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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Quattrochi, Dale A.↗
NASA NTRS2023

Shape from spectra

We introduce a new unified atmospheric–topographic correction approach that estimates surface geometry directly from the radiance measurement. Surface topography influences the at-sensor radiance measurement, making precise topography modeling critical in applications like vegetation or snow studies in mountainous terrain. Currently, elevation maps are used to derive topographic variables such as the slope and sky-view factor. This process is error-prone since static global digital elevation models do not generally achieve the accuracy required, and even minor mismatches in spatial resolution can introduce significant artifacts in downstream processing. Here we demonstrate that it is possible to estimate topographic parameters directly from spectral data, ensuring perfect physical consistency, temporal coincidence, and spatial alignment. We present experiments estimating topographic slope in two scenes in Southern California, with data from NASA’s Next Generation Airborne Visible/Near Infrared Imaging Spectrometer (AVIRIS-NG). We compared our radiance-based estimates against high-resolution lidar datasets. Our initial validation result showed a correlation of R 2 = 0.864 (n = 160) over the homogeneous surface of Beckman Auditorium’s cone-shaped roof on the Caltech campus in Pasadena, California. We then validate the model over a larger study site near Santa Clarita, California, finding R 2 = 0.923 (n = 40,000) in a 350 x 350m area. The accuracy of our model estimates, combined with its systematic advantages over the alternative, show the potential of the approach for use in both airborne campaigns and orbital missions.

Nimrod Carmon↗
NASA NTRS2014

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Quattrochi, Dale A.↗
NASA NTRS1984

Observational evidence for chromospheric footpoint penetration of nonthermal electrons during two well-observed flares

Recent advances have enabled simultaneous H-alpha and X-ray observations with substantially improved spatial, spectral, and temporal resolution. In this paper a study is conducted of two events observed as part of a coordinated observing program between the Solar Maximum Mission and Sacramento Peak Observatory: the flares of 1456 UT, 7 May 1980 and 1522 UT, 24 June 1980. Using recently developed physical models of static flare chromospheres, and corresponding theoretical H-alpha line profiles, effects of intense nonthermal electron heating can be distinguished from those of high conduction and pressure from the overlying flare corona. Both flares show the signature of intense chromospheric heating by fast electrons, temporally correlated with X-ray light curves at E greater than 27keV, and spatially associated with X-ray emission sites at E greater than 16 keV. Interpreting the H-alpha line profile observations using the theoretical H-alpha line profiles, values of the thick-target input power contained in nonthermal electrons that are observationally indistinguishable (within a factor of 2-3) from those inferred from the X-ray data are inferred. Although these events are small, the energy flux values are large: of order 10 to the 11th ergs per sq cm per s above 20 keV.

Canfield, R. C.↗
NASA NTRS2005

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Goetz, Scott J.↗
NASA NTRS1983

Simulating spatial and temporal variation of corn canopy temperature during an irrigation cycle

The canopy air temperature difference (delta T) which provides an index for scheduling irrigation was examined. The Monteith transpiration equation was combined with both uptake from a single layered root zone and change in internal storage of the plant and the continuity equation for water flux in the soil plant atmosphere system was solved. The model indicates that both daily total transpiration and soil induced depression of plant water potential may be inferred from mid-day delta T. It is suggested that for the soil plant weather data used in the simulation, either a mid day spatial variability of about 0.8K in canopy temperatures or a field averaged delta T of 2 to 4K may be a suitable criterion for irrigation scheduling.

Choudhury, B. J.↗
NASA NTRS1985

Solar and thermal radiation in the Venus atmosphere

Attention is given to the solar and thermal radiation fields of Venus. Direct measurements and the results of numerical models based on direct measurements are presented. Radiation outside the atmosphere is considered with emphasis placed on global energy budget parameters, spectral and angular dependences, spatial distribution, and temporal variations of solar and thermal radiation. Radiation fluxes inside the atmosphere below 90 km are also considered with attention given to the solar flux at the surface, solar and thermal radiation fluxes from 100 km to the surface, and radiative heating and cooling below 100 km.

Moroz, V. I.↗
NASA NTRS1989

Global backscatter assessment

The focus of this effort is the development of a global-scale model of aerosol backscatter for laser atmospheric wind sounder (LAWS) design and performance studies. Background parameters are derived from aerosol data sets with global-scale spatial and/or temporal coverage, using objective statistical decomposition and/or a priori stratification based on supplementary data. Backscatter coefficients at the LAWS design wavelength are derived from background aerosol physical, chemical, and optical data, or from direct backscatter measurements at other wavelengths, using background conversion factors. Direct measurements of aerosol backscatter at 10.6 microns from the Royal Signals and Radar Establishment (RSRE) and the Wave Propagation Laboratory (WPL) were selected. The RSRE backscatter data processing code were optimized under low backscatter conditions, performed detailed analyses of collocated intercomparisons between the two lidars, and assisted in the analysis of the long-term backscatter climatologies from the two lidars. Timely presentation of global backscattering experiment (GLOBE) research results to the global geophysical community is required.

Bowdle, David A.↗
NASA NTRS1994

Relationship between ozone and temperature trends in the lower stratosphere: Latitude and seasonal dependences

A one-dimensional radiative transfer model with fixed dynamical heating is used to calculate the approximate latitude and seasonal dependences of lower stratospheric temperature changes associated with observed ozone trends. The spatial and temporal distribution of ozone profile trends in the lower stratosphere is estimated from a combination of Nimbus 7 Solar Backscattered Ultraviolet (SBUV) global measurements of the ozone column below 32 mbar for the period 1979-1990 and balloon ozonesonde profile trends at northern middle latitudes. The calculated temperature trends near 100 mbar compare favorably with those recently derived by Randel and Cobb (1994) using data from Channel 4 of the Microwave Sounding Unit (MSU) on the NOAA operational satellites, although a number of quantitative differences are found. An independent analysis reported here of 100 mbar temperatures derived from northern hemisphere radiosonde data at the Free University of Berlin (FUB) supports the validity of the satellite-derived lower stratospheric temperature trends. These results are therefore generally consistent with the hypothesis that observed lower stratospheric cooling trends are predominantly determined by reductions in radiative heating associated with stratospheric ozone depletion.

Mccormack, John P.↗
NASA NTRS1995

Prediction of coronal and heliospheric magnetic fields: The promise of SOI-MDI on SOHO

Models of the coronal magnetic field have been developed over the years that reproduce the static characteristics of coronal and heliospheric structures fairly well. Limitations of spatial and temporal resolution and nonuniform quality of the input data have made it particularly difficult to investigate the response of the corona to rapidly changing photospheric conditions. The Solar Oscillations Investigation (SOI) experiment on SOHO, scheduled for launch late in 1995, will produce a series of full-disk photospheric magnetic field observations with 4" resolution about every 2 hours for the next several years. Higher resolution observations of the center of the disk will be available several times per day. These data should provide a basis for predicting the coronal and heliospheric field and their changes with unprecedented accuracy during the rising phase of Solar Cycle 23.

Hoeksema, J. T.↗
NASA NTRS2010

Magnetic Reconnection: A Fundamental Process in Space Plasmas

For many years, collisionless magnetic reconnect ion has been recognized as a fundamental process, which facilitates plasma transport and energy release in systems ranging from the astrophysical plasmas to magnetospheres and even laboratory plasma. Beginning with work addressing solar dynamics, it has been understood that reconnection is essential to explain solar eruptions, the interaction of the solar wind with the magnetosphere, and the dynamics of the magnetosphere. Accordingly, the process of magnetic reconnection has been and remains a prime target for space-based and laboratory studies, as well as for theoretical research. Much progress has been made throughout the years, beginning with indirect verifications by studies of processes enabled by reconnection, such as Coronal Mass Ejections, Flux Transfer Events, and Plasmoids. Theoretical advances have accompanied these observations, moving knowledge beyond the Sweet-Parker theory to the recognition that other, collisionless, effects are available and likely to support much faster reconnect ion rates. At the present time we are therefore near a break-through in our understanding of how collisionless reconnect ion works. Theory and modeling have advanced to the point that two competing theories are considered leading candidates for explaining the microphysics of this process. Both theories predict very small spatial and temporal scales. which are. to date, inaccessible to space-based or laboratory measurements. The need to understand magnetic reconnect ion has led NASA to begin the implementation of a tailored mission, Magnetospheric MultiScale (MMS), a four spacecraft cluster equipped to resolve all relevant spatial and temporal scales. In this presentation, we present an overview of current knowledge as well as an outlook towards measurements provided by MMS.

Hesse, Michael↗
NASA NTRS2016

Comparing Potential Recharge Estimates From Three Land Surface Models Across the Western US

Groundwater is a major source of water in the western US. However, there are limited recharge estimates available in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01-15% for Mosaic, 3.2-42% for Noah, and 6.7-31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge rates in data limited regions.

groundwater↗
NASA NTRS2018

An Overview of Mesoscale Aerosol Processes, Comparisons, and Validation Studies from DRAGON Networks

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

Holben, Brent N.↗
NASA NTRS2015

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Simulation↗
NASA NTRSDate not supplied

Comparison of Observed Longwave, Shortwave Irradiance and Surface Temperature from “MOSAiC” to CERES Radiative Transfer Calculations and Inputs

As atmospheric temperatures rise due to increased anthropogenic forcing, the effect is expected to be larger over the arctic than midlatitude and tropics, known as polar amplification. A multi-national program, the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was ran between Sept 2019 and Oct 2020. The project deployed scientific instruments on board the German research vessel Polarstern with the ship remaining across a year to observe all aspects of polar climate. The US DOE deployed the ARM AMF2 aboard the ship along with several off-ship sites for extended spatial observations. Of particular importance was the measurement of the energetics of the ice/ocean/atmosphere interactions through observations of surface irradiance and surface temperatures. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project produces the SYN1deg Edition 4 data product. This product provides high quality, hourly, globally gridded and temporally complete maps of top of atmosphere (TOA), in atmosphere, and surface irradiances. TOA fluxes are derived from CERES instruments and geostationary satellites. In addition, TOA, in atmosphere, and surface irradiances are computed using the Langley Fu and Liou radiative transfer model. The radiative transfer model is run hourly at 1 degree ~equal area spatial resolution. Meteorological profiles are provided by Global Modeling and Assimilation Office’s GEOS-541 reanalysis product. Cloud properties are derived solely from Terra and Aqua MODIS imagers northward of 60°. Here we compare SYN1deg hourly calculations of surface irradiance to observations from the AMF2 to validate the products estimates of surface irradiance in this challenging area. Along with the irradiance comparisons we take a close look at the surface temperature record in the GEOS-541 product and compare it over both time and space to several surface observations provided by MOSAiC. Along with the comparison to the re-analysis record we will compare these observed surface temperatures to those derived from the AIRS product, which is known to have some difficulty in extreme high latitude areas. The goals of this study are 1) understand computed surface downward irradiance and temperature error separated by surface type (e.g. sea ice or open water) and by season, and 2) error covariance in spatial and temporal space. We seek to use this information to extrapolate the error from the MOSAiC domain to a larger arctic region.

David A Rutan↗
NASA NTRS2018

First-Principle Dynamic Electro-Thermal Numerical Model of a Scanning Radiometer for Earth Radiation Budget Applications

Low Earth Observing instruments that are used to monitor the incoming solar and outgoing long wave radiation have been a crucial part of studying the Earth’s radiation budget for the past three decades. These instruments go through several robust design phases followed by vigorous ground calibration campaigns to set their baseline characterization spectrally, spatially, temporally and radiometrically. The knowledge from building and calibrating these instruments has aided in technology advancements and the need for developing more accurate instruments has increased. In order to understand the on-ground instrument performance, NASA Langley Research Center has partnered with the Thermal Radiation Group of Virginia Tech to develop a first-principle, dynamic, electrothermal, numerical model of a scanning radiometer that can be used to enhance the interpretation of an Earth radiation budget-like instrument on orbit. This paper will summarize the current efforts of developing this high-fidelity end-to-end model and also highlight how it can be applied to an Earth radiation budget instrument.

Ashraf, Anum Rauf Bark↗
NASA NTRSDate not supplied

NASA’s Atmospheric Science Data Center’s Approach to a Cloud-Based Model of Ingest, Archival, and Distribution of TEMPO Data: Methods, Challenges, and Best Practices

The National Aeronautics and Space Administration's (NASA) Atmospheric Science Data Center (ASDC) at NASA Langley Research Center in Hampton, VA provides atmospheric science data products and services to the science community, including enhanced search and subsetting capabilities for numerous datasets. The ASDC is the official Distributed Active Archive Center (DAAC) of record for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument. TEMPO will be situated on a geostationary satellite positioned at a longitude near the center of the conterminous United States and focused on North America, making hourly swaths of its field of regard from east to west. ASDC’s data products are currently hosted locally and services (e.g., spatial and temporal subsetting) are managed on premises. The ASDC is planning to provide TEMPO data and services in the cloud through the Earthdata Search platform. This presentation will discuss the ASDC’s approach to a cloud-based model of ingest, archival, and distribution of TEMPO data. Methods, challenges, best practices, lessons learned, and future plans will be discussed.

Iman Nasif↗
NASA NTRS2021

Global Soil Water Estimates as Landslide Predictor: The Effectiveness of SMOS, SMAP, and GRACE Observations, Land Surface Simulations, and Data Assimilation

This global feasibility study assesses the potential of coarse-scale, gridded soil water estimates for the probabilistic modeling of hydrologically-triggered landslides, using Soil Moisture Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) and Gravity Recovery and Climate Experiment (GRACE) remote sensing data, Catchment Land Surface Model (CLSM) simulations and six data products based on the assimilation of SMOS, SMAP, and/or GRACE observations into CLSM. SMOS or SMAP observations (~40-km resolution) are only available for less than 20% of the globally reported landslide events, because they are intermittent and uncertain in regions with complex terrain. GRACE terrestrial water storage estimates include 75% of the reported landslides but have coarse spatial and temporal resolutions (monthly, ~300-km). CLSM soil water simulations have the added advantage of complete spatial and temporal coverage, and are found to be able to distinguish between “stable slope” (no landslide) conditions and landslide-inducing conditions in a probabilistic way. Assimilating SMOS and/or GRACE data increases the landslide probability estimates based on soil water percentiles for the reported landslides, relative to model-only estimates at 36-km resolution for the period 2011-2016, unless the CLSM model-only soil water content is already high (≥ 50th percentile). The SMAP Level 4 data assimilation product (at 9-km resolution, period 2015-2019) more generally updates the soil water conditions towards higher landslide probabilities for the reported landslides, but is similar to model-only estimates for the majority of landslides where SMAP data cannot easily be converted to soil moisture owing to complex terrain.

Anne Felsberg↗