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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1984

Earth Observing System. Volume 1, Part 2: Science and Mission Requirements. Working Group Report Appendix

The Earth Observing System (EOS) is a planned NASA program, which will carry out multidisciplinary Earth science studies employing a variety of remote sensing techniques in the 1990's, as a prime mission, using the Space Station polar platform. Its primary goal is the generation of long term Earth science data sets of measurements and processes in the areas of agriculture, forestry, geology, hydrology, oceanography, snow and ice, troposphere and upper atmospheric chemistry, radiation and dynamics pertaining to global studies of Earth as a system, emphasizing the interactions and couplings of the atmospbere-ocean-land-cryosphere system. These results will provide the information needed to qualify our understanding of the global hydrological cycle, global biogeochemical cycles and global climate processes. This report provides the science rationale, recommended observational needs, the broad system configuration and a recommended implementation strategy to achieve the stated mission goals. The report is one volume of a proposed five volume set constituting the Phase A report as the Earth Observing System (EOS).

Goddard Space Flight Center↗
DOE OSTI2025

Improved Representations of Longwave Surface Emissivity to Reduce Surface and Atmospheric Heating Biases in Earth System Models

Abstract Many Earth system models (ESMs) approximate surface emissivity as a broadband constant. This approximation reduces the computational burden, yet omits the spectral structure of emissivity and atmospheric absorption. Neglecting spectral variation in surface emission introduces biases in longwave (LW) atmospheric fluxes and heating. Biases are strongest over surfaces with strongly varying emissivity and minimal atmospheric opacity. We examine these biases over water, ice, and snow surfaces. We partition spectral emissivity into the 16 spectral bands utilized by a single‐column atmospheric radiative transfer model (RRTMG_LW) commonly used in ESMs. We quantify flux and heating biases introduced by broadband assumptions relative to the spectrally resolved case for standard atmospheric profiles over each surface type. Current assumptions tend to overestimate upwelling surface fluxes; for example, the greybody assumption overestimates flux by 1.6 W/m 2 (0.52%) at the bottom of a mid‐latitude winter atmosphere over ice, and by 2.33 (1.0%) at the top of atmosphere. The blackbody assumption tends to artificially cool Earth's surface, stabilizing the lower troposphere. Interestingly, the optimal broadband emissivity can deviate from the Planck‐weighted mean by up to 3% depending on surface type and atmospheric profile. We investigate bias sensitivity to surface temperature, cloud water path, and atmospheric water vapor. Bias is most sensitive to water vapor content, and least sensitive to cloud water path. Lastly, we show that a modified greybody method with updated broadband values can reduce total surface flux bias up to 1.69 , comparable to a five‐band approach and at a fraction of the computational cost.

Manzo, L. [Department of Earth System Science Univ↗
NASA NTRS1994

A survey of geographical information systems applications for the Earth Science and Applications Division, Space Sciences Laboratory, Marshall Space Flight Center

The purpose of this document is to introduce Geographical Information System (GIS) terminology and summarize interviews conducted with scientists in the Earth Science and Applications Division (ESAD). There is a growing need in ESAD for GIS technology. With many different data sources available to the scientists comes the need to be able to process and view these data in an efficient manner. Since most of these data are stored in vastly different formats, specialized software and hardware are needed. Several ESAD scientists have been using a GIS, specifically the Man-computer Interactive Data Access System (MCIDAS). MCIDAS can solve many of the research problems that arise, but there are areas of research that need more powerful tools; one such example is the multispectral image analysis which is described in this document. Given the strong need for GIS in ESAD, we recommend that a requirements analysis and implementation plan be developed using this document as a basis for further investigation.

Rickman, D.↗
NASA NTRSDate not supplied

NASA’s Earth System Observatory Formulation Overview

NASA’s Earth System Observatory (ESO) is an array of Earth-focused, interconnected satellite missions focused on five core study areas: Surface Biology and Geology, Mass Change, Aerosols, Surface Deformation and Change, and Clouds, Convection, and Precipitation. Observatory development follows recommendations from the National Academies of Sciences, Engineering and Medicine’s 2017 Earth Science Decadal Survey. Data gathered by ESO missions will provide actionable science to inform decisions related to climate change, disaster mitigation, and wildfires, improve real-time agricultural processes, and many other applications. Targeting launch dates in the late 2020s and early 2030s, each ESO satellite will deliver valuable information, but by working together as a single observatory system, their combined data and imagery will provide the global community with a 4D, holistic view of Earth, from bedrock to atmosphere. The ESO is also building on the legacy of international collaboration in Earth science, with initial participation and collaboration on these missions across space agency partners, including the Japanese Aerospace Exploration Agency (JAXA), Centre National D'Etudes Spatiales (CNES), Canadian Space Agency (CSA), Deutsches Zentrum für Luft- und Raumfahrt (DLR), and Agenzia Spaziale Italiana (ASI). This paper provides an overview of ESO, as well as an update on ESO missions currently in formulation – the Atmosphere Observing System, Mass Change, and Surface Biology and Geology elements – including current mission architectures, international partner collaboration, science community engagement, and applications efforts, as well as how NASA and its partners will make ESO data accessible to users all over the world.

NASA Earth Science↗
NASA NTRS2000

EOS Reference Handbook 1999: A Guide to NASA's Earth Science Enterprise and the Earth Observing System

The content of this handbook includes Earth Science Enterprise; The Earth Observing System; EOS Data and Information System (EOSDIS); Data and Information Policy; Pathfinder Data Sets; Earth Science Information Partners and the Working Prototype-Federation; EOS Data Quality: Calibration and Validation; Education Programs; International Cooperation; Interagency Coordination; Mission Elements; EOS Instruments; EOS Interdisciplinary Science Investigations; and Points-of-Contact.

King, M. D.↗
NASA NTRSDate not supplied

Earth System Digital Twins (ESDT) Definition and Science Use Cases

NASA AIST Program is now designing and developing Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. In order to define ESDT's benefits to Earth Science, as well as the AIST capabilities required to develop such systems, the AIST Program has been developed 6 science use cases corresponding to 6 of the main Earth Science domains.

Earth Science Remote Sensing; Information Systems↗
DOE OSTI2025

Inter-Kingdom Viral Interactions

Please cite as : Josué A. Rodríguez-Ramos, Amy E. Zimmerman, Ruonan Wu, Sheryl Bell, Trinidad Alfaro, Kirsten Hofmockel, William C. Nelson. 2025. Inter-Kingdom Viral Interactions. [Data Set] PNNL DataHub. This data is published under a CC0 license. The authors encourage data reuse and request attribution by referencing the above citations for the data package and associated manuscript. Deciphering viral ecology in soils is challenging due to their high physiochemical and community complexity. To enhance detection of sub-communities of DNA and RNA viruses, we applied fractionation approaches to soils collected across a moisture gradient from a grassland field experiment. Analyses included metagenomics and metatranscriptomics of size-fractionated extracellular viruses (i.e., DNA and RNA viromes), metagenomics of bacteria/archaea- or eukaryote-enriched samples, and whole soil metatranscriptomes with rRNA-depletion or polyadenylation enrichment. While RNA virome and whole soil RNA methods captured similar viral diversity, RNA viromes identified longer, higher-quality genomes. Further, we showed that significantly more DNA viruses were active in higher moisture than lower moisture samples, whereas responses by overall diversity vary by genome type (DNA versus RNA genomes). Finally, we demonstrate the power of fractionation approaches for identifying distinct viral communities that infect unique hosts, which has significant implications for ecological investigations, particularly related to interkingdom interactions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Science Data Processing for the Advanced Microwave Scanning Radiometer: Earth Observing System

The National Aeronautics and Space Administration established the framework for the Science Investigator-led Processing Systems (SIPS) to enable the Earth science data products to be produced by personnel directly associated with the instrument science team and knowledgeable of the science algorithms. One of the first instantiations implemented for NASA was the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) SIPS. The AMSR-E SIPS is a decentralized, geographically distributed ground data processing system composed of two primary components located in California and Alabama. Initial science data processing is conducted at Remote Sensing Systems (RSS) in Santa Rosa, California. RSS ingests antenna temperature orbit data sets from JAXA and converts them to calibrated, resampled, geolocated brightness temperatures. The brightness temperatures are sent to the Global Hydrology and Climate Center in Huntsville, Alabama, which generates the geophysical science data products (e.g., water vapor, sea surface temperature, sea ice extent, etc.) suitable for climate research and applications usage. These science products are subsequently sent to the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado for archival and dissemination to the at-large science community. This paper describes the organization, coordination, and production techniques employed by the AMSR-E SIPS in implementing, automating and operating the distributed data processing system.

Goodman, H. Michael↗
DOE OSTI2026

Aerosol-deep convection interaction based on joint cell-thermal tracking in Large Eddy Simulations during the TRACER campaign

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

NASA Space controls research and technology program

The NASA technological organization is outlined. The Office of Aeronautics and Space Technology (OAST) is one of the four major technical offices that comprise NASA. The Office of Space Science and Applications administers programs directed towards using space-based or related techniques to further understanding of the total universe and to apply that understanding to practical applications in such areas as Astrophysics, Solar System exploration, Earth Sciences, Life Sciences, Communications and Information Systems. The Office of Space Flight administers the programs for all U.S. civil launch capability, plus Spacelab development and operations. The Office of Space Tracking & Data Systems administers the programs that operate and maintain a world-wide network of facilities for data acquisition, processing, and ground to spacecraft communications for all NASA missions. The OAST has primary responsibility within NASA for conducting space research and technology development to support commercial and military as well as NASA space interests.

Mciver, D. E.↗
DOE OSTI2025

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un↗
DOE OSTI2021

Interpretable Deep Learning for the Earth System with Fractal Nets

Focal Area 3: Explainable AI Our confidence in the projections made by Earth System Models (ESMs) depends on understanding them to be, in some important respects, faithful representations of the Earth system. Here we present an “explainable Artificial Intelligence (AI)” method that allows us to uncover the dynamical structure of the observed and modeled Earth system, discover hidden links across wide spatiotemporal scales, target model development efforts at poorly-represented dynamics, and optimize observed or modeled data collection to maximize predictive information. Science Challenge: Dynamical system science for the Earth system poses unique challenges given the large degree of internal climate variability. Thus, tools that help us understand how ESMs succeed and fail at representing these dynamics are crucial, particularly in relation to the observed system. Furthermore, the computational and memory constraints on ESM data output motivate in situ analysis of ESM dynamics, including automatic detection of dynamical shifts. Also, of key importance are procedures that leverage ESMs to optimize observational campaigns for improving process representation, reducing structural uncertainty and improving model skill.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

How Discipline-Oriented DAACs Collaborate to Support Interdisciplinary Earth Science

The Earth system is made of multiple complex subsystems. While scientists tend to specialize in single subsystems or even portions of a subsystem, to fully understand the physical, chemical and biological processes occurring on the Earth, we must understand how these systems interact. Thus, scientists need to be able to expand beyond their chosen field and collaborate across disciplines. The NASA Earth Observing System Data and Information System (EOSDIS) is focusing on new capabilities to make interdisciplinary science easier. The EOSDIS DAACS are responsible for archiving and distributing NASA’s rapidly growing collection of satellite, airborne and field data. Like the scientists they serve, the DAACs are discipline oriented. This has many advantages. Scientists are able to interact with experts on data in their domain and receive data appropriate for their research. However, discipline-oriented services may be confusing to cross-disciplinary users who may not know how to get started. Fortunately, collaboration across scientific communities is a specialty of the DAACs who support interdisciplinary users with a collaborative culture and technology that empowers the open sharing of data, information, and knowledge within the scientific community and the wider public to accelerate scientific research and understanding. This presentation will discuss the capabilities of a discipline-oriented approach to support future Earth science goals including those of Open Science and cross-disciplinary collaboration.

Sara Lubkin↗
DOE OSTI2025

Simulating Pyrocumulonimbus Clouds Using a Multiscale Wildfire Simulation Framework

Pyrocumulonimbus (pyroCb) clouds, driven by extreme fires under favorable meteorological conditions, can inject smoke into the stratosphere at magnitudes comparable to those of moderate volcanic eruptions, potentially altering the global radiative balance and atmospheric composition. However, simulating pyroCb is particularly challenging in Earth system models. Using the Energy Exascale Earth System Model (E3SM), we developed a novel global multiscale framework to model pyroCb events in California, which includes a high‐resolution fire radiative power time series, a one‐dimensional plume‐rise parameterization, a fire‐induced vertical water vapor transport scheme, and a surface wildfire sensible heat flux representation. Our simulation successfully reproduces many pyroCb features, including cloud height, spatiotemporal evolution, and convective intensity in comparison with satellite and ground‐based observations. Sensitivity experiments show that realistic pyroCb simulation depends on vertical water vapor transport. These advances provide a basis for future exploration of pyroCb impacts at regional and global scales within climate models.

E3SM↗
NASA NTRS1990

Earth Sciences Requirements for the Information Sciences Experiment System

The purpose of the workshop was to further explore and define the earth sciences requirements for the Information Sciences Experiment System (ISES), a proposed onboard data processor with real-time communications capability intended to support the Earth Observing System (Eos). A review of representative Eos instrument types is given and a preliminary set of real-time data needs has been established. An executive summary is included.

Bowker, David E.↗
DOE OSTI2025

Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations

Abstract Deep learning is a powerful tool to represent subgrid processes in climate models, but many application cases have so far used idealized settings and deterministic approaches. Here, we develop stochastic parameterizations with calibrated uncertainty quantification to learn subgrid convective and turbulent processes and surface radiative fluxes of a superparameterization embedded in an Earth System Model (ESM). We explore three methods to construct stochastic parameterizations: (a) a single Deep Neural Network (DNN) with Monte Carlo Dropout; (b) a multi‐member parameterization; and (c) a Variational Encoder Decoder with latent space perturbation. We show that the multi‐member parameterization improves the representation of convective processes, especially in the planetary boundary layer, compared to individual DNNs. The respective uncertainty quantification illustrates that methods (b) and (c) are advantageous compared to a dropout‐based DNN parameterization regarding the spread of convective processes. Hybrid simulations with our best‐performing multi‐member parameterizations remained challenging and crash within the first days. Therefore, we develop a pragmatic partial coupling strategy relying on the superparameterization for condensate emulation. Partial coupling reduces the computational efficiency of hybrid Earth‐like simulations but enables model stability over 5 months with our multi‐member parameterizations. However, our hybrid simulations exhibit biases in thermodynamic fields and differences in precipitation patterns. Despite this, the multi‐member parameterizations enable improvements in reproducing tropical extreme precipitation compared to a traditional convection parameterization. Despite these challenges, our results indicate the potential of a new generation of multi‐member machine learning parameterizations leveraging uncertainty quantification to improve the representation of stochasticity of subgrid effects.

Behrens, Gunnar [Deutsches Zentrum für Luft‐ und R↗
DOE OSTI2024

Reimagining Earth in the Earth System

Abstract Terrestrial, aquatic, and marine ecosystems regulate climate at local to global scales through exchanges of energy and matter with the atmosphere and assist with climate change mitigation through nature‐based climate solutions. Climate science is no longer a study of the physics of the atmosphere and oceans, but also the ecology of the biosphere. This is the promise of Earth system science: to transcend academic disciplines to enable study of the interacting physics, chemistry, and biology of the planet. However, long‐standing tension in protecting, restoring, and managing forest ecosystems to purposely improve climate evidences the difficulties of interdisciplinary science. For four centuries, forest management for climate betterment was argued, legislated, and ultimately dismissed, when nineteenth century atmospheric scientists narrowly defined climate science to the exclusion of ecology. Today's Earth system science, with its roots in global models of climate, unfolds in similar ways to the past. With Earth system models, geoscientists are again defining the ecology of the Earth system. Here we reframe Earth system science so that the biosphere and its ecology are equally integrated with the fluid Earth to enable Earth system prediction for planetary stewardship. Central to this is the need to overcome an intellectual heritage to the models that elevates geoscience and marginalizes ecology and local land knowledge. The call for kilometer‐scale atmospheric and ocean models, without concomitant scientific and computational investment in the land and biosphere, perpetuates the geophysical view of Earth and will not fully provide the comprehensive actionable information needed for a changing climate.

Meteorology & Atmospheric Sciences↗
NASA NTRS1997

The HSCaRS Summer Enrichment Program; Research Opportunities for Minority and Women Undergraduates in Global Change Science

The primary objective of the HSCaRS Summer Enrichment Program (SEP) is to make significant contributions to the NASA Mission to Planet Earth (MTPE) and the Alabama A&M University (AAMU) Center for Hydrology, Soil Climatology and Remote Sensing (HSCaRS) research missions by providing undergraduate student research internships with an emphasis on minority and women students. Additional objectives are to encourage more minority and women students to pursue advanced degrees in Earth system and global change science and to increase the participation of minority institutions in the U.S. Global Change Research Program. Also, the SEP strives to make students in the traditional science disciplines more aware of the opportunities in Earth System Science. In designing the SEP, it was acknowledged that HSCaRS was a new research effort and Center. Consequently, students were not expected to immediately recognize the Center as one would older, more established research laboratories with national reputations, such as Los Alamos, Battelle, National Consortium for Atmospheric Research (NCAR), etc. Yet we still wanted to compete nationally for the best students. Therefore, we designed the program with a competitive financial package that includes a stipend of $400 per week, round-trip transportation from home to the summer research site, and free campus housing and meal plans provided by Alabama A&M University. Students also received a modest living allowance of approximately $25 per week. The internship program was 10 weeks in residence at Alabama A&M University or IGCRE, and gave students the opportunity to select from six general research areas: micro-meteorology, soil data analysis, soil moisture modeling, instrumentation, geographic information systems, and computer science. Student participants also enrolled in an introductory global change science course as part of the summer program (a copy of the course outline is in the appendix). The program included participation in a field program for approximately two weeks. All students were required to participate in the field program as a learning experience, regardless of the relationship of the field program to their majors or particular research project.

Estes, Jr., Maurice G.↗