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At least 1,135 records · Page 63

All sources NASA NTRS DOE OSTI

NASA NTRS2014

NASA 2014 The Hyperspectral Infrared Imager (HyspIRI) - Science Impact of Deploying Instruments on Separate Platforms

The Hyperspectral Infrared Imager (HyspIRI) mission was recommended for implementation by the 2007 report from the U.S. National Research Council Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, also known as the Earth Science Decadal Survey. The HyspIRI mission is science driven and will address a set of science questions identified by the Decadal Survey and broader science community. The mission includes a visible shortwave infrared (VSWIR) imaging spectrometer, a multispectral thermal infrared (TIR) imager and an intelligent payload module (IPM). The IPM enables on-board processing and direct broadcast for those applications with short latency requirements. The science questions are organized as VSWIR-only, TIR-only and Combined science questions, the latter requiring data from both instruments. In order to prepare for the mission NASA is undertaking pre-phase A studies to determine the optimum mission implementation, in particular, cost and risk reduction activities. Each year the HyspIRI project is provided with feedback from NASA Headquarters on the pre-phase A activities in the form of a guidance letter which outlines the work that should be undertaken the subsequent year. The 2013 guidance letter included a recommendation to undertake a study to determine the science impact of deploying the instruments from separate spacecraft in sun synchronous orbits with various time separations and deploying both instruments on the International Space Station (ISS). This report summarizes the results from that study. The approach taken was to evaluate the impact on the combined science questions of time separations between the VSWIR and TIR data of <3 minutes, <1 week and a few months as well as deploying both instruments on the ISS. Note the impact was only evaluated for the combined science questions which require data from both instruments (VSWIR and TIR). The study concluded the impact of a separation of <3 minutes was minimal, e.g. if the instruments were on separate platforms that followed each other in a train. The impact of a separation of <1 week was strongly dependent on the question that was being addressed with no impact for some questions and a severe impact for others. The impact of a time separation of several months was severe and in many cases it was no longer possible to answer the sub-question. The impact of deploying the instruments on the ISS which is in a precessive (non-sun synchronous) orbit was also very question dependent, in some cases it was possible to go beyond the original question, e.g. to examine the impact of the diurnal cycle, whereas in other cases the question could not be addressed for example if the question required observations from the polar regions. As part of the study, the participants were asked to estimate, as a percentage, how completely a given sub-question could be answered with 100% indicating the question could be completely answered. These estimations should be treated with caution but nonetheless can be useful in assessing the impact. Averaging the estimates for each of the combined questions the results indicate that 97% of the questions could be answered with a separation of < 3 minutes. With a separation of < 1 week, 67% of the questions could be answered and with a separation of several months only 21% of the questions could be answered.

Turpie, Kevin↗

NASA NTRS2014

NASA 2014 The Hyperspectral Infrared Imager (HyspIRI) – science impact of deploying instruments on separate platforms

Quattrochi, Dale↗

DOE OSTI2025

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Chemistry data from soils and soil incubation experiments from the whole-soil warming experiment at Blodgett Forest, CA, 2018, from: “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile”

This dataset contains soil chemistry data of soils from the whole-soil warming experiment at Blodgett Forest in June 2018, and from laboratory incubation experiments conducted with a subset of those soils. Soil samples were collected at five different depths down to 80 cm from soil plots continuously heated by 4°C above ambient temperature for 4.5 years, and from the respective unheated control plots. Incubation experiments were conducted for 28 days with soils collected between 10-30 cm (“surface soils”) and 60-80 cm (“subsoils”) from heated and unheated field plots, amended in the laboratory with cellobiose (C, carbon amendment), or cellobiose plus ammonium and phosphate (CNP, combined carbon, nitrogen and phosphorus amendment). The dataset includes separate files for: (i) total carbon and nitrogen concentrations of initial field soils; (ii) carbon dioxide efflux rates at multiple times throughout the incubation experiments, and respective cumulative carbon dioxide efflux rates, as well as inorganic nitrogen concentrations at the beginning and end of the incubations, and net nitrogen mineralization rates and carbon use efficiency calculated at the end of the incubation. Analysis of these data has been published in Dove et al., (2021), “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile. Nat. Commun. 12:2089”, https://doi.org/10.1038/s41467-021-22408-5. This research was performed as part of the TES Belowground Biogeochemistry SFA project at Lawrence Berkeley National Laboratory.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1995

SEDAC data and applications development plan V(1)

This Data and Applications Development Plan describes how the Socioeconomic Data and Applications Center (SEDAC) at the Consortium for International Earth Science Information Network (CIESIN) is responding to SEDAC's mission to develop new applications and information products that synthesize earth science and socioeconomic data in ways that support decision making. The SEDAC data and applications development effort is a primary means by which the Earth Observing System Data and Information System (EOSDIS) program can help to ensure that the scientific investment embodied in NASA's Mission to Planet Earth (MTPE) program leads to tangible benefits to the American people. The Plan describes the major issues concerned with global climate change, identifies important decision makers and other users who would benefit from improved data and information, and assesses key opportunities for responding to the needs of these users and the scientists who work with them. It then details specific plans for developing selected integrated data products and services and for making them available to the target users on an operational basis. This report provides a summary of the activities performed in connection with NASA/GSFC Letter Contract NAS5-3263 for the period shown.

Chen, Robert S.↗

NASA NTRSDate not supplied

Assimilating Lessons Learned – From URGE to NASA's Student Airborne Science Activation (SaSa) Project

In the first half of 2021, formal and informal pods at several universities and NASA Center affiliates participated in the Unlearning Racism in Geosciences (URGE) curriculum and deliverables. As a result, several members from different URGE pods are propagating and applying the URGE lessons learned to the new 5-year NASA Student Airborne Science Activation project (SaSa). Starting in the Summer of 2022, SaSa will provide an 8-week summer Earth Science research experience focused on attracting and retaining early undergraduate students from historically underrepresented groups from minority-serving institutions (MSIs). The multicenter and field-based research experience will provide the students access to and experience with NASA airborne resources. Additionally, integrating NASA material into the MSI curricula and providing student mentorship at both MSIs and NASA Centers will enhance students' exposure to Earth Science research. The objectives of URGE and SaSa are highly compatible with one another, and the project timing allows for the integration of URGE lessons early in the SaSa curriculum design phase. As of December 2021, the first SaSa summer program application will be open and the first SaSa semester at the host MSIs will be completed. This presentation will discuss the assimilation of URGE lessons learned from our respective pods into the first SaSa academic semester and into the preparations for the first SaSa summer cohort. We will welcome additional feedback from the broader URGE community in advance of SaSa's first summer session.

Kristina Pistone↗

NASA NTRS1986

University participation via UNIDATA, part 1

The UNIDATA Project is a cooperative university project, operated by the University Corporation for Atmospheric Research (UCAR) with National Science Foundation (NSF) funding, aimed at providing interactive communication and computations to the university community in the atmospheric and oceanic sciences. The initial focus has been on providing access to data for weather analysis and prediction. However, UNIDATA is in the process of expanding and possibly providing access to the Pilot Climate Data System (PCDS) through the UNIDATA system in an effort to develop prototypes for an Earth science information system. The notion of an Earth science information system evolved from discussions within NASA and several advisory committees in anticipation of receiving data from the many Earth observing instruments on the space station complex (Earth Observing System).

Dutton, J.↗

NASA NTRS2013

A Cross-Track Cloud-Scanning Dual-Frequency Doppler (C2D2) Radar for the Proposed ACE Mission and Beyond

The National Resource Council’s Earth Science Decadal Survey” (NRCDS) has identified the Aerosol/Climate/Ecosystems (ACE) Mission as a priority mission for NASA Earth science. The NRC recommended the inclusion of "a cross-track scanning cloud radar with channels at 94 GHz and possibly 34 GHz for measurement of cloud droplet size, glaciation height, and cloud height". Several radar concepts have been proposed that meet some of the requirements of the proposed ACE mission but none have provided scanning capability at both 34 and 94 GHz due to the challenge of constructing scanning antennas at 94 GHz. In this paper, we will describe a radar design that leverages new developments in microwave monolithic integrated circuits (MMICs) and micro-machining to enable an electronically-scanned radar with both Ka-band (35 GHz) and W-band (94-GHz) channels. This system uses a dual-frequency linear active electronically-steered array (AESA) combined with a parabolic cylindrical reflector. This configuration provides a large aperture (3m x 5m) with electronic-steering but is much simpler than a two-dimension AESA of similar size. Still, the W-band frequency requires element spacing of approximately 2.5 mm, presenting significant challenges for signal routing and incorporation of MMICs. By combining (Gallium Nitride) GaN MMIC technology with micro-machined radiators and interconnects and silicon-germanium (SiGe) beamforming MMICs, we are able to meet all the performance and packaging requirements of the linear array feed and enable simultaneous scanning of Ka-band and W-band radars over swath of up to 100 km.

Aerosol/Climate/Ecosystems (ACE) Mission↗

NASA NTRS2016

2016 Decadal Update of the NASA ESTO Lidar Technologies Investment Strategy

We describe the 2016 update of the NASA Earth Science Technology Office (ESTO) investment strategy in the area of lidar technologies as pertaining to NASAs Earth Science measurement goals in the next decade.

2020 Astrophysics Decadal Survey↗

NASA NTRS2019

Integrated Analysis of Multiple User Metrics - A “Sequel”; and Introducing the Google Analytic

For decades, the Goddard Earth Sciences Data and Information Services Center (GES DISC) has archived and distributed enormous volumes of NASA Earth science data (accompanied with many developed tools and services) to various research/applications communities and the general public. Being “immersed” in the Big Data era, we have inevitably faced the challenges of our continually increasing archived data in both volume and variety, as well as enhanced user needs and demands. In recent years, we have actively analyzed different types of user metrics, such as operational distribution metrics (recording numbers of distinct users and downloaded data files, size of distributed data volume): user publication metrics (mining info from our Giovanni users’ publications): and Bugzilla metrics (collecting info from user questions or feedback from user assistance tickets). Such metrics have helped us achieve a better understanding of user needs, demands, characteristics, and behaviors, which has then helped us improve our user services. Now we will present a “Sequel” of integrated analysis of multiple metrics at the GES DISC by introducing and adding one new kind of metrics acquired via utilizing our recently implemented Google Analytic 360 suite. Several “newer” reports, e.g., “What web site features and links are the most popular (and least)?” and “What are the top 25 dataset Keyword searches?” retrieved from this new metrics set will be presented, along with the aforementioned “traditional” metrics results.

Shie, Chung-Lin↗

NASA NTRSDate not supplied

Creating a knowledge graph to connect scientific publications and datasets for improving discovery of GES DISC’s data and services

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes to the public hundreds of Earth Science data collections. These collections are used in research, resulting in thousands of scientific papers published each year. As new users come to GES DISC for the data, it is important for them to understand how these data were used in the prior research. For this we are creating the Knowledge Graph that connects research paper citation and the data collection metadata. The relationships created in the graph have potential for the Web applications that utilize this information to directly connect the paper research to the GES DISC datasets and services. We will demonstrate these relationships using the Web application prototype.

Nathaniel Ross Crosby↗

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 NTRSDate not supplied

Using XR for Improving Scientific Discovery With Numerical Weather Models

Earth science (ES) digital twins will help us understand the complex interactions and interrelationships that make up our Earth system and the impacts of earth science phenomena on it. Our work addresses two underdeveloped areas in current ES digital twin work: improving the understanding and interaction with ES model outputs by using Virtual and Mixed Reality (XR) tools and improving the non-intuitive mapping of continuous ES natural phenomena to gridded reference frames in current numerical models. Traditionally, scientists working on ES view and analyze the results of calculated or measured observables with static 1-dimensional (1D), 2D or 3D plots displayed on flat computer screens or paper. Using such limited mediums, it can be very difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. In addition, numerical models, such as the NASA Goddard Earth Observing System (GEOS) ES model, are almost exclusively formulated, visualized and analyzed in an Eulerian reference frame with fixed grid points in space and time. However, ES phenomena such as convective clouds, hurricanes and wildfire smoke plumes are visualized and analyzed in a Lagrangian reference frame: therefore it is often difficult and unnatural to understand these phenomena in relation to each other, visualized either in an Eulerian or Lagrangian context. In 3D visualizations, data generally takes one of three forms: gridded (e.g., voxelized) data, where space is divided into regions; point clouds, where data is represented as a set of points; and meshes, where objects are rendered as surfaces composed of small polygons (usually triangles). A gridded, Eulerian reference frame has been the default representation for the 2D visual analysis of atmospheric data in part because the numerical methods used to generate atmospheric model data in the first place use a gridded approach, with equations defining the relationships between the physical variables in each of a grid's cells across successive timesteps. In our work, we are particularly interested in data from GEOS. Another reason why gridded representations tend to be used for visualizing data from such models is because trajectories are difficult to interpret from representations on 2D surfaces, due to line-of-sight ambiguity. Instead of a fixed grid from GEOS, we embed a trajectory model to simulate particles' movement throughout a GEOS run. We then ingest these particle trajectories as animated point clouds with a NASA open source XR toolkit, the Mixed Reality Exploration Toolkit (MRET), and merge GEOS data with ES phenomena data onto one combined visualization that the user can intuitively interact with. Efficient rendering of arbitrarily large point clouds is an ongoing challenge being addressed by the computer science community, with the GPU-based optimizations and efficient GPU memory utilization a common theme of recent advances, especially for XR, where sustained high frame rate is mandatory to save the user from suffering due to simulation sickness. In this work, we describe and evaluate our progress in choosing and implementing appropriate methods for rendering arbitrarily large point clouds within MRET for XR. While tracking the XR headset enables the immersion of a user within a 3D scene of a data visualization, tracking of XR handheld controllers or user’s hands enables us to implement intuitive user interactions with the visualized datasets. Conventional tools require a user working with an ES visualization to conduct many interactions to commit their intended selections or manipulations with a visualized dataset; for example to specify a set of points in 3D space. Doing so in a 2D flat screen interface has traditionally required specifying a set of points in three distinct 2D coordinate systems (XY, XZ, and YZ), which is cumbersome. In other scientific domains, it has been shown that specifying or selecting a location or volume in XR using handheld controllers or tracked hands allows for greater speed and accuracy. We anticipate the same will hold true for atmospheric data, and we will share initial results of measuring the utility of such an interface. Notably, as the data being visualized is generated by GEOS as a prediction based on initial conditions, an intended application of our tool is to serve as part of an iterative feedback loop. Through XR, a scientist will review and manipulate a GEOS model run, modifying the conditions as needed to do subsequent runs of GEOS. Thereby, XR-based improvements to speed and accuracy of 3D tagging of points minimizes the effort required by both the scientist and the computer cluster conducting the necessary calculations.

Thomas Grubb↗

DOE OSTI2022

Organic carbon content and turnover time in relation to pedogenic iron and aluminum in four temperate forest soils sampled in 2007

Soil organic carbon (SOC) can be stabilized via association with iron (Fe) and aluminum (Al) minerals. Fe and Al can be strong predictors of SOC storage and turnover in soils with relatively high extractable metals content and moderately acidic to circumneutral pH. Here we test whether pedogenic Fe and Al influence SOC content and turnover in soils with low Fe and Al content and acidic pH. In soils from four sites spanning three soil orders, we quantified the amount of Fe and Al in operationally-defined poorly crystalline and organically-complexed phases using selective chemical dissolution applied to the soil fraction containing mineral-associated carbon. We evaluated the correlations of Fe and Al concentrations, mean annual precipitation (MAP), mean annual temperature (MAT), and pH with SOC content and 14C-based turnover times. We found that poorly crystalline Fe and Al content predicted SOC turnover times (p < 0.0001) consistent with findings of previous studies, while organically-complexed Fe and Al content was a better predictor of SOC concentration (p < 0.0001). Greater site-level MAP (p < 0.0001) and colder site-level MAT (p < 0.0001) were correlated with longer SOC turnover times but were not correlated with SOC content. Our results suggest that poorly crystalline Fe and Al effectively slow the turnover of SOC in these acidic soils, even when their combined content in the soil is less than 2% by mass. However, in the strongly acidic Spodosol, organo-metal complexes tended to be less stable resulting in a more actively cycling mineral-associated SOC pool. We characterized mineralogy and carbon content in soils from four forested sites in the eastern deciduous forest zone that span three soil orders. Using selective chemical dissolution applied to the soil fraction containing mineral-associated carbon, we quantified the amount of Fe and Al in operationally-defined poorly crystalline and organically-complexed phases, and correlated these with previously published SOC content and 14C-based turnover times (McFarlane et al. 2013). This dataset comprises site characterization undertaken in 2007 (.png) and subsequent soil analyses (.csv containing C, Fe, Al, 14C-derived TurnoverTime) concluded in 2010.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

Research and technology annual report, FY 1990

Given here is the annual report of the John C. Stennis Space Center (SSC), a NASA center responsible for testing NASA's large propulsion systems, developing supporting test technologies, conducting research in a variety of earth science disciplines, and facilitating the commercial uses of NASA-developed technologies. Described here are activities of the Earth Sciences Research Program, the Technology Development Program, commercial programs, the Technology Utilization Program, and the Information Systems Program. Work is described in such areas as forest ecosystems, land-sea interface, wetland biochemical flux, thermal imaging of crops, gas detectors, plume analysis, synthetic aperture radar, forest resource management, applications engineering, and the Earth Observations Commercial Applications Program.

Source record↗

NASA NTRS2010

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗

DOE OSTI2025

PreSens Dissolved Oxygen and Temperature Data, Old Woman Creek National Estuarine Research Reserve, Huron, OH, 2022-07-06 to 2023-12-15

This dataset contains collected dissolved oxygen (DO) and temperature measurements of the air, surface water, and underlying soil of a wetland at Old Woman Creek Estuarine Research Reserve in Huron, OH. Dissolved oxygen and temperature measurements were made in the first few centimeters of wetland sediment to assess how oxygen profiles changed over time with hydrological events. Measurements taken outside of the sediment were taken as comparison. Measurements were taken by hand with a PreSens Fibox 4 transmitter, paired with an oxygen dipping probe and temperature sensor, at each field outing. Measurements were taken approximately every 2 weeks around 10 AM EST. The PreSens_DO_Temp_Datafile.csv contains the recorded measurements, and the PreSens_InstallationMethods.csv describes the deployment of the sensor.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

Earth Radiation Budget Science, 1978

An earth radiation budget satellite system planned in order to understand climate on various temporal and spatial scales is considered. Topics discussed include: climate modeling, climate diagnostics, radiation modeling, radiation variability and correlation studies, cloudiness and the radiation budget, and radiation budget and related measurements in 1985 and beyond.

Source record↗