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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Analysis of Satellite and Airborne Imagery for Detection of Water Hyacinth and Other Invasive Floating Macrophytes and Tracking of Aquatic Weed Control Efficacy

Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed an 80 percent overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

Agriculture↗
NASA NTRS2017

Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer, One Quarter Scale Prototype Thermal Testing

The Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer (SPHEREx) instrument has been proposed as NASA Small Explorer (SMEX) and Medium Explorer (MIDEX) missions designed to perform an all-sky near-infrared survey. The primary science objective of the SPHEREx instrument is the mapping and cataloging of data on galaxy red shifts and absorption spectra. The SPHEREx instrument utilizes a linear variable band pass filter to provide discrete spectral coverage of the 0.75 to 5.0 μm range. The nominal on-orbit mission lifetime for the instrument is two years with continuous primary science imaging. The SPHEREx instrument will be placed in a near-circular LEO sun-synchronous terminator orbit with a mean altitude of 600 km, and solar beta angles ranging from 59° to 90°. A passive V-groove radiator cooling system was selected for the SPHEREx instrument. This design was chosen for its simplicity and lack of vibration. It includes five radiator stages with the coldest two stages providing temperatures below 80K and 55K for the 2.5μm and 5.3μm detectors respectively. A one quarter scale thermal prototype was constructed to characterize the performance of the SPHEREx thermal control subsystem. This prototype was directly derived and scaled from the current flight design, and accurately replicates all heat flow paths at scale. The prototype was tested in two bounding hot flight-like environments in the Cryogenic Systems Engineering, Advanced Thermal Technology Lab at NASA’s Jet Propulsion Laboratory. Following testing, a previously developed one quarter scale thermal model was correlated to the two conditions seen in test. The resultant correlated model is able to predict the prototype test temperatures to within 1K for all critical radiator stages. An overview of the thermal control design approach, the test configuration, and test and correlation results are presented.

Bolton, Douglas A.↗
NASA NTRS2019

Thermal History Mapping Technology for Turbine Engine Diagnostics

The infusion of ceramic matrix composites (CMCs) in next generation gas turbines represents daunting challenges as the failure of protective coating, known as Environmental Barrier Coating (EBC), means little remnant life of CMC components. Consequently reliable lifing is critical to the success of CMC components. Accurate thermal mapping of EBC in rig and engine test is of paramount importance because temperature is the most critical variable for EBC life. Current temperature measurement technologies include thermocouples, pyrometers, IR cameras, and thermal paints. Thermocouples require a passage to access the components and pyrometers and IR cameras require line-of-sight. Thermal paints are based on color-sensitive pigments that visually indicate the temperature that a component experienced. Thermal paints do not require line-of-sight, however, they have a low resolution and a limited temperature capability (~1400°C). Thermal history coating is based on oxide ceramic which luminesces when excited with a light source. The luminescence changes when the material's structure changes triggered by heat impact. The maximum temperature to which the material was exposed can be determined from the luminescence change. This paper describes the principles of this new technique and demonstrates its capabilities for EBCs exposed to excess of 1500°C.

Lee, Kang N.↗
NASA NTRS2020

The Age of Surface-Exposed Ice Along the Northern Margin of the Greenland Ice Sheet

Each summer, surface melting of the margin of the Greenland Ice Sheet exposes a distinctive visible stratigraphy that is related to past variability in subaerial dust deposition across the accumulation zone and subsequent ice flow toward the margin. Here we map this surface stratigraphy along the northern margin of the ice sheet using mosaicked Sentinel-2 multispectral satellite imagery from the end of the 2019 melt season and finer-resolution WorldView-2/3 imagery for smaller regions of interest. We trace three distinct transitions in apparent dust concentration and the top of a darker basal layer. The three dust transitions have been identified previously as representing late-Pleistocene climatic transitions, allowing us to develop a coarse margin chronostratigraphy for northern Greenland. Substantial folding of late-Pleistocene stratigraphy is observed but uncommon. The oldest conformal surface-exposed ice in northern Greenland is likely located adjacent to Warming Land and maybe up to ~55 thousand years old. Basal ice is commonly exposed hundreds of meters from the ice margin and may indicate a widespread frozen basal thermal state. We conclude that the ice margin across northern Greenland offers multiple opportunities to recover paleoclimatically distinct ice relative to previously studied regions in southwestern Greenland.

Joseph A Macgregor↗
NASA NTRS2020

The bioclimatic extent and pattern of the cold edge of the boreal forest: the circumpolar taiga-tundra ecotone

Current configurations of forest structure at the cold edge of the boreal may help understand the future of ecosystem functioning in high northern latitudes. The circumpolar biome boundary at the boreal (taiga) forest and tundra interface is an ecological transition zone (taiga-tundra ecotone; TTE) experiencing changes that affect its forest structure. We accounted for the TTE's horizontal forest structure with an estimate of its extent and pattern as represented by tree canopy cover (TCC). We quantified TCC patterns with an algorithm that describes its spatial gradient, and summarized landscape patterns of structure to represent heterogeneity, capturing abrupt, diffuse, and uniform forest at mesoscales. We used these landscape patterns to constrain the spatial extent of sparse and open canopy forest, and non-forest (forest-adjacent) edge that defines the TTE extent. The resulting map of the TTE extent is based on forest structure spatial patterns resolved at 30 m, highlights structural variability across landscapes, and helps distinguish tundra from boreal domains. We classified 14 594 landscapes as those associated with the TTE within a circumpolar bioclimatic envelope (11.575 million km2), where 44.83% of the area of these landscapes were forest and non-forest edge, yet 36.43% contributed to the TTE extent. We report the overall extent of the TTE (3.032 million km2) across North America and Greenland (53%), and Eurasia (47%), where 0.697 million km2 is non-forest edge, 0.549 million km2 is sparse forest, and 1.787 million km2 is open canopy forest. Diffuse forest landscapes dominate the TTE (79%), and abrupt landscapes (~19%) indicate portions of the TTE where sparse forest and non-forest edge are the prevailing structural patterns. This account of the TTE quantifies the area of the cold edge of the boreal forest where previous global estimates show high discrepancies, and can help target monitoring and prediction of circumpolar dynamics.

Paul M Montesano↗
NASA NTRSDate not supplied

Constraints on Wildfire Smoke Source Strength, Injection Height, and Particle Evolution

Aerosol sources are represented in climate and air quality models with an injection height and a source strength. We have applied a combination of Multi-angle Imaging SpectroRadiometer (MISR) and MODerate resolution Imaging Spectroradiometer (MODIS) observations to help constrain these two key model variables for wildfire smoke plumes. Injection height is obtained from MISR stereo imagery, which makes it possible to map plume elevation and estimate the associated motion vectors at plume altitude near-source, where contrast features in the plume can be identified in the multi-angle views. A current limitation of injection-height mapping is the relatively narrow MISR swath width (~380 km) and 10:30 AM equator crossing time on the day side of Earth. However, upcoming missions, as well as advanced imagers on geostationary platforms, promise to greatly expand the spatial and temporal range over which this technique can be applied. We estimate source strength by matching forward-simulated plume aerosol optical depth (AOD) from models with AOD snapshots retrieved from MODIS observations. This technique works best for large, isolated plumes common in boreal forest, and tends to fail where plume AOD is low and/or background AOD, distinct from the specific source of interest, is high. These two approaches for constraining aerosol modeling with satellite observations have been the subject of ongoing AeroCom/AeroSat studies by our group. A third effort applies the combination of MISR plume heights, wind vectors, and particle microphysical property constraints to infer smoke-plume particle evolution processes and timescales, including the emission and subsequent evolution of black and brown smoke. In this presentation, we will provide an update on the status of these efforts.

wildfire↗
NASA NTRSDate not supplied

Mapping National Forest Aboveground Biomass in Mexico by Integrating GEDI, Sentinel‐1 and Sentinel‐2 Data

Accurate mapping of forest aboveground biomass density (AGBD) is required to better understand the role of forests in the global carbon cycle and to support international policies for climate change mitigation and adaptation. Mexico is one of the countries having great potential for the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (or UN-REDD program) and there is a growing demand for unbiased Monitoring Reporting Verification systems at a national level. As an effort under NASA’s Carbon Monitoring System (CMS) program, we developed a machine learning model using multi-stream remote sensing measurements as well as topographic data to create a high spatial resolution AGBD map (~100 m) over Mexico (circa 2020). The remote sensing data includes Global Ecosystem Dynamic Investigation (GEDI) lidar, Sentinel 1 Synthetic-Aperture Radar (SAR), and Sentinel-2 multispectral imagery (MSI). GEDI onboard the International Space Station provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. Our analysis indicates that the developed random forest model can capture 63 % of the spatial variation (RMSE = 33.7 Mg/ha) of AGBD of Mexican forests. We find that shortwave infrared bands of Sentinel-2 MSI and topographical variables from elevation data are the most important variables in the developed AGBD model. Our study highlights methodological opportunities in synergistic uses of multiple sensors for large-scale forest AGBD mapping and shows potential for retrospective analysis and operational monitoring of forest AGBD and its dynamics.

Taejin Park↗
NASA NTRS1986

Spatial and temporal variability of infrared-observable properties of the Jovian atmosphere: A partial survey

Examination of infrared characteristics of the Jovian atmosphere are made using Voyager IRIS mapping from 1979, groud based scanning from 1979-1983, and ground based mapping from 1983 to the present. In general, there is a strong correlation between tropospheric thermal properties and the visual cloud albedo for all observations. The Voyager IRIS maps show no strong evidence for day/night differences. Temperature differences diminish with depth in the troposphere. Temporal changes over several weeks indicate a high correlation between thermal and visual properties, although no changes in the distribution of para H2 and ortho H2 are seen. Stratospheric banded organization is different from the troposphere, and there is a temperature enhancement near the north magnetic pole. The spatial distributions of ammonia gas and ammonia ice absorption are different. Stratospheric temperatures exhibit seasonal hemispheric asymmetry. Other temperature changes at and below the 150-mb level correlate with changes in the Jovian visual structure. The stratospheric temperature field is uncorrelated with visual features or temperatures below the 150-mb level. Elevated temperatures are observed near both north and south magnetic pole positions. Both the meridional positions and the relative intensities of stratospheric banded organization change significantly, especially after 1982. Ground based mapping confirms a correlation between temperatures and various measures of cloud distribution. Complex and unexpected characteristics are observed in the stratospheric temperature field; these include dramatic temporal changes on short time scales.

Orton, Glenn S.↗
NASA NTRS2014

Management and Climate Contributions to Satellite-Derived Active Fire Trends in the Contiguous United States

Fires in croplands, plantations, and rangelands contribute significantly to fire emissions in the United States, yet are often overshadowed by wildland fires in efforts to develop inventories or estimate responses to climate change. Here we quantified decadal trends, interannual variability, and seasonality of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of active fires (thermal anomalies) as a function of management type in the contiguous U.S. during 2001-2010. We used the Monitoring Trends in Burn Severity database to identify active fires within the perimeter of large wildland fires and land cover maps to identify active fires in croplands. A third class of fires defined as prescribed/other included all residual satellite active fire detections. Large wildland fires were the most variable of all three fire types and had no significant annual trend in the contiguous U.S. during 2001-2010. Active fires in croplands, in contrast, increased at a rate of 3.4 percent per year. Cropland and prescribed/other fire types combined were responsible for 77 percent of the total active fire detections within the U.S and were most abundant in the south and southeast. In the west, cropland active fires decreased at a rate of 5.9 percent per year, likely in response to intensive air quality policies. Potential evaporation was a dominant regulator of the interannual variability of large wildland fires, but had a weaker influence on the other two fire types. Our analysis suggests it may be possible to modify landscape fire emissions within the U.S. by influencing the way fires are used in managed ecosystems.

Satellite-derived↗
DOE OSTI2025

Flood Susceptibility Mapping Using Machine Learning and Geospatial-Sentinel-1 SAR Integration for Enhanced Early Warning Systems

This study presents a comprehensive framework for flood susceptibility mapping by integrating geospatial factors with both statistical and machine learning models. Thirteen Flood-related factors, including DEM, slope, TWI, NDVI, etc., are extracted as features of models, and historical flood data derived from Sentinel-1 SAR from 2018 to 2023 are used as the target variables of the models. These datasets are analyzed using a frequency-based statistical model and three machine learning models, including Random Forest, XGBoost, and CNN, to generate flood susceptibility maps. The performance of each model is evaluated through AUC; and SHAP scores are separately generated for Machine learning (ML) models to explain each feature contribution in the ML model. The generated susceptibility maps are validated by high-flood-risk locations monitored by flood sensors, BLE inundation models, and flood-prone areas suggested by the Local Community Task Force. The results indicate that the XGBoost model outperforms all other models, with an AUC of 0.92 and demonstrates the highest alignment with recommended high-flood-risk locations, while the frequency-based statistical model showed the weakest performance with an AUC of 0.65. SHAP value graphs highlight the elevation, slope, and TWI as the most influential features across all models. The susceptibility maps generated by the machine learning model show strong agreement with the BLE map and high-flood-risk areas identified by the local Community Task Force.

Google Engine↗
DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗
DOE OSTI2023

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

58 GEOSCIENCES↗
NASA NTRS2019

Diurnally Migrating Lunar Water: Evidence from Ultraviolet Data

Data from the Lunar Reconnaissance Orbiter Lyman Alpha Mapping Project and Diviner are consistent with surface water on the Moon varying in abundance with both terrain type and local time/temperature. A thermal desorption model including latitudinally varying desorption activation energy reproduces the observations. We interpret the observed variability in spectral slopes as water molecules in the uppermost lunar regolith (<1% of a monolayer) thermally adsorbing and desorbing from grains depending upon the local temperature and availability of chemisorption sites. The Lyman Alpha Mapping Project data also demonstrate that in the Earth's magnetotail, where the solar wind source of protons is absent, a decrease in H2O on the surface is not observed. This rules out a steady state process involving aprompt solar wind source and favors a migration mechanism for the distribution of adsorbed water onthe Moon.

Diurnally↗
DOE OSTI2024

Simulated Feasibility of 3-D Lightning Mapping From Space

In addition to the awe it inspires, lightning can illuminate the microphysical processes hidden away within deep convection. The current generation of space-based lightning mapping uses mostly 2-D optical imaging to connect overall flash characteristics to their parent storm dynamics, but are missing a dimension’s worth of information. With lightning now classified as an essential climate variable, future spaceborne mappers will need improved capabilities to take advantage of the 3-D structure of lightning flashes to support meteorological and climate modeling. We report here on a study of the feasibility of high-resolution 3-D lightning mapping using a radio frequency (RF)-based network of satellites from low-Earth orbit (LEO). Lightning sources are simulated using existing lightning mapping array (LMA) tools, modified for orbital detection, and spatially reconstructed using a Levenberg–Marquardt geolocation algorithm to assess sources of uncertainty in these solutions. We analyze the benefits and limitations of this approach compared to existing orbital and ground-based methods. Results of this study show that lightning can be mapped in 3-D with a vertical location accuracy better than 2 km using as few as five satellites in LEO capable of measuring the time-of-arrival of impulsive RF signals in the very high-frequency (VHF) band. The consequence of this study is that high-resolution, spaceborne 3-D mapping of lightning is achievable across most of the globe, having crucial implications for our understanding of not only lightning, but also severe weather development, climate science, and more.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Citizen and machine learning-aided high-resolution mapping of urban heat exposure and stress

Abstract Through conversion of land cover to more built-up, impervious surfaces, cities create hotter environments than their surroundings for urban residents, with large differences expected between different parts of the city. Existing measurements of ambient air temperature and heat stress, however, are often insufficient to capture the intra-urban variability in heat exposure. This study provides a replicable method for modeling air temperature, humidity, and moist heat stress over the urban area of Chapel Hill while engaging citizens to collect high-temporal and spatially-resolved air temperature and humidity measurements. We use low-cost, consumer-grade sensors combined with satellite remote sensing data and machine learning to map urban air temperature and relative humidity over various land-cover classes to understand intra-urban spatial variability of ambient heat exposure at a relatively high resolution (10 m). Our findings show that individuals may be exposed to higher levels of air temperature and moist heat stress than weather station data suggest, and that the ambient heat exposure varies according to land cover type, with tree-covered land the coolest and built-up areas the warmest, and time of day, with higher air temperatures observed during the early afternoon. Combining our resulting dataset with sociodemographic data, policymakers and urban planners in Chapel Hill can use data output from this method to identify areas exposed to high temperature and moist heat stress as a first step to design effective mitigation measures.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Physical and Radiative Characteristics and Long Term Variability of the Okhotsk Sea Ice Cover

Much of what we know about the large scale characteristics of the Okhotsk Sea ice cover comes from ice concentration maps derived from passive microwave data. To understand what these satellite data represents in a highly divergent and rapidly changing environment like the Okhotsk Sea, we analyzed concurrent satellite, aircraft, and ship data and characterized the sea ice cover at different scales from meters to tens of kilometers. Through comparative analysis of surface features using co-registered data from visible, infrared and microwave channels we evaluated how the general radiative and physical characteristics of the ice cover changes as well as quantify the distribution of different ice types in the region. Ice concentration maps from AMSR-E using the standard sets of channels, and also only the 89 GHz channel for optimal resolution, are compared with aircraft and high resolution visible data and while the standard set provides consistent results, the 89 GHz provides the means to observe mesoscale patterns and some unique features of the ice cover. Analysis of MODIS data reveals that thick ice types represents about 37% of the ice cover indicating that young and new ice represent a large fraction of the lice cover that averages about 90% ice concentration, according to passive microwave data. A rapid decline of -9% and -12 % per decade is observed suggesting warming signals but further studies are required because of aforementioned characteristics and because the length of the ice season is decreasing by only 2 to 4 days per decade.

Nishio, Fumihiko↗
DOE OSTI2023

Field Validation of Air-Source Heat Pumps for Cold Climates

Heating energy is the largest end-use for U.S. residential buildings accounting for approximately one-third of residential building energy consumption (EIA 2021). Historically, air-source heat pumps have been limited to temperate climates because of subpar performance at extremely cold outdoor air temperatures. However, recent advances to cold-climate air-source heat pump technology, which typically rely on inverter-driven, variable-speed compressors and variable-speed fans, have significantly improved low-temperature heat pump performance enabling the technology to save energy for many homes in cold climates. The primary objective of this project was to measure in-field performance of centrally ducted, variable-capacity air-source heat pumps in cold climates to validate performance and develop field-based performance maps. The project focused on quantifying heat pump performance at cold temperatures. The sites identified for the study were primarily located in the Northwest United States since homes in the region tend to have all-electric space heating systems and high-efficiency heat pumps have been incentivized in the region for several years. NREL partnered with Ecotope, Inc., a small energy consulting firm located in Seattle, WA, for site recruitment, monitoring equipment installation, data quality management. All the sites included in the study had previously installed a high-efficiency, central heat pump system. One site was in a Denver, CO suburb, which was the only dual fuel heat pump in the study. We used airside and power measurements, collected at 5-second intervals, to quantify heat pump capacity, coefficient of performance (COP), and auxiliary heater energy consumption. We developed algorithms to automatically determine the heat pump operating mode including defrost and auxiliary heating operation. A whole-house thermal and duct audit was completed during the initial site visit to estimate winter heating loads and assess heat pump sizing. Whole-home heating design loads were calculated at ASHRAE 99% design temperatures and compared to manufacturer-reported maximum capacities to assess the heat pump sizing at each site.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1976

Study of the lower stratospheric thermal structure and total ozone from Nimbus-4 IRIS

The global distribution of temperature in the stratosphere from 100 to 10 mbar and the total ozone in the atmosphere are remotely sensed from the Nimbus-4 IRIS measurements for a period of about one year. The temperature and ozone data are presented in the form of monthly mean global maps. The standard deviations of temperature and ozone with respect to zonal averages are calculated. The mean and the variable state of the stratosphere are discussed with the help of these observations. The lower stratosphere in the tropical regions reveals a significant wave number one pattern in the circulation. The Arctic and Antarctic stratospheric winter circulation regimes display a different behavior apparently due to the ocean and orographic differences.

Prabhakara, C.↗