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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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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Towards a More Realistic Representation of Surface Albedo in NASA CERES Satellite Products: A Comparison with MOSAiC Field Campaign

Observing the Arctic from space is one of the most challenging tasks in climate science. Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other scene type and comes from several sources. The one-year long MOSAiC expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes has been conducted using in-situ measurements from MOSAiC flux stations. The CERES SYN1deg product overestimates the SW_down flux by 11.40 Wm-2 and underestimates the SW_up flux by −15.70 Wm-2 and LW_down fluxes by −13.30 Wm-2 at the surface during summertime. In addition, large differences are found in the LW_up flux (~320 Wm-2) when the surface reaches melting point (~0℃). The large negative bias in upwelling shortwave flux can be attributed to the underestimation of surface albedo (−0.15) in SYN1deg. In addition to direct comparison, a series of perturbation experiments with a radiative transfer model are performed to estimate the contributions to the differences. By correcting both cloud and albedo inputs, the biases in SW_net flux and LW_net flux can be reduced to less than half of the control run biases to +19.90% and −10.53%, respectively. Furthermore, a compensating effect between underestimation of broadband albedo and overestimation of spectral albedo in visible and mid-infrared bands in SYN1deg datasets is found and contributes to the shortwave flux differences. The difference in CERES broadband albedo (~20 Wm 2) contributes to larger uncertainty in SW_up flux than spectral albedo shape (~3 Wm 2). The results of this study inform the future development of CERES products and will ultimately reduce uncertainties in Arctic surface radiation budget derived from satellite measurements.

Yiyi Huang↗
NASA NTRSDate not supplied

Planning Satellite Swarm Measurements for Climate Models: Comparing Dynamic Constraint Processing and MILP Methods

We present D-SHIELD, a challenging climate science application to plan coordinated measurements (observations) for a constellation of satellites, each containing two different sensors, each with 61 pointing angle options. The L-band and P-band radar sensors collect data fed into a soil moisture model which tracks and predicts soil moisture across 1.67 million Ground Positions (GP). Soil moisture is an important predictor of wildfires, and then a predictor of floods, landslides and debris flow after a fire. Each measurement covers multiple GP due to the sensor footprint. Each GP has a "model error" which represents the uncertainty of the the soil moisture state prediction. Model error changes at different rates for each GP as the time since last observation increases and after significant events like rain. The planner's goal is to select measurements which maximize soil moisture model improvement (reduce model uncertainty). This problem is combinatorically explosive, involving many degrees of freedom for planner choices. Good domain heuristics can find solutions within a reasonable time for our application needs but cannot be proven optimal. In this paper we compare two different planning approaches to this problem: Dynamic Constraint Processing (DCP) and Mixed Integer Linear Programming (MILP). We match inputs and metrics for both DCP and MILP algorithms to enable a direct apples-to-apples comparison. We demonstrate and discuss the trades between DCP flexibility and performance vs. MILP's promise of provable optimality.

Rich Levinson↗
NASA NTRS2022

Congo Basin, a neglected world heritage

The Congo Basin has received little attention, climatically speaking, compared to the Amazon Basin and even other parts of Africa. This world’s second largest forest has distinct meteorological characteristics, and its ecosystem is controlled by complex interactions between many climatic phenomena that act across scales(Fig. 1). Due to its location, the Congo rainforest also contributes to processes responsible for interhemispheric climatic communications in Africa. At the larger scale, the basin regulates the global tropical circulation by serving as one of the world’s most convectively active regions. Therefore, the Congo Basin offers a unique natural laboratory for climate science explorations and the implications for people and ecosystems. But, why this green heart of Africa has been neglected and what we should do about it?

Amin Dezfuli↗
NASA NTRS2021

Ambient Performance Testing of the CubeSat Infrared Atmospheric Sounder (CIRAS)

Hyperspectral infrared measurements of Earth’s atmosphere from space have proven their value for weather forecasting, climate science and atmospheric composition. The CubeSat Infrared Atmospheric Sounder (CIRAS) instrument will demonstrate a fully functional infrared temperature, water vapor and carbon monoxide sounder in a CubeSat sized volume for at least an order of magnitude lower cost than legacy systems. Design for a CubeSat significantly reduces cost of access to space and enables flight in a constellation to reduce revisit time and enable new measurements including 3D winds. A technology demonstration of CIRAS is currently under development at JPL. The effort has completed integration and ambient testing of a high fidelity brassboard, complete with the flight configured optics assembly developed by Ball Aerospace with a JPL Immersion Grating and Black Silicon Entrance Slit. The brassboard includes a flight-configured High Operating Temperature Barrier Infrared Detector (HOT-BIRD) mounted in an Integrated Dewar Cryocooler Assembly (IDCA), enabling testing in the ambient environment. Ambient testing included radiometric testing of the system to characterize the instrument operability and NEdT. Spatial testing was performed to characterize the system line spread function (LSF) in two axes and report FWHM of the LSF. Spectral testing involved an air path test to characterize the spectral/spatial transformation matrix, and an etalon was used to measure the Spectral Response Functions (SRFs). Results of the testing show the CIRAS performs exceptionally well and meets the key performance required of the system. The end result of testing is the CIRAS instrument now meets TRL 4 with confidence in a brassboard configuration ready for thermal vacuum (TVac) testing necessary to achieve TRL 5 for the system.

Wilson, Robert C.↗
NASA NTRSDate not supplied

The HySICS Pointing System: Precision Pointing of CLARREO Pathfinder from the ISS

The CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) mission will measure Earth-reflected sunlight with unparalleled accuracy over existing reflected solar (RS) sensors and will also serve as an on-orbit inter-calibration reference to other orbiting sensors. In order to achieve these goals, the HySICS (HyperSpectral Imager for Climate Science) instrument will need to be pointed at a diverse set of targets including: nadir earth, co-aligned earth scans with other orbiting sensors, the Sun, and the Moon. The HySICS Pointing System (HPS) was developed to provide independent pointing at these targets from its mounting location on the ISS. This paper is focused on the HPS and describes: an overview of the CPF mission, an overview of the HPS requirements, the HPS hardware architecture, the various pointing modes that allow the HPS to point at its targets, challenges associated with performing this mission on the ISS, test results from subsystem-level HPS testing, and finally lessons learned that pertain to algorithm/software development and to the benefits of reusing pointing control hardware/architecture from the TSIS-1 mission that also has a 2-axis pointing system on the ISS from the development process.

orbit↗
NASA NTRS2024

CLARREO Pathfinder Solar Diffuser Calibration Progress

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission’s Hyperspectral Imager for Climate Science (HySICS) instrument’s transmissive flight diffuser calibration is presented. The absolute Bidirectional Transmittance Distribution Function (BTDF) measurement of the transmissive diffuser is needed to calculate the instrument’s absolute efficiency. Along with a known solar irradiance source such as Total Solar Irradiance Sensor (TSIS), it can provide an absolute irradiance measurement path on orbit, with NIST traceability. This provides an additional path for CPF to cross compare with other on orbit sensors’ measurement such as Visible-Infrared Imaging Radiometer Suite (VIIRS), Clouds and the Earth’s Radiant Energy System (CERES). The flight diffuser was calibrated at NASA’s Goddard Space Flight Center (GSFC) using the Facility’s Optical Scatterometer.

Bidirectional Transmittance Distribution Function↗
NASA NTRSDate not supplied

CLARREO Pathfinder Mission Overview and its Intercalibration Capabilities

NASA's Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission will deploy an Earth-observing reflected solar (RS) spectrometer, designed to measure Earth-reflected solar radiation from the International Space Station with a remarkable SI-traceable radiometric uncertainty of 0.3% (k=1). This spectrometer, known as the Hyperspectral Imager for Climate Science (HySICS), will provide measurements within a spectral range of 350-2300 nm with 3-nm spectral intervals. Covering a nadir swath of 70 km, HySICS captures 480 discrete measurement pixels that provide spectrally-resolved Earth-reflected radiances. The CPF mission encompasses two principal objectives. The first objective is to demonstrate on-orbit calibration methodologies that achieve and uphold an unprecedented level of accuracy while maintaining traceability to SI standards. The second objective is to showcase an innovative on-orbit intercalibration approach, which involves the intercalibration of two other RS sensors—namely, the shortwave (SW) channel of the Clouds and the Earth’s Radiant Energy System (CERES) and the Reflective Solar (RS) bands of the Visible Infrared Imager Radiometer Suite (VIIRS)—against CPF benchmark measurements. The targeted intercalibration methodology uncertainty for these target instruments is 0.3% (k=1). Empowered by the CPF payload's two-axis pointing capability, moderate spatial sampling of 0.5 km, and wide spectral coverage, the CPF instrument will capture near-simultaneous temporal, spatial, angular, and spectrally matched observations with intercalibration targets. The CPF intercalibration science development team has devised novel methods to address spatial, spectral, polarization, and angular differences between CPF and the target instruments' intercalibration footprints to achieve the stringent 0.3% intercalibration methodology uncertainty. Comprehensive details of these methods and their validation will be elaborated upon during the conference presentation.

Hyperspectral↗
NASA NTRSDate not supplied

3D Geolocation of Simulated Lightning Sources from Low-Earth Orbit

The recent removal of the Lightning Imaging Sensor from the International Space Station has left an observational gap in lightning detection from low-Earth orbit (LEO). However, new studies have demonstrated the potential for 3D geolocation of lightning sources using orbiting sensors. The Cubespark mission concept aims to take advantage of these developments by deploying a constellation of satellites with radio frequency (RF) sensors and optical imagers to not only map lightning locations, but also to collect bi-spectral flash images. These new capabilities include mapping storm charge structure, flash channel structure, and distinguishing microphysical processes throughout flash development, helping link microphysics and convective processes with overall flash and storm structure around the globe from LEO. In this study, we simulate lightning RF sources in the very high frequency (VHF) band, extrapolate their signals to space-based detection using an improved ionospheric model, and reconstruct their 3D locations using a time-of-arrival (TOA) minimization algorithm. Various constellation configurations, locations, and atmospheric conditions are considered in order to identify and quantify the three main sources of geolocation error: geometric, ionospheric, and instrumental effects. The promising results of this study emphasize the potential of space-based 3D lightning mapping under diverse conditions. 3D resolution is shown to be better than 1-2 km in many cases, enabling new global applications in meteorology and climate sciences. Here we present a selection of these geolocation results as seen from space alongside recent advancements, paving the way for a future generation of LEO lightning mappers.

CubeSpark↗
NASA NTRS2024

Simulated Feasibility of 3D Lightning Mapping from Space

In addition to the awe it inspires, lightning can illuminate the microphysical processes hidden away within deep convection. The current generation of space-based lightning mapping uses mostly 2D optical imaging to connect overall flash characteristics to their parent storm dynamics, but are missing a dimension’s worth of information. With lightning now classified as an essential climate variable, future spaceborne mappers will need improved capabilities to take advantage of the 3D structure of lightning flashes to support meteorological and climate modeling. We report here on a study of the feasibility of implementing a radio frequency (RF)–based network of satellites for 3D lightning mapping in high resolution from low Earth orbit (LEO). Lightning sources are simulated using existing tools of the Lightning Mapping Array (LMA), modified for orbital detection, and spatially reconstructed using a Levenberg-Marquardt geolocation algorithm to assess sources of uncertainty in these solutions. We analyze the benefits and limitations of this approach compared to existing orbital and ground-based methods. Results of this study show that lightning can be mapped in 3D with a vertical location accuracy better than 2 km using as few as five satellites in LEO capable of measuring the time-of-arrival of impulsive RF signals in the very high frequency (VHF) band. The consequence of this study is that high-resolution, spaceborne 3D mapping of lightning is achievable across most of the globe, having crucial implications for our understanding of not only lightning, but also severe weather development, climate science, and more.

CubeSpark↗
NASA NTRS2024

Advanced Libya-4 radiometric and atmospheric characterization utilizing MODIS and VIIRS full-scan reflective solar band measurements

The NASA Clouds and the Earth's Radiant Energy System (CERES) project provides observed flux and cloud products to the climate science community. The CERES instruments, along with the MODIS and VIIRS imagers, are onboard the Terra, Aqua, NPP, and NOAA20 satellites. In order to produce seamless multi-platform integrated products, long-term sensor stability and inter-calibration are required. Inter-calibration between sensors within the same sun-synchronous orbit relies on Earth invariant targets because simultaneous nadir overpasses are not possible. To facilitate inter-calibration efforts, the CERES Imager and Geostationary Calibration Group (IGCG) has improved the Libya-4 target characterization. Improvements include full scan angle characterization to enable daily observations, clear-sky identification using individual scan angle dynamic spatial homogeneity thresholds, and atmospheric corrections. The water vapor correction was found to be effective across the full scan, whereas the ozone and aerosol corrections were less effective. The atmospheric-corrected normalized radiance temporal fluctuations are similar across scan angles, spectral bands, and between the MODIS and VIIRS imagers, suggesting that the fluctuations are a result of the natural variability of the Libya-4 surface reflectance. The Libya-4 surface variability is more than likely caused by changes in the prevailing winds that alter sand dune orientation and resulting shadows. The full-scan-imager atmosphere and angle corrected reflected solar band radiance trend standard errors are between 0.6% and 1.0%, and for near-nadir observations, are between 0.5% and 0.8%. The advanced characterization suggests that the Libya-4 short-term surface reflectance anomalies may need to be considered for imager stability monitoring and inter-calibration efforts.

Libya-4 Pseudo-invariant Calibration Site↗
NASA NTRSDate not supplied

The Next Generation of Lightning Mapping

With the removal of the Lightning Imaging Sensor from the International Space Station, a gap has opened in lightning observation from low-Earth orbit. The CubeSpark mission concept aims to fill this role using a constellation of satellites with radio frequency (RF) sensors and bi-spectral optical imagers to observe lightning flashes more completely and with better resolution than is currently possible from space. In this study, we assess the feasibility of multiple methods of not only mapping lightning locations, but also inferring 3D flash and charge structures. This is done primarily by simulating lightning emissions in the very high frequency (VHF) band, modeling their propagation to orbital sensors, and reconstructing their locations using time-of-arrival (TOA) minimization algorithms. Constellation shape, number, and atmospheric conditions are varied in order to quantify the three main sources of geolocation error: geometric, ionospheric, and instrumental effects. The promising results presented here demonstrate 3D resolution better than 1-2 km in many cases, enabling new applications in meteorology and climate sciences.

CubeSpark↗
NASA NTRS2012

Climate Change Adaptation Science Activities at NASA Johnson Space Center

The Johnson Space Center (JSC), located in the southeast metropolitan region of Houston, TX is the prime NASA center for human spaceflight operations and astronaut training, but it also houses the unique collection of returned extraterrestrial samples, including lunar samples from the Apollo missions. The Center's location adjacent to Clear Lake and the Clear Creek watershed, an estuary of Galveston Bay, puts it at direct annual risk from hurricanes, but also from a number of other climate-related hazards including drought, floods, sea level rise, heat waves, and high wind events all assigned Threat Levels of 2 or 3 in the most recent NASA Center Disaster/Risk Matrix produced by the Climate Adaptation Science Investigator Working Group. Based on prior CASI workshops at other NASA centers, it is recognized that JSC is highly vulnerable to climate-change related hazards and has a need for adaptation strategies. We will present an overview of prior CASI-related work at JSC, including publication of a climate change and adaptation informational data brochure, and a Resilience and Adaptation to Climate Risks Workshop that was held at JSC in early March 2012. Major outcomes of that workshop that form a basis for work going forward are 1) a realization that JSC is embedded in a regional environmental and social context, and that potential climate change effects and adaptation strategies will not, and should not, be constrained by the Center fence line; 2) a desire to coordinate data collection and adaptation planning activities with interested stakeholders to form a regional climate change adaptation center that could facilitate interaction with CASI; 3) recognition that there is a wide array of basic data (remotely sensed, in situ, GIS/mapping, and historical) available through JSC and other stakeholders, but this data is not yet centrally accessible for planning purposes.

Stefanov, William L.↗
NASA NTRSDate not supplied

Systemic Risk From the Perspective of Climate, Environmental and Disaster Risk Science and Practice

Understanding and managing systemic risk is more important than ever due to our immense global connectivity (e.g., between sectors, such as food-health-water-energy, countries and continents, down to individuals). Despite the fact that the notion of systemic risk is several decades old, the term is used in diverse ways across different disciplines (e.g., financial systems, medicine, earth system sciences, disaster risk research and climate science). Triggered by the repercussions of the global financial crisis of the late 2000s, and more recently the COVID-19 pandemic, which are clear realization of systemic risk, the perception of systemic risk has often been focused on global and catastrophic or even existential risks. Systemic risk, however, can be seen as a feature of systems at all possible scales (e.g., global, national, regional, local) with system boundaries varying depending on the context. Addressing current societal challenges, such as climate change, in terms of systemic risk requires integrating different systems perspectives and fostering system thinking, while implementing key intergovernmental agendas, such as the Paris Agreement, the Sendai Framework for Disaster Risk Reduction and the Sustainable Development Goals. Based on insights gained and knowledge collected from an expert workshop, literature review and expert elicitation, we give an integrated perspective of climate, environmental and disaster risk science and practice on systemic risk as summarized in a Briefing Note to the International Science Council. We provide an overview of concepts of systemic risk that have evolved over time and identify commonalities across terminologies and perspectives associated with systemic risk used in different contexts. Key attributes of systemic risk are outlined without prescribing a single definition, and information and data requirements are discussed that are essential for a better and more actionable understanding of the systemic nature of risk. Finally, the opportunities to connect research and policy for addressing systemic risk are highlighted.

systemic risk↗
DOE OSTI2026

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2024

Shifting institutional culture to develop climate solutions with Open Science

This call to action by Drs. Johnson and Wilkinson is part of a mosaic of voices sharing tangible progress within the climate movement 1,2. This call speaks to us as environmental and Earth scientists motivated by the urgency of climate change and social inequity and who contribute to finding science-driven climate solutions as part of our daily jobs. Unfortunately, we are often unable to efficiently move this critical and urgent work forward because we are impeded by cumbersome daily workflows and restrictive workplace cultures. Our workplaces have not kept pace with the modern realities of data-intensive science: increasing data volumes and storage needs, rapidly evolving technology, new skill requirements, and a growing need for extensive and diverse collaboration. Struggling with old approaches and learning new ones in isolation can fuel burnout and turnover, preventing us from working on science-driven climate solutions effectively.

open science↗
DOE OSTI2026

Unlocking the benefits of transparent and reusable science for climate-risk management

People around the world seek climate-risk information to guide their decisions. For instance, projections about future flood risk inform where households choose to live, how lenders manage credit risks, and which communities receive federal funding. Yet data limitations and fundamental validation challenges raise important concerns about the reliability of such projections. The principles of transparency and reusability help address these concerns by enabling scrutiny of assumptions and methods, development of foundational data and tools, and consistent application of evaluation standards. While there is ongoing debate about how much transparency commercial climate-risk services should provide, many expect non-commercial actors to lead the way on operationalizing transparency and reusability to fulfill their knowledge-building role in the climate-risk ecosystem. However, despite prominent success stories, we find a substantial gap between principles and practice: only four percent of the most-cited peer-reviewed climate-risk studies in recent years fully share their data and code despite this being a widely accepted minimum standard for transparency. We highlight low-cost measures that non-commercial researchers can take now to improve transparency and reusability. We also emphasize that transformative progress requires substantial investment, cross-sector collaboration, and careful consideration of tradeoffs, data rights, and multiple perspectives on equity. We hope this perspective accelerates both immediate actions and longer-term conversations to improve the ability of science to effectively support timely, evidence-based, and sound climate-risk management.

Open Science↗
NASA NTRS1979

ICEX: Ice and Climate Experiment. Report of science and applications working group

The Ice and Climate Experiment (ICEX), a proposed program of coordinated investigations of the ice and snow masses of the Earth (the "cryosphere") is described. These investigations are to be carried out with the help of satellite, aircraft, and surface based observations. Measurements derived from the investigations will be applied to an understanding of the role of the cryosphere in the system that determines the Earth's climate, to a better prediction of the responses of the ice and snow to climatic change, to studies of the basic nature of ice forms and ice dynamics, and to the development of operational techniques for assisting such activities in the polar regions as transportation, exploitation of natural resources, and petroleum exploration and production. A high-inclination satellite system with a set of remote-sensing instruments specially tailored to the task of observing the important features of snow, sea ice, and the ice sheets of Greenland and the Antarctic is to be used to record the near-simultaneous observations of multiple geophysical parameters by complementary sensors.

Source record↗