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At least 253 records · Page 14

LandScan Mosaic Rapid Population Update: Jamaica After Hurricane Melissa (V1)

During a natural disaster such as Hurricane Melissa, understanding where people are located is critical for situational awareness, operational planning and humanitarian support and consequence assessment. Traditional population datasets focus on mapping populations based on residential, or "business-as-usual" scenarios. However, natural disasters can create disruptions in daily routines of population in addition to the magnitude of the population displacement, depending on the type, duration, context, and location of the event. The Geospatial Science and Human Security Division at Oak Ridge National Laboratory (ORNL) produced this latest LandScan Mosaic Rapid Population Update for Jamaica following Hurricane Melissa, a category 5 hurricane that made landfall on Jamaica on October 28 2025. This Rapid Population Update captures the immediate population displacement following the hurricane using a combination of open-source building damage assessment data from Microsoft, flood exposure data from the Global Flood Monitoring service, reported population displacement information, and humanitarian shelter locations from the Jamaican Office of Disaster Preparedness and Emergency Management and the underlying LandScan Mosaic Jamaica as a base population.

97 MATHEMATICS AND COMPUTING↗

Summary of Expansions and Updates in R&D GREET® 2025

The research and development (R&D) version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model, or R&D GREET, is developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in all transportation sub-sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy technology systems. Argonne has expanded and updated the model in many areas in R&D GREET 2025. This report provides a summary of the expansions and updates. R&D GREET is designed as an attributional LCA model, but specific consequential effects for certain pathways are included by default when they are scientifically important and/or highly policy relevant. For example, two major consequential elements – induced land use change (ILUC) for biofuels and avoided emissions for certain RNG-based pathways – are implemented by default in R&D GREET because they are highly relevant to our user base and crucial for a comprehensive evaluation of the environmental effects of these technologies. In a future version of R&D GREET, these consequential elements for biofuels and RNG could be more clearly distinguished from core attributional results. We will consider adding a highly visible toggle that would allow users to turn off or adjust these consequential impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Summer 2025 Solar Industry Update [Slides]

Each quarter, NREL conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.

14 SOLAR ENERGY↗

Fall 2025 Solar Industry Update [Slides]

Each quarter, the National Laboratory of the Rockies conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.

14 SOLAR ENERGY↗

Core Model Proposal #338: Regional Forest Markets and Crop Trade Updates

The main purpose of this proposal is to update the forest (i.e., Roundwood) trade modeling in GCAM from HOV (Heckscher-Ohlin Vanek) based fully integrated world market to segmented regional markets using the logit-based Armington approach. We also improve agricultural trade-related data, update trade (Armington) parameters based on literature information, and allow elastic forest demand responses. This CMP is an extension of previous GCAM agricultural trade CMPs (289 & 312).

99 GENERAL AND MISCELLANEOUS↗

Updating and Evaluating Anthropogenic Emissions for NOAA’s Global Ensemble Forecast Systems for Aerosols (GEFS-Aerosols): Application of an SO 2 Bias-Scaling Method

We updated the anthropogenic emissions inventory in NOAA’s operational Global Ensemble Forecast for Aerosols (GEFS-Aerosols) to improve the model’s prediction of aerosol optical depth (AOD). We used a methodology to quickly update the pivotal global anthropogenic sulfur dioxide (SO 2 ) emissions using a speciated AOD bias-scaling method. The AOD bias-scaling method is based on the latest model predictions compared to NASA’s Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2). The model bias was subsequently applied to the CEDS 2019 SO 2 emissions for adjustment. The monthly mean GEFS-Aerosols AOD predictions were evaluated against a suite of satellite observations (e.g., MISR, VIIRS, and MODIS), ground-based AERONET observations, and the International Cooperative for Aerosol Prediction (ICAP) ensemble results. The results show that transitioning from CEDS 2014 to CEDS 2019 emissions data led to a significant improvement in the operational GEFS-Aerosols model performance, and applying the bias-scaled SO 2 emissions could further improve global AOD distributions. The biases of the simulated AODs against the observed AODs varied with observation type and seasons by a factor of 3~13 and 2~10, respectively. The global AOD distributions showed that the differences in the simulations against ICAP, MISR, VIIRS, and MODIS were the largest in March–May (MAM) and the smallest in December–February (DJF). When evaluating against the ground-truth AERONET data, the bias-scaling methods improved the global seasonal correlation (r), Index of Agreement (IOA), and mean biases, except for the MAM season, when the negative regional biases were exacerbated compared to the positive regional biases. The effect of bias-scaling had the most beneficial impact on model performance in the regions dominated by anthropogenic emissions, such as East Asia. However, it showed less improvement in other areas impacted by the greater relative transport of natural emissions sources, such as India. The accuracies of the reference observation or assimilation data for the adjusted inputs and the model physics for outputs, and the selection of regions with less seasonal emissions of natural aerosols determine the success of the bias-scaling methods. A companion study on emission scaling of anthropogenic absorbing aerosols needs further improved aerosol prediction.

54 ENVIRONMENTAL SCIENCES↗

The K2 and TESS Synergy. I. Updated Ephemerides and Parameters for K2-114, K2-167, K2-237, and K2-261

Although the Transiting Exoplanet Survey Satellite (TESS) primary mission observed the northern and southern ecliptic hemispheres, generally avoiding the ecliptic, and the Kepler space telescope during the K2 mission could only observe near the ecliptic, many of the K2 fields extend far enough from the ecliptic plane that sections overlap with TESS fields. Using photometric observations from both K2 and TESS, combined with archival spectroscopic observations, we globally modeled four known planetary systems discovered by K2 that were observed in the first year of the primary TESS mission. Specifically, we provide updated ephemerides and system parameters for K2-114 b, K2-167 b, K2-237 b, and K2-261 b. These were some of the first K2 planets to be observed by TESS in the first year and include three Jovian sized planets and a sub-Neptune with orbital periods less than 12 days. In each case, the updated ephemeris significantly reduces the uncertainty in prediction of future times of transit, which is valuable for planning observations with the James Webb Space Telescope and other future facilities. The TESS extended mission is expected to observe about half of the K2 fields, providing the opportunity to perform this type of analysis on a larger number of systems.

79 ASTRONOMY AND ASTROPHYSICS↗

A More Precise Measurement of the Radius of PSR J0740+6620 Using Updated NICER Data

PSR J0740+6620 is the neutron star with the highest precisely determined mass, inferred from radio observations to be 2.08 ± 0.07 M ⊙ . Measurements of its radius therefore hold promise to constrain the properties of the cold, catalyzed, high-density matter in neutron star cores. Previously, Miller et al. and Riley et al. reported measurements of the radius of PSR J0740+6620 based on Neutron Star Interior Composition Explorer (NICER) observations accumulated through 2020 April 17, and an exploratory analysis utilizing NICER background estimates and a data set accumulated through 2021 December 28 was presented in Salmi et al. Here we report an updated radius measurement, derived by fitting models of X-ray emission from the neutron star surface to NICER data accumulated through 2022 April 21, totaling ~1.1 Ms additional exposure compared to the data set analyzed in Miller et al. and Riley et al., and to data from XMM-Newton observations. We find that the equatorial circumferential radius of PSR J0740+6620 is ${12.92}_{-1.13}^{+2.09}$ km (68% credibility), a fractional uncertainty ~83% the width of that reported in Miller et al., in line with statistical expectations given the additional data. If we were to require the radius to be less than 16 km, as was done in Salmi et al., then our 68% credible region would become $R={12.76}_{-1.02}^{+1.49}$ km, which is close to the headline result of Salmi et al. Our updated measurements, along with other laboratory and astrophysical constraints, imply a slightly softer equation of state than that inferred from our previous measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open-data, open-science approach, is to make annually updated reliable global climate indicators available in the public domain. As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO 2 e yr -1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO 2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.

54 ENVIRONMENTAL SCIENCES↗

Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1)

Abstract. The Community Atmosphere Model (CAM6.1), the atmospheric component of the Community Earth System Model (CESM; version 2.1), simulates the life cycle (emission, transport, and deposition) of mineral dust and its interactions with physio-chemical components to quantify the impacts of dust on climate and the Earth system. The accuracy of such quantifications relies on how well dust-related processes are represented in the model. Here we update the parameterizations for the dust module, including those on the dust emission scheme, the aerosol dry deposition scheme, the size distribution of transported dust, and the treatment of dust particle shape. Multiple simulations were undertaken to evaluate the model performance against diverse observations, and to understand how each update alters the modeled dust cycle and the simulated dust direct radiative effect. The model–observation comparisons suggest that substantially improved model representations of the dust cycle are achieved primarily through the new more physically-based dust emission scheme. In comparison, the other modifications induced small changes to the modeled dust cycle and model–observation comparisons, except the size distribution of dust in the coarse mode, which can be even more influential than that of replacing the dust emission scheme. We highlight which changes introduced here are important for which regions, shedding light on further dust model developments required for more accurately estimating interactions between dust and climate.

54 ENVIRONMENTAL SCIENCES↗

Winter 2026 Solar and Storage Industry Update

Each quarter, the Nationa Laboratory of the Rockies conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.

14 SOLAR ENERGY↗

DEPRECATED - State Policies and Programs for Community Solar (2024 Q2 Update)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/249 The purpose of this dataset is to summarize current community solar policies and low-income stipulations by the state in the United States as of April 2024. This list has been reviewed, but errors may exist, and the list may not be comprehensive. NREL invites input to update or add to the database. To submit updates, additions, or corrections please find contact information on the current data set page linked above.

14 SOLAR ENERGY↗

DEPRECATED - State Policies and Programs for Community Solar (2024 Q3 Update)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nlr.gov/submissions/249 The purpose of this dataset is to summarize current community solar policies and low-income stipulations by state in the United States as of June 2024. The "State_Program" sheet summarizes the key policy details for each state. This list has been reviewed, but errors may exist, and the list may not be comprehensive. NREL invites input to update or add to the database. To submit updates, additions, or corrections please find contact information on the current data set page linked above.

14 SOLAR ENERGY↗

Updating inertial navigation systems with VOR/DME information.

Demonstration that updating an inertial navigation system (INS) with VOR/DME information (from one or two stations) by means of a maximum-likelihood filter results in substantial improvements in navigational accuracy over that obtained by the use of a single VOR/DME (current practice). When continuously updating, the use of a high-quality INS (0.01 deg/hr gyro drift) instead of a low-quality INS (1.0 deg/hr gyro drift) does not substantially improve position accuracy. In-flight alignment (or realignment) of an INS to an accuracy comparable to that of ground alignment can be accomplished by using two DMEs. Several reduced-order suboptimal filters were found to perform nearly optimally.

Bobick, J. C.↗

Modification and updating of the Manned Activity Scheduling System (MASS) for shuttle and shuttle payloads analysis. Volume 1: Model specifications

The LRC MASS was modified and updated to include logic for efficient analysis of space shuttle payload operations. All MASS computer models were reviewed for compatibility with, and applicability to, the shuttle sortie mission. The MASS modification efforts were concentrated on two computer programs, the general scheduling model (GSM) and one day model (ODM). A new computer program, the DAYLIB Tape Processor, was developed to update the link between the GSM and ODM. The resulting MASS is an operationally efficient analytical tool that will allow a rapid assessment of shuttle and shuttle payload operations.

Ring, R. C.↗

Updating coastal and navigational charts using ERTS-1 data

A successful processing algorithm for extracting water depth information from ERTS data has been developed. Depth charts for two geographical areas have been constructed representing different solar illumination and water transparency conditions. Absolute depth calculations for water depth to 4.5 fathoms have been demonstrated for the Little Bahama Bank. Depth Charts also were constructed using data in Band 4 and 5 of the ERTS-1 MSS for areas in Lake Michigan. This data represented a low sun angle, poor light transmission in water conditions and gave useful results to 200 meters. In both cases, the ERTS map represented an update in shallow water detail in comparison with available navigation charts for the areas tested. Present processing costs to provide MSS depth charts are estimated to be on the order of $1.50 per sq. mile. The updating of navigation charts for areas hazardous to shipping is an achievable direct application.

Polcyn, F. C.↗

A 30-day forecast experiment with the GISS model and updated sea surface temperatures

The GISS model was used to compute two parallel global 30-day forecasts for the month January 1974. In one forecast, climatological January sea surface temperatures were used, while in the other observed sea temperatures were inserted and updated daily. A comparison of the two forecasts indicated no clear-cut beneficial effect of daily updating of sea surface temperatures. Despite the rapid decay of daily predictability, the model produced a 30-day mean forecast for January 1974 that was generally superior to persistence and climatology when evaluated over either the globe or the Northern Hemisphere, but not over smaller regions.

Spar, J.↗

On the computation and updating of the modified Cholesky decomposition of a covariance matrix

Methods for obtaining and updating the modified Cholesky decomposition (MCD) for the particular case of a covariance matrix when one is given only the original data are described. These methods are the standard method of forming the covariance matrix K then solving for the MCD, L and D (where K=LDLT); a method based on Householder reflections; and lastly, a method employing the composite-t algorithm. For many cases in the analysis of remotely sensed data, the composite-t method is the superior method despite the fact that it is the slowest one, since (1) the relative amount of time computing MCD's is often quite small, (2) the stability properties of it are the best of the three, and (3) it affords an efficient and numerically stable procedure for updating the MCD. The properties of these methods are discussed and FORTRAN programs implementing these algorithms are listed.

Vanrooy, D. L.↗