Search NASA⌕ Search

SEARCH · Search NASA

Results for “oceanography”

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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Quasi‐Steady State Supersaturation: Do High Values Derived From ESCAPE Represent Real High Supersaturations and the Potential for Condensational Invigoration?

Deep convective clouds were intensively sampled during the Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) with coordinated flights of the NRC Convair-580 and SPEC Learjet. A total of 219 updraft core segments were sampled over coastal Texas and Louisiana under diverse meteorological conditions. Median updraft properties included widths of ∼1 km, velocities of 4.8 m s −1 , droplet number concentrations of ∼400 cm −3 , and liquid water contents of 0.9 g m −3 . The limitations of using the quasi-steady state approximation to derive supersaturations were explored. Supersaturation (S QSS ) estimated from in situ observations under a quasi-steady state assumption averaged 0.4% but occasionally exceeded 2%, with values >1% (high supersaturations) identified as statistical outliers. Two case studies illustrated the conditions linked to high supersaturations. In a storm over the Gulf, median core S QSS reached 2.46% in the developing stage compared to 2.17% in the mature stage under similar thermodynamic conditions. In a storm over coastal Louisiana, S QSS peaked near 11% within a 13.7-m s −1 updraft, accompanied by predominantly supercooled liquid droplets at −13°C and exceptionally low diameter concentrations of 0.29 mm cm −3 . Bootstrap analysis of all sampled cores showed that high supersaturations are most probable in cold and mixed-phase regimes with moderate to strong updrafts and are strongly influenced by vertical velocity and droplet number concentrations. In conclusion, while extreme supersaturations (∼10%) were rare, their occurrence underscores the need for targeted multiplatform observations to resolve their spatiotemporal variability and assess their potential role in deep convective invigoration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Atmospheric wind energization of ocean weather

Ocean weather comprises vortical and straining mesoscale motions, which play fundamentally different roles in the ocean circulation and climate system. Vorticity determines the movement of major ocean currents and gyres. Strain contributes to frontogenesis and the deformation of water masses, driving much of the mixing and vertical transport in the upper ocean. While recent studies have shown that interactions with the atmosphere damp the ocean’s mesoscale vortices O(100) km in size, the effect of winds on straining motions remains unexplored. Here, we derive a theory for wind work on the ocean’s vorticity and strain. Using satellite and model data, we discover that wind damps strain and vorticity at an equal rate globally, and unveil striking asymmetries based on their polarity. Subtropical winds damp oceanic cyclones and energize anticyclones outside strong current regions, while subpolar winds have the opposite effect. A similar pattern emerges for oceanic strain, where subtropical convergent flow is damped along the west-equatorward east-poleward direction and energized along the east-equatorward west-poleward direction. These findings reveal energy pathways through which the atmosphere shapes ocean weather.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A pronounced decline in northern vegetation resistance to flash droughts from 2001 to 2022

Climate change has led to the transition of droughts into rapid and intensified phenomena known as flash droughts, presenting considerable challenges for risk management, particularly concerning their impact on ecosystem productivity. Quantifying the ecosystem’s capacity to maintain productivity during flash droughts, referred to as ecosystem resistance, is crucial to assess drought impacts. However, it remains uncertain how the resistance of ecosystem productivity to flash drought changes over time. Here we show that vegetation resistance to flash droughts declines by up to 27% (±5%) over the Northern Hemisphere hotspots during 2001-2022, including eastern Asia, western North America, and northern Europe. The notable decline in vegetation resistance is mainly attributed to increased vapour pressure deficit and temperature, and enhanced vegetation structural sensitivity to water availability. Flash droughts pose higher ecological risks than slowly-developing droughts during the growing seasons, where ecosystem productivity experiences faster decline rates with a shorter response time. Our results underscore the limited ecosystem capacity to resist flash droughts under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Global climate mode resonance due to rapidly intensifying El Niño-Southern Oscillation

The El Niño-Southern Oscillation (ENSO) influences climate variability globally, encompassing various other modes of variability, and thus represents a key predictable climate signal on seasonal timescales. Yet, its response to greenhouse warming remains uncertain, with models projecting a range of outcomes. Here, we demonstrate that in response to warming, a state-of-the-art high-resolution climate model simulates a rapid transition from a moderate-amplitude irregular regime, as observed in the current climate, to a highly regular oscillation with intensifying amplitude. This behaviour can be attributed to increasing air-sea feedbacks, which approach criticality in the second half of this century, and growing atmospheric noise. As ENSO intensifies in this model, it synchronizes with other prominent climate modes, such as the North Atlantic Oscillation and the Indian Ocean Dipole, thereby imprinting its regular, predictable variability on them. If realized, this global climate mode resonance would have wide-ranging whiplash impacts on regional hydroclimates.

Atmospheric dynamics↗
DOE OSTI2025

Faster recovery of North Atlantic tropical cyclone-induced cold wakes in recent decades

Intense winds associated with tropical cyclones (TCs) generate surface ocean cooling in their wakes, which can persist for several weeks in their aftermath. While multi-decadal observations of the sea surface have shown a substantial warming of the ocean, long-term changes in cold wake recovery time remain largely unknown. Here we find a trend toward faster recovery of TC cold wakes in the Atlantic main development region (MDR) since 2001. This is due primarily to a decrease in the strength of the North Atlantic trade winds, which reduces evaporative cooling of the ocean. The faster damping of TC cold wakes has led to a significant increase in the intensification of subsequent TCs that encounter lingering wakes from prior TCs, with a magnitude that is about 9% of that from long-term warming of the ocean. Finally, earth system model simulations indicate that the observed decrease in the cold wake recovery time will likely continue into the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Heterotrophic respiration by soil microbes in a changing climate

Soil microbes strongly influence the soil organic carbon (SOC) pool, which globally stores ~2,000 PgC. Specifically, the balance between microbial heterotrophic respiration (R H ), which degrades SOC, and plant–microbe interactions that stabilize SOC determines whether terrestrial ecosystems are a net source or sink of CO 2 to the atmosphere. Here, in this Review, we evaluate how climate change alters these competing processes. R H is approximately half of total soil respiration, at ~50 PgC yr −1 , with 70% occurring in topsoils. Warming accelerates microbial metabolism, with a 10 °C temperature increase estimated to raise R H by ~50%, an effect that is particularly strong in Arctic soils. Warming also reduces soil moisture, further modulating R H , which responds nonlinearly to soil moisture, being limited by saturation and desiccation and meeting a maximum at intermediate levels. Consequently, R H is highly sensitive to future precipitation changes and drought. However, soil management strategies could enhance SOC stocks and persistence under climate change. Bacterial and fungal inoculants can promote SOC production and stabilization, while deep-rooting plants increase SOC inputs to deeper layers that experience lower R H . Agricultural practices and biochar amendments can also enhance SOC and reduce R H . Expanding field trials across regions, climates and soil types would improve empirical understanding of these responses and support better representation of R H in predictive models, enabling more accurate assessments of climate impacts on SOC storage.

Jansson, Janet K. [Pacific Northwest National Labo↗
DOE OSTI2024

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗
DOE OSTI2025

Diel partitioning in microbial phosphorus acquisition in the Sargasso Sea

The daily cycle of photosynthetic primary production at the base of marine food webs is often limited by the availability of scarce nutrients. Microbial competition for these scarce resources can be alleviated insofar as the intensity of nutrient uptake and assimilation activities are distributed heterogeneously across organisms over periodic input cycles. Recent analysis of community transcriptional dynamics in the nitrogen-limited subtropical North Pacific gyre revealed evidence of temporal partitioning of nitrogen uptake and assimilation between eukaryotic phytoplankton, cyanobacteria, and heterotrophic bacteria over day-night cycles. Here, we present results from a Lagrangian metatranscriptomic time series survey in the Sargasso Sea and demonstrate temporally partitioned phosphorus uptake in this phosphorus-limited environment. In the Sargasso, heterotrophic bacteria, eukaryotic phytoplankton, and cyanobacteria express genes for phosphorus assimilation during the morning, day, and dusk, respectively. In conclusion, these results support the generality of temporal niche partitioning as an emergent mechanism that can structure uptake of limiting nutrients and facilitate coexistence of diverse microbes in open ocean ecosystems.

biological oceanography↗
DOE OSTI2025

Evaluating probabilistic deep learning methods for uncertainty quantification of temperature downscaling

Deep learning (DL) has emerged as a promising tool for downscaling coarse-resolution climate data to high-resolution outputs, enabling improved regional climate predictions. A critical aspect of DL-based downscaling is the incorporation of uncertainty quantification (UQ), which enhances the interpretability and reliability of predictions—key factors for climate risk assessment and decision-making. This study develops a DL model to downscale 2 m temperature across the contiguous United States using reanalysis datasets. We systematically evaluate three epistemic UQ methods—deep ensembles (DEns), Monte Carlo dropout (MCD), and Flipout—based on their probabilistic accuracy, downscaling performance, sensitivity to geographical features, and computational efficiency. Results indicate that MCD generally outperforms Flipout and DEns in terms of calibration and downscaling accuracy. However, DEns demonstrate lower calibration errors in coastal regions, indicating its higher confidence within these areas. Flipout, in contrast, is more sensitive to elevation gradients and exhibits higher calibration errors in mountainous regions. Hence, the choice of UQ method for this task depends on the specific requirements of the application. For applications that prioritize overall calibration, downscaling accuracy, and computational efficiency, MCD is a strong candidate. These findings highlight the importance of selecting UQ methods based on application-specific requirements, such as geographical context and computational constraints. By addressing the trade-offs between UQ methods, this study provides actionable insights for improving the reliability, scalability, and utility of DL-based downscaling in climate science.

Environmental sciences↗
DOE OSTI2026

A Comprehensive Calibration Framework for the Northwest River Forecast Center

We present a comprehensive framework developed by the Northwest River Forecast Center for calibrating hydrologically diverse basins. The framework includes models for snow, soil moisture, routing, channel loss, and consumptive use. Data inputs include a wide range of open-access datasets for meteorology, land use, topography, and land cover. The framework uses conceptual hydrologic models to handle basins with various hydrologic regimes including rain-driven and snowmelt-dominated basins. We also develop a flexible automatic calibration system that can handle numerous unobservable model parameters in a computationally efficient manner. A single-basin automatic calibration run can typically be completed on a modern laptop in under 10 min. We found that model performance metrics for this new approach match the quality of the NWRFC's previous labor-intensive manual calibrations. The model performance also rivals that of a state-of-the-art deep learning model at a fraction of the computational cost. This framework presents a new standard for the quality of calibrations possible with lumped conceptual hydrologic models, combining careful data curation, an objective calibration framework, and expert local knowledge. In addition, we have made software packages available for the entire suite of National Weather Service River Forecast System models, including SAC-SMA, SNOW-17, and Lag-K. These modern interfaces are intended to increase accessibility and facilitate future research.

Forecasting↗
DOE OSTI2024

Ekman-driven salt transport as a key mechanism for open-ocean polynya formation at Maud Rise

Open-ocean polynyas formed over the Maud Rise, in the Weddell Sea, during the winters of 2016–2017. Such polynyas are rare events in the Southern Ocean and are associated with deep convection, affecting regional carbon and heat budgets. Using an ocean state estimate, we found that during 2017, early sea ice melting occurred in response to enhanced vertical mixing of heat, which was accompanied by mixing of salt. The melting sea ice compensated for the vertically mixed salt, resulting in a net buoyancy gain. An additional salt input was then necessary to destabilize the upper ocean. This came from a hitherto unexplored polynya-formation mechanism: an Ekman transport of salt across a jet girdling the northern flank of the Maud Rise. Such transport was driven by intensified eastward surface stresses during 2015–2018. Our results illustrate how highly localized interactions between wind, ocean flow and topography can trigger polynya formation in the open Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE)

Convective clouds play an important role in Earth’s climate system and are a known source of extreme weather. Gaps in our understanding of convective vertical motions, microphysics, and precipitation across a full range of aerosol and meteorological regimes continue to limit our ability to predict the occurrence and intensity of these cloud systems. To improve predictability, the National Science Foundation (NSF) sponsored a large field experiment entitled “Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE).” ESCAPE took place between 30 May and 30 September 2022 in the vicinity of Houston, Texas, because this area frequently experiences isolated deep convection that interacts with the region’s mesoscale circulations and its range of aerosol conditions. ESCAPE focused on collecting observations of isolated deep convection through innovative sampling and developing novel analysis techniques. This included the deployment of two research aircraft, the National Research Council of Canada Convair-580 and the Stratton Park Engineering Company Learjet, which combined conducted 24 research flights from 30 May to 17 June. On the ground, three mobile X-band radars and one mobile Doppler lidar truck equipped with soundings were deployed from 30 May to 28 June. From 1 August to 30 September 2022, a dual-polarization C-band radar was deployed and operated using a novel, multisensor agile adaptive sampling strategy to track the entire life cycle of isolated convective clouds. Analysis of the ESCAPE observations has already yielded preliminary findings on how aerosols and environmental conditions impact the convective life cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The ATTO-Campina site: A new observatory for tropical convection and gas-aerosol-cloud-precipitation interactions in the Amazon

We present results from ATTO-Campina, a new permanent observational site in central Amazon, about 4 km from the ATTO towers. Operational since 2020, ATTO-Campina characterizes atmospheric, cloud and rainfall properties through remote sensing. The goal is to provide continuous, complementary measurements to the ATTO towers, addressing the rainforest’s complex gas-aerosol-cloud-precipitation dynamics. Using a 3.5-year dataset, we classified convective clouds into three types: shallow cumulus (ShCu), congestus (Con) or (Deep) clouds. The shallow-to-deep transition takes about three hours, starting with ShCu formation at 11:00 local time. The accumulated rainfall peak follows at about 16:00. Only weak downdrafts are present in the upper troposphere where previous studies indicate new particle formation (NPF) occurrence. Strong downdrafts are mostly limited to heights below 5 km. Con and Deep convective days have higher concentrations of ultrafine aerosol and lower concentrations of accumulation-mode particles compared to ShCu. Convective clouds also significantly modify gas mixing ratios. Deep convective clouds are associated with high near-surface O3, consistent with downward transport from the midtroposphere. Our results showcase the added detail achieved by integrating data from the ATTO towers and ATTO-Campina sites. Together, these sites support better understanding of interconnected gas-aerosol-cloud-precipitation processes in the Amazon and their evolution under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Relative Importance of Forced and Unforced Temperature Patterns in Driving the Time Variation of Low-Cloud Feedback

Abstract Atmospheric models forced with observed sea surface temperatures (SSTs) suggest a trend toward a more-stabilizing cloud feedback in recent decades, partly due to the surface cooling trend in the eastern Pacific (EP) and the warming trend in the western Pacific (WP). Here, we show model evidence that the low-cloud feedback has contributions from both forced and unforced feedback components and that its time variation arises in large part through changes in the relative importance of the two over time, rather than through variations in forced or unforced feedbacks themselves. Initial-condition large ensembles (LEs) suggest that the SST patterns are dominated by unforced variations for 30-yr windows ending prior to the 1980s. In general, unforced SSTs are representative of an ENSO-like pattern, which corresponds to weak low-level stability in the tropics and less-stabilizing low-cloud feedback. Since the 1980s, the forced signals have become stronger, outweighing the unforced signals for the 30-yr windows ending after the 2010s. Forced SSTs are characterized by relatively uniform warming with an enhancement in the WP, corresponding to a more-stabilizing low-cloud feedback in most cases. The time-evolving SST pattern due to this increasing importance of forced signals is the dominant contributor to the recent stabilizing shift of low-cloud feedback in the LEs. Using single-forcing LEs, we further find that if only greenhouse gases evolve with time, the transition to the domination of forced signals occurs 10–20 years earlier compared to the LEs with full forcings, which can be understood through the compensating effect between aerosols and greenhouse gases.

58 GEOSCIENCES↗
DOE OSTI2026

Data for Soil Oxygen Dynamics: A Key Mediator of Tile Drainage Impacts on Coupled Hydrological, Biogeochemical, and Crop Systems

Tile drainage removes excess water and is an essential, widely adopted management practice to enhance crop productivity in the US Midwest and throughout the world. Tile drainage has been shown to significantly change hydrological and biogeochemical cycles by lowering the water table and reducing the residence time of soil water, although examining the complex interactions and feedbacks in an integrated hydrology–biogeochemistry–crop system remains elusive. Oxygen dynamics are critical to unraveling these interactions and have been ignored or oversimplified in existing models. Understanding these impacts is essential, particularly so because tile drainage has been highlighted as an adaptation under projected wetter springs and drier summers in the changing climate in the US Midwest. We used the ecosys model that uniquely incorporates first-principle soil oxygen dynamics and crop oxygen uptake mechanisms to quantify the impacts of tile drainage on hydrological and biogeochemical cycles and crop growth in corn–soybean rotation fields. The model was validated with data from a multi-treatment, multi-year experiment in Washington, IA. The relative root mean square error (rRMSE) for the corn and soybean yield in validation is 5.66 % and 12.57 %, respectively. The Pearson coefficient (r) of the monthly tile flow during the growing season is 0.78. Plant oxygen stress turns out as an emergent property of the equilibrium between the soil oxygen supply and biological demand. The impact of tile drainage on the system is achieved through a series of coupled feedback mechanisms. The model results show that tile drainage reduces the soil water content and enhances soil oxygenation. It additionally increases the subsurface discharge and elevates inorganic nitrogen leaching, with seasonal variations influenced by climate and crop phenology. The improved aerobic condition alleviates crop oxygen stress during wet springs, thereby promoting crop root growth during the early growth stage. The development of greater root density, in turn, mitigates water stress during dry summers, leading to an overall increase in the crop yield by ∼6 %. These functions indicate the potential of tile drainage in bolstering crop resilience to climate change and the use of this modeling tool for large-scale assessments of tile drainage. The model reveals the underlying causal mechanisms that drive the agroecosystem response to drainage on the coupled hydrology, biogeochemistry, and crop system dynamics.

Modeling↗
DOE OSTI2024

SCEC/USGS Community Stress-Drop Validation Study: How Spectral Fitting Approaches Influence Measured Source Parameters

Spectral source parameters used to estimate an earthquake’s stress drop (⁠Δσ⁠) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress‐Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low‐frequency displacement (⁠Ω 0 ⁠) and corner frequency (⁠ƒ c ⁠) by fitting a smooth function to benchmark displacement spectra. Participants used linear‐ or log‐sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate ⁠Ω 0 ⁠, ƒ c ⁠, and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in and can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade‐off between Ω 0 and ƒ c may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω 0 and somewhat higher ƒ c compared to those assuming a Brune model, although resulting Δσ estimates are similar. Finally, when compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ⁠.

58 GEOSCIENCES↗
DOE OSTI2025

Fiber-Optic Sensing for Earthquake Hazards Research, Monitoring, and Early Warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

58 GEOSCIENCES↗
DOE OSTI2025

Mantaray: A Rust Package for Ray Tracing Ocean Surface Gravity Waves

Ocean surface gravity waves are an important component of air-sea interaction, influencing energy, momentum, and gas exchanges across the ocean-atmosphere interface. In specific applications such as refraction by ocean currents or bathymetry, ray tracing provides a computationally efficient way to gain insight into wave propagation. In this paper, we introduce Mantaray, an open-source software package implemented in Rust, with a Python interface, that solves the ray equations for ocean surface gravity waves. Mantaray is designed for performance, robustness, and ease of use. The package is modular to facilitate further development and can currently be applied to both idealized and realistic wave propagation problems (Fig. 1).

16 TIDAL AND WAVE POWER↗