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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Towards a Multisensor Approach to Improve on Current TRMM Retrievals of Clouds and Precipitation

The Tropical Rainfall Measuring Mission (TRMM) was designed to measure tropical rainfall and its variation from a low inclination orbiting satellite. The TRMM payload was carefully chosen to overcome a number of limitations of past satellite observing systems. This payload is predicated on the combination of active and passive observations from the TRMM Precipitation Radar (PR) and TRMM Microwave Imager (TMI) and Visible and Infrared Scanner (VIRS). Our research over the past three years has been devoted to the challenge of developing the most effective way of combining complementary information from these sensors to provide the most consistent estimate of precipitation. We have approached this problem from three directions. The first was to carry out preliminary analysis of passive microwave and infrared data from the TMI and VIRS instruments to understand the character of clear and cloudy skies in the basis defined by polarization and brightness temperature differences. Using this information as a foundation, the properties of two retrieval algorithms were analyzed, one for retrieving ice clouds from VIRS that was developed in parallel with this project and the other for rainfall from the TMI. Finally, the knowledge gleaned from each of these studies, coupled with ancillary data from NWP models and a broadband radiative transfer model, was used to create and algorithm for synthesizing the principal components of the Earth's energy budget from the basic building blocks of the atmosphere, gases, clouds, and precipitation. Principal results from each of these areas of research and their role in the TRMM and climate communities are summarized.

Stephens, Graeme L.↗
NASA NTRS2002

The Impact of TRMM Data on Numerical Forecast of Mesoscale Systems

The impact of surface rainfall data derived from the TRMM Microwave Image (TMI) on the numerical forecast of mesoscale systems is evaluated. A series of numerical experiments are performed that assimilate TMI rainfall data into the Penn State University/National Centers for Atmospheric Research (PSU/NCAR) Mesoscale Model version 5 (MM5) using a four-dimensional variational data assimilation (4DVAR) technique. Experiments are conducted incorporating TMI rainfall data into the mesoscale model to improve hurricane initialization. It is found that assimilation of rainfall data into the model is beneficial in producing a more realistic eye and rain bands and also helps to improve the intensity forecast for the hurricane. Further 4DVAR experiments are performed on mesoscale convective systems (MCSs). Detailed results and related issues will be presented during the conference.

Pu, Zhao-Xia↗
NASA NTRS2002

Use of Collocated KWAJEX Satellite, Aircraft, and Ground Measurements for Understanding Ambiguities in TRMM Radiometer Rain Profile Algorithm

Coordinated ground, aircraft, and satellite observations are analyzed from the 1999 TRMM Kwajalein Atoll field experiment (KWAJEX) to better understand the relationships between cloud microphysical processes and microwave radiation intensities in the context of physical evaluation of the Level 2 TRMM radiometer rain profile algorithm and uncertainties with its assumed microphysics-radiation relationships. This talk focuses on the results of a multi-dataset analysis based on measurements from KWAJEX surface, air, and satellite platforms to test the hypothesis that uncertainties in the passive microwave radiometer algorithm (TMI 2a12 in the nomenclature of TRMM) are systematically coupled and correlated with the magnitudes of deviation of the assumed 3-dimensional microphysical properties from observed microphysical properties. Re-stated, this study focuses on identifying the weaknesses in the operational TRMM 2a12 radiometer algorithm based on observed microphysics and radiation data in terms of over-simplifications used in its theoretical microphysical underpinnings. The analysis makes use of a common transform coordinate system derived from the measuring capabilities of the aircraft radiometer used to survey the experimental study area, i.e., the 4-channel AMPR radiometer flown on the NASA DC-8 aircraft. Normalized emission and scattering indices derived from radiometer brightness temperatures at the four measuring frequencies enable a 2-dimensional coordinate system that facilities compositing of Kwajalein S-band ground radar reflectivities, ARMAR Ku-band aircraft radar reflectivities, TMI spacecraft radiometer brightness temperatures, PR Ku-band spacecraft radar reflectivities, bulk microphysical parameters derived from the aircraft-mounted cloud microphysics laser probes (including liquid/ice water contents, effective liquid/ice hydrometeor radii, and effective liquid/ice hydrometeor variances), and rainrates derived from any of the individual ground, aircraft, or satellite algorithms applied to the radar or radiometer measurements, or their combination. The results support the study's underlying hypothesis, particularly in context of ice phase processes, in that the cloud regions where the 2a12 algorithm's microphysical database most misrepresents the microphysical conditions as determined by the laser probes, are where retrieved surface rainrates are most erroneous relative to other reference rainrates as determined by ground and aircraft radar. In reaching these conclusions, TMI and PR brightness temperatures and reflectivities have been synthesized from the aircraft AMPR and ARMAR measurements with the analysis conducted in a composite framework to eliminate measurement noise associated with the case study approach and single element volumes obfuscated by heterogeneous beam filling effects. In diagnosing the performance of the 2a12 algorithm, weaknesses have been found in the cloud-radiation database used to provide microphysical guidance to the algorithm for upper cloud ice microphysics. It is also necessary to adjust a fractional convective rainfall factor within the algorithm somewhat arbitrarily to achieve satisfactory algorithm accuracy.

Smith, Eric A.↗
NASA NTRS2004

A Model for Estimation of Rain Rate on Tropical Land from TRMM Microwave Imager Radiometer Observations

Over the tropical land regions observations of the 85 GHz brightness temperature (T(sub 85v)) made by the TRMM Microwave Imager (TMI) radiometer when analyzed with the help of rain rate (R(sub pR)) deduced from the TRMM Precipitation Radar (PR) indicate that there are two maxima in rain rate. One strong maximum occurs when T(sub 85) has a value of about 220 K and the other weaker one when T(sub 85v) is much colder approx. 150 K. Together with the help of earlier studies based on airborne Doppler Radar observations and radiative transfer theoretical simulations, we infer the maximum near 220 K is a result of relatively weak scattering due to super cooled rain drops and water coated ice hydrometeors associated with a developing thunderstorm (Cb) that has a strong updraft. The other maximum is associated with strong scattering due to ice particles that are formed when the updraft collapses and the rain from the Cb is transit2oning from convective type to stratiform type. Incorporating these ideas and with a view to improve the estimation of rain rate from existing operational method applicable to the tropical land areas, we have developed a rain retrieval model. This model utilizes two parameters, that have a horizontal scale of approx. 20km, deduced from the TMI measurements at 19, 21 and 37 GHz (T(sub 19v), T(sub 21v), T(sub 37v). The third parameter in the model, namely the horizontal gradient of brightness temperature within the 20 km scale, is deduced from TMI measurements at 85 GHz. Utilizing these parameters our retrieval model is formulated to yield instantaneous rain rate on a scale of 20 km and seasonal average on a mesoscale that agree well with that of the PR.

Prabhakara, C.↗
NASA NTRS2005

Combined Radar and Radiometer Analysis of Precipitation Profiles for a Parametric Retrieval Algorithm

A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ice hydrometeor models. The PR path-integrated attenuation (PIA), where available, is further used to adjust DSD in a manner that is similar to the PR operational algorithm. Combined with the TMI-retrieved nonraining geophysical parameters, the three-dimensional structure of the geophysical parameters is obtained across the satellite-observed domains. Microwave brightness temperatures are then computed for a comparison with TMI observations to examine if the radar-retrieved rainfall is consistent in the radiometric measurement space. The inconsistency in microwave brightness temperatures is reduced by iterating the retrieval procedure with updated assumptions of the DSD and ice-density models. The proposed methodology is expected to refine the a priori rain profile database and error models for use by parametric passive microwave algorithms, aimed at the Global Precipitation Measurement (GPM) mission, as well as a future TRMM algorithms.

Masunaga, Hirohiko↗
NASA NTRS2010

Improving a Spectral Bin Microphysical Scheme Using TRMM Satellite Observations

Comparisons between cloud model simulations and observations are crucial in validating model performance and improving physical processes represented in the mod Tel.hese modeled physical processes are idealized representations and almost always have large rooms for improvements. In this study, we use data from two different sensors onboard TRMM (Tropical Rainfall Measurement Mission) satellite to improve the microphysical scheme in the Goddard Cumulus Ensemble (GCE) model. TRMM observed mature-stage squall lines during late spring, early summer in central US over a 9-year period are compiled and compared with a case simulation by GCE model. A unique aspect of the GCE model is that it has a state-of-the-art spectral bin microphysical scheme, which uses 33 different bins to represent particle size distribution of each of the seven hydrometeor species. A forward radiative transfer model calculates TRMM Precipitation Radar (PR) reflectivity and TRMM Microwave Imager (TMI) 85 GHz brightness temperatures from simulated particle size distributions. Comparisons between model outputs and observations reveal that the model overestimates sizes of snow/aggregates in the stratiform region of the squall line. After adjusting temperature-dependent collection coefficients among ice-phase particles, PR comparisons become good while TMI comparisons worsen. Further investigations show that the partitioning between graupel (a high-density form of aggregate), and snow (a low-density form of aggregate) needs to be adjusted in order to have good comparisons in both PR reflectivity and TMI brightness temperature. This study shows that long-term satellite observations, especially those with multiple sensors, can be very useful in constraining model microphysics. It is also the first study in validating and improving a sophisticated spectral bin microphysical scheme according to long-term satellite observations.

Li, Xiaowen↗
NASA NTRS2013

Launch and Assembly Reliability Analysis for Mars Human Space Exploration Missions

NASA s long-range goal is focused upon human exploration of Mars. Missions to Mars will require campaigns of multiple launches to assemble Mars Transfer Vehicles in Earth orbit. Launch campaigns are subject to delays, launch vehicles can fail to place their payloads into the required orbit, and spacecraft may fail during the assembly process or while loitering prior to the Trans-Mars Injection (TMI) burn. Additionally, missions to Mars have constrained departure windows lasting approximately sixty days that repeat approximately every two years. Ensuring high reliability of launching and assembling all required elements in time to support the TMI window will be a key enabler to mission success. This paper describes an integrated methodology for analyzing and improving the reliability of the launch and assembly campaign phase. A discrete event simulation involves several pertinent risk factors including, but not limited to: manufacturing completion; transportation; ground processing; launch countdown; ascent; rendezvous and docking, assembly, and orbital operations leading up to TMI. The model accommodates varying numbers of launches, including the potential for spare launches. Having a spare launch capability provides significant improvement to mission success.

Cates, Grant R.↗
NASA NTRS2015

Tropical Cyclone Diurnal Cycle as Observed by TRMM

Using infrared satellite data, previous work has shown a consistent diurnal cycle in the pattern of cold cloud tops around mature tropical cyclones. In particular, an increase in the coverage by cold cloud tops often occurs in the inner core of the storm around the time of sunset and subsequently propagates outward to several hundred kilometers over the course of the following day. This consistent cycle may have important implications for structure and intensity changes of tropical cyclones and the forecasting of such changes. Because infrared satellite measurements are primarily sensitive to cloud top, the goal of this study is to use passive and active microwave measurements from the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR), respectively, to examine and better understand the tropical cyclone diurnal cycle throughout a larger depth of the storm's clouds. The National Hurricane Center's best track dataset was used to extract all PR and TMI pixels within 1000 km of each tropical cyclone that occurred in the Atlantic basin between 1998-2011. Then the data was composited according to radius (100-km bins from 0-1000 km) and local standard time (LST; 3-hr bins). Specifically, PR composites involved finding the percentage of pixels with reflectivity greater than or equal to 20 dBZ at various heights (i.e., 2-14 km in increments of 2 km) as a function of radius and time. The 37- and 85- GHz TMI channels are especially sensitive to scattering by precipitation-sized ice in the mid to upper portions of clouds. Hence, the percentage of 37- and 85-GHz polarization corrected temperatures less than various thresholds were calculated using data from all storms as a function of radius and time. For 37 GHz, thresholds of 260 K, 265 K, 270 K, and 275 K were used, and for 85 GHz, thresholds of 200-270 K in increments of 10 K were utilized. Note that convection forced by the interactions of a tropical cyclone with land (e.g., due to frictional convergence) may disrupt the natural convective cycle of a cyclone. Hence, only data pertaining to storms whose centers were greater than 300 km from land were included in the composites. Early results suggest the presence of a diurnal cycle in the PR composites of all Atlantic basin tropical cyclones from a height of 2-12 km from approximately 0-400 km radius, but the cycle is most apparent above 6 km. At a height of 8 km, there is a peak (minimum) in the percentage of PR pixels greater than or equal to 20 dBZ near 0 (21) LST in the inner core with some indication that this signal propagates outward with time. In contrast, the 37- and 85-GHz composites show little indication of a diurnal cycle at any radii, regardless of the threshold used. Ongoing work with this project will involve sub-setting the composites according to storm intensity to see if the diurnal cycle varies with storm strength. Moderate to strong vertical wind shear often leads to asymmetries in tropical cyclone convection and may disrupt the cyclone's natural diurnal cycle. Therefore, wind shear thresholds will be applied to the composites to determine if the diurnal cycle becomes more apparent in a low shear environment. Finally, other work to be completed will involve developing composites for other tropical cyclone basins, including the East Pacific, Northwest Pacific, South Pacific, and Indian Ocean.

tropical cyclones↗
NASA NTRS2015

A Prototype Hail Detection Algorithm and Hail Climatology Developed with the Advanced Microwave Sounding Unit (AMSU)

In previous studies published in the open literature, a strong relationship between the occurrence of hail and the microwave brightness temperatures (primarily at 37 and 85 GHz) was documented. These studies were performed with the Nimbus‐7 SMMR, the TRMM Microwave Imager (TMI) and most recently, the Aqua AMSR‐E sensor. This lead to climatologies of hail frequency from TMI and AMSR‐E, however, limitations include geographical domain of the TMI sensor (35 S to 35 N) and the overpass time of the Aqua satellite (130 am/pm local time), both of which reduce an accurate mapping of hail events over the global domain and the full diurnal cycle. Nonetheless, these studies presented exciting, new applications for passive microwave sensors. Since 1998, NOAA and EUMETSAT have been operating the AMSU‐A/B and the MHS on several operational satellites: NOAA‐15 through NOAA‐19; MetOp‐A and ‐B. With multiple satellites in operation since 2000, the AMSU/MHS sensors provide near global coverage every 4 hours, thus, offering a much larger time and temporal sampling than TRMM or AMSR‐E. With similar observation frequencies near 30 and 85 GHz and additionally three at the 183 GHz water vapor band, the potential to detect strong convection associated with severe storms on a more comprehensive time and space scale exists. In this study, we develop a prototype AMSU‐based hail detection algorithm through the use of collocated satellite and surface hail reports over the continental U.S. for a 12‐year period (2000‐2011). Compared with the surface observations, the algorithm detects approximately 40 percent of hail occurrences. The simple threshold algorithm is then used to generate a hail climatology that is based on all available AMSU observations during 2000‐11 that is stratified in several ways, including total hail occurrence by month (March through September), total annual, and over the diurnal cycle. Independent comparisons are made compared to similar data sets derived from other satellite, ground radar and surface reports. The algorithm was also applied to global land measurements for a single year and showed close agreement with other satellite based hail climatologies. Such a product could serve as a prototype for use with a future geostationary based microwave sensor such as NASA's proposed PATH mission.

Ferraro, Ralph↗
NASA NTRS2017

Evaluation of APREQCFR Coordination Procedures for Charlotte Douglas International Airport

NASA has been collaborating with the Federal Aviation Administration (FAA) and aviation industry partners to develop and demonstrate new concepts and technologies for the Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the goal of The IADS capabilities in the ATD-2 project is to increase predictability and increase throughput via improving TMI compliance. The IADS capabilities that will impact TMI compliance are built upon previous NASA research, the Precision Departure Release Capability (PDRC). The proposed paper will evaluate the APREQCFR process between ATC Tower and Center and information sharing between ATC Tower and the airline Ramp tower. Subjective measures collected from the HITL surveys (e.g., workload, situational awareness, acceptability, usability) and performance metrics such as TMI, TMAT, and pushback advisory compliance from APREQCFR flights and will be reported.

APREQ scheduling↗
NASA NTRSDate not supplied

Predicting Air Traffic Management Initiatives Using Supervised Learning

Terminal Traffic Management Initiatives (TMIs) such as Ground Stops (GS) and Ground Delay Programs (GDP) are implemented to manage excess demand or lowered capacity at an airport. Air Traffic Flow Management (TFM) specialists identify situations such as aviation constraints, current and forecasted weather conditions, airport demand and capacity, and initiate TMIs for safe and orderly movement of air traffic. In this paper, we outline supervised learning techniques that can be used to predict and recommend TMIs at an airport based on current weather and airport conditions. Our research involves building classic Machine Learning (ML) models such as Logistic Regression, K-Nearest Neighbor, Random Forest and XGBoost, as well as Long short-term memory (LSTM) networks. We trained the models on 3-year historical data (weather, airport demand, capacity and TMIs) from Newark (EWR) airport which was selected based on its higher TMI implementation rates and varied weather conditions. Although Random Forest and XGBoost algorithms are able to predict if a TMI is needed or not, they have difficulty in predicting specific program type. For this purpose, we found that LSTM time-series forecasting models performed better as they also learn from past TMI program type sequences. This study also lays down the foundation for advanced modeling techniques and architectures to predict TMIs in advance for future periods. The ability to predict TMIs in advance will be highly beneficial to the traffic controllers and managers as this will help them to prepare for and manage TMIs more efficiently.

Manoj Agrawal↗
DOE OSTI2025

The relative importance of building design parameters in reducing energy use and sensible heat release from buildings in light of forecasted future weather data and building coverage ratio

Buildings typically have a 60-to-75-year lifespan before they require significant maintenance or modifications. However, most builders evaluate the performance of their new buildings using whole-building energy simulation tools based on the current typical meteorological year (TMY) file or actual meteorological year. The energy use consumption and sensible heat release pattern observed from buildings could potentially change based on shifting global climates. Therefore, the recommended energy-efficiency design parameters might also change during these periods. In this study, we evaluate the role of different building design parameters, such as material reflectivity, HVAC COP, and insulation values, on building energy usage and sensible heat release from buildings with different building coverage ratios (BCR), based on the current and future weather file TMY (fTMY) for the middle of the century (2040–2060). The role of sensible heat release from buildings is not accounted for accurately while estimating building energy usage in most whole-building energy simulations. The study conducts a series of whole-building energy simulation analyses using EnergyPlus to evaluate the role of different design parameters based on TMY and fTMY weather conditions. The analysis is conducted for two hot desert climatic cities: Phoenix (USA) and Abu Dhabi (UAE). The results show that, for the base case in a future climate, the sensible heat release is reduced by an average of 30% due to the reduced delta T between the surface and ambient air. Further, the results show an increase in total energy consumption by 5% annually. The results also show that, for buildings with traditional coatings, shorter buildings release more heat than taller buildings. On the other hand, for buildings with reflective paints, shorter buildings release less heat than taller buildings. The findings from this study can be used by policymakers, utility companies, and builders to better understand the relative role of different building design parameters while constructing new and retrofitting existing buildings.

Alhazmi, Mansour [King Fahd University of Petroleu↗
NASA NTRS2016

TRMM Data Improvement as Part of the GPM Data Processing

NASA has a long standing commitment to the improvement of its mission datasets. Indeed, data reprocessing is always built into the plans, schedule and budget for the mission data processing system. However, in addition to these ongoing mission reprocessing, NASA also supports a final reprocessing of all the data for a mission upon its completion (known as Phase F). TRMM Phase F started with the end of the TRMM mission in June of 2015. This last reprocessing has two overall goals: improvement of the TRMM mission data products; incorporation of the 17+ years of TRMM data into the ongoing NASA/JAXA GPM data processing. The first goal guarantees that the latest algorithms used for precipitation retrievals will also be used in reprocessing the TRMM data. The second goal ensures that as GPM algorithms are improved, the entire TRMM data will always be reprocessed with each GPM reprocessing. In essence TRMM becomes another of the GPM constellation satellites. This paper will concentrate on presenting the improvements to TMI level 1 data including calibration, geolocation, and emissive antenna corrections. It will describe the format changes that will occur how the TMI level 1C product will be intercalibrated using GMI as the reference calibration. It will also provide an overview of changes in the precipitation radar products as well as the combined TMIPR product.

GPM↗
DOE OSTI2026

AutoBEM: A scalable framework for nationwide building energy simulation and retrofit evaluation in the United States

This paper presents AutoBEM, an integrated, automated framework for nationwide building energy modeling and retrofit evaluation in the United States. Unlike prior UBEM platforms that either rely primarily on representative stock sampling or operate at city scale, AutoBEM automates the generation of building-resolved, physics-based EnergyPlus/OpenStudio simulation models at national scale using GIS-derived geometry, prototype-based assumptions, and standardized scalable workflows. Leveraging the Model America dataset and high-performance computing, AutoBEM generates and simulates energy models for 122.9 million buildings, representing 97.8% of the U.S. building stock. These models are being made publicly and freely available as the Model America v1.0 (MAv1) dataset. AutoBEM supports detailed, building-level assessments of energy consumption, CO2 emissions, and post-processed anthropogenic heat emissions (AHE), and evaluates 151 energy conservation measures (ECMs) using localized utility pricing and building characteristics. In addition, AutoBEM incorporates both typical and future climate conditions through integration with Typical Meteorological Year (TMY) and Future TMY (fTMY) weather data derived from IPCC scenarios. In a case study of Phoenix, Arizona, AutoBEM identified several high-efficiency HVAC upgrades and selected envelope measures with short modeled payback periods (1.5 years) for certain building types and standards. Simulations under future climate scenarios (SSP5–RCP8.5) project an 11.3% increase in electricity use and a 32% reduction in natural gas demand by 2100, underscoring the need for climate-adaptive retrofit planning. By enabling reproducible, bottom-up, and location-specific analysis at scale, AutoBEM provides a step toward a national digital twin of the built environment and supports data-driven screening and planning for decarbonization, resilience, and energy equity.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2021

Further Investigations of Racemic and Chiral Molecular Sieves of the STW Topology

Large single crystals of pure-silica STW-type molecular sieves are prepared using 1,2,3,4,5-pentamethylimidazolium (12345PMI) and 2-ethyl-1,3,4-trimethylimidazolium (2E134TMI) as organic structure-directing agents (OSDAs) and α-amino acid additives. The effects of the amount and type of amino acid on the crystallization of pure-silica STW materials are investigated. Room-temperature single-crystal X-ray diffractometry shows that 12345PMI better fits the STW cage than 2E134TMI and is fully consistent with computed simulations. The synthesis of an enantioenriched R-STW-type molecular sieve having a Si/Ge ratio of 2.2 is achieved using a chiral, dicationic OSDA that contains two stereocenters. Furthermore, the conformation of the chiral OSDA in the chiral framework has been obtained from a Rietveld refinement using synchrotron powder diffraction data and is the first structure refinement of an enantioenriched, inorganic molecular sieve prepared from a pure, asymmetric OSDA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Stability of the modulator in a plasma-modulated plasma accelerator

We explore the regime of operation of the modulator stage of a recently proposed laser-plasma accelerator scheme [Phys. Rev. Lett. 127, 184801 (2021)], dubbed the plasma-modulated plasma accelerator (P-MoPA). The P-MoPA scheme offers a potential route to high-repetition-rate, GeV-scale plasma accelerators driven by picosecond-duration laser pulses from, for example, kilohertz thin-disk lasers. The first stage of the P-MoPA scheme is a plasma modulator in which a long, high-energy “drive” pulse is spectrally modulated by copropagating in a plasma channel with the low-amplitude plasma wave driven by a short, low-energy “seed” pulse. The spectrally modulated drive pulse is converted to a train of short pulses, by introducing dispersion, which can resonantly drive a large wakefield in a subsequent accelerator stage with the same on-axis plasma density as the modulator. In this paper we derive the 3D analytic theory for the evolution of the drive pulse in the plasma modulator and show that the spectral modulation is independent of transverse coordinate, which is ideal for compression into a pulse train. We then identify a transverse mode instability (TMI), similar to the TMI observed in optical fiber lasers, which sets limits on the energy of the drive pulse for a given set of laser-plasma parameters. We compare this analytic theory with particle-in-cell (PIC) simulations and find that even higher energy drive pulses can be modulated than those demonstrated in the original proposal.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Development of the Contamination Distribution Centered Toxics Mobility Vulnerability Index in the Beaumont–Port Arthur Region of Texas

This study advances the Toxics Mobility Inventory (TMI) and the Toxics Mobility Vulnerability Index (TMVI) to develop a new tool to assess the movement of hazardous substances and their implications for vulnerable communities. It emphasizes the need to include contamination distribution variables in such indices to address disproportionate impacts and more accurately reflect vulnerability. The study uses the TMI framework and TMVI methodology in the Beaumont–Port Arthur region of Texas, also integrating contamination distribution considerations into the analysis to develop a new framework and process. The new Contamination Distribution Centered Toxics Mobility Vulnerability Index (CDC-TMVI) consolidates climate change and topography variables into a broader built environment vulnerability category while introducing a contamination sources category. Using ArcGIS Pro and ToxPi tools, the study evaluates 27 geospatial variables across four categories: built environment vulnerability, social vulnerability, health outcomes, and contamination sources. The results indicate significant contributions from contamination and social vulnerability variables, highlighting areas with higher risks of flooding and air pollution. This article advocates for future research and policy efforts to enhance the integration of contamination sources and their spatial distributions into toxics mobility assessments to better protect vulnerable populations. Furthermore, the unique methodology and findings serve as a basis for developing targeted measures and strategic planning to improve environmental health.

contamination↗
DOE OSTI2025

Investigating Building Energy Consumption and CO2 Emission in Phoenix Using AutoBEM and Future Typical Meteorological Year (fTMY) Weather Data

This research investigates the energy performance and CO2 emissions of each building stock across the Phoenix metropolitan area using the Automatic Building Energy Modeling (AutoBEM) framework and Model America v2 (MAv2) dataset from Oak Ridge National Laboratory (ORNL). Typical Meteorological Year (TMY) and Future Typical Meteorological Year (fTMY) files were used for AutoBEM simulation. The simulation results from TMY and fTMY were compared. It was found that a projected 10.28% increase in total CO2 emissions and a 9.30% rise in total energy consumption by 2080–2099 relative to current typical conditions. The results highlight the disparities in emissions among different building stocks and the influence of climate change on future energy demand. The findings underscore the necessity of targeted policy interventions and retrofitting strategies (eg. advanced HVAC systems, improved insulation, reflective roofing) to mitigate emissions in high-energy-use and emission-intensed buildings, particularly as climate conditions evolve. This study contributes to the growing understanding of building-sector emissions and their long-term implications under future climate scenarios.

Li, Hang [ORNL] (ORCID:0000000306001920)↗