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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Earth-Atmospheric Coupling During Strong Earthquakes by Analyzing MODIS Data

Interactions between the Earth and the atmosphere during major earthquakes (M greater than 5) are the subject of this investigation. Recently a mechanism has been proposed predicting the build-up of positive ground potentials prior to strong earthquake activity. Connected phenomena include: transient conductivity of rocks, injection of currents, possibly also electromagnetic emission and light emission from high points at the surface of the Earth. To understand this process we analyze vertical atmospheric profiles, land surface and brightness (temperature) data, using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite launched in December 1999. MODIS covers the entire Earth every 1-2 days in 36 wavelength bands (20 visible and 16 infrared) at different spatial resolutions (250 m, 500 m, and 1 km). Using MODIS data we look for correlations between the atmospheric dynamics and solid Earth processes for the January 2001 strong earthquakes in San Salvador and India. As part of the build-up of positive grounds potential, an IR luminescence is predicted to occur in the 8-12 micrometer band. We use the MODIS data to differentiate between true "thermal" signals and IR luminescence. Indeed, on the basis of a temporal and spatial distribution analysis, a thermal anomaly pattern is found that appears to be related to the seismic activity. Aerosol content and atmospheric instability parameters also change when ground charges build up causing ion emission and leading to a thin aerosol layer over land. We analyze the aerosol content, atmospheric pressure, moisture profile and lifted index. Anomalous trends have been identified in few days prior to the main shocks. The significance of this observation should be explored further using other data sets.

Ouzounov, Dimitar↗
NASA NTRS2012

The Algorithm Theoretical Basis Document for the Derivation of Range and Range Distributions from Laser Pulse Waveform Analysis for Surface Elevations, Roughness, Slope, and Vegetation Heights

The primary purpose of the GLAS instrument is to detect ice elevation changes over time which are used to derive changes in ice volume. Other objectives include measuring sea ice freeboard, ocean and land surface elevation, surface roughness, and canopy heights over land. This Algorithm Theoretical Basis Document (ATBD) describes the theory and implementation behind the algorithms used to produce the level 1B products for waveform parameters and global elevation and the level 2 products that are specific to ice sheet, sea ice, land, and ocean elevations respectively. These output products, are defined in detail along with the associated quality, and the constraints, and assumptions used to derive them.

Brenner, Anita C.↗
NASA NTRS1992

Soil surface CO2 fluxes and the carbon budget of a grassland

Measurements of soil surface CO2 fluxes are reported for three sites within the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) area, and simple empirical equations are fit to the data to provide predictions of soil fluxes from environmental observations. A prototype soil chamber, used to make the flux measurements, is described and tested by comparing CO2 flux measurements to a 40-L chamber, a 1-m/cu chamber, and eddy correlation. Results suggest that flux measurements with the prototype chamber are consistent with measurements by other methods to within about 20 percent. A simple empirical equation based on 10-cm soil temperature, 0- to 10-cm soil volumetric water content, and leaf area index predicts the soil surface CO2 flux with a rms error of 1.2 micro-mol sq m/s for all three sites. Further evidence supports using this equation to evaluate soil surface CO2 during the 1987 FIFE experiment. The soil surface CO2 fluxes when averaged over 24 hours are comparable to daily gross canopy photosynthetic rates. For 6 days of data the net daily accumulation of carbon is about 0.6 g CO2 sq m/d; this is only a few percent of the daily gross accumulation of carbon by photosynthesis. As the soil became drier in 1989, the net accumulation of carbon by the prairie increased, suggesting that the soil flux is more sensitive to temperature and drought than the photosynthetic fluxes.

Norman, J. M.↗
NASA NTRS2016

Ultra-Compact Raman Spectrometer for Planetary Explorations

To develop a compact Raman spectroscopy system with features that will make it suitable for future space missions which require surface landing. Specifically, this system will be appropriate for any mission in which planetary surface samples need to be measured and analyzed.

Davis, Derek↗
NASA NTRS2018

Assessing Version 4 of the SMAP L4_SM Data Product

Version 4 of the SMAP Level 4 Surface and Root Zone Soil Moisture (L4_SM) product benefits from an improved land surface modeling system. Surface soil moisture is typically drier by several volumetric percent in Version 4 compared to Version 3, whereas root zone soil moisture is wetter in Version 4 in some regions and drier in others. Results from core validation site comparisons show that Version 4 of the L4_SM data product meets the accuracy requirement, which is formulated in terms of the RMSE after removal of the long-term mean difference (ubRMSE). The overall ubRMSE of the 3-hourly L4_SM data at the 9 km scale is 0.039 m3 m-3 for surface soil moisture and 0.029 m3 m-3 for root zone soil moisture, below the 0.04 m3 m-3 requirement. L4_SM surface and root zone soil moisture estimates are more skillful than model-only simulation estimates that are not informed by SMAP brightness temperature observations, with statistically significant improvements at the 5% level for surface soil moisture R and anomaly R values. Results from comparisons of the L4_SM product to in situ measurements from more than 400 sparse network sites corroborate the core validation site results.

Reichle, R.↗
NASA NTRSDate not supplied

The Application of Remote Sensing using NASA Earth Observations paired with Sociodemographic Indicators to Identify Communities Most Susceptible to Urban Heat Exposure in Austin, Texas

In recent years, Austin, Texas has experienced an increase in population and urban development. Additionally, the City’s climate—already characterized by periods of extreme heat and drought—continues to change. As temperatures and demand for utilities and cooling resources rise, the number of heat-related deaths and illnesses in socially vulnerable populations (e.g., older, lower-income populations) is expected to increase. The City of Austin, The University of Texas at Austin (UT Austin), and The University of Texas Health Science Center at Houston (UT Health) partnered with NASA DEVELOP to examine the distribution of urban heat throughout the City. This project used land surface temperature, greenness, plant water content, and urban surface material analysis parameters derived from NASA Earth observations from Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), and Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The project team produced three different indices to create a spatial analysis for the study area including a social vulnerability index (SoVI), heat exposure index (HEI), and an overall heat priority index (HPI) score. This overall score was determined with a weighted analysis of heat-related environmental variables from NASA Earth observations and socioeconomic data from the 2019 American Community Survey. Based on the HPI score, the project team identified 121 census block groups out of 605 total that are designated as being most at risk of adverse impacts from extreme heat events. To test the sensitivity of the HPI, the team used a Monte Carlo analysis using different approaches for geographic scale, variable inclusion, census uncertainty, and index aggregation. Based on the sensitivity analysis, the resulting HPI score showed the metric was consistent with the baseline HPI. This provided increased confidence the score can be used as a tool to make informed infrastructure improvement plans in targeted areas (e.g., siting of cooling centers) and ensure equitable sustainable development.

Ryan Hammock↗
NASA NTRS1989

A CCIR aeronautical mobile satellite report

Propagation effects in the aeronautical mobile-satellite service differ from those in the fixed-satellite service and other mobile-satellite services because: small antennas are used on aircraft, and the aircraft body may affect the performance of the antenna; high aircraft speeds cause large Doppler spreads; aircraft terminals must accommodate a large dynamic range in transmission and reception; and due to their high speeds, banking maneuvers, and three-dimensional operation, aircraft routinely require exceptionally high integrity of communications, making even short-term propagation effects very important. Data and models specifically required to characterize the path impairments are discussed, which include: tropospheric effects, including gaseous attenuation, cloud and rain attenuation, fog attenuation, refraction and scintillation; surface reflection (multipath) effects; ionospheric effects such as scintillation; and environmental effects (aircraft motion, sea state, land surface type). Aeronautical mobile-satellite systems may operate on a worldwide basis, including propagation paths at low elevation angles. Several measurements of multipath parameters over land and sea were conducted. In some cases, laboratory simulations are used to compare measured data and verify model parameters. The received signals is considered in terms of its possible components: a direct wave subject to atmospheric effects, and a reflected wave, which generally contains mostly a diffuse component.

Davarian, Faramaz↗
NASA NTRS1985

Measurements of the surface energy budget in the southern Gobi Desert of China, and in the Rocky Mountains of Colorado

Observations of the land surface energy balance were made in the Gobi desert and at two mountain sites in northern Colorado. The Gobi study included 12 days of observations in spring (April 8 to 20, 1984) and 31 days in summer at the same site (June 17 to July 18, 1984). The Colorado study included 126 days (March 13 to July 17, 1984) at a valley site and 34 days (July 31 to September 3, 1984) at a mountain top location. The data for each study included continuous observations of upward and downward radiative fluxes in three wave bands, soil temperature and moisture at four levels, air temperature and humidity at four levels and UVW wind components at three levels. Analyses of the Gobi data include definition of the impact of variable atmospheric moisture on the surface energy balance between spring and summer. In addition, diurnal wind circulations forced by heating of the northern edge of the Tibetan Plateau were observed during both periods.

Reiter, E. R.↗
NASA NTRS2011

Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.

Shen, Suhung↗
NASA NTRS2013

Use of In Situ and Airborne Multiangle Data to Assess MODIS and Landsat-Based Estimates of Directional Reflectance and Albedo

The quantification of uncertainty in satellite-derived global surface albedo products is a critical aspect in producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A challenge in validating albedo measurements acquired from space is the ability to overcome the spatial scaling errors that can produce disagreements between satellite and field-measured values. Here, we present the results from an accuracy assessment of MODIS and Landsat-TM albedo retrievals, based on collocated comparisons with tower and airborne Cloud Absorption Radiometer (CAR) measurements collected during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC). The initial focus was on evaluating intersensor consistency through comparisons of intrinsic bidirectional reflectance estimates. Local and regional assessments were then performed to obtain estimates of the resulting scaling uncertainties, and to establish the accuracy of albedo reconstructions during extended periods of precipitation. In general, the satellite derived estimates met the accuracy requirements established for the high-quality MODIS operational albedos at 500 m (the greater of 0.02 units or +/-10% of surface measured values). However, results reveal a high degree of variability in the root-mean-square error (RMSE) and bias of MODIS visible (0.3-0.7 μm) and Landsat-TM shortwave (0.3-5.0 μm) albedos; where, in some cases, retrieval uncertainties were found to be in excess of 15%. Results suggest that an overall improvement in MODIS shortwave albedo retrieval accuracy of 7.8%, based on comparisons between MODIS and CAR albedos, resulted from the removal of sub-grid scale mismatch errors when directly scaling-up the tower measurements to the MODIS satellite footprint.

biosphere↗
NASA NTRS2018

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +/-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

retrieval algorithm↗
NASA NTRS2018

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

calibration↗
NASA NTRS2023

The Earth in Living Color - NASA’s Surface Biology and Geology Designated Observable

The Surface Biology and Geology (SBG) Designated Observable will transform our understanding of the global land surface, inland and coastal aquatic ecosystems through visible-to-shortwave infra-red imaging (VSWIR) spectroscopy and thermal infra-red (TIR) imaging. SBG is one of four high-priority observables recommended in the 2017 NASA Earth Science Decadal Survey t o address science questions on vegetation and aquatic ecosystem health, snow-cover dynamics, volcanic activity, and minerology. With a planned launch readiness date of 2028, SBG is currently in Pre-Phase A, with Level 1 requirements being developed for a two-spacecraft architecture, including an additional constellation pathfinder. The recommended architecture emerged from an extensive study (2018-2021) that engaged the research and applications community to consider the science questions and measurement objectives of the Decadal Survey. A Science and Applications Traceability Matrix was used as a basis for scoring candidate architectures, with inputs from four working groups that covered algorithms, applications, calibration and validation, and modeling. Two pathfinder studies, Modeling End-to-End Traceability in support of SBG (MEET-SBG) and Space-based Imaging Spectroscopy and Thermal pathfindER (SISTER) are providing pre-launch modeling tools and data for algorithm development to support science value trades. The architecture consists of one spacecraft hosting a wide-swath VSWIR imaging spectrometer providing 30-m ground-sample distance (GSD), a spectral range of 380-2500 nm (at 10 nm resolution), 16-day revisit with 400 signal-to-noise for VNIR and 250 for SWIR (at 25% reflectance). A separate spacecraft will host a wide swath thermal imager, with five to seven bands placed between 4-12 μm), with 60-m (GSD), 3- day revisit, and 0.2K noise-equivalent differential temperature (NeDT). A VNIR compact camera will be hosted on the TIR spacecraft to enable coincident TIR and VNIR observations. A constellation pathfinder will evaluate options for enabling VSWIR mission continuity using Small Sats or data buys. Partnerships with international space agencies contribute technology as well as improvements to temporal revisit. SBG, when launched, will be the first dedicated mission collecting the full spectra of the Earth’s ‘living color’ and will play a critical role in NASA’s Earth System Observatory.

David S Schimel↗
NASA NTRS2019

Detecting Layer Height of Smoke Aerosols over Vegetated Land and Water Surfaces via Oxygen Absorption Bands: Hourly Results from EPIC/DSCOVR in Deep Space

We present an algorithm for retrieving aerosol layer height (ALH) and aerosol optical depth (AOD) for smoke over vegetated land and water surfaces from measurements of the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR). The algorithm uses Earth-reflected radiances in six EPIC bands in the visible and near-infrared and incorporates flexible spectral fitting that accounts for specifics of land and water surface reflectivity. The fitting procedure first determines AOD using EPIC atmospheric window bands (443 nm, 551 nm, 680nm, and 780 nm), then uses oxygen (O2) A and B bands (688 nm and 764 nm) to derive ALH, which represents an optical centroid altitude. ALH retrieval over vegetated surface primarily takes advantage of measurements in the O2B band. We applied the algorithm to EPIC observations of several biomass burning events over the United States and Canada in August 2017. We found that the algorithm can be used to obtain AOD and ALH multiple times daily over water and vegetated land surface. Validation is performed against aerosol extinction profiles detected by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and against AOD observed at nine Aerosol Robotic Network (AERONET) sites, showing, on average, an error of 0.58 km and a bias of -0.13 km in retrieved ALH and an error of 0.05 and a bias of 0.03 in retrieved AOD. Additionally, we show that the aerosol height information retrieved by the present algorithm can potentially benefit the retrieval of aerosol properties from EPIC’s ultraviolet (UV) bands.

Cloud–Aerosol Lidar with Orthogonal Polarization (↗
NASA NTRS2009

The Urban Environmental Monitoring/100 Cities Project: Legacy of the First Phase and Next Steps

The Urban Environmental Monitoring (UEM) project, now known as the 100 Cities Project, at Arizona State University (ASU) is a baseline effort to collect and analyze remotely sensed data for 100 urban centers worldwide. Our overarching goal is to use remote sensing technology to better understand the consequences of rapid urbanization through advanced biophysical measurements, classification methods, and modeling, which can then be used to inform public policy and planning. Urbanization represents one of the most significant alterations that humankind has made to the surface of the earth. In the early 20th century, there were less than 20 cities in the world with populations exceeding 1 million; today, there are more than 400. The consequences of urbanization include the transformation of land surfaces from undisturbed natural environments to land that supports different forms of human activity, including agriculture, residential, commercial, industrial, and infrastructure such as roads and other types of transportation. Each of these land transformations has impacted, to varying degrees, the local climatology, hydrology, geology, and biota that predate human settlement. It is essential that we document, to the best of our ability, the nature of land transformations and the consequences to the existing environment. The focus in the UEM project since its inception has been on rapid urbanization. Rapid urbanization is occurring in hundreds of cities worldwide as population increases and people migrate from rural communities to urban centers in search of employment and a better quality of life. The unintended consequences of rapid urbanization have the potential to cause serious harm to the environment, to human life, and to the resulting built environment because rapid development constrains and rushes decision making. Such rapid decision making can result in poor planning, ineffective policies, and decisions that harm the environment and the quality of human life. Slower, more thought-out, decision making could result in more favorable outcomes. The harm to the environment includes poor air quality, soil erosion, polluted rivers and aquifers, and loss of wildlife habitat. Human life is then threatened because of increased potential for disease spreading, human conflict, environmental hazards, and diminished quality of life. The built environment is potentially threatened when cities are built in areas that can be impacted by events such as hurricanes, tsunamis, earthquakes, fires, and landslides. Our goals include assessing the threat of such events on cities and the people living there.

Stefanov, William L.↗
NASA NTRS1986

Data needs and data bases for climate studies

Two complementary global digital data bases of vegetation and land use, compiled at 1 deg resolution from published sources for use in climate studies, are discussed. The data bases were implemented, in several individually tailored formulations, in a series of climate related applications including: land-surface prescriptions in three-dimensional general circulation models, global biogeochemical cycles (CO2, methane), critical-area mapping for satellite monitoring of land-cover change, and large-scale remote sensing of surface reflectance. The climate applications are discussed with reference to data needs, and data availability from traditional and remote sensing sources.

Matthews, Elaine↗
NASA NTRS2016

Distribution and Validation of CERES Irradiance Global Data Products Via Web Based Tools

The CERES SYN1deg product provides climate quality 3-hourly globally gridded and temporally complete maps of top of atmosphere, in atmosphere, and surface fluxes. This product requires efficient release to the public and validation to maintain quality assurance. The CERES team developed web-tools for the distribution of both the global gridded products and grid boxes that contain long term validation sites that maintain high quality flux observations at the Earth's surface. These are found at: http://ceres.larc.nasa.gov/order_data.php. In this poster we explore the various tools available to users to sub-set, download, and validate using surface observations the SYN1Deg and Surface-EBAF products. We also analyze differences found in long-term records from well-maintained land surface sites such as the ARM central facility and high quality buoy radiometers, which due to their isolated nature cannot be maintained in a similar manner to their land based counterparts.

Rutan, David↗
NASA NTRS2021

Chapter 6: Fundamental Satellite Precipitation Data Records

The observation and measurement of precipitation across a range of temporal and spatial scales is of great importance for many user requirements and applications. Precipitation is a key component of the global energy and water cycle moving water, and its’ associated energy, through the Earth system at relatively fine spatial and temporal scales. At the societal level, precipitation provides fresh water and moderates our climate, but can also be destructive through storms, droughts and spreading diseases. Monitoring and measuring the distribution and quantities of precipitation, across the Earth’s surface is therefore crucial to physical and social applications, together with changes in precipitation over time. While conventional surface instruments provide a reasonably long record, these tend to be confined to well populated land surface areas: most ocean regions and sparsely populated regions have few measurements. Satellite-based precipitation products can provide global measurements, although the timespan of such products is limited and the data record is comprised of different instruments that operate over different periods of record. The challenge of any climate record is to provide a consistent product over the full period of record. Many satellite precipitation products incorporate ancillary data, such as surface gauge data or model data, which may limit their utility in the validation or verification of other climate data records. This chapter provides a review of the importance of precipitation to the climate system, the basis of satellite precipitation retrievals, climate data records of satellite data for precipitation retrievals and the development of fundamental precipitation data records for climate applications.

Climate data record↗