Search NASA⌕ Search

SEARCH · Search NASA

Results for “deep lower atmosphere”

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.

420 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

First N 2 Profile for Venus’ Deep Lower Atmosphere

We present the first N 2 profile for Venus’ deep lower atmosphere (<15 km) and a constrained isotopic composition for cloud N 2 [1]. This work directly addresses unresolved questions for Venus using legacy observations. Prior to this work, there were no reported measurements for N 2 abundances at <15 km and the isotopic composition remained unconstrained [2]. The N 2 parameters are critical to understanding the evolution and thermal properties of the atmosphere [3-7]. Our N 2 results were obtained by re-analysis of data acquired in 1978 by the Pioneer Venus Large Probe Neutral Mass Spectrometer (LNMS) [8]. The archived mass spectra from 64.2 to 0.2 km were treated using the analytical procedures specifically developed for the LNMS [9-11]. Judicious peak fitting permitted disambiguation of (A) N 2 + and CO + at 28 u and (B) 14 N 15 N+, 13 CO + , and C 2 H 5 + at 29 u. Quality controls included comparing the (A) LNMS CO + /CO 2 + ratios to the NIST database and literature and (B) fitted counts for CO + to the expected counts of CO + calculated from C 18 O + and 13 CO + using the LNMS 16 O/ 18 O and 12 C/ 13 C ratios (obtained from CO 2 ). Our results show that N 2 is uniformly mixed across the deep lower atmosphere between ~0.2 and 15 km (2.49 ± 0.10 v%). In contrast, N 2 is non-uniformly mixed across the sub-cloud atmosphere and clouds (~15–59 km), where N 2 abundances increase by ~ 2-fold between ~15 km (2.45 ± 0.32 v%) and ~59-51 km (5.21 ± 0.18 v%). Using the cloud data, we also obtained a constrained 15 N/ 14 N ratio (2.93×10 -3 ± 0.13×10 -3 ) and δ 15 N value (-204 ± 35‰). Thus, the LNMS results [1] suggest that (A) the atmosphere is unstable at <15 km, (B) N 2 is not well-mixed >15 km, and (C) the cloud δ 15 N falls between Earth and the solar wind [12, 13]. Comparisons of the N 2 abundances and isotopic compositions for nitrogen, carbon, and oxygen to other Venus measurements will be discussed.

deep lower atmosphere↗
NASA NTRS2022

Model Spread in Tropical Low Cloud Feedback Tied to Overturning Circulation Response to Warming

Among models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6), here we show that the magnitude of the tropical low cloud feedback, which contributes considerably to uncertainty in estimates of climate sensitivity, is intimately linked to tropical deep convection and its effects on the tropical atmospheric overturning circulation. First, a reduction in tropical ascent area and an increased frequency of heavy precipitation result in high cloud reduction and upper-tropospheric drying, which increases longwave cooling and reduces subsidence weakening, favoring low cloud reduction (Radiation-Subsidence Pathway). Second, increased longwave cooling decreases tropospheric stability, which also reduces subsidence weakening and low cloudiness (Stability-Subsidence Pathway). In summary, greater high cloud reduction and upper-tropospheric drying (negative longwave feedback) lead to a more positive cloud feedback among CMIP6 models by contributing to a greater reduction in low cloudiness (positive shortwave feedback). Varying strengths of the two pathways contribute considerably to the intermodel spread in climate sensitivity.

Atmospheric dynamics↗
NASA NTRS2026

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen↗
DOE OSTI2024

Anticipating Optical Availability in Hybrid RF/FSO Links Using RF Beacons and Deep Learning

Radiofrequency (RF) communications offer reliable but low data rates and energy-inefficient satellite links, while free-space optical (FSO) promises high bandwidth but struggles with disturbances imposed by atmospheric effects. A hybrid RF/FSO architecture aims to achieve optimal reliability along with high data rates for space communications. Accurate prediction of dynamic ground-to-satellite FSO link availability is critical for routing decisions in low-earth orbit constellations. In this paper, we propose a system leveraging ubiquitous RF links to proactively forecast FSO link degradation prior to signal drops below threshold levels. This enables pre-calculation of rerouting to maximally maintain high data rate FSO links throughout the duration of weather effects. We implement a supervised learning model to anticipate FSO attenuation based on the analysis of RF patterns. Through the simulation of a dense lower earth orbit (LEO) satellite constellation, we demonstrate the efficacy of our approach in a simulated satellite network, highlighting the balance between predictive accuracy and prediction duration. An emulated cloud attenuation model is proposed to provide insight into the temporal profiles of RF signals and their correlation to FSO channel dynamics. Our investigation sheds light on the trade-offs between prediction horizon and accuracy arising from RF beacon numbers and proximity.

FSO availability↗
DOE OSTI2025

Unveiling the lithium-ion transport mechanism in Li{sub 2}ZrCl{sub 6} Solid-State Electrolyte {ital via} deep learning-accelerated molecular dynamics simulations.

Lithium zirconium chlorides (LZCs) present a promising class of cost-effective solid electrolytes for next-generation all-solid-state batteries. The unique crystal structure of LZCs plays a crucial role in facilitating lithium-ion mobility, which further affects the electrochemical performance. To understand the underlying mechanism governing ion transport, we employed deep learning-accelerated molecular dynamics simulation on Li2ZrCl6 (trigonal alpha- and monoclinic beta-LZC), focusing specifically on the zirconium coordination environment. Our results reveal that disordered alpha-LZC exhibits the highest ionic conductivity, while beta-LZC demonstrates significantly lower conductivity, closely aligning with experimental findings. The study confirms that across all phases, lithium migration proceeds via the site-to-site hopping mechanism, where variations in site residence times critically impact the overall ionic conductivity. In alpha-LZCs, lithium ions prefer to anisotropically diffuse across interlayers as the result of a lower energy barrier, driven primarily by collective diffusion. In contrast, lithium ions in beta-LZC primarily isotropically diffuse within the intralayer, hindered by higher energy barriers and determined by individual diffusion. The variation in ZrCl6 2- octahedral unit softening, induced by the specific layered arrangement of zirconium atoms, emerges as a critical determinant of the energy barriers across the LZC phases. These atomic-scale insights into the transport processes provide valuable guidance for the rational design and optimization of LZCs-based electrolytes, accelerating their practical application in advanced energy storage technologies.

Guo, Hanzeng↗
DOE OSTI2026

Aerosol-deep convection interaction based on joint cell-thermal tracking in Large Eddy Simulations during the TRACER campaign

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Atmospheric, Non-Combusting Droplet Sizing and Spray Imaging Results From a Non-Proprietary Aero Gas Turbine Engine Pressure Swirl Atomizer using Shadowgraphy and Planar Laser Scatter

Members from industry and federal agencies of the United States have developed a collaborating group focused on improving the understanding of the atomization processes common to gas turbine engines. The group is aimed on providing high quality data using x-ray diagnostics in the internal geometry and the near-field dense spray as well as optical diagnostics in the visible spectrum, downstream of the nozzle. This paper reports results from one of the two non-proprietary injectors designs from the group: the primary-secondary injector. In particular, we characterize the spray from only the primary, pressure-swirl atomizing circuit using water through the nozzle. We observed Sauter mean diameter decreased with increased water pressure drop across the nozzle. SMD was also collected at three axial distances and showed decreased size with distance from the nozzle. Planar laser sheet droplet scattering provided qualitative assessment of the spray. Higher water pressure drops provided better atomization than lower pressure drops. The addition of swirling air flow through the injector alleviates and improves the atomization quality, particularly at the lower water pressure drops.

optical diagnostics↗
DOE OSTI2026

Aragonite saturation horizon variability along North Pacific seamounts and implications for deep-sea coral reefs

The 2014 discovery of living deep-sea coral reefs along the Northwest Hawaiian Islands (NWHI) and lower Emperor Seamount Chain (ESC), despite the North Pacific’s shallow aragonite saturation horizon (ASH) and high CaCO3 dissolution rates, underscores the need to understand the local seawater chemistry that allows these reefs to persist. We investigated seawater carbonate chemistry using discrete samples along the NWHI and ESC from two cruises ~1 year apart (08/26/21 – 09/26/21, 09/09/22 – 10/24/22). Across the two cruises, ASH depth difference ranged from 15 to 77 m. Since the Pacific ASH shoals by 1–2 m yr?¹, this long-term trend cannot explain the magnitude of ASH change observed between cruises. Temperature-salinity plots similarly indicate no major shifts in intermediate water masses that could account for these changes. Instead, ASH depth variability was primarily governed by localized biogeochemical processes, namely changes in intermediate water respiration and CaCO3 dissolution. Indicators for dissolution (TA*) and respiration (AOU) suggest changes in ASH depth were driven by changes in dissolution at the northern- and southern-most sites, whereas respiration exerted stronger control at central sites. Combining 2021 and 2022 data with data from 2014 – 2019 (excluding 2018) revealed high interannual ASH variability, by as much as >200 m at one site. Deep-sea coral reefs across the NWHI and ESC currently reside close to the ASH depth and likely experience seasonal and interannual shifts between under- and supersaturation. As ocean acidification progresses however, persistent exposure to undersaturated seawater could further threaten these critical deep-sea ecosystems.

coral reefs↗
DOE OSTI2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology↗
DOE OSTI1968

Kryptonate Hydrogen Detection System (Final Report)

A prototype model of a multipurpose instrument which demonstrates the applicability of the Kryptonate® technique for detecting hydrogen gas was developed. This report describes the construction of the instrument and presents a laboratory evaluation of its performance. Performance was excellent. The instrument was designed to detect hydrogen in air at concentrations of 0-3% by volume, and to detect hydrogen in nitrogen or other inert gas at concentrations of 0-10% by volume. Other detection levels (both higher and lower) could be set if required. Ultimate response times can be made of the order of 0.5 seconds. The instrument is an all solid state device operating from 120V 60 Hz power source. The instrument has been designed to enable modifications to be made with a minimum amount of difficulty.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

High-Resolution Global Ocean Simulation in the SWOT ERA: Introducing ECCO Llc4320v2

The Surface Water and Ocean Topography (SWOT) mission is opening up new opportunities to evaluate and drive improvement in km-scale global ocean and atmosphere-ocean models via its simultaneous swath observations of sea-surface height, wind speed, and significant wave height down to 2 km scales globally. Motivated by this, we have initiated a collaborative effort at NASA Ames to run a new global ocean-sea-ice simulation in MITgcm at a nominal 1/48-deg resolution of the year 2023 that enables direct comparisons with SWOT observations. New features relative to a prior simulation at a similar resolution of the year 2012 include much more realistic tidal forcing, thermodynamic coupling in ice-shelf cavities, high-frequency hourly atmospheric forcing, much improved river runoff, double the vertical resolution in the deep ocean (173 vs 90 levels), updated bathymetry including improvements in finescale bathymetry derived from SWOT, and updated vertical mixing scheme parameters that improve the equatorial Pacific circulation.

ECCO↗
NASA NTRSDate not supplied

From Exploration Flight Test-1 to Artemis II--A NASA Langley's Orion Aerosciences Overview

The Orion Aerosciences program at NASA Langley has played a central role in advancing the aerodynamic and aeroheating prediction capabilities required for the Orion crew vehicle’s return from deep space. This presentation provides a technical overview of aerosciences contributions spanning Exploration Flight Test-1 (EFT-1), Artemis I, and the ongoing post-flight analysis of Artemis II. EFT-1 provided the first high-energy entry dataset for Orion, enabling critical validation of aerodynamic force and moment predictions, static and dynamic stability characteristics, and aeroheating environments at relevant flight Mach and Reynolds numbers. Flight-derived pressure data were used to refine the Flush Air Data System (FADS) methodology for atmospheric density reconstruction and to improve Best Estimated Trajectory (BET) solutions. The EFT-1 data also offered key insights into heat shield performance, including char layer recession, in-depth thermal response, and material retention behavior under flight conditions, informing updates to both thermal response models and uncertainty quantification practices. Building on EFT-1, Artemis I extended the database to true lunar-return conditions. Observations of heat shield performance, including localized char loss, bondline response, and recession variability, provided an unprecedented opportunity to reassess Thermal Protection System (TPS) and aeroheating modeling assumptions. Aerodynamic reconstruction efforts incorporated improved FADS calibration, enhanced atmospheric modeling, and refined force and moment databases to reduce trajectory and load uncertainties. Aeroheating comparisons between pre-flight predictions and flight data enabled targeted model updates, particularly in transitional flow environments and wake heating regions. For Artemis II, these lessons were systematically incorporated into the pre-flight prediction process. Updates included refined aerodynamic databases anchored to flight-validated corrections, improved density estimation and BET methodologies using enhanced database interpolation algorithm and FADS modeling, and revised aeroheating design environments informed by Artemis I material response observations. By the time of the workshop, Artemis II post-flight analysis will be underway, and preliminary findings will be presented where available, including early comparisons of aerodynamic reconstruction, atmospheric density estimation, and thermal protection system performance relative to updated predictions. Collectively, this body of work is a testament to the dedicated and multidisciplinary team whose sustained efforts have contributed to the program’s success and to the progressive maturation of Orion aerosciences modeling through numerical modeling, ground and flight data assimilation. The integrated advancement of aerodynamics, trajectory reconstruction, FADS-based density estimation, and aeroheating analysis has reduced predictive uncertainty and strengthened confidence for future crewed lunar and deep-space missions.

Orion↗
NASA NTRSDate not supplied

The Aeolus-Earth DWTS Heliophysics Mission

The Aeolus-Earth Mission (DWTS-Helio) is a recently selected NASA Heliophysics investigation that will apply the innovative Doppler Wind Temperature Sounder (DWTS) technique to the Space Atmosphere Interaction Region (SAIR) at ~105-180 km. The technique, invented by Gordley & Marshall (2011), applies the Doppler Scanning with Gas Filter (DSGF) technique using a cryo-cooled MWIR radiometer to view the limb of the atmosphere from LEO (orbital velocity creates the Doppler shifts required by the technique). For this implementation of DWTS, a Nitric Oxide (NO) low pressure gas cell is used. The limb of the atmosphere is observed from a spacecraft at orbital velocity, and as an observed air volume passes through the field of view, this velocity creates a set of Doppler-shifted images. These images are used to create Doppler Integrated Pass (DIP) signals, from which atmospheric temperature and wind profiles are extracted (it may be considered a converse of the successful in-flight calibration of gas cells used for the HALOE instrument). The technique is relative, removing the need for absolute radiances, and the signal-to-noise ratio for this technique is high, resulting in good measurement precision. Different gas cells can be used to create different altitude coverage and may be combined to measure a more continuous altitude range. For example, using a NO cell captures the lower atmosphere from 30-50km as well as the SAIR, while using the 13 isotopologue of CO2 would capture 50-120km. Due to the desired data volume as well as power and thermal considerations, this initial Aeolus-Earth flight will be more suited for a ‘hosted’ payload on an Orbital Maneuvering Vehicle platform instead of the ‘free-flyer’ option originally investigated. Lastly, the technique is sufficiently powerful that a two-channel system could produce full Mars atmosphere data not currently possible.

DWTS↗
NASA NTRSDate not supplied

Artemis CubeSats Help Advance Exploration of the Moon, Mars, and Beyond

On April 1, NASA launched the Artemis II mission – the first crewed mission of the Artemis campaign. The nine-day lunar flyby launched on the agency’s SLS (Space Launch System) rocket and had four astronauts test the Orion spacecraft in high Earth orbit and in deep space. Four 12U CubeSats also launched on the mission, housed within the SLS’s Orion stage adapter (OSA). The spacecraft were deployed approximately five-and-a-half hours into the flight, following Orion separation and departure from SLS, as the SLS interim cryogenic propulsion stage (ICPS) and the attached OSA were in a high Earth orbit on an atmospheric disposal trajectory. All four CubeSats were successfully deployed from the launch vehicle. Deployment statuses of the spacecraft, along with updates about the SLS rocket and Artemis missions, are reported in this paper. The paper will also discuss opportunities for CubeSat payloads on future Artemis missions.

David Hitt↗
NASA NTRSDate not supplied

Artemis CubeSats Help Advance Exploration of the Moon, Mars, and Beyond

On April 1, NASA launched the Artemis II mission – the first crewed mission of the Artemis campaign. The nine-day lunar flyby launched on the agency’s SLS (Space Launch System) rocket and had four astronauts test the Orion spacecraft in high Earth orbit and in deep space. Four 12U CubeSats also launched on the mission, housed within the SLS’s Orion stage adapter (OSA). The spacecraft were deployed approximately five-and-a-half hours into the flight, following Orion separation and departure from SLS, as the SLS interim cryogenic propulsion stage (ICPS) and the attached OSA were in a high Earth orbit on an atmospheric disposal trajectory. All four CubeSats were successfully deployed from the launch vehicle. Deployment statuses of the spacecraft, along with updates about the SLS rocket and Artemis missions, are reported in this paper. The paper will also discuss opportunities for CubeSat payloads on future Artemis missions.

Russell Lane↗
NASA NTRS1983

The Deep Space Network: A Radio Communications Instrument for Deep Space Exploration

The primary purpose of the Deep Space Network (DSN) is to serve as a communications instrument for deep space exploration, providing communications between the spacecraft and the ground facilities. The uplink communications channel provides instructions or commands to the spacecraft. The downlink communications channel provides command verification and spacecraft engineering and science instrument payload data.

N A Renzetti↗