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Results for “Air-Sea Interactions”

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.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Radar image interpretation techniques applied to sea ice geophysical problems

The geophysical science problems in the sea ice area which at present concern understanding the ice budget, where ice is formed, how thick it grows and where it melts, and the processes which control the interaction of air-sea and ice at the ice margins is discussed. The science problems relate to basic questions of sea ice: how much is there, thickness, drift rate, production rate, determination of the morphology of the ice margin, storms feeling for the ice, storms and influence at the margin to alter the pack, and ocean response to a storm at the margin. Some of these questions are descriptive and some require complex modeling of interactions between the ice, the ocean, the atmosphere and the radiation fields. All involve measurements of the character of the ice pack, and SAR plays a significant role in the measurements.

Carsey, F. D.↗
NASA NTRS2000

A neural network to retrieve the mesoscale instantaneous latent heat flux over oceans from SSM/I observations

The turbulent latent and sensible heat fluxes are necessary to study heat budget of the upper ocean or initialize ocean general circulation models. In order to retrieve the latent heat flux from satellite observations authors mostly use a bulk approximation of the flux whose parameters are derived from different instrument. In this paper, an approach based on artificial neural networks is proposed and compared to the bulk method on a global data set and 3 local data sets.

SSM/I latent heat flux air-sea interactions↗
DOE OSTI2025

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗
NASA NTRS1999

Predicting Decade-to-Century Climate Change: Prospects for Improving Models

Recent research has led to a greatly increased understanding of the uncertainties in today's climate models. In attempting to predict the climate of the 21st century, we must confront not only computer limitations on the affordable resolution of global models, but also a lack of physical realism in attempting to model key processes. Until we are able to incorporate adequate treatments of critical elements of the entire biogeophysical climate system, our models will remain subject to these uncertainties, and our scenarios of future climate change, both anthropogenic and natural, will not fully meet the requirements of either policymakers or the public. The areas of most-needed model improvements are thought to include air-sea exchanges, land surface processes, ice and snow physics, hydrologic cycle elements, and especially the role of aerosols and cloud-radiation interactions. Of these areas, cloud-radiation interactions are known to be responsible for much of the inter-model differences in sensitivity to greenhouse gases. Recently, we have diagnostically evaluated several current and proposed model cloud-radiation treatments against extensive field observations. Satellite remote sensing provides an indispensable component of the observational resources. Cloud-radiation parameterizations display a strong sensitivity to vertical resolution, and we find that vertical resolutions typically used in global models are far from convergence. We also find that newly developed advanced parameterization schemes with explicit cloud water budgets and interactive cloud radiative properties are potentially capable of matching observational data closely. However, it is difficult to evaluate the realism of model-produced fields of cloud extinction, cloud emittance, cloud liquid water content and effective cloud droplet radius until high-quality measurements of these quantities become more widely available. Thus, further progress will require a combination of theoretical and modeling research, together with intensified emphasis on both in situ and space-based remote sensing observations.

Somerville, Richard C. J.↗
NASA NTRS1992

Large-scale ocean-atmosphere interactions in a simplified coupled model of the midlatitude wintertime circulation

Midlatitude ocean-atmosphere interactions are studied in simulations from a simplified coupled model that includes synoptic-scale atmospheric variability, ocean current advection of SST, and air-sea heat exchange. Although theoretical dynamical ('identical twin') predictions using this model have shown that the SST anomalies in this model indeed influence the atmosphere, it is found here that standard cross correlation and empirical orthogonal function analyses of monthly mean model output yield the standard result, familiar from observational studies, that the atmosphere forces the ocean with little or no feedback. Therefore, these analyses are inconclusive and leave open the question of whether anomalous SST is influencing the atmosphere. In contrast, it is found that compositing strong warm events of model SST is a useful indicator of ocean forcing the atmosphere. Additional evidence is presented for oceanic influence on the atmosphere, namely, that ocean current advection appears to enhance the persistence of model SST anomalies through a feedback effect that is absent when only heat flux is allowed to influence SST anomaly evolution.

Miller, Arthur J.↗
DOE OSTI2025

Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments

Tropical cyclones (TCs) have ranked as the deadliest and most financially crippling natural disasters in the United States. It is imperative to assess potential shifts in TC intensity within the paradigm of an evolving climate. In this study we apply a fixed-constraint storyline approach that holds storm tracks and initial conditions constant to probe future TC intensity in the North Atlantic Basin. First, we simulate 618 historical TC events using the Risk Analysis Framework for Tropical Cyclones (RAFT)'s deep-learning intensity model. Next, we apply warming signals derived from eight CMIP6 climate scenarios and rerun each event to explore how intensities respond across scenarios. Finally, we develop an interactive dashboard that allows users to explore individual storm simulations and the scenario-modified environmental drivers. Together, this dataset and tool provide a clear, illustrative way to investigate how TC intensity responds to changes in air-sea state.

Climate Change↗
NASA NTRS1981

The relationship among sea surface roughness variations, oceanographic analyses, and airborne remote sensing analyses

The synthetic aperture radar (SAR) was studied to determine whether it could image large scale estuaries and oceanic features such as fronts and to explain the electromagnetic interaction between SAR and the individual surface front features. Fronts were observed to occur at the entrance to the Chesapeake Bay. The airborne measurements consisted of data collection by SAR onboard an F-4 aircraft and real aperture side looking radar (SLAR) in Mohawk aircraft. A total of 89 transects were flown. Surface roughness and color as well as temperature and salinity were evaluated. Cross-frontal surveys were made. Frontal shear and convergence flow were obtained. Surface active organic materials, it was indicated, are present at the air-sea interface. In all, 2000 analyses were conducted to characterize the spatial and temporal variabilities associated with water mass boundaries.

Oertel, G. F.↗
DOE OSTI2026

Numerical Analysis of Offshore Wind-Farm-Induced Drag Effects on Coastal Upwelling Dynamics

Wind farms extract momentum from the atmospheric flow, generating wind-speed deficits both within the plant, and extending downstream. When located offshore, these deficits modulate air-sea coupling, potentially impacting coastal upwelling in sensitive regions. We investigate impacts of wind farms on coastal upwelling using kilometre-scale, three-way-coupled simulations with the coupled ocean-atmosphere-wave-sediment transport system for the US West Coast. Wind-farm effects are represented by a generalised turbine drag formulation, an idealised, height-dependent body force whose magnitude is systematically varied. This approach isolates the leading-order fluid-dynamical response in a realistic coastal configuration. The atmospheric adjustment exhibits an approximately linear relation between drag force and wind-speed deficit, with wakes that expand downstream and increase in magnitude as drag increases. An empirical orthogonal function analysis of sea-surface-temperature anomalies reveals the emergence of a canonical dipole pattern under strong drag forcing. Subsurface diagnostics show consistent shoaling of the mixed layer and suppressed upward velocities in areas near wind-farm region, accompanied by compensating enhancements of shoaling closer to the coast. These results identify turbine drag as a control parameter in assessing interactions between wind-farm wake and coastal upwelling and provide scaling relationships for understanding offshore wind-farm effects on the coastal circulation dynamics.

16 TIDAL AND WAVE POWER↗