fluxes were measured from distinct Juncus roemerianus and Spartina alterniflora patches. The porewater concentrations were collected across a vertical profile (~50 cm depth) at centric locations within 25 m2 plots where we measured the leaf fluxes. US-LA3 included an additional set of measurements in open water spots. We aimed to evaluate differences in leaf fluxes and porewater pools of CO2 and CH4 of representative ecohydrological patches across a salinity gradient. We also used this dataset to help develop ELM-Wet, a more realistic representation of wetland carbon biogeochemical processes within the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM) Land Model version 1 (ELM v.1). The files can be opened with regular text editors or spreadsheet programs. Version 2.0 (8/26/2025): This is the latest version of this dataset. The update includes additional samples of soil porewater CH4/CO2 concentrations from June-2021 to November-2022, as well as minor adjustments made to V1 samples via changing Henry's solubility to account for porewater salinity. Additionally leaf-level measurments of spectral indices, PSRI, NDVI, and PRI have been added to complement Leaf-level flux measurements. All V1 data sets have been integrated into V2 sheets, ensuring data from the previous version is contained with the additional samples and consistent with V2 metadata.

54 ENVIRONMENTAL SCIENCES↗

Greenhouse gas and dissolved oxygen production and consumption rates associated with Regier et al. (2023)

Tidal inundation along the coastal terrestrial-aquatic interface controls soil and sediment biogeochemistry and gas dynamics. Although a rich literature exist on studies of the influence of tidal waters on the biogeochemistry of coastal ecosystem soils, few studies have experimentally addressed the reverse question: How do soils (or sediments) from different coastal ecosystems influence the biogeochemistry of the tidal waters that inundate them? We conducted short-term microcosm laboratory experiments where seawater was amended with sediments and soils collected across regional gradients of inundation exposure (i.e., frequently to rarely inundated) and measured changes in dissolved oxygen and greenhouse gas concentrations to calculate gas consumption or production rates occurring during seawater exposure to terrestrial materials. This data package contains dissolved oxygen and greenhouse gas data collected during incubation of soils and sediments collected at 18 sites, which were used in the publication Regier et al. (2023) entitled “Coastal inundation regime moderates the short-term effects of sediment and soil additions on seawater oxygen and greenhouse gas dynamics: a microcosm experiment” which is published in Frontiers in Marine Science (DOI: https://doi.org/10.3389/fmars.2023.1308590).---Acknowledging EXCHANGE: General Support and Data Product UseWe ask that users of EXCHANGE data add the following acknowledgement when publishing data in scholarly articles and data repositories:"This research is based on work supported by COMPASS-FME, a multi-institutional project supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Environmental System Science Program."

54 ENVIRONMENTAL SCIENCES↗

Optimization of a Parallel Ocean General Circulation Model

Global climate modeling is one of the grand chalenges of computational science, and ocean modeling plays an important role in both understanding the current climatic conditions and predicting the future climate change.

Optimization Ocean Modeling Parallel Computations↗

NASA/GSFC Research Activities for the Global Ocean Carbon Cycle: A Prospectus for the 21st Century

There are increasing concerns that anthropogenic inputs of carbon dioxide into the Earth system have the potential for climate change. In response to these concerns, the GSFC Laboratory for Hydrospheric Processes has formed the Ocean Carbon Science Team (OCST) to contribute to greater understanding of the global ocean carbon cycle. The overall goals of the OCST are to: 1) detect changes in biological components of the ocean carbon cycle through remote sensing of biooptical properties, 2) refine understanding of ocean carbon uptake and sequestration through application of basic research results, new satellite algorithms, and improved model parameterizations, 3) develop and implement new sensors providing critical missing environmental information related to the oceanic carbon cycle and the flux of CO2 across the air-sea interface. The specific objectives of the OCST are to: 1) establish a 20-year time series of ocean color, 2) develop new remote sensing technologies, 3) validate ocean remote sensing observations, 4) conduct ocean carbon cycle scientific investigations directly related to remote sensing data, emphasizing physiological, empirical and coupled physical/biological models, satellite algorithm development and improvement, and analysis of satellite data sets. These research and mission objectives are intended to improve our understanding of global ocean carbon cycling and contribute to national goals by maximizing the use of remote sensing data.

Gregg, W. W.↗

Exploring the Ocean Worlds

Including Earth, roughly a dozen water ocean worlds exist in the solar system: the relict worlds Ceres and Mars, large Jovian and Saturnian icy moons with vast interior oceans, and Kuiper Belt Objects like Triton, Charon, and Pluto whose geologies are dominated by water and ammonia. The ocean-world science puzzle – which may reveal whether life is widespread in the cosmos, why it exists where it does, and how it originates – can only be solved by exploring all of them. Potential life in these places could not have shared our origins, yet these worlds contain the only evidence about life that we can touch, essentially forever. Thus, their exploration has existential significance. Planning a multiworld exploration campaign would be a multi-generational undertaking. The technical challenges are diverse and formidable, far harder than at Mars: missions to the Jovian and Saturnian ocean worlds are severely powerlimited; trip times can be more than a decade. And the science targets are global-scale oceans beneath kilometers of cryogenic ice. Today, we lack the instrumentation, subsystems, and machine-intelligence technologies needed. A systematic OWEP (ocean worlds exploration program) strategy can make most effective use of funding and time. The three priority ocean-world targets are Europa at Jupiter, and Enceladus and Titan at Saturn. Five hypothetical programmatic scenarios are compared to the default case. A coherent OWEP should have several parts: first, dedicated continuous investment in enabling technologies; and second, two directed-purpose, medium-class (~$1B) missions per decade that conduct pivotal investigations on a documented roadmap. A robust OWEP would cost about 1/40th more per year than NASA’s current budget.

Naderi, Firouz↗

Program Options to Explore Ocean Worlds

Including Earth, roughly a dozen water ocean worlds exist in the solar system: the relict worlds Ceres and Mars, vast oceans inside most of the large Jovian and Saturnian icy moons, and Kuiper Belt Objects like Triton, Charon, and Pluto whose geologies are dominated by water and ammonia. Key pieces of the ocean-world science puzzle – which when completed may reveal whether life is widespread in the cosmos, why it exists where it does, and how it originates – are distributed among them. The eventual exploration of all these worlds will yield humanity’s total tangible knowledge about life in the universe, essentially forever. Thus, their exploration has existential significance for humanity’s self-regard, and indeed perhaps of our place in the natural scheme. The matter of planning how to pursue such a difficult and unprecedented exploration opportunity is therefore historic. The technical challenges are formidable, far harder than at Mars: missions to the Jovian and Saturnian ocean worlds are severely power-limited; trip times can be as much as a half decade and decade, respectively. And the science targets are global-scale oceans beneath kilometers of cryogenic ice. Reaching and exploring them would be a multi-generational undertaking, so again it is essential to plan and prepare. Today, we lack the instrumentation, subsystems, and remote operational-intelligence technologies needed to build and use exploration avatars as good as what we can envision needing. Each ocean world holds a piece of the puzzle, but the three priority targets are Europa at Jupiter, and Enceladus and Titan at Saturn. As with the systematic exploration of Mars, exploring these diverse worlds poses a complex technical and programmatic challenge – a strategic challenge – that needs to be designed and managed if each generation is to see its work bear fruit, and if the space science community is to make most effective use of the public money devoted to the quest. Strategic programs benefit from coherence. In only 15 years, the Mars Exploration Program (MEP) has transformed humanity’s view of Mars as a once and future habitable place, a world quite possibly holding relict evidence of life. Finding such evidence, we would study it to know if that life shared an origin common with Earth life. However, life in the ocean worlds could not have shared our origin, so exploring them opens another level in our quest to understand life in the universe: not only to places with vast salt-water seas known to contain organics and hydrothermal seafloors active today, but to places where anything alive cannot be related to us. MEP’s success – from its presence in the public consciousness to its rewriting of planetary habitability – make it an obvious template and source of lessons learned for a viable ocean worlds exploration program (OWEP). Six attributes of the MEP are analyzed for application to a potential OWEP. From this, five hypothetical programmatic scenarios are compared to the default case, and conclusions drawn. A coherent OWEP should have several parts: first, dedicated continuous investment in enabling technologies; and second, two directed-purpose, medium-class (~$1B) missions per decade that conduct pivotal investigations on a documented roadmap. Science could start in 2035, informing development of decadal flagship missions after Europa Clipper, to the places revealed to hold the most promise. The fastest pace of scientific discoveries would require access to high-performance propulsion infrastructure, e.g., the Space Launch System, Falcon Heavy, and high-power in-space solar electric propulsion, all capable of halving trip time. Not including these boosts, such a program would cost about a half-billion dollars more per year than NASA’s existing mission portfolio; the program architecture funded today cannot deliver a strategic OWEP while also sustaining balance among other solar system exploration priorities and opportunities.

Naderi, F.↗

The Marine Resources Experiment Program (MAREX)

The Satellite Ocean Color Science Working Group was established to consider the scientific utility of repeated satellite measurements of ocean color, especially for measuring global ocean chlorophyll and for studying the fate of global primary productivity in the sea. Results of the group's deliberations are presented. The scientific requirements are given for ocean color data from a CZCS follow on sensor in order to address global primary productivity, fishery, and carbon storage problems. Some specific experiments, called the marine resource experiment and designed to determine critical nutrient fluxes, photosynthetic rates, and primary productivity and biomass, are outlined.

Source record↗

Program Options to Explore Ocean Worlds

vast oceans inside most of the large Jovian and Saturnian icy moons, and Kuiper Belt Objects like Triton, Charon, and Pluto whose geologies are dominated by water and ammonia. Key pieces of the ocean-world science puzzle – which when completed may reveal whether life is widespread in the cosmos, why it exists where it does, and how it originates – are distributed among them. The eventual exploration of all these worlds will yield humanity’s total tangible knowledge about life in the universe, essentially forever. Thus, their exploration has existential significance for humanity’s self-regard, and indeed perhaps of our place in the natural scheme. The matter of planning how to pursue such a difficult and unprecedented exploration opportunity is therefore historic. The technical challenges are formidable, far harder than at Mars: missions to the Jovian and Saturnian ocean worlds are severely power-limited; trip times can be as much as a half decade and decade, respectively. And the science targets are global-scale oceans beneath kilometers of cryogenic ice. Reaching and exploring them would be a multi-generational undertaking, so again it is essential to plan and prepare. Today, we lack the instrumentation, subsystems, and remote operationalintelligence technologies needed to build and use exploration avatars as good as what we can envision needing.

Naderi, F.↗

Conducting Efficient Remote Science and Planning Operations for Ocean Exploration Using Exploration Ground Data Systems (xGDS)

NASA Ames’ Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade. In the last two years, we have participated in SUBSEA, a multi-institution collaborative project*. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC)**. In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule. The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team’s ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. * SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA’s Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island’s Graduate School of Oceanography (GSO).

Cohen, Tamar E.↗