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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Distributive On-line Processing, Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time- consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions, for example, when preparing data for input into modeling systems. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Time plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. In the future, we will add correlation plots, GIS-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), a stable, secure data server that provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. In our case, we use this approach to read pre-processed binary files and/or to read and extract the needed parts from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS processing and analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, G.↗
NASA NTRS2005

NASA GES DISC On-line Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current NASA Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time-consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Hovmoller plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. Another analysis suite deals with parameter intercomparison: scatter plots, temporal correlation maps, GIs-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), and provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. We use this approach to read pre-processed binary files and/or to read and extract the needed parts directly from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, Gregory G.↗
NASA NTRS2005

Investigations of Desert Dust and Smoke in the North Atlantic in Support of the TOMS Instrument

During the initial period of the work we concentrated on Saharan dust storms and published a sequence of papers (Colarco et a1 2002,2003a,b, Toon, 2004). The U.S. Air Force liked the dust model so well that they appropriated it for operational dust storm forecasting (Barnum et al., 2004). The Air Force has used it for about 5 yrs in the Middle East where dust storms cause significant operational problems. The student working on this project, Peter Colarco, has graduated and is now a civil servant at Goddard where he continues to interact with the TOMS team. This work helped constrain the optical properties of dust at TOMS wavelengths, which is useful for climate simulations and for TOMS retrievals of dust properties such as optical depth. We also used TOMS data to constrain the sources of dust in Africa and the Middle East, to determine the actual paths taken by Saharan dust storms, to learn more about the mechanics of variations in the optical depths, and to learn more about the mechanisms controlling the altitudes of the dust. During the last two years we have been working on smoke from fires. Black carbon aerosols are one of the leading factors in radiative forcing. The US Climate Change Science Program calls this area out for specific study. It has been suggested by Jim Hansen, and Mark Jacobsen among others, that by controlling emissions of black carbon we might reduce greenhouse radiative forcing in a relatively painless manner. However, we need a greatly improved understanding of the amount of black carbon in the atmosphere, where it is located, where it comes from, how it is mixed with other particles, what its actual optical properties are, and how it evolves. In order to learn about these issues we are using a numerical model of smoke. We have applied this model to the SAFARI field program data, and used the TOMS satellite observations in that period (Sept. 2000). Our goal is to constrain source function estimates for black carbon, and smoke optical properties.

Toon, Owen B.↗
NASA NTRS2009

Surface Emissivity Retrieved with Satellite Ultraspectral IR Measurements for Monitoring Global Change

Surface and atmospheric thermodynamic parameters retrieved with advanced ultraspectral remote sensors aboard Earth observing satellites are critical to general atmospheric and Earth science research, climate monitoring, and weather prediction. Ultraspectral resolution infrared radiance obtained from nadir observations provide atmospheric, surface, and cloud information. Presented here is the global surface IR emissivity retrieved from Infrared Atmospheric Sounding Interferometer (IASI) measurements under "clear-sky" conditions. Fast radiative transfer models, applied to the cloud-free (or clouded) atmosphere, are used for atmospheric profile and surface parameter (or cloud parameter) retrieval. The inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral infrared sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface (or cloud microphysical) parameters. Rapidly produced surface emissivity is initially evaluated through quality control checks on the retrievals of other impacted atmospheric and surface parameters. Surface emissivity and surface skin temperature from the current and future operational satellites can and will reveal critical information on the Earth s ecosystem and land surface type properties, which can be utilized as part of long-term monitoring for the Earth s environment and global climate change.

Zhou, Daniel K.↗
NASA NTRS2011

Contributions to Climate Research Using the AIRS Science Team Version-5 Products

This paper compares recent spatial anomaly time series of OLR (Outgoing Longwave Radiation) and OLRCLR (Clear Sky OLR) as determined using CERES and AIRS observations over the time period September 2002 through June 2010. We find excellent agreement in OLR anomaly time series of both data sets in almost every detail, down to the 1 x 1 spatial grid point level. This extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies that both sets of results must be highly stable. This agreement also validates to some extent the anomaly time series of the AIRS derived products used in the computation of the AIRS OLR product. The paper then examines anomaly time series of AIRS derived products over the extended time period September 2002 through April 2011. We show that OLR anomalies during this period are closely in phase with those of an El Nino index, and that recent global and tropical mean decreases in OLR and OLR(sub CLR) are a result of a transition from an El Nino condition at the beginning of the data record to La Nina conditions toward the end of the data period. This relationship can be explained by temporal changes of the distribution of mid-tropospheric water vapor and cloud cover in two spatial regions that are in direct response to El Nino/La Nina activity which occurs outside these spatial regions

Susskind, Joel↗
NASA NTRS2010

Solar Radiation Transport in the Cloudy Atmosphere: A 3D Perspective on Observations and Climate Impacts

The interplay of sunlight with clouds is a ubiquitous and often pleasant visual experience, but it conjures up major challenges for weather, climate, environmental science and beyond. Those engaged in the characterization of clouds (and the clear air nearby) by remote sensing methods are even more confronted. The problem comes, on the one hand, from the spatial complexity of real clouds and, on the other hand, from the dominance of multiple scattering in the radiation transport. The former ingredient contrasts sharply with the still popular representation of clouds as homogeneous plane-parallel slabs for the purposes of radiative transfer computations. In typical cloud scenes the opposite asymptotic transport regimes of diffusion and ballistic propagation coexist. We survey the three-dimensional (3D) atmospheric radiative transfer literature over the past 50 years and identify three concurrent and intertwining thrusts: first, how to assess the damage (bias) caused by 3D effects in the operational 1D radiative transfer models? Second, how to mitigate this damage? Finally, can we exploit 3D radiative transfer phenomena to innovate observation methods and technologies? We quickly realize that the smallest scale resolved computationally or observationally may be artificial but is nonetheless a key quantity that separates the 3D radiative transfer solutions into two broad and complementary classes: stochastic and deterministic. Both approaches draw on classic and contemporary statistical, mathematical and computational physics.

Davis, Anthony B.↗
NASA NTRS2011

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

Kim, Edward↗
NASA NTRS2012

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201l. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record -- provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica--parameters such as surface temperature.

Kim, Edward↗
NASA NTRS2012

Warming Experiments Underpredict Plant Phenological Responses to Climate Change

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

phenology↗
NASA NTRS2005

Sea Level Rise in Santa Clara County

Presentation by Cristina Milesi, First Author, NASA Ames Research Center, Moffett Field, CA at the "Meeting the Challenge of Sea Level Rise in Santa Clara County" on June 19, 2005 Santa Clara County, bordering with the southern portion of the San Francisco Bay, is highly vulnerable to flooding and to sea level rise (SLR). In this presentation, the latest sea level rise projections for the San Francisco Bay will be discussed in the context of extreme water height frequency and extent of flooding vulnerability. I will also present preliminary estimations of levee requirements and possible mitigation through tidal restoration of existing salt ponds. The examples will draw mainly from the work done by the NASA Climate Adaptation Science Investigators at NASA Ames.

Sea Level↗
NASA NTRS2015

First SNPP Cal/Val Campaign: Satellite and Aircraft Sounding Retrieval Intercomparison

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (SNPP) satellite Environmental Data Record (EDR) is retrieved from calibrated ultraspectral radiance so called Sensor Data Record (SDR). It is critical to understand the accuracy of retrieved EDRs, which mainly depends on SDR accuracy (e.g., instrument random noise and absolute accuracy), an ill-posed retrieval system, and radiative transfer model errors. There are few approaches to validate EDR products, e.g., some common methods are to rely on radiosonde measurements, ground-based measurements, and dedicated aircraft campaign providing in-situ measurements of atmosphere and/or employing similar ultraspectral interferometer sounders. Ultraspectral interferometer sounder aboard aircraft measures SDR to retrieve EDR, which is often used to validate satellite measurements of SDR and EDR. The SNPP Calibration/Validation Campaign was conducted during May 2013. The NASA high-altitude aircraft ER-2 that carried ultraspectral interferometer sounders such as the NASA Atmospheric Sounder Testbed-Interferometer (NAST-I) flew under the SNPP satellite that carries the Cross-track Infrared Sounder (CrIS). Here we inter-compare the EDRs produced with different retrieval algorithms from SDRs measured by the sensors from satellite and aircraft. The available dropsonde and radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis were also used to draw the conclusion from this experiment.

Zhou, Daniel K.↗
NASA NTRS2016

Second SNPP Cal/Val Campaign: Environmental Data Retrieval Analysis

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (Soumi NPP) satellite Environmental Data Records (EDRs) are retrieved from calibrated ultraspectral radiance or Sensor Data Records (SDRs). Understanding the accuracy of retrieved EDRs is critical. The second Suomi NPP Calibration/Validation field campaign was conducted during March 2015 with flights over Greenland. The NASA high-altitude ER-2 aircraft carrying ultraspectral interferometer sounders such as the National Airborne Sounder Testbed-Interferometer (NAST-I) flew under the Suomi NPP satellite that carries the Crosstrack Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Herein we inter-compare the EDRs produced from different retrieval algorithms employed on these satellite and aircraft campaign data. The available radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses are used to assess atmospheric temperature and moisture retrievals from the aircraft and satellite platforms. Preliminary results of this experiment under a winter, Arctic environment are presented.

Zhou, Daniel K.↗
NASA NTRS2016

In Situ Air Temperature and Humidity Measurements Over Diverse Land Covers in Greenbelt, Maryland, November 2013-November 2015

As our climate changes through time there is an ever-increasing need to quantify how and where it is changing so that mitigation strategies can be implemented. Urban areas have a disproportionate amount of warming due, in part, to the conductive properties of concrete and asphalt surfaces, surface albedo, heat capacity, lack of water, etc. that make up an urban environment. The NASA Climate Adaptation Science Investigation working group at Goddard Space Flight Center in Greenbelt, MD, conducted a study to collect temperature and humidity data at 15 min intervals from 12 sites at the center. These sites represent the major surface types at the center: asphalt, building roof, grass field, forest, and rain garden. The data show a strong distinction in the thermal properties of these surfaces at the center and the difference between the average values for the center compared to a local meteorological station. The data have been submitted to Oak Ridge National Laboratory Distributed Active Archive Center (ORNL-DAAC) for archival in comma separated value (csv) file format (Carroll et al.,2016) and can be found by following this link: http:daac.ornl.govcgi-bindsviewer.pl?ds_id1319.

Carroll, Mark L.↗
NASA NTRS2021

Challenges to Aboveground Biomass Prediction from Waveform Lidar

Accurate accounting of aboveground biomass density (AGBD) is crucial for carbon cycle, biodiversity, and climate change science. The Global Ecosystem Dynamics Investigation (GEDI), which maps global AGBD from waveform lidar, is the first of a new generation of Earth observation missions designed to improve carbon accounting. This paper explores the possibility that lidar waveforms may not be unique to AGBD—that forest stands with different AGBD may produce highly similar waveforms—and we hypothesize that non-uniqueness may contribute to the large uncertainties in AGBD predictions. Our analysis integrates simulated GEDI waveforms from 428 in situ stem maps with output from an individual-based forest gap model, which we use to generate a database of potential forest stands and simulate GEDI waveforms from those stands. We use this database to predict the AGBD of the 428 in situ stem maps via two different methods: a linear regression from waveform metrics, and a waveform-matching approach that accounts for waveform-AGBD non-uniqueness. We find that some in situ waveforms are more unique to AGBD than others, which notably impacts AGBD prediction uncertainty (7–411 Mg ha−1, average of 167 Mg ha−1). We also find that forest structure complexity may influence the non-uniqueness effect; stands with low structural complexity are more unique to AGBD than more mature stands with multiple cohorts and canopy layers. These findings suggest that the non-uniqueness phenomena may be introduced by the measuring characteristics of waveform lidar in combination with how forest structure manifests at small scales, and we discuss how this complexity may complicate uncertainty estimation in AGBD prediction. This analysis suggests a limit to the accuracy and precision of AGBD predictions from lidar waveforms seen in empirical studies, and underscores the need for further exploration of the relationships between lidar remote sensing measurements, forest structure, and AGBD.

GEDI↗
NASA NTRS2022

Irrigation and Warming Drive the Decreases in Surface Albedo Over High Mountain Asia

Human and climate induced land surface changes resulting from irrigation, snow cover decreases, and greening impact the surface albedo over High Mountain Asia (HMA). Here we use a partial information decomposition approach and remote sensing data to quantify the effects of the changes in leaf area index, soil moisture, and snow cover on the surface albedo in HMA, home to over a billion people, from 2003 to 2020. The study establishes strong evidence of anthropogenic agricultural water use over irrigated lands (e.g., Ganges-Brahmaputra) which causes the highest surface albedo decreases (≤1%/year). Greening and decreased snow cover from warming also drive changes in visible and near-infrared surface albedo in different areas of HMA. The significant role of irrigation and greening in influencing albedo suggests the potential of a positive feedback cycle where albedo decreases lead to increased evaporative demand and increased stress on water resources.

Climate sciences↗
NASA NTRS2022

Compound Heat and Moisture Extreme Impacts on Global Crop Yields Under Climate Change

Extreme heat, drought and moisture excess are increasingly co-occurring within a single growing season, impacting crop yields in global breadbasket regions. In this Review, we synthesize understanding of compound heat and moisture extremes, their impacts on global crop yields and implications for adaptation. Heat and moisture extremes and their impacts become compounded through crop-physiological interactions, heat–moisture couplings in the climate system and crop–atmosphere interactions. Since around 2000, these compound extremes, and hot droughts in particular, have been linked to especially poor harvests (up to 30% yield losses) in regions such as India, Ethiopia, the USA, Europe and Russia. However, in some cases, combinations of crop stresses might generate compensating effects. Compound extremes are projected to increase in frequency and amplitude in the future, but, owing to the biophysical interdependence among temperature, water and crop physiology, the net yield effects of such future compound extremes remain uncertain. Accordingly, compound extremes will necessitate comprehensive agricultural adaptation strategies geared towards multi-stress resilience, as adaptations that work for single climate stresses could be maladaptive under combined stresses. An integrated understanding of heat and water in soil–plant–atmosphere dynamics is urgently needed to understand risks and suitably adapt cropping systems to compounding climate impacts.

Agroecology↗
NASA NTRS2022

Rapid Glacier Retreat Rates Observed in West Antarctica

The Pope, Smith, and Kohler glaciers, in the Amundsen Sea Embayment of West Antarctica, have experienced enhanced ocean-induced ice-shelf melt, glacier acceleration, ice thinning, and grounding line retreat in the past thirty years. Here we present observations of the grounding line retreat of these glaciers since 2014 using a constellation of interferometric radar satellites combined with precision surface elevation data. We find that the grounding lines develop spatially-variable, kilometre-scale, tidally-induced migration zones. After correction for tidal effects, we detect a sustained pattern of retreat coincident with high melt rates of un-grounded ice, marked by episodes of more rapid retreat. In 2017, Pope Glacier retreated 3.5 km in 3.6 months, or 11.7 km/yr. In 2016-2018, Smith West retreated at 2 km/yr and Kohler at 1.3 km/yr. While the retreat slowed down in 2018-2020, these retreat rates are faster than anticipated by numerical models on yearly time scales. We hypothesize that the rapid retreat is caused by un-represented, vigorous ice-ocean interactions acting within newly-formed cavities at the ice-ocean boundary.

Climate change↗