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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 NTRS2011

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Peters-Lidard, Christa D.↗
DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗
NASA NTRS1989

Basic properties of developed wind waves and their influence on microwave remote sensing signatures

Error trends in wind speed measurements by satellite scatterometer altimeter and microwave radiometer are shown to be correlated with the degree of wave development. These errors are analyzed theoretically by studying the rms wave slope which, directly or indirectly, affects all microwave signatures. For equilibrium sea state, the influence of spectrum parameters on the wave slope is reviewed. In well-developed seas, the dominant wavelength is shown to have no effect on the slope. Temporal-spatial rates of steep and breaking waves are derived and compared with field observations. The inner scale that determines a rapid falloff of spectral density function at high frequencies is estimated. The dependence of the spectral parameters on wind speed and sea maturity is studied using NOAA buoy observations. It is concluded that the removal of environmental error trends from satellite measurements can be best accomplished by a joint processing of microwave returns from several independent instruments.

Glazman, Roman E.↗
DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗
DOE OSTI2023

Refractivity Observations from Radar Phase Measurements: The 22 May 2002 Dryline Case during IHOP Project

The dryline, often associated with the development of severe storms in the Southern Great Plains of the United States of America, is a boundary layer phenomenon that occurs when a warm and moist air mass from the Gulf of Mexico meets a hot and dry air mass from the southwest desert area. An accurate knowledge of the water vapor spatio-temporal variability in the lower part of the atmosphere is crucial for a better understanding of the evolution of the dryline. The tropospheric refractivity, directly related to water vapor content, is a proxy for the water vapor content of the troposphere. It has already been demonstrated that the refractivity and the refractivity vertical gradient can be jointly estimated from radar phase measurements. In fact, it has been shown that using kriging interpolation techniques, accurate refractivity maps within the coverage area of the radar can be obtained with high temporal resolution. In this paper, a detailed analysis of the time series of radar-based refractivity maps obtained during a dryline that occurred on the afternoon of 22 May 2002 during the International H 2 O Project is presented. Comparisons between the time series of radar refractivity maps, obtained with the NCAR S-Pol radar, and the refractivity measurements derived from automatic ground-based weather stations and the AERI instrument, placed at different locations within the coverage area of the NCAR S-Pol radar, demonstrate the accuracy of radar refractivity estimates even for highly variable conditions, both in time and space, in the troposphere. Correlation coefficients higher than 0.95 are obtained in all weather station locations. Regarding the RMSE, errors less than 6 N-units are obtained for all cases, being even as low as 2.92 N-units at some locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate Change and Changes in Compound Coastal-Riverine Flooding Hazard Along the U.S. Coasts

The cooccurrence of coastal and riverine flooding leads to compound events with substantial impacts on people and property in low-lying coastal areas. Climate change could increase the level of compound flood hazard through higher extreme sea levels and river flows. Here, a bivariate flood hazard assessment method is proposed to estimate compound coastal-riverine frequency under current and future climate conditions. A copula-based approach is used to estimate the joint return period (JRP) of compound floods by incorporating sea-level rise (SLR) and changes in peak river flows into the marginal distributions of flood drivers. Specifically, the changes in JRP of compound major coastal-riverine flooding defined based on simultaneous exceedances above major coastal and riverine thresholds, are explored by midcentury. Subsequently, the increase in the probability of occurrence of at least one compound major coastal-riverine flooding for a given period of time is quantified. The proposed compound flood hazard assessment is conducted at 26 paired tidal-riverine stations along the Contiguous United States coast with long-term data and defined flood thresholds. We show that the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal-riverine flood probability under current conditions. However, future SLR scenarios show the highest frequency amplification along the southeast Atlantic coast. The impact of changes in peak river flows is found to be considerably less than that of SLR. Climate change impacts, especially SLR, may lead to more frequent compound events, which cannot be ignored for future adaptation responses in estuary regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Latent Heating from TRMM Satellite Measurements

Rainfall production is the fundamental variable within the Earth's hydrological cycle because it is both the principal forcing term in surface water budgets and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations within the tropics - as well as modifying the energetic efficiencies of midlatitude weather systems. This paper focuses on the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission (TRMM) satellite observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional account of rainfall over the global tropics and sub-tropics, information which can be used to estimate the space-time structure of latent heating across the Earth's low latitudes. The paper examines how the observed TRMM distribution of rainfall has advanced an understanding of the global water and energy cycle and its consequent relationship to the atmospheric general circulation and climate via latent heat release. A set of algorithm methodologies that are being used to estimate latent heating based on rain rate retrievals from the TRMM observations are described. The characteristics of these algorithms and the latent heating products that can be generated from them are also described, along with validation analyses of the heating products themselves. Finally, the investigation provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

Tao, Wei-Kuo↗
NASA NTRSDate not supplied

NASA’s NextGen Remote Sensing Instruments Have Arrived: Data Products For Studying Disease Vectors

Remote sensing can be used to measure, evaluate or estimate both the environment (state functions) and interfaces (processfunctions) defining vector habitats. The products of remote sensing can be integrated directly into the epidemiological equationsto significantly enhance our understanding of disease vector’s life cycles and habitats. The next generation of NASA’s remotesensing instruments which have become recently operational will provide a significant enhancement in our ability to studydisease vector’s life cycles and habitats. These instruments are on the International Space Station (ISS) and includeECOSTRESS, DESIS, and GEDI. ECOSTRESS is a 5 channel, thermal IR instrument with 70 m resolution and approximately1-5 day repeat cycle of day/night pairs. DESIS jointly developed by German Aerospace Center and Teledyne Brown Engineeringis a hyperspectral sensor system of 235 channels and 30 m resolution. DESIS data is only being acquired on demand. GEDI is ahigh-resolution laser ranger used for observing Earth’s forests and topography. NASA’s current ISS instrument configuration provides measurements of the critical environmental measures of environmentalstate functions important to vector & disease life cycles. Remote sensing data provide a spatial context and time series oflandscape scale process functions represented by land use mapping and measurements of ecological functions. Global publichealth is entering a new information age through the use of spatial models of disease vector/host ecologies driven by the use ofremotely sensed data to measure environmental and structural factors critical in determining disease vector habitats. In 2018, NASA initiated a new study for the Surface Biology and Geology (SBG) Designated Observable, identified in the 2018National Academies’ Decadal Survey entitled, “Thriving on Our Changing Planet: A Decadal Strategy for Earth Observationfrom Space.” (https://www.nap.edu/catalog/24938/thriving-on-our-changing-planet-a-decadal-strategy-for-earth) . The SBG isplanned to collect global remote sensing measurements using a hyperspectral spectrometer and multispectral thermal data. Thesedata sets will provide a significant enhancement in our ability to study disease vector’s life cycles and habitats globally. The 3sensors on the ISS provide precursor data to prepare the community for the application of future SBG data toward diseasestudies.

Disease Vectors↗
NASA NTRS2020

History and Logic Model NASA Goddard Space Flight Center Instrument and Payload Systems Engineering Technical Performance Study

Historically, some NASA missions have exceeded schedule and cost commitments. Studies suggest technical performance is a contributor. The 1980 NASA Project Management Study concluded, "one of the most significant contributors to cost and schedule growth is inadequate definition of technical and management aspects of a program..." (as cited in GAO/NSIAD-93-97, p. 11). The 1991 NASA Roles and Missions Report identified a "need for increased emphasis on technological readiness and requirements on the front end of a program" (as cited in GAO/NSIAD-93-97, p. 11). The 1992 NASA Program Costs Report stated that NASA officials identified, among other things, "insufficient definition studies... [and] program redesigns and technical complexities" as reasons for cost and schedule overruns (GAO/NSAID-93-97, p. 11). The 2002 Task Force on Acquisition of National Security Space Programs found "requirements definition and control issues, unhealthy cost bias in proposal evaluation, widespread lack of budget reserves required to implement high risk programs on schedule, and an overall underappreciation of the importance of appropriately staffed and trained system engineering staff to manage the technologically demanding and unique aspects of space programs" (DoD, 2003, p.i.) In 2007, The NASA Office of the Chief Engineer chartered the NASA Instrument Capability Study (NICS) “to determine whether NASA instrument developers are facing challenges that impact the capability to design and build quality instruments or whether there are flaws in the acquisition strategy evidenced by schedule delays, cost overruns, and increased technical risk via design deficiencies. The... team was also chartered to determine if occurrences [are]... isolated cases or if there are generic issues... If the issues [are] found to be generic, the team [is] to offer solutions to recover such capability" (NICS Report, 2008, p. vi). The 2008 NICS Report, led by Goddard Space Flight Center (GSFC), identified challenges to instrument technical performance consistent with findings from previous reports. In 2017, the Instrument Project Division (IPD) Implementation Study was initiated to determine if there was a change in meeting schedule and cost commitments after implementing certain NICS recommendations. In 2018, the Instrument Technical Performance Study was initiated to determine the current state of Instrument Technical Performance in the GSFC Payload & Instrument Systems Engineering Branch. The purpose of the combined studies is to answer the question, "Is there a relationship between meeting NASA scientific instrument technical success and meeting schedule and cost commitments? If yes, what is the relationship?" References Department of Defense Office of the Under Secretary of Defense for Acquisition, Technology, and Logistics. (2003). The report of the defense science board/ air force scientific advisory board joint task force on acquisition of national security space programs. Washington DC. Government Accounting Office. (1992). NASA program costs: Space missions require substantially more funding than initially estimated. GAO/NSIAD-93-97. Washington DC. National Aeronautics and Space Administration, National Oceanic and Atmospheric Agency, Department of Defense. (2008). The NASA instrument capability study final report. NP-2008-11-058-GSFC. Washington DC.

Robbins, Geraldine↗
DOE OSTI2025

Sensitive detection of structural dynamics using a statistical framework for comparative crystallography

Chemical and conformational changes are crucial to protein function and its pharmacological control. X-ray crystallography can reveal these changes in atomic detail, but standard analysis methods, which refine separate datasets, often overlook differences that are subtle or arise in only a subset of molecules. Direct comparison of crystallographic datasets is, in principle, more powerful, but systematic errors (“scales”) often mask changes in the crystallographic observables (“structure factors”). Machine learning algorithms that jointly estimate scales and structure factors can address this limitation. Here, we augment this approach with multivariate, structured priors derived from crystallographic theory, implemented in the variational deep learning framework Careless. Doing so strongly improves the detection of protein dynamics, element-specific anomalous signals, and the binding of drug candidates, offering a robust approach to comparative crystallography and, potentially, to detection of protein dynamics by other structure determination methods.

Hekstra, Doeke R. [Harvard Univ., Cambridge, MA (U↗
DOE OSTI2023

New approaches to an old problem: addressing spatial gaps in the World Stress Map

Abstract A well-recognized characteristic of the World Stress Map (WSM) database is the continued presence of large spatial gaps in the distribution of the data records despite the more than 40-year development history of the database. The current release has more than 30 000 high-quality (A–C) data records (often referred to as ‘stress indicators’), but while some continental areas (such as Australia) have seen a significant increase in spatial converge with the latest release, other continental regions (Africa, central Asia, most of South America) remain markedly sparse. In this contribution we (1) review the current state of the spatial distribution of stress indicators in the continental regions (above sea-level); (2) quantify the clustering of the stress indicators in the latest WSM release using the Hopkins statistic as a way to explore the current spatial distribution of the indicators and assess future WSM releases; and (3) present three approaches (joint inversion, seismic anisotropy and InSAR) that provide a way to fill in the gaps (both in the S Hmax orientation and principal stress magnitudes) in regions that lack active seismicity and where borehole drilling is cost prohibitive. These three approaches have the potential to guide procedures for improving a priori estimates of the ambient stress field in the Earth's crust and reduce the uncertainty in predicting both the magnitude and orientation of the principal tectonic stresses.

58 GEOSCIENCES↗
DOE OSTI2025

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗
NASA NTRS1992

Development of a machine vision system for automated structural assembly

Research is being conducted at the LaRC to develop a telerobotic assembly system designed to construct large space truss structures. This research program was initiated within the past several years, and a ground-based test-bed was developed to evaluate and expand the state of the art. Test-bed operations currently use predetermined ('taught') points for truss structural assembly. Total dependence on the use of taught points for joint receptacle capture and strut installation is neither robust nor reliable enough for space operations. Therefore, a machine vision sensor guidance system is being developed to locate and guide the robot to a passive target mounted on the truss joint receptacle. The vision system hardware includes a miniature video camera, passive targets mounted on the joint receptacles, target illumination hardware, and an image processing system. Discrimination of the target from background clutter is accomplished through standard digital processing techniques. Once the target is identified, a pose estimation algorithm is invoked to determine the location, in three-dimensional space, of the target relative to the robots end-effector. Preliminary test results of the vision system in the Automated Structural Assembly Laboratory with a range of lighting and background conditions indicate that it is fully capable of successfully identifying joint receptacle targets throughout the required operational range. Controlled optical bench test results indicate that the system can also provide the pose estimation accuracy to define the target position.

Sydow, P. Daniel↗
DOE OSTI2025

Fast, differentiable, and extensible big bang nucleosynthesis package

Here, we introduce light isotope nucleosynthesis with JAX (LINX), a new differentiable public big bang nucleosynthesis code designed for fast parameter estimation. By leveraging JAX, LINX achieves both speed and differentiability, enabling the use of Bayesian inference, including gradient-based methods. We discuss the formalism used in LINX for rapid primordial elemental abundance predictions and give examples of how LINX can be used. When combined with differentiable cosmic microwave background power spectrum emulators, LINX can be used for joint cosmic microwave background and big bang nucleosynthesis analyses without requiring extensive computational resources, including on personal hardware.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2007

NASA Tech Briefs, March 2007

Topics include: Advanced Systems for Monitoring Underwater Sounds; Wireless Data-Acquisition System for Testing Rocket Engines; Processing Raw HST Data With Up-to-Date Calibration Data; Mobile Collection and Automated Interpretation of EEG Data; System for Secure Integration of Aviation Data; Servomotor and Controller Having Large Dynamic Range; Digital Multicasting of Multiple Audio Streams; Translator for Optimizing Fluid-Handling Components; AIRSAR Web-Based Data Processing; Pattern Matcher for Trees Constructed From Lists; Reducing a Knowledge-Base Search Space When Data Are Missing; Ground-Based Correction of Remote-Sensing Spectral Imagery; State-Chart Autocoder; Pointing History Engine for the Spitzer Space Telescope; Low-Friction, High-Stiffness Joint for Uniaxial Load Cell; Magnet-Based System for Docking of Miniature Spacecraft; Electromechanically Actuated Valve for Controlling Flow Rate; Plumbing Fixture for a Microfluidic Cartridge; Camera Mount for a Head-Up Display; Core-Cutoff Tool; Recirculation of Laser Power in an Atomic Fountain; Simplified Generation of High-Angular-Momentum Light Beams; Imaging Spectrometer on a Chip; Interferometric Quantum-Nondemolition Single-Photon Detectors; Ring-Down Spectroscopy for Characterizing a CW Raman Laser; Complex Type-II Interband Cascade MQW Photodetectors; Single-Point Access to Data Distributed on Many Processors; Estimating Dust and Water Ice Content of the Martian Atmosphere From THEMIS Data; Computing a Stability Spectrum by Use of the HHT; Theoretical Studies of Routes to Synthesis of Tetrahedral N4; Estimation Filter for Alignment of the Spitzer Space Telescope; Antenna for Measuring Electric Fields Within the Inner Heliosphere; Improved High-Voltage Gas Isolator for Ion Thruster; and Hybrid Mobile Communication Networks for Planetary Exploration.

Source record↗
NASA NTRS2009

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

Peters-Lidard, Christa D.↗
NASA NTRS1978

Possible effects of solar UV variations on ozone and climate

A one-dimensional photochemical model was used to estimate the consequences of 27-day, 11-year, 22-year, and several-hundred-year variations of ultraviolet solar radiation on the concentration of ozone and nitrogen dioxide, and a one-dimensional radiative-convective equilibrium model was used to assess the joint effect of the radiation and concentration variations on the global temperature structure. For the several-hundred-year variations, the ozone column density increases by about 17.5% from minimum to maximum solar UV flux. For the 11-year period the ozone column density fluctuates by only about 7%, the lack of a full response being due to the time required for vertical motions to redistribute ozone from the altitudes of maximum production to those of maximum steady-state value. The 22-year period shows a full response, which the density varies by less than a percent for the 27-day period. Climatic consequences of these results are briefly discussed.

Pollack, J. B.↗
DOE OSTI2023

Marine carbon dioxide removal (mCDR) test site needs: A joint PNNL-PMEL workshop report

This workshop report summarizes testing and capability needs for marine Carbon Dioxide Removal (mCDR) research identified by researchers from DOE’s Pacific Northwest National Laboratory (PNNL) and NOAA’s Pacific Marine Environmental Laboratory (PMEL) as essential to advancing the state of the science and technology. A one-day workshop was held for 36 hybrid participants on June 2, 2023 at PNNL’s Marine and Coastal Sciences Laboratory in Sequim, WA. The workshop began with DOE and NOAA leadership offering perspectives on the mission alignment and long-term implementation of mCDR research within NOAA’s Office of Ocean and Atmospheric Research (OAR), DOE’s Water Power Technologies Office (WPTO), and DOE’s Office of Fossil Energy and Carbon Management (FECM). As identified by the participants and by program leadership at both agencies, many mCDR strategies are in early stages of development making it difficult to reliably estimate their impact. The essential next step in proving the efficacy, safety, and sustainability of these solutions and identifying market potential requires studies under field-relevant conditions.

13 HYDRO ENERGY↗