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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

The Role and Evolution of NASA's Earth Science Data Systems

One of the three strategic goals of NASA is to Advance understanding of Earth and develop technologies to improve the quality of life on our home planet (NASA strategic plan 2014). NASA's Earth Science Data System (ESDS) Program directly supports this goal. NASA has been launching satellites for civilian Earth observations for over 40 years, and collecting data from various types of instruments. Especially since 1990, with the start of the Earth Observing System (EOS) Program, which was a part of the Mission to Planet Earth, the observations have been significantly more extensive in their volumes, variety and velocity. Frequent, global observations are made in support of Earth system science. An open data policy has been in effect since 1990, with no period of exclusive access and non-discriminatory access to data, free of charge. NASA currently holds nearly 10 petabytes of Earth science data including satellite, air-borne, and ground-based measurements and derived geophysical parameter products in digital form. Millions of users around the world are using NASA data for Earth science research and applications. In 2014, over a billion data files were downloaded by users from NASAs EOS Data and Information System (EOSDIS), a system with 12 Distributed Active Archive Centers (DAACs) across the U. S. As a core component of the ESDS Program, EOSDIS has been operating since 1994, and has been evolving continuously with advances in information technology. The ESDS Program influences as well as benefits from advances in Earth Science Informatics. The presentation will provide an overview of the role and evolution of NASAs ESDS Program.

Remote Sensing↗
NASA NTRS2001

The Computational Complexity, Parallel Scalability, and Performance of Atmospheric Data Assimilation Algorithms

The computational complexity of algorithms for Four Dimensional Data Assimilation (4DDA) at NASA's Data Assimilation Office (DAO) is discussed. In 4DDA, observations are assimilated with the output of a dynamical model to generate best-estimates of the states of the system. It is thus a mapping problem, whereby scattered observations are converted into regular accurate maps of wind, temperature, moisture and other variables. The DAO is developing and using 4DDA algorithms that provide these datasets, or analyses, in support of Earth System Science research. Two large-scale algorithms are discussed. The first approach, the Goddard Earth Observing System Data Assimilation System (GEOS DAS), uses an atmospheric general circulation model (GCM) and an observation-space based analysis system, the Physical-space Statistical Analysis System (PSAS). GEOS DAS is very similar to global meteorological weather forecasting data assimilation systems, but is used at NASA for climate research. Systems of this size typically run at between 1 and 20 gigaflop/s. The second approach, the Kalman filter, uses a more consistent algorithm to determine the forecast error covariance matrix than does GEOS DAS. For atmospheric assimilation, the gridded dynamical fields typically have More than 10(exp 6) variables, therefore the full error covariance matrix may be in excess of a teraword. For the Kalman filter this problem can easily scale to petaflop/s proportions. We discuss the computational complexity of GEOS DAS and our implementation of the Kalman filter. We also discuss and quantify some of the technical issues and limitations in developing efficient, in terms of wall clock time, and scalable parallel implementations of the algorithms.

Lyster, Peter M.↗
NASA NTRS2003

Targeted Research and Technology Within NASA's Living With a Star Program

NASA's Living With a Star (LWS) initiative is a systematic, goal-oriented research program targeting those aspects of the Sun-Earth system that affect society. The Targeted Research and Technology (TR&T) component of LWS provides the theory, modeling, and data analysis necessary to enable an integrated, system-wide picture of Sun-Earth connection science with societal relevance. Recognizing the central and essential role that TR&T would have for the success of the LWS initiative, the LWS Science Architecture Team (SAT) recommended that a Science Definition Team (SDT), with the same status as a flight mission definition team, be formed to design and coordinate a TR&T program having prioritized goals and objectives that focused on practical societal benefits. This report details the SDT recommendations for the TR&T program.

Hesse, Michael↗
NASA NTRS2004

Targeted Research and Technology Within NASA's Living With a Star Program

Targeted Research & Technology (TR&T) NASA's Living With a Star (LWS) initiative is a systematic, goal-oriented research program targeting those aspects of the Sun-Earth system that affect society. The Targeted Research and Technology (TR&T) component of LWS provides the theory, modeling, and data analysis necessary to enable an integrated, system-wide picture of Sun-Earth connection science with societal relevance. Recognizing the central and essential role that TR&T would have for the success of the LWS initiative, the LWS Science Architecture Team (SAT) recommended that a Science Definition Team (SDT), with the same status as a flight mission definition team, be formed to design and coordinate a TR&T program having prioritized goals and objectives that focused on practical societal benefits. This report details the SDT recommendations for the TR&T program.

Antiochos, Spiro↗
NASA NTRS2014

The Experimental Regional Ensemble Forecast System (ExREF): Its Use in NWS Forecast Operations and Preliminary Verification

The Experimental Regional Ensemble Forecast (ExREF) system is a tool for the development and testing of new Numerical Weather Prediction (NWP) methodologies. ExREF is run in near‐realtime by the Global Systems Division (GSD) of the NOAA Earth System Research Laboratory (ESRL) and its products are made available through a website, an ftp site, and via the Unidata Local Data Manager (LDM). The ExREF domain covers most of North America and has 9‐km horizontal grid spacing. The ensemble has eight members, all employing WRF‐ARW. The ensemble uses a variety of initial conditions from LAPS and the Global Forecasting System (GFS) and multiple boundary conditions from the GFS ensemble. Additionally, a diversity of physical parameterizations is used to increase ensemble spread and to account for the uncertainty in forecasting extreme precipitation events. ExREF has been a component of the Hydrometeorology Testbed (HMT) NWP suite in the 2012‐2013 and 2013‐2014 winters. A smaller domain covering just the West Coast was created to minimize band‐width consumption for the NWS. This smaller domain has and is being distributed to the National Weather Service (NWS) Weather Forecast Office and California Nevada River Forecast Center in Sacramento, California, where it is ingested into the Advanced Weather Interactive Processing System (AWIPS I and II) to provide guidance on the forecasting of extreme precipitation events. This paper will review the cooperative effort employed by NOAA ESRL, NASA SPoRT (Short‐term Prediction Research and Transition Center), and the NWS to facilitate the ingest and display of ExREF data utilizing the AWIPS I and II D2D and GFE (Graphical Software Editor) software. Within GFE is a very useful verification software package called BoiVer that allows the NWS to utilize the River Forecast Center's 4 km gridded QPE to compare with all operational NWP models 6‐hr QPF along with the ExREF mean 6‐hr QPF so the forecasters can build confidence in the use of the ExREF in preparing their rainfall forecasts. Preliminary results will be presented.

Reynolds, David↗
NASA NTRS2014

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than algorithms without the ultraviolet Rrs bands. This suggests that satellite sensors with ultraviolet capability could provide better retrievals of CDOM. Because of the strong correlations between CDOM parameters and DOM constituents in the coastal ocean, satellite observations of CDOM parameters can be applied to study the distributions, sources and sinks of DOM, which are relevant for understanding the carbon cycle, modeling the Earth system, and to discern how the Earth is changing.

CDOM Properties↗
NASA NTRS2014

The Large-Scale Current System During Auroral Substorms

We present an empirical model of the equivalent current system in the ionosphere during the peak of a classical bulge-type auroral sub storm. This model is derived from measurements made by ~110 ground magnetometer stations during 116 substorms. The data are temporally and spatially organized using global auroral images obtained by the Polar Visible Imaging System Earth Camera. The empirical equivalent current system displays three key features: a poleward shift of the westward electrojet connecting the postmidnight and premidnight components; a polar cap swirl; and significantly different magnitudes of the postmidnight and premidnight westward electrojets. This leads us to propose a two-wedge current system linking the ionosphere to the magnetosphere. The bulge current wedge is located in the premidnight region just equatorward of the open-closed field line boundary while another three-dimensional current system is located in the postmidnight region well within the auroral oval. We use Biot and Savart calculations and Tsyganenko mapping and show that this new model is a likely solution for the large-scale current system.

magnetic storms↗
NASA NTRS2018

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Earth observations↗
NASA NTRS2023

Surface Biology and Geology Imaging Spectrometer: A Case Study to Optimize the Mission Design Using Intrinsic Dimensionality

The information content that can be derived from spectroscopic imagery tends to increase with finer ground sampling distance, finer spectral sampling, more frequent revisit, and higher signal-to-noise ratios (SNRs). However, these parameters are not independent, and it is thus impossible to design a space-borne imaging spectrometer to maximize all of them simultaneously. We present an instrument model and simulation environment that enable us to find the optimal combination of these four mission design parameters, using intrinsic dimensionality (ID) as the metric. ID is the size of the signal subspace – the maximum degrees of freedom when noise can be disregarded – and is a metric that is independent of any one particular algorithm or application area. This study is important for upcoming missions such as NASA's Earth System Observatory mission to study the Earth's Surface Biology and Geology (SBG), which will comprise a visible to shortwave infrared spectrometer in addition to a multi-channel thermal radiometer on a separate platform. When evaluating a desert site and a tropical forested site, we find that spectral resolution drives information content, with a significant drop in normalized ID (15–45% decrease) when simulating 15 nm spectral sampling as opposed to 10 nm spectral sampling. However, there was some variation between sites, with the forested site benefiting from 5 nm spectral sampling, whereas the desert site had poorer results at this resolution, due to the impact on noise. At 10 nm spectral sampling, ground sampling distances in the range 30–50 m provided the optimal balance between spatial resolution and SNR, although more frequent revisit, potentially by combining data from multiple missions, would maximize total information content.

Mission design↗
NASA NTRSDate not supplied

Open Source Application of Fusing Aerosol Products from GEO and LEO Satellites

Retrieving aerosol optical depths (AODs) from sun-synchronous polar orbiting (aka low earth orbit, LEO) satellites, such as MODISs, and VIIRSs, OMI, TROPOMI, etc, has become well-established as a tool for extracting information on particulate matter (PM) and related processes in the atmosphere. However, with recently launched geostationary satellites (GEO), such as GOES-16/17/18, and Himawari-8/9, and Meteosat Third Generation (MTG) they provide a much higher temporal resolution (order of 10 minutes), typically an image once or more per hour during daylight compared to LEO once per day. By combining these observations, we may be able to characterize the diurnal cycle of global AOD at the local, regional and global scale. While the science community is still exploring the new data from GEO observations, we have been thinking about how to properly combine/merge/fuse those data considering differences in their spatial and temporal resolutions. However, this poses a “Big Data” challenge. The big data challenge is not just about data storage, but also about data discoverability, and accessibility, and even more, about data migration/mirroring in the cloud-computing environment. This paper is merely showing some of the efforts and approaches we have attempted in fusing six satellites’ Level 2 aerosol data (three are from GEO (GOES-16/17 and Himawari-8), and the other three are from LEO (TERRA/MODIS, AQUA/MODIS, SNPP-VIIRS) from Dark Target (DT) aerosol retrieval algorithm. Having the on-demand capability of fusing remote sensing products onto the desired temporal and spatial domain enables researchers and application practitioners to better manipulate and work with satellite and sensor data. It is our hopeWe hope that by making such an open-source package, and the accompanying functionality, the scientific community will be granted easier access to aerosol data processing resources. The MEaSUREs Program (Making Earth System Data Records for Use in Research Environments) expands our understanding of the Earth's current system through atmospheric and surface measurements. In an effort to aid the scientific research component and improve open source methods, this project developed Python code for fusing six satellite Level 2 aerosol data (three are from geostationary satellites (GEO), and the other three are from low earth orbital satellites (LEO)) from Dark Target Aerosol Retrieval Algorithm.

Jennifer Wei↗
NASA NTRS2023

NASA’s Atmosphere Observing System (AOS), From A Precipitation Perspective

NASA is developing the Atmosphere Observing System (AOS) mission as part of its Earth System Observatory (ESO) in response to priorities identified in the 2017 Earth Science Decadal Survey. AOS addresses the Decadal Survey’s call for missions measuring the targeted observables “clouds, convection, and precipitation”; “aerosol and cloud radiative properties”, and “aerosol vertical profiles”. AOS is currently in Phase A, the concept and technology development phase, with plans for satellite launches in the late 2020’s and early 2030’s, and suborbital measurements to include field campaigns after those satellite launches. Key precipitation-related instrumentation includes Doppler radars capable of measuring clouds and precipitation, and passive microwave radiometers with channels between 89-700 GHz. Other instrumentation includes dual-wavelength backscatter lidars, a multi-wavelength and multi-angle polarimeter, a far infrared imaging radiometer, and aerosol and moisture limb sounders that will contribute to studies of coupled aerosol-cloud-precipitation processes. From the perspective of precipitation science, a Ku-band Doppler radar in a 55° inclined orbit provided by JAXA will continue the heritage of precipitation radar measurements made by the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM), while adding information about Doppler-derived particle vertical motions. With assumptions about particle terminal velocities, the Doppler measurements will enable estimates of the vertical air motion in storms. A higher frequency (W and/or Ka band) radar on a satellite in a polar sun-synchronous orbit will add similar information with greater sensitivity to clouds and to light precipitation. Passive microwave radiometers for AOS will be less capable than those from TRMM and GPM from a precipitation-measurement perspective, but more capable of adding information about cloud processes. Synergies among these and other instruments are expected to advance process-level understanding of aerosols, clouds, and precipitation.

Daniel J Cecil↗
NASA NTRS1994

Environmental Durability Issues for Solar Power Systems in Low Earth Orbit

Space solar power systems for use in the low Earth orbit (LEO) environment experience a variety of harsh environmental conditions. Materials used for solar power generation in LEO need to be durable to environmental threats such as atomic oxygen, ultraviolet (UV) radiation, thermal cycling, and micrometeoroid and debris impact. Another threat to LEO solar power performance is due to contamination from other spacecraft components. This paper gives an overview of these LEO environmental issues as they relate to space solar power system materials. Issues addressed include atomic oxygen erosion of organic materials, atomic oxygen undercutting of protective coatings, UV darkening of ceramics, UV embrittlement of Teflon, effects of thermal cycling on organic composites, and contamination due to silicone and organic materials. Specific examples of samples from the Long Duration Exposure Facility (LDEF) and materials returned from the first servicing mission of the Hubble Space Telescope (HST) are presented. Issues concerning ground laboratory facilities which simulate the LEO environment are discussed along with ground-to-space correlation issues.

Degroh, Kim K.↗
NASA NTRS1974

On the access to an earth resources data processing system

The Purdue/LARS earth resources data processing system is briefly described. The considerations to which an organization would want to give attention before obtaining a remote terminal to this system are discussed. The support of such a terminal which Purdue/LARS is willing to propose is described.

Phillips, T. L.↗
NASA NTRS1992

A distributed analysis and visualization system for model and observational data

The objective of this proposal is to develop an integrated and distributed analysis and display software system which can be applied to all areas of the Earth System Science to study numerical model and earth observational data from storm to global scale. This system will be designed to be easy to use, portable, flexible and easily extensible and to adhere to current and emerging standards whenever possible. It will provide an environment for visualization of the massive amounts of data generated from satellites and other observational field measurements and from model simulations during or after their execution. Two- and three-dimensional animation will also be provided. This system will be based on a widely used software package from NASA called GEMPAK and prototype software for three dimensional interactive displays built at NCSA. The underlying foundation of the system will be a set of software libraries which can be distributed across a UNIX based supercomputer and workstations.

Wilhelmson, Robert↗
NASA NTRS1993

A distributed analysis and visualization system for model and observational data

The objective of this proposal is to develop an integrated and distributed analysis and display software system which can be applied to all areas of the Earth System Science to study numerical model and earth observational data from storm to global scale. This system will be designed to be easy to use, portable, flexible and easily extensible and designed to adhere to current and emerging standards whenever possible. It will provide an environment for visualization of the massive amounts of data generated from satellites and other observational field measurements and from model simulations during or after their execution. Two- and three-dimensional animation will also be provided. This system will be based on a widely used software package from NASA called GEMPAK and prototype software for three-dimensional interactive displays built at NCSA. The underlying foundation of the system will be a set of software libraries which can be distributed across a UNIX based supercomputer and workstations.

Wilhelmson, Robert↗
NASA NTRS2017

Embracing Open Source for NASA's Earth Science Data Systems

The overarching purpose of NASAs Earth Science program is to develop a scientific understanding of Earth as a system. Scientific knowledge is most robust and actionable when resulting from transparent, traceable, and reproducible methods. Reproducibility includes open access to the data as well as the software used to arrive at results. Additionally, software that is custom-developed for NASA should be open to the greatest degree possible, to enable re-use across Federal agencies, reduce overall costs to the government, remove barriers to innovation, and promote consistency through the use of uniform standards. Finally, Open Source Software (OSS) practices facilitate collaboration between agencies and the private sector. To best meet these ends, NASAs Earth Science Division promotes the full and open sharing of not only all data, metadata, products, information, documentation, models, images, and research results but also the source code used to generate, manipulate and analyze them. This talk focuses on the challenges to open sourcing NASA developed software within ESD and the growing pains associated with establishing policies running the gamut of tracking issues, properly documenting build processes, engaging the open source community, maintaining internal compliance, and accepting contributions from external sources. This talk also covers the adoption of existing open source technologies and standards to enhance our custom solutions and our contributions back to the community. Finally, we will be introducing the most recent OSS contributions from NASA Earth Science program and promoting these projects for wider community review and adoption.

Earth Science↗