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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Simplifying Analysis of Hierarchical HDF5 and NetCDF4 Files with Xarray-Datatree

NASA’s Earth Observing System Data and Information System (EOSDIS) contains thousands of Earth science datasets from satellites, models, and field campaigns. EOSDIS data are stored in formats that are well supported by the Earth Science community. These formats include the Hierarchical Data Format (HDF), with derivative flavors such as HDF-5 and the Network Common Data Format (NetCDF-4). The HDF specification allows for a directory-like hierarchy within a single file, known as "groups". Observational data and associated metadata within a single file can be distributed amongst multiple internal groups, which can also be nested to multiple levels. Working with datasets that have a group hierarchical structure can be difficult because of the nested structure of groups. Widely used packages, such as xarray, have data models that do not accommodate the hierarchical structure within HDF files, requiring users to traverse the file and open different HDF groups as separate, unrelated objects. Xarray-datatree is a Python package developed to solve the difficulty of traversing HDFs with a hierarchical group structure by creating a tree-like hierarchical data structure in xarray. The tree-like structure allows each group to be accessed once a DataTree object is instantiated. The migration of xarray-datatree into the xarray core library will reduce barriers to accessing Earth science data by eliminating the need to understand and traverse the specific hierarchy of a grouped HDF file.

Eni Awowale↗
NASA NTRS2024

The SWOT Mission Will Reshape Our Understanding of the Global Terrestrial Water Cycle

Simultaneously integrating Surface Water and Ocean Topography (SWOT) measurements and those from other Earth observing satellites into hydrological modeling systems will transform our understanding of the global terrestrial water cycle. Such an opportunity comes with big challenges that the scientific community is now presented with.

Natural hazards↗
DOE OSTI2015

A simple object-oriented and open-source model for scientific and policy analyses of the global climate system – Hector v1.0

Simple climate models play an integral role in the policy and scientific communities. They are used for climate mitigation scenarios within integrated assessment models, complex climate model emulation, and uncertainty analyses. Here we describe Hector v1.0, an open source, object-oriented, simple global climate carbon-cycle model. This model runs essentially instantaneously while still representing the most critical global-scale earth system processes. Hector has a three-part main carbon cycle: a one-pool atmosphere, land, and ocean. The model's terrestrial carbon cycle includes primary production and respiration fluxes, accommodating arbitrary geographic divisions into, e.g., ecological biomes or political units. Hector actively solves the inorganic carbon system in the surface ocean, directly calculating air–sea fluxes of carbon and ocean pH. Hector reproduces the global historical trends of atmospheric [CO 2 ], radiative forcing, and surface temperatures. The model simulates all four Representative Concentration Pathways (RCPs) with equivalent rates of change of key variables over time compared to current observations, MAGICC (a well-known simple climate model), and models from the 5th Coupled Model Intercomparison Project. Hector's flexibility, open-source nature, and modular design will facilitate a broad range of research in various areas.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Heliophysics Science Enabled By the Return to the Moon

The lunar plasma and radiation environment and those physical processes that drive and control it, are intrinsically part of the science domain of the Heliophysics Division. Since the inception of the space program with Explorer 1 in 1958 and continuing to the present, scientists in the Heliophysics community have concentrated on characterizing and understanding the connected Sun-Earth system including the regions the Moon traverses and the interaction of plasmas and radiation with large and small bodies. This has been accomplished with in situ and remote sensing instrumentation and physics- and numerically-based models that provide understanding of the dominant mechanisms that define the environment in which the Moon is immersed. Therefore, the Heliospheric science community is uniquely and in many cases exclusively qualified to address interesting and compelling science problems that are enabled by the return to the Moon. This talk will provide an overview of representative, high-priority science investigations that are made possible by the return to the lunar surface. The content of this presentation is a result of an ongoing effort to inventory and articulate compelling science topics and how they are enabled by the return to the Moon.

Spann, James F.↗
NASA NTRS2023

Mesoscale Phenomena and Their Contribution to the Global Response: A Focus on the Magnetotail Transition Region and Magnetosphere-Ionosphere Coupling

An important question that is being increasingly studied across subdisciplines of Heliophysics is “how do mesoscale phenomena contribute to the global response of the system?” This review paper focuses on this question within two specific but interlinked regions in Near-Earth space: the magnetotail’s transition region to the inner magnetosphere and the ionosphere. There is a concerted effort within the Geospace Environment Modeling (GEM) community to understand the degree to which mesoscale transport in the magnetotail contributes to the global dynamics of magnetic flux transport and dipolarization, particle transport and injections contributing to the storm-time ring current development, and the substorm current wedge. Because the magnetosphere-ionosphere is a tightly coupled system, it is also important to understand how mesoscale transport in the magnetotail impacts auroral precipitation and the global ionospheric system response. Groups within the Coupling, Energetics and Dynamics of Atmospheric Regions Program (CEDAR) community have also been studying how the ionosphere-thermosphere responds to these mesoscale drivers. These specific open questions are part of a larger need to better characterize and quantify mesoscale “messengers” or “conduits” of information—magnetic flux, particle flux, current, and energy—which are key to understanding the global system. After reviewing recent progress and open questions, we suggest datasets that, if developed in the future, will help answer these questions.

transition region↗
NASA NTRS2018

The SMAP Level-4 ECO Project: Improving Terrestrial Flux Estimates Through Coupled Hydrology-Vegetation Data Assimilation

Simulations of hydrologic and vegetation states as well as water, energy and carbon fluxes from the land surface to the atmosphere are crucial for a wide range of applications, including agricultural advisories, forecasts of (short-term) atmospheric behavior and seasonal weather predictions including forecasts of extreme events, such as heatwaves or droughts. The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Eco-Hydrology (L4-ECO) project aims to improve modeled estimates of the terrestrial water, energy and carbon fluxes and states by developing a fully-coupled hydrology-vegetation data assimilation system. This system is developed around the NASA Goddard Earth Observing System (GEOS) Catchment-CN land surface model, which combines land hydrology and energy balance components of the GEOS Catchment model with dynamic vegetation components of the Community Land Model version 4. Catchment-CN fully couples the terrestrial water, energy and carbon cycles, allowing feedbacks from the land hydrology to the biosphere and vice versa.Here, we implement a calibration of the Catchment-CN vegetation parameterization against observations of the fraction of absorbed photosynthetically active radiation (FPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve the model's standalone skill. Later, the DA algorithm used to produce the SMAP L4 soil moisture product will be adapted to Catchment-CN to assimilate SMAP brightness temperatures and inform the model's land hydrology component. Finally, the DA system will be further extended to assimilate MODIS FPAR observations in order to constrain the model's dynamic vegetation component.In this presentation, we demonstrate that the Catchment-CN parameter calibration leads to more realistic vegetation simulations and reduces the root mean squared error between modeled and observed vegetation states across the model's various plant functional types. We also show that the assimilation of SMAP observations is able to improve the average correlation, bias and unbiased RMSE between the modeled surface and root zone soil moisture estimates, and ground observations from the SMAP core validation sites.

Kolassa, Jana↗
NASA NTRS2023

Is the Global MHD Modeling of the Magnetosphere Adequate for GIC Prediction: the May 27–28, 2017 Storm

Practical steps taken by the international community to reduce the damage to technological systems from space weather include the development of numerical models capable of real-time predictions of electromagnetic disturbances at the Earth’s surface. Here we examine the feasibility of a version of the Space Weather Modeling Framework (SWMF) global MHD simulation code similar to that used by the NOAA Space Weather Prediction Center to predict the level of geomagnetic field variability, and consequently geomagnetically induced currents (GICs). We consider the contribution of geomagnetic disturbances to the bursts of GIC in the electric power line of the Kola Peninsula during the May 27–28, 2017 storm and compare the observations with results of the global MHD model. During the maximal disturbance magnetic field variations at East Scandinavian stations become more irregular, as intense Pi3 pulsations are superposed on the magnetic bay. These pulsations are not quasi-sinusoidal waves like typical Pc5 pulsations, but they are rather a quasi-periodic sequence of magnetic impulses with time scales ~5–15 min. During this period with elevated Pi3 activity very high values of GIC were recorded (variations >100 A) in the electric power transmission line. The SWMF modeling reasonably well reproduces the global magnetospheric parameters, such as SYM-H index or cross-polar potential. However, the magnetic field variability dB/dt in the East Scandinavia predicted by the modeling has turned out to be more than order of magnitude less than that observed. Thus, the version of SWMF with the grid used by NOAA SWPC still cannot adequately predict for the May 27–28 event the fine structure of the storm/substorm—Pi3 geomagnetic disturbances, and consequently the magnitude of the GIC that they drive.

geomagnetically induced currents↗
DOE OSTI2014

3rd Annual Earth System Grid Federation and 3rd Annual Earth System Grid Federation and Ultrascale Visualization Climate Data Analysis Tools Face-to-Face Meeting Report December 2013

The climate and weather data science community gathered December 3–5, 2013, at Lawrence Livermore National Laboratory, in Livermore, California, for the third annual Earth System Grid Federation (ESGF) and Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) Face-to-Face (F2F) Meeting, which was hosted by the Department of Energy, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, the European Infrastructure for the European Network of Earth System Modelling, and the Australian Department of Education. Both ESGF and UV-CDAT are global collaborations designed to develop a new generation of open-source software infrastructure that provides distributed access and analysis to observed and simulated data from the climate and weather communities. The tools and infrastructure developed under these international multi-agency collaborations are critical to understanding extreme weather conditions and long-term climate change, while the F2F meetings help to build a stronger climate and weather data science community and stronger federated software infrastructure. The 2013 F2F meeting determined requirements for existing and impending national and international community projects; enhancements needed for data distribution, analysis, and visualization infrastructure; and standards and resources needed for better collaborations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

NAIRAS Model Nowcasting and Forecasting of the Aviation Radiation Environment

The Nowcast of Aerospace Ionizing RAdiation System (NAIRAS) predicts dosimetric quantities for quantifying human radiation exposure and differential/integral flux/fluence quantities for assessing single event effects (SEE) in avionic systems from galactic cosmic rays (GCR), trapped inner belt protons, and solar energetic particle (SEP) events from the Earth’s surface to the space environment. Real-time predictions of the aviation radiation environment are available at NASA Goddard Space Flight Center’s Community Coordinated Modeling Center (CCMC) integrated Space Weather Analysis (iSWA) data feeds and cygnets, and a run-on-request (RoR) capability has also been deployed at CCMC. Recent model improvements include a more accurate atmospheric ionizing radiation transport methodology and more robust and reliable SEP nowcast dose predictions. In addition, preliminary results of SEP dose forecasts are shown by coupling the University of Malaga Solar Energetic Particle (UMASEP) model of integral proton flux forecasts with the NAIRAS model. These model updates and improvements are presented, and results are shown for aircraft, high-latitude balloon, and low-Earth orbit flights during quiescent and solar-geomagnetic disturbed conditions. Model comparisons with flight measurements are also shown.

NAIRAS↗
NASA NTRS2016

Enabling Research Tools for Sustained Climate Assessment

The U.S. Global Change Research Program Sustained Assessment process benefits from long-term investments in Earth science research that enable the scientific community to conduct assessment-relevant science. To this end, NASA initiated several research programs over the past five years to support the Earth observation community in developing indicators, datasets, research products, and tools to support ongoing and future National Climate Assessments. These activities complement NASA's ongoing Earth science research programs. One aspect of the assessment portfolio funds four "enabling tools" projects at NASA research centers. Each tool leverages existing capacity within the center, but has developed tailored applications and products for National Climate Assessments. The four projects build on the capabilities of a global atmospheric reanalysis (MERRA-2), a continental U.S. land surface reanalysis (NCA-LDAS), the NASA Earth Exchange (NEX), and a Regional Climate Model Evaluation System (RCMES). Here, we provide a brief overview of each enabling tool, highlighting the ways in which it has advanced assessment science to date. We also discuss how the assessment community can access and utilize these tools for National Climate Assessments and other sustained assessment activities.

Research↗
DOE OSTI2021

Learning from learning machines: improving the predictive power of energy-water-land nexus models with insights from complex measured and simulated data

Focal Area(s): Insights gleaned from complex data (observed and simulated) using AI; Predictive modeling through the use of AI techniques and AI-derived model components, including physics- and knowledge-informed models; Energy-water-land nexus and integrated energy systems – models of MultiSector dynamics. Science Challenge: Scientific communities are in need of tools for the computational integration of physics-based models, experimental data, and empirical/observational studies across a broad range of temporal and spatial scales to explore and meet EESSD grand challenges. We require AI algorithms for the discovery of process-drivers in the Earth-energy-human system and to link them with complex measured and simulated data. We aim to understand the energy-water-land nexus, particularly under extreme forcing scenarios and rare events, leveraging scale-aware AI process models, including probabilistic uncertainties, and benefiting from the emerging 5G-enabled landscape-scale sensing and edge computing capabilities. These models are needed to identify instabilities and tipping points that manifest extreme system behaviors with consequences for integrated energy systems and the environment. This work requires fundamental advances in uncertainty quantification, in particular, to identify and model unlikely but catastrophic outliers. Specifically, we need models that are interpretable to domain scientists and, essentially, explainable to public and private stake holders.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Development of a NASA Integrated Technical Workforce Career Development Model Entitled Requisite Occupation Competencies and Knowledge -- the ROCK

This paper shares the findings of NASA's Integrated Learning and Development Program (ILDP) in its effort to reinvigorate the HANDS-ON practice of space systems engineering and project/program management through focused coursework, training opportunities, on-the job learning and special assignments. Prior to March 2005, NASA responsibility for technical workforce development (the program/project manager, systems engineering, discipline engineering, discipline engineering and associated communities) was executed by two parallel organizations. In March 2005 these organizations merged. The resulting program-ILDP-was chartered to implement an integrated competency-based development model capable of enhancing NASA's technical workforce performance as they face the complex challenges of Earth science, space science, aeronautics and human spaceflight missions. Results developed in collaboration with NASA Field Centers are reported on. This work led to definition of the agency's first integrated technical workforce development model known as the Requisite Occupation Competence and Knowledge (the ROCK). Critical processes and products are presented including: 'validation' techniques to guide model development, the Design-A-CUrriculuM (DACUM) process, and creation of the agency's first systems engineering body-of-knowledge. Findings were validated via nine focus groups from industry and government, validated with over 17 space-related organizations, at an estimated cost exceeding $300,000 (US). Masters-level programs and training programs have evolved to address the needs of these practitioner communities based upon these results. The ROCK reintroduced rigor and depth to the practitioner's development in these critical disciplines enabling their ability to take mission concepts from imagination to reality.

Menrad, Robert J.↗
NASA NTRS2003

Performance of Goddard Earth Observing System GCM Column Radiation Models under Heterogeneous Cloud Conditions

We test the performance of the shortwave (SW) and longwave (LW) Column Radiation Models (CORAMs) of Chou and collaborators with heterogeneous cloud fields from a global single-day dataset produced by NCAR's Community Atmospheric Model with a 2-D CRM installed in each gridbox. The original SW version of the CORAM performs quite well compared to reference Independent Column Approximation (ICA) calculations for boundary fluxes, largely due to the success of a combined overlap and cloud scaling parameterization scheme. The absolute magnitude of errors relative to ICA are even smaller for the LW CORAM which applies similar overlap. The vertical distribution of heating and cooling within the atmosphere is also simulated quite well with daily-averaged zonal errors always below 0.3 K/d for SW heating rates and 0.6 K/d for LW cooling rates. The SW CORAM's performance improves by introducing a scheme that accounts for cloud inhomogeneity. These results suggest that previous studies demonstrating the inaccuracy of plane-parallel models may have unfairly focused on worst scenario cases, and that current radiative transfer algorithms of General Circulation Models (GCMs) may be more capable than previously thought in estimating realistic spatial and temporal averages of radiative fluxes, as long as they are provided with correct mean cloud profiles. However, even if the errors of the particular CORAMs are small, they seem to be systematic, and the impact of the biases can be fully assessed only with GCM climate simulations.

Oreopoulos, L.↗
DOE OSTI2021

Biomass burning aerosols in most climate models are too absorbing

Uncertainty in the representation of biomass burning (BB) aerosol composition and optical properties in climate models contributes to a range in modeled aerosol effects on incoming solar radiation. Depending on the model, the top-of-the-atmosphere BB aerosol effect can range from cooling to warming. By relating aerosol absorption relative to extinction and carbonaceous aerosol composition from 12 observational datasets to nine state-of-the-art Earth system models/chemical transport models, we identify varying degrees of overestimation in BB aerosol absorptivity by these models. Modifications to BB aerosol refractive index, size, and mixing state improve the Community Atmosphere Model version 5 (CAM5) agreement with observations, leading to a global change in BB direct radiative effect of -0.07 W m -2 , and regional changes of -2 W m -2 (Africa) and -0.5 W m -2 (South America/Temperate). Our findings suggest that current modeled BB contributes less to warming than previously thought, largely due to treatments of aerosol mixing state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Confronting Earth System Model trends with observations

Anthropogenically forced climate change signals are emerging from the noise of internal variability in observations, and the impacts on society are growing. For decades, Climate or Earth System Models have been predicting how these climate change signals will unfold. While challenges remain, given the growing forced trends and the lengthening observational record, the climate science community is now in a position to confront the signals, as represented by historical trends, in models with observations. This review covers the state of the science on the ability of models to represent historical trends in the climate system. It also outlines robust procedures that should be used when comparing modeled and observed trends and how to move beyond quantification into understanding. Finally, this review discusses cutting-edge methods for identifying sources of discrepancies and the importance of future confrontations.

58 GEOSCIENCES↗
NASA NTRS2018

The SMAP Level-4 ECO Product - Phase 1: Improving Vegetation Simulations Through Observation-Driven Parameter Estimation

Simulations of hydrological fields as well as water, energy and carbon fluxes from the land surface to the atmosphere are crucial for a wide range of applications, including agricultural advisories, forecasts of (short-term) atmospheric behavior and seasonal weather predictions including forecasts of extreme events, such as heatwaves or droughts. The NASA Soil Moisture Active Passive (SMAP) mission Level-4 (L4) Eco-Hydrology (ECO) project aims to improve modeled estimates of the terrestrial water, energy and carbon fluxes and states by developing a fully-coupled hydrology-vegetation data assimilation (DA) algorithm. The DA system is developed for the NASA Goddard Earth Observing System version 5 (GEOS-5) Catchment-CN land surface model, which combines land hydrology components of the GEOS-5 Catchment model with dynamic vegetation components of the Community Land Model version 4. Catchment-CN fully couples the terrestrial water, energy and carbon cycles, allowing feedbacks from the land hydrology to the biosphere and vice versa. For SMAP L4 ECO a calibration of the Catchment-CN vegetation parameterization against observations of the fraction of absorbed photosynthetically active radiation (FPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) is implemented to improve the model's standalone skill. Next, the DA algorithm used to produce the SMAP L4 soil moisture product is adapted to Catchment-CN to assimilate SMAP brightness temperatures and inform the model's land hydrology component. The DA system is further extended to assimilate MODIS FPAR observations in order to constrain the model's dynamic vegetation component. In this presentation, we demonstrate that the Catchment-CN parameter calibration leads to more realistic vegetation simulations and reduces the root mean squared error between modeled and observed vegetation states across the model's various plant functional types. We also show that the assimilation of SMAP observations is able to improve the average correlation, bias and unbiased RMSE between the modeled surface and root zone soil moisture estimates, and ground observations from the SMAP core validation sites.

Kolassa, J.↗
NASA NTRS2000

Remote sensing and human health: new sensors and new opportunities

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Systeme Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

Satellite Communications↗
NASA NTRS2009

Scientific Benefits of Space Science Models Archiving at Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) hosts a set of state-of-the-art space science models ranging from the solar atmosphere to the Earth's upper atmosphere. CCMC provides a web-based Run-on-Request system, by which the interested scientist can request simulations for a broad range of space science problems. To allow the models to be driven by data relevant to particular events CCMC developed a tool that automatically downloads data from data archives and transform them to required formats. CCMC also provides a tailored web-based visualization interface for the model output, as well as the capability to download the simulation output in portable format. CCMC offers a variety of visualization and output analysis tools to aid scientists in interpretation of simulation results. During eight years since the Run-on-request system became available the CCMC archived the results of almost 3000 runs that are covering significant space weather events and time intervals of interest identified by the community. The simulation results archived at CCMC also include a library of general purpose runs with modeled conditions that are used for education and research. Archiving results of simulations performed in support of several Modeling Challenges helps to evaluate the progress in space weather modeling over time. We will highlight the scientific benefits of CCMC space science model archive and discuss plans for further development of advanced methods to interact with simulation results.

Kuznetsova, Maria M.↗