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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Precision orbit determination of altimetric satellites

The ability to determine accurate global sea level variations is important to both detection and understanding of changes in climate patterns. Sea level variability occurs over a wide spectrum of temporal and spatial scales, and precise global measurements are only recently possible with the advent of spaceborne satellite radar altimetry missions. One of the inherent requirements for accurate determination of absolute sea surface topography is that the altimetric satellite orbits be computed with sub-decimeter accuracy within a well defined terrestrial reference frame. SLR tracking in support of precision orbit determination of altimetric satellites is significant. Recent examples are the use of SLR as the primary tracking systems for TOPEX/Poseidon and for ERS-1 precision orbit determination. The current radial orbit accuracy for TOPEX/Poseidon is estimated to be around 3-4 cm, with geographically correlated orbit errors around 2 cm. The significance of the SLR tracking system is its ability to allow altimetric satellites to obtain absolute sea level measurements and thereby provide a link to other altimetry measurement systems for long-term sea level studies. SLR tracking allows the production of precise orbits which are well centered in an accurate terrestrial reference frame. With proper calibration of the radar altimeter, these precise orbits, along with the altimeter measurements, provide long term absolute sea level measurements. The U.S. Navy's Geosat mission is equipped with only Doppler beacons and lacks laser retroreflectors. However, its orbits, and even the Geosat orbits computed using the available full 40-station Tranet tracking network, yield orbits with significant north-south shifts with respect to the IERS terrestrial reference frame. The resulting Geosat sea surface topography will be tilted accordingly, making interpretation of long-term sea level variability studies difficult.

Shum, C. K.↗
NASA NTRS1998

The Study of Effects of Time Variations in the Earth's Gravity Field on Geodetic Satellites

The temporal variations in the Earth's gravity field are the consequences of complex interactions between atmosphere, ocean, solid Earth, hydrosphere and cryosphere. The signal ranges from several hours to 18.6 years to geological time scale. The direct and indirect consequences of these variations are manifested in such phenomena as changes in the global sea level and in the global climate pattern. These signals produce observable geodetic satellites. The primary objectives of the proposed effects on near-Earth orbiting investigation include (1) the improved determination of the time-varying gravity field parameters (scale from a few hour to 18.6 year and secular) using long-term satellite laser rs ranging (SLR) observations to multiple geodetic satellites, and (2) the enhanced understanding of these variations with their associated meteorological and geophysical consequences.

Shum, C. K.↗
NASA NTRS2000

Teleconnection Linking Asian/Pacific Monsoon Variability and Summertime Droughts and Floods Over the United States

Major droughts and floods over the U.S. continent may be related to a far field energy source in the Asian Pacific. This is illustrated by two climate patterns associated with summertime rainfall over the U.S. and large-scale circulation on interannual timescale. The first shows an opposite variation between the drought/flood over the Midwest and that over eastern and southeastern U.S., coupled to a coherent wave pattern spanning the entire East Asia-North Pacific-North America region related to the East Asian jetstream. The second shows a continental-scale drought/flood in the central U.S., coupled to a wavetrain linking Asian/Pacific monsoon region to North America.

Lau, K. M.↗
NASA NTRS2012

Late-glacial and Holocene Vegetation and Climate Variability, Including Major Droughts, in the Sky Lakes Region of Southeastern New York State

Sediment cores from Lakes Minnewaska and Mohonk in the Shawangunk Mountains of southeastern New York were analyzed for pollen, plantmacrofossils, macroscopic charcoal, organic carbon content, carbon isotopic composition, carbon/nitrogen ratio, and lithologic changes to determine the vegetation and landscape history of the greater Catskill Mountain region since deglaciation. Pollen stratigraphy generally matches the New England pollen zones identified by Deevey (1939) and Davis (1969), with boreal genera (Picea, Abies) present during the late Pleistocene yielding to a mixed Pinus, Quercus and Tsuga forest in the early Holocene. Lake Minnewaska sediments record the Younger Dryas and possibly the 8.2 cal kyr BP climatic events in pollen and sediment chemistry along with an ~1400 cal yr interval of wet conditions (increasing Tsuga and declining Quercus) centered about 6400 cal yr BP. BothMinnewaska andMohonk reveal a protracted drought interval in themiddle Holocene, ~5700-4100 cal yr BP, during which Pinus rigida colonized the watershed, lake levels fell, and frequent fires led to enhanced hillslope erosion. Together, the records show at least three wet-dry cycles throughout the Holocene and both similarities and differences to climate records in New England and central New York. Drought intervals raise concerns for water resources in the New York City metropolitan area and may reflect a combination of enhanced La Niña, negative phase NAO, and positive phase PNA climatic patterns and/or northward shifts of storm tracks.

Drought↗
NASA NTRS2014

Surface Ozone Variability and Trends over the South African Highveld from 1990 to 2007

Surface ozone is a secondary air pollutant formed from reactions between nitrogen oxides (NOx = NO + NO2) and volatile organic compounds in the presence of sunlight. In this work we examine effects of the climate pattern known as the El Niño-Southern Oscillation (ENSO) and NOx variability on surface ozone from 1990 to 2007 over the South African Highveld, a heavily populated region in South Africa with numerous industrial facilities. Over summer and autumn (December-May) on the Highveld, El Niño, as signified by positive sea surface temperature (SST) anomalies over the central Pacific Ocean, is typically associated with drier and warmer than normal conditions favoring ozone formation. Conversely, La Niña, or negative SST anomalies over the central Pacific Ocean, is typically associated with cloudier and above normal rainfall conditions, hindering ozone production. We use a generalized regression model to identify any linear dependence that the Highveld ozone, measured at five air quality monitoring stations, may have on ENSO and NOx. Our results indicate that four out of the five stations exhibit a statistically significant sensitivity to ENSO at some point over the December-May period where El Niño amplifies ozone formation and La Niña reduces ozone formation. Three out of the five stations reveal statistically significant sensitivity to NOx variability, primarily in winter and spring. Accounting for ENSO and NOx effects throughout the study period of 18 years, two stations exhibit statistically significant negative ozone trends in spring, one station displays a statistically significant positive trend in August, and two stations show no statistically significant change in surface ozone.

NOx↗
NASA NTRS2018

The Aeolus Mission Concept, an Innovative Mission to Study the Winds and Climate of Mars

Aeolus is a mission to provide the first set of global, seasonal, and diurnal data to characterize winds and study the climate of Mars. Aeolus measures surface and atmospheric temperatures, aerosol abundances, and Doppler shifts in atmospheric spectral lines. The payload includes a system of four of a new type of miniaturized Spatial Heterodyne Spectrometer (SHS) paired to two orthogonal viewing telescopes that can measure CO2 (daytime absorption) and O2 (day and night emission) lines in the Martian atmosphere. The Thermal Limb Sounder (TLS) instrument measures atmospheric temperature profiles and aerosol (H2O ice clouds, dust) profiles, and the Surface Radiometric Sensor Package (SuRSeP) measures the total reflected solar radiance, and surface temperatures down to 140K. These combined spectral and thermal measurements will provide a new understanding of the global energy balance, dust transport processes, and climate cycles in the Martian atmosphere. The mission concept for Aeolus consists of a single sub-100 kg secondary spacecraft in a highly inclined orbit, allowing it to pass over all local times. Aeolus attains global coverage of the surface for a mission duration of one Martian year, to capture climate patterns during each Martian season. This paper gives an overview of the Aeolus payload, spacecraft, and the methodology used to mature the Aeolus mission concept.

Mauro, David↗
NASA NTRS2021

Tonlé Sap Food Security and Agriculture: Evaluating the Effects of Land Use and Hydrological Change on Ecosystem Vitality using Remotely-Sensed Data in the Tonlé Sap Lake Basin

Tonlé Sap Lake, the largest lake in Southeast Asia, is a critical source of fish and freshwater resources for the region. The health of this freshwater system is under pressure from accelerating dam construction, intensifying agriculture, deforestation, and changing climate patterns, forcing tradeoffs between immediate food security and the long-term vitality and productivity of the ecosystem. Efficient freshwater system monitoring is crucial to navigating these challenges. In collaboration with Conservation International, the Cambodian Ministry of Water Resources and Meteorology, and the Tonlé Sap Authority, we developed and tested remotely-sensed proxies for sub-indicators of the Freshwater Health Index (FHI), which is typically calculated using in situ datasets. We used landcover datasets derived from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), PROBA-V Vegetation sensor (VGT), Sentinel-2 Multispectral Imager (MSI), Advanced Very High Resolution Radiometer (AVHRR), and Envisat Medium Resolution Imaging Spectrometer (MERIS) as inputs to calculate land cover naturalness and bank modification. Additionally, we created a lake-level time series using a collection of altimetry data sources to estimate deviation from natural flow. We observed a decrease in landcover naturalness and a breakdown in the volume and regularity of annual lake levels from 2000-2020, reflecting increased pressure on water supply and agricultural productivity. At least 8% of forested areas in the basin were lost and rice harvest intensity increased over the course of the study period. These results will help our partners make informed decisions regarding freshwater management. Furthermore, our remotely-sensed FHI analysis can be replicated in other regions, providing decision makers with a snapshot of freshwater health in data-scarce environments.

Marco Vallejos↗
NASA NTRS2021

Bhutan Agriculture: Developing a Crop Mask for Rice and Creating a Data Collection Protocol Utilizing Remotely Sensed Data in Bhutan

Rice cultivation in Bhutan has been increasingly threatened by deteriorating soil health and outbreaks of diseases and pests associated with the global change in climate patterns. Field surveys, which the national government of Bhutan has relied on to monitor remote agricultural lands, are becoming increasingly overwhelmed by growing threats to agricultural health. To address these concerns, NASA DEVELOP partnered with the Department of Agriculture of Bhutan, the Bhutan Foundation, and the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER) and worked to increase the government of Bhutan’s agricultural monitoring capacity. Utilizing Earth observations including Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Shuttle Radar Topography Mission (SRTM), and Planet imagery, the DEVELOP team worked with NASA SERVIR and created a sampling protocol to identify rice plantations and supplement field surveys for more efficient agriculture monitoring. The analysis focused on districts Paro, Punakha, Samtse, Sarpang, Trongsa, Zhemgang, Wangdue Phodrang, and Samdrup Jongkhar in the year 2020 during the period of transplantation (June) to harvesting of rice (November). The team provided the partners with a sampling protocol for integrating NASA Earth observations into their crop monitoring methods, as well as a crop mask for rice identification and to aid crop management. The crop mask for rice was developed using the Random Forest (RF) classifier for the eight districts of Bhutan. Visually, the random forest model has proved to be more accurate and precise than the classification and Regression Tree model. Statistically, the Random Forest model was 91.8% accurate in identifying rice in Bhutan.

Yeshey Seldon↗
NASA NTRSDate not supplied

Runway Configuration Management with Offline Reinforcement Learning

Runway configuration management (RCM) is a challenging task, and it affects the efficiency of the National Airspace System (NAS) and airport surface operations significantly. Each airport, depending on the geometry, capacity, local climate patterns, etc. has multiple configurations for the runway usage for arriving and departing flights. Many factors such as the incoming/outgoing traffic load, wind direction and speed, convective weather, cloud ceiling and other environmental factors might affect the choice of a runway configuration at any point in time. However, other factors such as safety measures and regulations, noise abatement, capacity of each configuration, and preference of the air traffic controllers (ATCs) can also play a significant role in selecting the configuration. A sub-optimal selection of the runway configuration, or delay in making configuration changes might result in significant increase in taxi times for aircraft on the surface of the airport, fuel and energy use of the aircraft, and maintenance costs. It can also lead to safety concerns, such as an aircraft performing one or more go-arounds before being able to land. All these factors make RCM an extremely important and challenging decision-making process for the ATCs. The current state of practice sets the runway configuration by the ATCs based on relevant information available at the time including weather, traffic, noise abatement, safety bounds, etc. This makes the decision-making process subjective based on the accuracy of the available information and the bias in human decision making. Unfortunately, this approach yields poor results (e.g., significant delays) if the predicted outcomes are uncertain and their relative impact is not well understood. This is especially evident when the uncertainty increases the size of possible predicted outcomes (combinatorial explosion in possible scenarios) that cannot be handled by human reasoning. On the other hand, an automated approach based on machine intelligence can make use of historical data and search through all (or significant amount of) possible scenarios under uncertainty and make well-informed decisions.

Milad Memarzadeh↗
NASA NTRS2023

Farming the Future: An Approach to Precision Agriculture through UAS-based Thermal Scanners

Food waste is a global issue, and it is extremely prevalent in the United States (U.S.) where one-third of the food produced goes to waste. The most common item found in landfills is food waste, which is why it is one of the most significant contributors to global warming with 8%. These negative environmental impacts also return to affect agriculture, as global warming changes climate patterns and adversely affects farming practices. In addition, the resources that were used to grow the produce are also wasted, including money, water, and time. To tackle this problem at its roots, this paper includes a design of an unmanned thermal drone that can be a farmer’s third eye. This drone will scan over farms and provide data to the farmers about the health, ripeness, and moisture content of their crops through mounted thermal cameras and artificial intelligence. The information provided via these drones will help farmers to make more informed decisions about their crops, decreasing the chances that the crops will go bad in the field. These drones will be one of the first steps in preventing food waste, which will, in turn, help to reduce global emissions that result from farming.

UAS supported agriculture↗
NASA NTRS2023

Tropical Three-dimensional Cloud Climatology during El Niño Events with CALIPSO Level-3 Cloud Products

The El Niño–Southern Oscillation (ENSO) is a large-scale climatic phenomenon that originates in the tropical Pacific Ocean but affects global climate patterns. Its warm phase El Niño occurs irregularly every two to seven years and peaks in winter. A previous case study showed opposite cloud anomalies at high, middle and low altitude regions during a weak 2006/2007 El Niño and a moderate 2009/2010 El Niño, suggesting a non-linear response of tropical clouds to El Niño sea surface temperature (SST) forcing. To further understand the cloud response to SST, we examine the three-dimensional (3-D) cloud anomalies during all recent five El Niño events since 2006 using level-3 (L3) cloud products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission. During its 17+ years operation, CALIPSO delivered near-global measurements of cloud and aerosol profiles at unprecedented high resolution and sensitivity. In this work, we provide a comprehensive picture of cloud anomalies during El Niño, with a particular focus on thin cirrus clouds at high altitudes, which are challenging for passive sensor detection algorithms. Specifically, the vertical cloud anomalies are calculated with the L3 3-D Cloud Occurrence Product, the horizontal cloud anomalies are from the L3 Global Energy and Water Exchanges (GEWEX) product, and the ice cloud extinction profiles and ice water content are obtained from the L3 Ice Cloud product. These findings will improve current knowledge of ENSO from a new perspective.

El Nino↗
NASA NTRS2003

Real-time, Quasi-Global, Multi-Satellite Precipitation Analysis Using TRMM and other Satellite Observations

A TRMM-based 3-hr analyses that use TRMM observations to calibrate polar-orbit microwave observations from SSM/I (and other satellites) and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map is described. This TRMM standard product will be available for the entire TRMM period (January 1998-present) in 2003 as part of Version 6 of the TRMM products. A real-time version of this merged product is being produced and is available at 0.25" latitude-longitude resolution over the latitude range from 50 N-500S. Examples will be shown, including its use in monitoring flood conditions and in relating weather-scale patterns to climate-scale patterns. Plans to incorporate the TRMM data and 3-hourly analysis into the Global Precipitation Climatology Project (GPCP) products are outlined. The outcome in the near future should be an improved global analysis and climatology on monthly scales for the 23 year period and finer time scale analyses for more recent periods, including 3-hourly analyses over the globe. These technique developments are potential prototypes for analyses with the Global Precipitation Measurement (GPM) mission.

Adler, Robert F.↗
NASA NTRS2004

Global, Multi-Satellite Precipitation Analysis at Fine Time Scales using TRMM Plus other Satellites

A TRMM-based 3-hr analyses that uses TRMM observations to calibrate polar-orbit microwave observations from SSM/I (and other satellites, including AMSR on AQUA and ADEOS II) and geosynchronous IR observations is described. The various calibrated observations are combined into a final, 3-hr resolution map. This TRMM standard product will be available for the entire TRMM period (January 1998-present) in 2003 as product 3B-42 of the TRMM Version 6. A real-time version of this merged product is being produced and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25 degrees latitude-longitude resolution over the latitude range from 50 degrees N-50 degrees S. Examples will be shown, including its use in monitoring flood conditions and in relating weather-scale patterns to climate-scale patterns. Incorporation of this approach into the Global Precipitation Climatology Project (GPCP) will also be discussed.

Adler, Robert↗
NASA NTRS2000

Topographic Response to the Yakutat Block Collision

The principal objective of this grant and this research were to investigate the topographic development of an active glaciated orogenic belt in southern Alaska as that development relates to patterns of erosion and crustal deformation. A specific objective of the research was to investigate feedbacks between mountain building, orographic affects on climate, and patterns of exhumation and rock uplift. To that end, an orogen-scale analysis of topography was conducted with the aid of digital elevation models, magnitudes and patterns of crustal deformation were compiled from existing literature, present and past climate patterns were constrained using the modern and past distribution of glaciers, and styles, magnitudes, and extent of erosion were constrained with observations from the 1998 field season.

Stock, Joann M.↗
NASA NTRS2011

Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Extremes in rainfall (drought and flood) during the period 2004 - 2009 have privileged different disease vectors. Chikungunya outbreaks occurred during the severe drought from late 2004 to 2006 over coastal East Africa and the western Indian Ocean islands and in the later years India and Southeast Asia. The chikungunya pandemic was caused by a Central/East African genotype that appears to have been precipitated and then enhanced by global-scale and regional climate conditions in these regions. Outbreaks of Rift Valley fever occurred following excessive rainfall period from late 2006 to late 2007 in East Africa and Sudan, and then in 2008 - 2009 in Southern Africa. The shift in the outbreak patterns of Rift Valley fever from East Africa to Southern Africa followed a transition of the El Nino/Southern Oscillation (ENSO) phenomena from the warm El Nino phase (2006-2007) to the cold La Nina phase (2007-2009) and associated patterns of variability in the greater Indian Ocean basin that result in the displacement of the centres of above normal rainfall from Eastern to Southern Africa. Understanding the background patterns of climate variability both at global and regional scale and their impacts on ecological drivers of vector borne-diseases is critical in long-range planning of appropriate response and mitigation measures.

Anyamba, Assaf↗
NASA NTRS2010

Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach

The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.

Smith, James A.↗
NASA NTRS2019

Global Disease Outbreaks Associated with the 2015-2016 El Niño Event

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015–2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14–81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5–28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

El Nino↗
NASA NTRS1995

Soil Polygenesis as a Function of Quaternary Climate, Northern Great Basin, USA

Polygenetic soils are those that record multiple morphological, mineralogical, and chemical imprints as the geographical pattern of climates shifts spatially and new boundaries are established. Optimal conditions for interpreting paleoclimates from polygenetic soils occur when precipitation and/or temperature changes are great enough to produce new soil properties without obliterating existing properties.

Polygenetic Soil↗