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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Community Involvement in Enhancing the Global Change Master Directory (GCMD) Controlled Vocabularies (Keywords)

NASA's Global Change Master Directory (GCMD) develops and expands a hierarchical set of controlled vocabularies (keywords) covering the Earth sciences and associated information (data centers, projects, platforms, instruments, etc.). The purpose of the keywords is to describe Earth science data and services in a consistent and comprehensive manner, allowing for the precise searching of metadata and subsequent retrieval of data and services. The keywords are accessible in a standardized SKOSRDFOWL representation and are used as an authoritative taxonomy, as a source for developing ontologies, and to search and access Earth Science data within online metadata catalogues. The keyword development approach involves: (1) receiving community suggestions, (2) triaging community suggestions, (3) evaluating the keywords against a set of criteria coordinated by the NASA ESDIS Standards Office, and (4) publication/notification of the keyword changes. This approach emphasizes community input, which helps ensure a high quality, normalized, and relevant keyword structure that will evolve with users changing needs. The Keyword Community Forum, which promotes a responsive, open, and transparent processes, is an area where users can discuss keyword topics and make suggestions for new keywords. The formalized approach could potentially be used as a model for keyword development.

governance↗
NASA NTRS2013

Datacasting V3.0

Datacasting V3.0 provides an RSSbased feed mechanism for publishing the availability of Earth science data records in real time. It also provides a utility for subscribing to these feeds and sifting through all the items in an automatic manner to identify and download the data records that are required for a specific application. Datacasting is a method by which multiple data providers can publish the availability of new Earth science data and users download those files that meet a predefined need; for example, to only download data files related to a specific earthquake or region on the globe. Datacasting is a server-client architecture. The server-side software is used by data providers to create and publish the metadata about recently available data according to the Datacasting RSS (Really Simple Syndication) specification. The client software subscribes to the Datacasting RSS and other RSS-based feeds. By configuring filters associated with feeds, data consumers can use the client to identify and automatically download files that meet a specific need. On the client side, a Datacasting feed reader monitors the server for new feeds. The feed reader will be tuned by the user, via a graphical user interface (GUI), to examine the content of the feeds and initiate a data pull after some criteria are satisfied. The criteria might be, for example, to download sea surface temperature data for a particular region that has cloud cover less than 50% and during daylight hours. After the granule is downloaded to the client, the user will have the ability to visualize the data in the GUI. Based on the popular concept of podcasting, which gives listeners the capability to download only those MP3 files that match their preference, Earth science Datacasting will give users a method to download only the Earth science data files that are required for a particular application.

Bingham, Andrew W.↗
NASA NTRS2012

Soil Moisture Active/Passive (SMAP) Forward Brightness Temperature Simulator

The SMAP is one of four first-tier missions recommended by the US National Research Council's Committee on Earth Science and Applications from Space (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, Space Studies Board, National Academies Press, 2007) [1]. It is to measure the global soil moisture and freeze/thaw from space. One of the spaceborne instruments is an L-band radiometer with a shared single feedhorn and parabolic mesh reflector. While the radiometer measures the emission over a footprint of interest, unwanted emissions are also received by the antenna through the antenna sidelobes from the cosmic background and other error sources such as the Sun, the Moon and the galaxy. Their effects need to be considered accurately, and the analysis of the overall performance of the radiometer requires end-to-end performance simulation from Earth emission to antenna brightness temperature, such as the global simulation of L-band brightness temperature simulation over land and sea [2]. To assist with the SMAP radiometer level 1B algorithm development, the SMAP forward brightness temperature simulator is developed by adapting the Aquarius simulator [2] with necessary modifications. This poster presents the current status of the SMAP forward brightness simulator s development including incorporating the land microwave emission model and its input datasets, and a simplified atmospheric radiative transfer model. The latest simulation results are also presented to demonstrate the ability of supporting the SMAP L1B algorithm development.

Peng, Jinzheng↗
DOE OSTI2024

Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications

Abstract Robust quantification of predictive uncertainty is a critical addition needed for machine learning applied to weather and climate problems to improve the understanding of what is driving prediction sensitivity. Ensembles of machine learning models provide predictive uncertainty estimates in a conceptually simple way but require multiple models for training and prediction, increasing computational cost and latency. Parametric deep learning can estimate uncertainty with one model by predicting the parameters of a probability distribution but does not account for epistemic uncertainty. Evidential deep learning, a technique that extends parametric deep learning to higher-order distributions, can account for both aleatoric and epistemic uncertainties with one model. This study compares the uncertainty derived from evidential neural networks to that obtained from ensembles. Through applications of the classification of winter precipitation type and regression of surface-layer fluxes, we show evidential deep learning models attaining predictive accuracy rivaling standard methods while robustly quantifying both sources of uncertainty. We evaluate the uncertainty in terms of how well the predictions are calibrated and how well the uncertainty correlates with prediction error. Analyses of uncertainty in the context of the inputs reveal sensitivities to underlying meteorological processes, facilitating interpretation of the models. The conceptual simplicity, interpretability, and computational efficiency of evidential neural networks make them highly extensible, offering a promising approach for reliable and practical uncertainty quantification in Earth system science modeling. To encourage broader adoption of evidential deep learning, we have developed a new Python package, Machine Integration and Learning for Earth Systems (MILES) group Generalized Uncertainty for Earth System Science (GUESS) (MILES-GUESS) ( https://github.com/ai2es/miles-guess ), that enables users to train and evaluate both evidential and ensemble deep learning. Significance Statement This study demonstrates a new technique, evidential deep learning, for robust and computationally efficient uncertainty quantification in modeling the Earth system. The method integrates probabilistic principles into deep neural networks, enabling the estimation of both aleatoric uncertainty from noisy data and epistemic uncertainty from model limitations using a single model. Our analyses reveal how decomposing these uncertainties provides valuable insights into reliability, accuracy, and model shortcomings. We show that the approach can rival standard methods in classification and regression tasks within atmospheric science while offering practical advantages such as computational efficiency. With further advances, evidential networks have the potential to enhance risk assessment and decision-making across meteorology by improving uncertainty quantification, a longstanding challenge. This work establishes a strong foundation and motivation for the broader adoption of evidential learning, where properly quantifying uncertainties is critical yet lacking.

Schreck, John S.↗
NASA NTRSDate not supplied

Keywords for All People: How Keyword Governance and Coordination with the NASA ESDIS Standards Coordination Office (ESCO) Improves GCMD Keywords for Discuvery and Use

The Global Change Master Directory (GCMD) Keywords, initiated over twenty years ago, are a hierarchical set of controlled Earth Science vocabularies that help ensure Earth science data, services, and variables are described in a consistent and comprehensive manner and allow for the precise searching of metadata and subsequent retrieval of data, services, and variables. GCMD keywords are periodically analyzed for relevancy and will continue to be refined and expanded in response to user needs. The periodic analysis is a result of successful coordination with the ESDIS Standards Coordination Office (ESCO), which is responsible for standards activities across ESDIS, and assists with providing valuable stakeholder and subject matter expert (SME) feedback on GCMD vocabularies. The ESCO is also turning to the GCMD to discuss how the keyword review process can be improved and more streamlined. In addition to the ESCO, keyword requests and feedback are also received through the GCMD Keyword Forum.

Tyler Stevens↗
NASA NTRSDate not supplied

Aerosol Wind Profiler (AWP) Doppler Wind Lidar Airborne Observations During the NOAA Joint Venture 3-D Wind Measurement Demonstration and NASA Active-Passive Profiling Experiment (APEX)

The NASA Langley Research Center (LaRC) has recently completed development of the Aerosol Wind Profiler (AWP) airborne Doppler wind lidar (DWL) instrument. AWP was supported by the NASA Earth Science Technology Office and the Earth Science Division, a project that adapted the Wind-Space Pathfinder (Wind-SP) DWL transceiver onto a structure for flight aboard a variety of NASA research aircraft. AWP demonstrates many technologies required for a space DWL mission, including a coherent-detection, optical heterodyne laser transmitter with high pulse energy (up to ~55 mJ) and repetition rate (200 Hz), electronic control of the beam path allowing for multiple viewing angles (allowing vector wind measurements) with no moving parts, compact highly-stable and tunable reference lasers allowing for high-precision measurement of velocity at long ranges while mitigating the impact of satellite platform velocity, and many others. AWP represents NASA’s only currently operational airborne 3-D wind profiling sensor. NASA LaRC was selected by the NOAA Joint Venture (JV) program to conduct a suborbital 3-D Wind measurement campaign demonstrate how data from a coherent-detection DWL like AWP could serve NOAA’s weather analysis and forecasting needs. The NOAA JV program is designed to work with the private sector, academia and other federal agencies to explore the feasibility and capability of emerging technologies spacecraft and other mission-specific tools to meet NOAA’s mission requirements. AWP was initially demonstrated on the NASA DC-8 within this JV program in October 2023, piggybacking on the NASA EcoDemonstrator mission focused on in-situ sampling of jet aircraft emissions and contrail formation from Everett, Washington. The in-situ sampling resulted in very frequent and rapid aircraft attitude changes which unfortunately degraded AWP data quality. But, during times with level flight and AVAPS dropsonde operations, AWP demonstrated excellent precision (< 2 m/s RMS) with high vertical (< 100 meter) resolution and 2 km spacing between profiles. AWP will be flown again on the NASA LaRC Gulfstream-3 from mid-September to mid-October 2024 out of Hampton, VA to complete the NOAA JV 3-D wind demonstration. Additional AWP flights will occur in early November from southern California during the NASA Active-Passive Profiling Experiment (APEX), focused on underflights of the NASA ER-2 equipped with many atmospheric profiling sensors. This presentation will summarize AWP measurements collected during these two fall 2024 flight campaigns, and how the AWP data compares with AVAPS dropsonde, NOAA weather prediction model, and GOES atmospheric motion vector data.

Kristopher Bedka↗
NASA NTRS2019

NASA ESDIS Standards Office

The ESDIS Standards Office (ESO) assists NASA’s Earth Science Data and Information System (ESDIS) project in formulating standards policy for NASA Earth Science Data Systems, coordinates standards activities within ESDIS, and provides technical expertise and assistance with standards related tasks within the NASA Earth Science Data System Working Groups (ESDSWG).

Enloe, Yonsook↗
NASA NTRS2007

The Crew Earth Observations Experiment: Earth System Science from the ISS

This viewgraph presentation reviews the use of Astronaut Photography (AP) as taken from the International Space Station (ISS) in Earth System Science (ESS). Included are slides showing basic remote sensing theory, data characteristics of astronaut photography, astronaut training and operations, crew Earth observations group, targeting sites and acquisition, cataloging and database, analysis and applications for ESS, image analysis of particular interest urban areas, megafans, deltas, coral reefs. There are examples of the photographs and the analysis.

Stefanov, William L.↗
NASA NTRS2016

NASA ESTO Lidar Technologies Investment Strategy: 2016 Decadal Update

The NASA Earth Science Technology Office (ESTO) recently updated its investment strategy in the area of lidar technologies as it pertains to NASA's Earth Science measurement goals in the next decade. The last ESTO lidar strategy was documented in 2006. The current (2016) report assesses the state-of-the-art in lidar technologies a decade later. Lidar technology maturation in the past decade has been evaluated, and the ESTO investment strategy is updated and laid out in this report according to current NASA Earth science measurement needs and new emerging technologies.

earth science↗
NASA NTRS2022

A Long-Lived Lander for Venus Surface Insitu Science

Earth’s sister planet, Venus, continues to hide important scientific clues about our solar system, terrestrial planets around other stars, and about our home planet as well. Venus was the first planet human-built spacecraft have flown by, several missions have orbited around it and many short-duration landers operated have landed on it, yet there are still many important and basic science questions that need answering about this mysterious body. This fact exists because the planet poses significant challenges to acquiring the needed data when relying on tradition planetary spacecraft design approaches. This presentation will provide a short background, description, and status of a project that is taking a novel approach to meet some of the Venus challenges and prepare NASA to address the key science questions about its climate, surface, and eventually interior.

Venus↗
DOE OSTI2022

Role of copper in nitrous oxide accumulation in wetland soils from Illinois and South Carolina and stream sediments from Tennessee

Denitrification is microbially-mediated through enzymes containing metal cofactors. Laboratory studies of pure cultures have highlighted that the availability of copper (Cu), required for the multicopper enzyme nitrous oxide reductase, can limit nitrous oxide (N2O) reduction. However, in natural aquatic systems, such as wetlands and hyporheic zones in stream beds, the role of Cu in controlling denitrification remains incompletely understood. In this study, we collected soils and sediments from three natural environments -- riparian wetlands, marsh wetlands, and a stream -- to investigate their nitrogen species transformation activity at background Cu levels and different supplemented Cu loadings. All of the systems contained solid-phase associated Cu below or around geological levels (40–280 nmol g-1) and exhibited low dissolved Cu (3–50 nM), which made them appropriate sites for evaluating the effect of limited Cu availability on denitrification.The dataset contains the variation in the nutrient (nitrate (NO3-), nitrite (NO2-), and ammonium (NH4+)) and N2O concentrations during the incubation experiments to evaluate the effect of Cu. We have also reported the variation in metal concentrations (Cu, iron(Fe) and manganese (Mn)) and dissolved organic carbon (DOC) concentrations during the incubations. The parameters obtained using a kinetic model to quantitatively report the effect of Cu on nitrogen species conversion in natural aquatic systems are also added in the dataset. The dataset also contains the labile concentration of Cu estimated using a speciation model in MINTEQ. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units.Our study suggests that high concentrations of N2O accumulated in all microcosms lacking Cu amendment except for one stream sediment sample. With Cu added to provide dissolved concentrations at trace levels (10–300 nM), the reduction rate of N2O to N2 in the wetland soils and stream sediments was enhanced. A kinetic model could account for the trends in nitrogen species by combining the reactions for microbial reduction of NO3- to NO2-/N2O/N2 and abiotic reduction of NO2 to nitrogen (N2_. The model revealed that the rate of N2O to N2 conversion increased significantly in the presence of Cu. For riparian wetland soils and stream sediments, the kinetic model also suggested that overall denitrification is driven by abiotic reduction of NO2- in the presence of inorganic electron donors. This study demonstrated that natural aquatic systems containing Cu at concentrations less than or equal to crustal abundances may display incomplete reduction of N2O to N2 that would cause N2O accumulation and release to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Regier et al. (2025), "Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest"

Rising sea levels and intensifying storms increase flooding pressure on coastal forests, but the mechanisms that drive coastal forest mortality remain unclear. This study used an ecosystem-scale manipulation (TEMPEST, Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments) to simulate hurricane-level flooding of a coastal forest and explore the individual and interactive impacts of inundation and salinity. This dataset comprises the results reported by Regier et al. (2025) in their paper "Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest." It consists of measurements of:- Belowground conductance- Soil dissolved oxygen and redox- Soil and tree greenhouse gas fluxes- Leaf photosynthesis, stomatal conductance, and intercellular carbon dioxide- Sap flux- Soil volumetric water content and electrical conductivityAll files are plain-text CSV (comma separated value) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

EOSDIS: Archive and Distribution Systems in the Year 2000

Earth Science Enterprise (ESE) is a long-term NASA research mission to study the processes leading to global climate change. The Earth Observing System (EOS) is a NASA campaign of satellite observatories that are a major component of ESE. The EOS Data and Information System (EOSDIS) is another component of ESE that will provide the Earth science community with easy, affordable, and reliable access to Earth science data. EOSDIS is a distributed system, with major facilities at seven Distributed Active Archive Centers (DAACs) located throughout the United States. The EOSDIS software architecture is being designed to receive, process, and archive several terabytes of science data on a daily basis. Thousands of science users and perhaps several hundred thousands of non-science users are expected to access the system. The first major set of data to be archived in the EOSDIS is from Landsat-7. Another EOS satellite, Terra, was launched on December 18, 1999. With the Terra launch, the EOSDIS will be required to support approximately one terabyte of data into and out of the archives per day. Since EOS is a multi-mission program, including the launch of more satellites and many other missions, the role of the archive systems becomes larger and more critical. In 1995, at the fourth convening of NASA Mass Storage Systems and Technologies Conference, the development plans for the EOSDIS information system and archive were described. Five years later, many changes have occurred in the effort to field an operational system. It is interesting to reflect on some of the changes driving the archive technology and system development for EOSDIS. This paper principally describes the Data Server subsystem including how the other subsystems access the archive, the nature of the data repository, and the mass-storage I/O management. The paper reviews the system architecture (both hardware and software) of the basic components of the archive. It discusses the operations concept, code development, and testing phase of the system. Finally, it describes the future plans for the archive.

Behnke, Jeanne↗
NASA NTRSDate not supplied

Preserving NASA Historic and Current Mission Data and Adding Value to These for Future Researchers

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been actively involved in many aspects of ensuring the long-term preservation of NASA earth science data and knowledge. This involves both the recovery and preservation of early NASA meteorological and other earth observation data, as well as preserving the more recent Earth Observation System (EOS) mission data sets which continue or have reached their end of lifetime. The GES DISC adds value to these preserved data by adding metadata and making the data available online to future researchers. The early NASA meteorological and earth observation data sets from the 1960s and 70s were originally archived on magnetic tapes, and visualizations of these data were preserved on 70-mm film. As these media have aged, their contents have been at risk of permanent loss. NASA has given the task of preserving these early data sets to the GES DISC and making these data sets easily available to the public. The data from these early missions are potentially useful to climate researchers as these are some of the only global measurements made at their time. These old data on magnetic tapes and film strips do not contain easily readable metadata, and so to add value the GES DISC has added digital metadata to them so that the data are searchable and findable. The GES DISC is also involved in preserving the data and knowledge from the EOS era missions. The GES DISC follows the guidelines developed for the preservation of data as specified in the NASA EOS Data and Information System (EOSDIS) Earth Science Data Preservation Content Specification (423-SPEC-001) document. To date, the GES DISC has consulted with the data science teams from the following missions: UARS, Earth Probe TOMS, Aura HIRDLS, and SORCE, in order to properly preserve their data and accompanying documentation. The GES DISC is also currently working with the EOS science teams from TRMM, AIRS, MLS, OMI and additional missions to ensure that the relevant documents and data sets are properly archived for future researchers. A standardized procedure for mission data preservation following 423-SPEC-001 makes preservation among the many NASA EOSDIS data centers uniform, so that these could be transitioned easily to a common EOSDIS preservation repository. This presentation will give an overview of the preservation and recovery of the old NASA historical data sets archived at the GES DISC, as well as the data and documentation preservation efforts of the EOS era missions.

James Johnson↗
NASA NTRS2008

Accessing and Utilizing Remote Sensing Data for Vectorborne Infectious Diseases Surveillance and Modeling

Background: The transmission of vectorborne infectious diseases is often influenced by environmental, meteorological and climatic parameters, because the vector life cycle depends on these factors. For example, the geophysical parameters relevant to malaria transmission include precipitation, surface temperature, humidity, elevation, and vegetation type. Because these parameters are routinely measured by satellites, remote sensing is an important technological tool for predicting, preventing, and containing a number of vectorborne infectious diseases, such as malaria, dengue, West Nile virus, etc. Methods: A variety of NASA remote sensing data can be used for modeling vectorborne infectious disease transmission. We will discuss both the well known and less known remote sensing data, including Landsat, AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), TRMM (Tropical Rainfall Measuring Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), EO-1 (Earth Observing One) ALI (Advanced Land Imager), and SIESIP (Seasonal to Interannual Earth Science Information Partner) dataset. Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center. It provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. After remote sensing data is obtained, a variety of techniques, including generalized linear models and artificial intelligence oriented methods, t 3 can be used to model the dependency of disease transmission on these parameters. Results: The processes of accessing, visualizing and utilizing precipitation data using Giovanni, and acquiring other data at additional websites are illustrated. Malaria incidence time series for some parts of Thailand and Indonesia are used to demonstrate that malaria incidences are reasonably well modeled with generalized linear models and artificial intelligence based techniques. Conclusions: Remote sensing data relevant to the transmission of vectorborne infectious diseases can be conveniently accessed at NASA and some other websites. These data are useful for vectorborne infectious disease surveillance and modeling.

Kiang, Richard↗
NASA NTRS2000

New Millennium EO3

The New Millennium Program (NMP) is a NASA technology program that focuses on the validation of advanced spacecraft and instrumentation technologies in space. This program specifically seeks technologies that could significantly benefit future space and Earth science missions by enabling new science capabilities and reducing life cycle costs. These technologies must also require a validation in space to mitigate risks to the first science users, and provide cross-cutting benefits to both NASA's Earth and Space Science enterprises. The NASA Office of Earth Science (OES) directed the NMP to focus the third Earth Observing mission, E03, on innovative measurement concepts that would facilitate remote sensing observations from orbits beyond conventional low-Earth orbit (LEO). These orbits include geosynchronous orbits, highly elliptical orbits, mid-Earth and high-Earth orbits, and other unique vantage points such as L1 and L2. To maximize the input from the Earth science community, a NASA Research Announcement (NRA) was released to solicit innovative measurement concepts for this NMP flight. Because the NMP is a technology validation program, rather than a conventional science program, the NRA required that these measurement concepts employ revolutionary technologies and/or measurement strategies that will enable future science missions from orbits beyond LEO. Another requirement was that a validation in space was needed to reduce real or perceived risks of this concept to future science users. The proposals submitted in response to this NRA were peer reviewed by the NASA OES. The measurement concepts selected through this process will be summarized in this presentation. The E03 measurement concept NRA did not solicit complete mission concepts or flight hardware. Instead, the selected investigators will join integrated project formulation teams to define the mission for the demonstration of the measurement technique and participate in mission design trades and implementation planning. The teams will define and document the measurement approach, the required technologies, the validation plan, the scalability of the design to future science missions, and the infusion path for the completely validated instrument. During this project formulation phase, the specific technologies required to implement each measurement concept will be solicited through an open technology solicitation, and the technology providers will be added to the integrated teams. Once a complete candidate mission concept has been formulated for each measurement concept, these concepts will be subjected to a comprehensive review. The Associate Administrator of the OES will use the results of this review to select a single concept for the E03 flight opportunity. That mission concept will enter its implementation phase, which is expected to last for less than 36 months before launch. During this phase, and after launch, the implementation team will work with the NMP to document and disseminate the information gathered during the flight qualification testing and operations of the measurement concept and its component technologies. This information will be archived and published, where appropriate, to encourage the rapid infusion of these validated technologies into future space and Earth science missions. I

Li, Fuk K.↗
NASA NTRS1990

Towards a coherent remote sensing data policy

Access to space-based remote sensing data is critical for earth science and the study of global change. This article summarizes a variety of U.S. government earth science data policies and problems. The authors examine current efforts to develop data policies for the next generation of U.S. remote sensing programs, noting likely problems based on past experiences. They argue that the goal of U.S. earth science data policy should be to provide the widest possible dissemination of data. Setting such a goal permits the development of a simple, coherent data policy that serves scientific, commercial, and U.S. government interests.

Shaffer, Lisa R.↗
NASA NTRSDate not supplied

VEDA Visualization Exploration & Data Analysis

Why? - Interdisciplinary science depends on large amount of Earth science data and computational resources - Working with these datasets is non-trivial - Big data science requires advanced distributed computing knowledge What? VEDA is an open platform that brings key Earth science datasets next to open source tools for data processing, analysis, visualization, and exploration in a managed and more accessible computing environment.

Manil Maskey↗