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NASA NTRSDate not supplied

Advancing Open Science in Atmospheric Research: Integrating Data Usability and Machine Learning

In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences." "In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences.

Jennifer Wei↗
NASA NTRSDate not supplied

A Reference Ocean Surface Emission and Backscatter Model from Microwaves to Infrared

Satellite observations are vital for the initialization of Numerical Weather Prediction models, and very important for climate monitoring and prediction, as well as other applications such as hydrology and flood awareness prediction. Knowledge of radiative contributions from the Earth's surface is needed to sound the lower troposphere from space. The lack of a reference quality ocean emission and backscatter model is a major gap in our ability to provide absolute calibration of the satellite based observing system. Uncertainty in emissivity models is not well characterized and different models are used for different spectral bands, for active and passive instruments. An International Space Science Institute (ISSI) team was put together [4] to address these issues. The objectives of the team are to provide a reference model as a community software (i.e., documented and freely available code), that is maintained and supported, has traceable uncertainty estimations, and that enables new science from microwaves to infrared with bidirectional reflectance distribution function (BRDF) capability. We will present the model and its various components, discussing the choices between various parameterizations, building on the LOCEAN model of [2]. The model predictions will be evaluated at various frequencies, including comparisons to radiometric observations by SMAP, AMSR2 and GMI (e.g., [5]). We will discuss early model evaluation in the infrared and for active microwave sensors. Areas of ongoing research include improving the foam parametrization (coverage and emissivity) to provide consistent performances across frequencies, building on [1], and the azimuthal dependence of the active and passive signals. The model will be used to generate training data for fast models e.g., Fastem, [3], that are used in operational data assimilation and climate re-analysis.

Emmanuel Dinnat↗
NASA NTRS2012

Roadmap for In-Space Propulsion Technology

NASA has created a roadmap for the development of advanced in-space propulsion technologies for the NASA Office of the Chief Technologist (OCT). This roadmap was drafted by a team of subject matter experts from within the Agency and then independently evaluated, integrated and prioritized by a National Research Council (NRC) panel. The roadmap describes a portfolio of in-space propulsion technologies that could meet future space science and exploration needs, and shows their traceability to potential future missions. Mission applications range from small satellites and robotic deep space exploration to space stations and human missions to Mars. Development of technologies within the area of in-space propulsion will result in technical solutions with improvements in thrust, specific impulse (Isp), power, specific mass (or specific power), volume, system mass, system complexity, operational complexity, commonality with other spacecraft systems, manufacturability, durability, and of course, cost. These types of improvements will yield decreased transit times, increased payload mass, safer spacecraft, and decreased costs. In some instances, development of technologies within this area will result in mission-enabling breakthroughs that will revolutionize space exploration. There is no single propulsion technology that will benefit all missions or mission types. The requirements for in-space propulsion vary widely according to their intended application. This paper provides an updated summary of the In-Space Propulsion Systems technology area roadmap incorporating the recommendations of the NRC.

Meyer, Michael↗
NASA NTRSDate not supplied

Sensitivity of the ACCP Value Framework Science Benefit Score

NASA’s priorities for Earth Science are informed by the 2017-2027 Decadal Survey for Earth Science and Applications from Space of the National Academies of Sciences, Engineering and Medicine. In that document, five Designated Observables are identified as priorities for implementation: Aerosols, Cloud-Convection-Precipitation, Surface Biology, Mass Change, and Surface Deformation Change. In 2019, NASA initiated four multi-year studies to formulate, assess, and recommend potential Observing System concepts that are responsive to the recommendations of the Earth Science Decadal Survey. The Aerosols, Clouds, Convection, and Precipitation (ACCP) study investigates opportunities for synergistic science resulting from implementations that combine both Aerosols science objectives and Clouds, Convection, and Precipitation science objectives. For the ACCP study, a Value Framework was designed to introduce structure, transparency, and traceability in the mission down-select decision process. This paper presents a sensitivity analysis that was conducted to characterize the behavior of the science benefit score of the ACCP Value Framework. it includes derivations of the sensitivity analysis equations, numerical analyses of the behavior of the combined benefit score, and the conclusions drawn from the results of the work that was conducted. The results of this analysis were key to ensuring that the aggregated science benefit scores would enable the team to differentiate and contrast across concepts.

John McLaughlan↗
NASA NTRS2016

Persistent Identifiers Implementation in EOSDIS

This presentation provides the motivation for and status of implementation of persistent identifiers in NASA's Earth Observation System Data and Information System (EOSDIS). The motivation is provided from the point of view of long-term preservation of datasets such that a number of questions raised by current and future users can be answered easily and precisely. A number of artifacts need to be preserved along with datasets to make this possible, especially when the authors of datasets are no longer available to address users questions. The artifacts and datasets need to be uniquely and persistently identified and linked with each other for full traceability, understandability and scientific reproducibility. Current work in the Earth Science Data and Information System (ESDIS) Project and the Distributed Active Archive Centers (DAACs) in assigning Digital Object Identifiers (DOI) is discussed as well as challenges that remain to be addressed in the future.

persistent identifiers↗
NASA NTRSDate not supplied

TPSAS-NF1676L-19005-DND

Science is an economic investment by the public. We will be managing Earth’s climate until civilization moves elsewhere. We currently have no national or international climate observing system, nor a plan to create one. Should we invest in one? Is it worth it? What is the economic value of an advanced climate observing system? How would you estimate it? We have a few traceable estimates of the economic value of weather prediction for severe storms, hurricanes, floods and droughts. Climate scientists often say that the results from their research “will inform societal decisions with trillion dollar impacts”. But is this statement verified and traceable in any way? How could we quantify an economic value to climate science? Recall that climate change science value exists decades into the future. Its value has to be treated as a risk/benefit economic analysis. A rigorous analysis must take into account the uncertainties in climate science, economic impacts, and policy (see Figure 1 below).

Bruce A Wielicki↗
NASA NTRS2003

Current Developments in Future Planetary Probe Sensors for TPS

In-situ Thermal Protection System (TPS) sensors are required to provide traceability of TPS performance and sizing tools. Traceability will lead to higher fidelity design tools, which in turn will lead to lower design safety margins, and decreased heatshield mass. Decreasing TPS mass will enable certain missions that are not otherwise feasible, and directly increase science payload. NASA Ames is currently developing two flight measurements as essential to advancing the state of TPS traceability for material modeling and aerothermal simulation: heat flux and surface recession (for ablators). The heat flux gage is applicable to both ablators and non-ablators and is therefore the more generalized sensor concept of the two with wider applicability to mission scenarios. This paper describes the development of a microsensor capable of surface and in-depth temperature and heat flux measurements for TPS materials appropriate to Titan, Neptune, and Mars aerocapture, and direct entry. The thermal sensor will be monolithic solid state devices composed of thick film platinum RTD on an alumina substrate. Choice of materials and critical dimensions are used to tailor gage response, determined during calibration activities, to specific (forebody vs. aftbody) heating environments. Current design has maximum operating temperature of 1500 K, and allowable constant heat flux of q=28.7 watts per square centimeter, and time constants between 0.05 and 0.2 seconds. The catalytic and radiative response of these heat flux gages can also be changed through the use of appropriate coatings. By using several co-located gages with various surface coatings, data can be obtained to isolate surface heat flux components due to radiation, catalycity and convection. Selectivity to radiative heat flux is a useful feature even for an in-depth gage, as radiative transport may be a significant heat transport mechanism for porous TPS materials in Titan aerocapture. This paper also reports on progress to adapt a previously flown surface recession sensor, based on the Jupiter probe Galileo Analog Resistance Ablation Detector (ARAD), to appropriate aerocapture conditions.

Martinez, Ed↗
NASA NTRS2005

Development of Solid State Thermal Sensors for Aeroshell TPS Flight Applications

In-situ Thermal Protection System (TPS) sensors are required to provide verification by traceability of TPS performance and sizing tools. Traceability will lead to higher fidelity design tools, which in turn will lead to lower design safety margins, and decreased heatshield mass. Decreasing TPS mass will enable certain missions that are not otherwise feasible, and directly increase science payload. NASA Ames is currently developing two flight measurements as essential to advancing the state of TPS traceability for material modeling and aerothermal simulation: heat flux and surface recession (for ablators). The heat flux gage is applicable to both ablators and non-ablators and is therefore the more generalized sensor concept of the two with wider applicability to mission scenarios. This paper describes the continuing development of a thermal microsensor capable of surface and in-depth temperature and heat flux measurements for TPS materials appropriate to Titan, Neptune, and Mars aerocapture, and direct entry. The thermal sensor is a monolithic solid state device composed of thick film platinum RTD on an alumina substrate. Choice of materials and critical dimensions are used to tailor gage response, determined during calibration activities, to specific (forebody vs. aftbody) heating environments. Current design has maximum operating temperature of 1500K, and allowable constant heat flux of q=28.7 W/cm(sup 2), and time constants between 0.05 and 0.2 seconds. The catalytic and radiative response of these heat flux gages can also be changed through the use of appropriate coatings. By using several co-located gages with various surface coatings, data can be obtained to isolate surface heat flux components due to radiation, catalycity and convection. Selectivity to radiative heat flux is a useful feature even for an in-depth gage, as radiative transport may be a significant heat transport mechanism for porous TPS materials in Titan aerocapture.

Martinez, Ed↗
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 NTRS2016

Exploring the Science Trade Space with the JPL Innovation Foundry A-Team

The JPL Innovation Foundry has established a new approach for exploring, developing, and evaluating early concepts with a group called the Architecture Team (A-Team). The A-Team combines innovative collaborative methods and facilitated sessions with subject matter experts and analysis tools to help mature mission concepts. Science, implementation, and programmatic elements are all considered during an ATeam study. In these studies, Concept Maturity Levels (CML) are used to group methods. These levels include idea generation and capture (CML 1), initial feasibility assessment (CML 2), and trade space exploration (CML 3). Methods used for exploring the science objectives, feasibility, and scope will be described including use of a new technique for understanding the most compelling science, called a Science Return Diagram (SRD). In the process of developing the SRD, gradients in the science trade space are uncovered along with their implications for implementation and mission architecture. Special attention is paid towards developing complete investigations, establishing a series of logical claims that lead to the natural selection of a measurement approach. Over 20 science-focused A-Team studies have used these techniques to help science teams refine their mission objectives, make implementation decisions and reveal the mission concept’s most compelling science. This paper will describe the A-Team process for exploring the mission concept's science trade space and the Science Return Diagram technique.In June of 2011 a new collaborative engineering approach forearly concept formulation began in the JPL InnovationFoundry [1], six months later becoming the “A-Team” [2].Responding to a need for exploring mission architecturelevel trades [3], the A-Team precedes Team X [4,5] in asequence of concurrent engineering teams at JPL that can beused to mature a concept from a “cocktail napkin” level ideato a complete mission point design. The A-Team efficientlyexplores the science, implementation, and programmatictrade space in early concept formulation. Small, facilitatedgroups of experts generate innovative ideas, quantitativelyassess feasibility, and discover key sensitivities in the tradespace through collaborative analysis and use of advancedmethods and tools. The A-Team process builds off theexperience within JPL and other recent approaches to earlyconcept formulation [6] including best practices of the JPLInnovation Foundry, Project Systems Engineering &Formulation Section, Team Eureka and the Rapid MissionArchitecture Team[7].The A-Team is a focal point for innovative formulationapproaches and people within JPL. It relies on a largebackground of study resources, creative thinkers and “greybeard” scrutinizers, advanced tools, and subject matterexperts with both breadth and depth in experience andexpertise that are all available at JPL. The A-Team isdesigned to be a rapid and efficient process takingapproximately 6 weeks (the entire process can be as short asjust a few days or as long as up to three months) and costingthe equivalent of a work-month of a full-time employee orless. Studies begin with detailed planning and client reviewfollowed by study sessions, analysis work, and reporting.The staffing on each study is customized to the study goalsand objectives, and it is addressed early in the A-Teamprocess. Sessions are generally half-day or whole-day eventsand conducted over a series of days with focused agendas thatare moderated by a trained facilitator. Preliminary results andknowledge capture are available within hours of each session,and a final report is generally available two weeks later.One of the biggest challenges facing early conceptdevelopment is understanding the gradient in science returnversus various available mission scenarios and payload options. Often times, major areas of scientific inquiry havealready been prioritized by science groups, including throughthe National Research Council’s Decadal Studies inAstronomy, Planetary, and Earth Science. Yet science teamscontinue to struggle, especially in competitive missionsolicitations, to capture the right amount of scope that’sachievable within the cost constraints of the opportunity.Often the desire to completely and comprehensively study ascience area in just one mission (after all, true missionopportunities are rare) drives teams to take on too much,providing requirements that are unachievable within theresources of the opportunity without inducing unacceptableimplementation risk. Alternatively, science teams can seekto reduce risk by using an established instrument, but havenot thought through the traceability and key aspects of thescience question to justify its use. Both scenarios lead to badassumptions at the beginning of the concept development thatcan then ripple through implementation option choices,potentially preventing what would have been a good scienceinvestigation from being selected.The purpose of this paper is first to provide some additionalbackground and summary of the A-Team process, tools,people, and facilities. We then focus on the A-Teammethodology for overcoming the barriers of defining thescience scope well at the early concept development stage.This includes understanding the science story andtraceability, and then examining the gradient in science returnversus key characteristics of observables, developing theright payload and mission requirement specification throughexamining the science and implementation trade space.

Ziemer, John K.↗
NASA NTRSDate not supplied

NASA's CLARREO Pathfinder Mission: The Reflected Solar’s First SITSat

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder mission will take reflected solar (RS) highly accurate measurements needed to monitor Earth’s climate and will be the first RS SI-traceable Satellite Sensor (SITSat). The mission includes a RS spectrometer that will be installed on the International Space Station (ISS) and take measurements for at least one year. CLARREO Pathfinder (CPF) will use on-orbit calibration to achieve an unprecedented high accuracy with SI-traceability and the inter-calibration of other on-orbit instruments. The spectrometer is based on the HyperSpectral Imager for Climate Science (HySICS) instrument developed by the University of Colorado/Laboratory for Atmospheric and Space Physics of Boulder, CO, USA. HySICS is being designed to have a radiometric uncertainty of 0.3% (1-sigma), a five to ten times improvement over existing spaceflight RS instruments. High accuracy SI-traceable measurements such as these are critical to develop long-term climate-quality data sets. Additionally, by measuring spectral reflectance with high accuracy the CPF instrument will serve as an on-orbit intercalibration radiometric reference for operational Earth-viewing sensors, such as the Clouds and Earth’s Radiant Energy System (CERES) broadband shortwave instrument and the Visible/Infrared Imaging Radiometer Suite (VIIRS). Two-axis pointing, a spectral range from 350 nm to 2300 nm, and a spectral resolution ≤6 nm enable CPF to provide nearly coincident temporal, spatial, angular, and spectral matching of intercalibration targets, with sampling sufficient to reduce random errors. The intercalibration method will refine knowledge of target sensors’ effective offsets, gain, non-linearity, spectral response, and polarization sensitivity (as is relevant). Calibrated reflectance and reflected radiance spectra will be distributed to the scientific community through a NASA Distributed Active Archive Center (DAAC). We will present an overview of the CLARREO Pathfinder mission, its anticipated impact on monitoring climate variability, and the novel CPF direct intercalibration approach.

climate↗
NASA NTRS2010

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

Sandford, Stephen P.↗
NASA NTRS2017

Embracing Open Source for NASA's Earth Science Data Systems

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

Earth Science↗
NASA NTRSDate not supplied

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder Intercalibration Data Analysis Strategy

One of the prime science objectives of NASA’s Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission is to acquire unprecedentedly accurate Système Internationale (SI)-traceable Earth-view measurements that can be used as reference for intercalibrating the Clouds and the Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard NOAA-20 satellite. The hyperspectral nature of CPF measurements will significantly reduce spectrally induced biases when intercalibrating multiband or broadband satellite instruments with CPF. This advancement eliminates the requirement for spectral band adjustment factors, representing a substantial improvement in sensor intercalibration studies. The CPF intercalibration team is aiming to achieve a maximum intercalibration methodology uncertainty of 0.3 % (k=1). Our studies have revealed that the most significant contribution to the targeted uncertainty budget originates from the combined effects of spatial and temporal matching errors. Spatial matching error arises from discrepancies in CPF and target instrument pixel resolution and geolocation uncertainty, while temporal matching error is caused by changes in scene radiances over time, occurring between when the target and reference instruments observe the same scenes. To estimate the maximum expected uncertainty contribution from these sources, spatial and temporal matching noise analyses were conducted using algorithmically filtered Landsat 9 Operational Land Imager (OLI) and Geostationary Operational Environmental Satellite (GOES)-16 ABI CONUS scan data as proxies for CPF and target instruments. In the upcoming conference presentation, we will elaborate on the methodology employed in these experiments, provide details of the data filtering algorithms, and present results of the spatial and temporal matching uncertainty analyses.

Intercalibration↗
NASA NTRSDate not supplied

Modeling Entry Systems to Explore Our Solar System

Exploration of our Solar System is a foundational element of NASA’s identity. Delivering a scientific payload through an atmosphere to the surface of a planetary body requires safely navigating the extreme temperatures and stresses generated by flying many times the speed of sound. An entry system is the outer shell of a vehicle designed to protect the payload and, as a single point of failure for a mission, reliability is paramount. Unfortunately, it is not possible to fully replicate the flight environment in ground test facilities – so how do we confidently design a vehicle that needs to work the first time, every time? Modeling and simulation are critical tools for filling gaps in ground test capability and providing traceability from ground to flight. Modeling an entry system is a truly interdisciplinary effort, requiring knowledge of fluid dynamics, high-temperature chemistry, radiation, materials science, structural dynamics, guidance and control – and, finally, the mathematical and computing capability to pull it all together. In this talk, Dr. Michael Barnhardt will discuss the latest research in modeling entry systems and how it is being used in NASA’s exploration missions.

Entry systems↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
NASA NTRS2000

ScienceDesk Project Overview

NASA's ScienceDesk Project at the Ames Research Center is responsible for scientific knowledge management which includes ensuring the capture, preservation, and traceability of scientific knowledge. Other responsibilities include: 1) Maintaining uniform information access which is achieved through intelligent indexing and visualization, 2) Collaborating both asynchronous and synchronous science teamwork, 3) Monitoring and controlling semi-autonomous remote experimentation.

Keller, Richard M.↗