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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

The GLAS Science Algorithm Software (GSAS) User's Guide Version 7

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document is the final version of the GLAS Science Algorithm Software Users Guide document. It contains the instructions to install the GLAS Science Algorithm Software (GSAS) in the production environment that was used to create the standard data products. It also describes the usage of each GSAS program in that environment with their required inputs and outputs. Included are a number of utility programs that are used to create ancillary data files that are used in the processing but generally are not distributed to the public as data products. Of importance is the values for the large number of constants used in the GSAS algorithm during processing are provided in an appendix.

Lee, Jeffrey E.↗
NASA NTRS2002

Atmospheric Measurements by the 2002 Geoscience Laser Altimeter System Mission

The NASA Earth Observing System (EOS) program is a multiple platform NASA initiative for the study of global change. As part of the EOS project, the Geoscience Laser Altimeter System (GLAS) was selected as a laser sensor filling complementary requirements for several earth science disciplines including atmospheric and surface applications. Late in 2002, the GaAs instrument is to be launched for a three to five year observational mission. For the atmosphere, the instrument is designed to full fill comprehensive requirements for profiling of radiatively significant cloud and aerosol. Algorithms have been developed to process the cloud and aerosol data and provide standard data products. After launch there will be a three-month project to analyze and understand the system performance and accuracy of the data products. As an EOS mission, the GaAs measurements and data products will be openly available to all investigators. An overview of the instrument, data products and evaluation plan is given.

Spinhirne, James D.↗
NASA NTRSDate not supplied

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder Intercalibration Data Analysis Strategy

One of the prime science objectives of NASA’s Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission is to acquire unprecedentedly accurate Système Internationale (SI)-traceable Earth-view measurements that can be used as reference for intercalibrating the Clouds and the Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard NOAA-20 satellite. The hyperspectral nature of CPF measurements will significantly reduce spectrally induced biases when intercalibrating multiband or broadband satellite instruments with CPF. This advancement eliminates the requirement for spectral band adjustment factors, representing a substantial improvement in sensor intercalibration studies. The CPF intercalibration team is aiming to achieve a maximum intercalibration methodology uncertainty of 0.3 % (k=1). Our studies have revealed that the most significant contribution to the targeted uncertainty budget originates from the combined effects of spatial and temporal matching errors. Spatial matching error arises from discrepancies in CPF and target instrument pixel resolution and geolocation uncertainty, while temporal matching error is caused by changes in scene radiances over time, occurring between when the target and reference instruments observe the same scenes. To estimate the maximum expected uncertainty contribution from these sources, spatial and temporal matching noise analyses were conducted using algorithmically filtered Landsat 9 Operational Land Imager (OLI) and Geostationary Operational Environmental Satellite (GOES)-16 ABI CONUS scan data as proxies for CPF and target instruments. In the upcoming conference presentation, we will elaborate on the methodology employed in these experiments, provide details of the data filtering algorithms, and present results of the spatial and temporal matching uncertainty analyses.

Intercalibration↗
DOE OSTI2023

Earth System Model Simulations of Ameriflux sites using dynamic roots and dynamic leaf to root allocation

This data package contains point-scale Earth System Model simulations run with DOE's E3SM Model. The package includes four sets of simulations, one set of simulations run in the default configuration, a second set of simulations run with the dynamic root module enabled, the third set with dynamic leaf to fine root allocation, and the fourth with the combination of dynamic roots and dynamic allocation. These simulations were run in point mode a Ameriflux sites, US-MMS, US-Moz, US-Syv, and US-NR1. These datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and R.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

How numerical tracers and water isotope ratios help us better understand the hydrological cycle and its representation in Earth system models [Slides]

Outline: Water isotope ratios and fractionation; Isotope tracers in Earth system models; Generalized "process-oriented" water tracers in Earth system models; Opportunities in E3SM. Water isotope ratio data are rapidly becoming more available, providing a critical link between models and observations, as well as providing new opportunities to improve process representations (e.g., T/ET partitioning, cloud processes, partitioning of streamflow, coastal or urban impacts on hydrology, etc.)

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

The Earth Observing System (EOS) Ground System: Leveraging an Existing Operational Ground System Infrastructure to Support New Missions

The Earth Observer System (EOS) was officially established in 1990 and went operational in December 1999 with the launch of its flagship spacecraft Terra. Aqua followed in 2002 and Aura in 2004. All three spacecraft are still operational and producing valuable scientific data. While all are beyond their original design lifetime, they are expected to remain viable well into the 2020s. The EOS Ground System is a multi-mission system based at NASA Goddard Space Flight Center that supports science and spacecraft operations for these three missions. Over its operational lifetime to date, the EOS Ground System has evolved as needed to accommodate mission requirements. With an eye towards the future, several updates are currently being deployed. Subsystem interconnects are being upgraded to reduce data latency and improve system performance. End-of-life hardware and operating systems are being replaced to mitigate security concerns and eliminate vendor support gaps. Subsystem hardware is being consolidated through the migration to Virtual Machine based platforms. While mission operations autonomy was not a design goal of the original system concept, there is an active effort to apply state-of-the-art products from the Goddard Mission Services Evolution Center (GMSEC) to facilitate automation where possible within the existing heritage architecture. This presentation will provide background information on the EOS ground system architecture and evolution, discuss latest improvements, and conclude with the results of a recent effort that investigated how the current system could accommodate a proposed new earth science mission.

Earth Science Mission Operations (ESMO)↗
NASA NTRS2019

Using the NASA GeneLab Data System to Study the Metagenomes of Spaceships and Their Occupants

With humans pushing to live further off Earth for longer periods of time, it is increasingly important to understand the changes that occur in biological systems during spaceflight whether these be astronauts, their microbial commensals, or their plant-based life support systems. In a three-part presentation, we discuss GeneLab and recent discoveries regarding the microbiota of spacecrafts and space-flown animals. Part 1: GeneLab: Open Science for Life in Space, Jonathan Galazka, NASA Ames Research Center To accelerate the pace of discovery from precious spaceflight biological experiments, NASA as develop the GeneLab data system (genelab.nasa.gov), which allows unfettered access to omics data from spaceflight and spaceflight relevant experiments. GeneLab houses metagenomic datasets from spacecraft and relevant spacecraft models. Users can download this data and associated metadata to make new discoveries about how microbial communities may change and adapt to spaceflight.

Galazka, Jonathan M.↗
NASA NTRSDate not supplied

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗
DOE OSTI2021

Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets

Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision- and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2013

The Earth System Grid Federation: An Open Infrastructure for Access to Distributed Geospatial Data

The Earth System Grid Federation (ESGF) is a multi-agency, international collaboration that aims at developing the software infrastructure needed to facilitate and empower the study of climate change on a global scale. The ESGF s architecture employs a system of geographically distributed peer nodes, which are independently administered yet united by the adoption of common federation protocols and application programming interfaces (APIs). The cornerstones of its interoperability are the peer-to-peer messaging that is continuously exchanged among all nodes in the federation; a shared architecture and API for search and discovery; and a security infrastructure based on industry standards (OpenID, SSL, GSI and SAML). The ESGF software is developed collaboratively across institutional boundaries and made available to the community as open source. It has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the entire model output used for the next international assessment report on climate change (IPCC-AR5) and a suite of satellite observations (obs4MIPs) and reanalysis data sets (ANA4MIPs).

Climate Modelling↗
DOE OSTI2021

Implementation of an Orographic Drag Scheme Considering Orographic Anisotropy in All Flow Directions in the Earth System Model CAS‐ESM 2.0

Abstract A reasonable representation of orographic anisotropy in earth system models is vital for improving weather and climate modeling. In this study, we implement the orographic drag scheme, including 3‐D orographic anisotropy (3D‐AFD), into the Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM 2.0). Three groups of simulations named sensitivity run, medium‐range forecast, and seasonal forecast respectively are conducted using the updated CAS‐ESM model and validated against station observation and reanalysis data. These simulations are run using the three schemes—3D‐AFD scheme, the 3D orographic anisotropy scheme for the eight‐direction (3D‐8x), and the 2D isotropic scheme (2D)—to compare their performance in CAS‐ESM 2.0. Sensitivity runs show that the 3D‐AFD provide more continuous transition of calculated drag as function of wind direction than the 3D‐8x, while the drag calculated using the 2D scheme show no variation with change of wind direction. Enhanced drag in the medium range and seasonal forecast using the updated CAS‐ESM alleviates part of the winter wind speed bias over the Tibetan Plateau (TP) and the cold bias over TP and the Siberian polar region. It is shown that the 3D‐AFD scheme alleviates more bias than that of the 3D‐8x scheme (by wind speed reduction of 1 ∼ 2 m/s and temperature of 1 ∼ 2 K) especially in the seasonal forecast. The results suggest that reasonable representation of the orographic anisotropy is important in climate modeling.

Xie, Jinbo↗
NASA NTRS1992

Current status and future developments in radar remote sensing

Some of the major initiatives and directions of remote sensing using SAR (Synthetic Aperture Radar) data alone and in conjunction with other sensors for earth science investigations are outlined. Specific emphasis is on areas key to global monitoring using SAR data from spaceborne platforms: calibration, geophysical processing, and generation of digital elevation models. Calibration as used here encompasses end-to-end system characterization over the life of a sensor and characterization of data products relative to past and future sensors. Geophysical processing is defined here to include any processing which results in derived geophysical units. An additional data type, topography, which is required to complete the three-dimensional view of surface properties and correct for distortions inherent in SAR is discussed. Future challenges in radar remote sensing include development of strategies to extrapolate from regional to global scale models and development of new sensor technology.

Evans, Diane L.↗
NASA NTRS2006

A conceptual venus rover mission using advanced radioisotope power system

The primary goal of this study is to examine the feasibility of using the novel Advanced RPS-driven Stirling thermoacoustic system to enable extended science operations in the extremely hostile surface environment of Venus. The mission concept entails landing a rover onto the Venus surface, conducting science measurements in different areas on the surface, and returning the science data to Earth. The study focused on developing a rover design to satisfy the science goals with the capability to operate for 60 days. This mission life influences several design parameters, including Earth elevation angle and the maximum communications range to Earth.

TASHE rover↗
NASA NTRS2014

The Asteroid Impact and Deflection Assessment Mission and its Potential Contributions to Human Exploration of Asteroids

The joint ESA and NASA Asteroid Impact and Deflection Assessment (AIDA) mission will directly address aspects of NASA's Asteroid Initiative and will contribute to future human exploration. The NASA Asteroid Initiative is comprised of two major components: the Grand Challenge and the Asteroid Mission. The first component, the Grand Challenge, focuses on protecting Earth's population from asteroid impacts by detecting potentially hazardous objects with enough warning time to either prevent them from impacting the planet, or to implement civil defense procedures. The Asteroid Mission, involves sending astronauts to study and sample a near-Earth asteroid (NEA) prior to conducting exploration missions of the Martian system, which includes Phobos and Deimos. AIDA's primary objective is to demonstrate a kinetic impact deflection and characterize the binary NEA Didymos. The science and technical data obtained from AIDA will aid in the planning of future human exploration missions to NEAs and other small bodies. The dual robotic missions of AIDA, ESA's Asteroid Impact Monitor (AIM) and NASA's Double Asteroid Redirection Test (DART), will provide a great deal of technical and engineering data on spacecraft operations for future human space exploration while conducting in-depth scientific examinations of the binary target Didymos both prior to and after the kinetic impact demonstration. The knowledge gained from this mission will help identify asteroidal physical properties in order to maximize operational efficiency and reduce mission risk for future small body missions. The AIDA data will help fill crucial strategic knowledge gaps concerning asteroid physical characteristics that are relevant for human exploration considerations at similar small body destinations.

Abell, Paul A.↗
NASA NTRS2013

Achieving Lights-Out Operation of SMAP Using Ground Data System Automation

The approach used in the SMAP ground data system to provide reliable, automated capabilities to conduct unattended operations has been presented. The impacts of automation on the ground data system architecture were discussed, including the three major automation patterns identified for SMAP and how these patterns address the operations use cases. The architecture and approaches used by SMAP will set the baseline for future JPL Earth Science missions.

Soil Moisture Active Passive (SMAP)↗
NASA NTRS2016

A Natural Interaction Interface for UAVs Using Intuitive Gesture Recognition

The popularity of unmanned aerial vehicles (UAVs) is increasing as technological advancements boost their favorability for a broad range of applications. One application is science data collection. In fields like Earth and atmospheric science, researchers are seeking to use UAVs to augment their current portfolio of platforms and increase their accessibility to geographic areas of interest. By increasing the number of data collection platforms UAVs will significantly improve system robustness and allow for more sophisticated studies. Scientists would like be able to deploy an available fleet of UAVs to fly a desired flight path and collect sensor data without needing to understand the complex low-level controls required to describe and coordinate such a mission. A natural interaction interface for a Ground Control System (GCS) using gesture recognition is developed to allow non-expert users (e.g., scientists) to define a complex flight path for a UAV using intuitive hand gesture inputs from the constructed gesture library. The GCS calculates the combined trajectory on-line, verifies the trajectory with the user, and sends it to the UAV controller to be flown.

Chandarana, Meghan↗
NASA NTRS2017

Giovanni - The Bridge Between Data and Science

This article describes new features in the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni), a user-friendly online tool that enables visualization, analysis, and assessment of NASA Earth science data sets without downloading data and software. Since the satellite era began, data collected from Earth-observing satellites have been widely used in research and applications; however, using satellite-based data sets can still be a challenge to many. To facilitate data access and evaluation, as well as scientific exploration and discovery, the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) has developed Giovanni for a wide range of users around the world. This article describes the latest capabilities of Giovanni with examples, and discusses future plans for this innovative system.

GPM↗
NASA NTRS2017

Big lunar data visualization and analysis

NASA's earth and planetary spacecraft return large amounts of remote sensing data, such as imagery and raw science measurements, in support of remarkable research. Not only does the data lead to new scientific discoveries about our planet and the solar system, it provides a wealth of information to educate, inspire, and engage the public at large. To leverage this rich data for mission planning, scientific research, public outreach and education, it is essential to make it accessible and understandable, analyzable, all while appealing to their interests. This presentation will highlight web-based capabilities that showcase NASA's large volume of lunar data collected from past and current Moon missions. It is particularly relevant as the new Administration has more plans for the Moon. We will illustrate big data visualization and analysis in easy-touse and interactive mediums for diverse use.

Malhotra, Shan↗