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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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Megafires are increasing in the Western US due to sustained drought and prolonged fire exclusion. LANL uniquely positioned to lead in both modeling (fine scales, coupled fire-atmosphere, 3D fuels) and observations (CAFÉ).
With its mountain-to-coast hydroclimate, strong influence of Pacific Ocean weather systems and climate patterns, and unique land use history with strong rural-to-urban gradients, the Puget Sound region is a natural laboratory for studying a number of complex processes in, and interactions among, different Earth and human systems. A 1-year scoping study was initiated by the Earth and Environmental Systems Modeling program of the Department of Energy’s Office of Science Biological and Environmental Research. It was intended to elucidate and highlight the rich opportunities Puget Sound offers to advance our understanding of and ability to simulate Earth system changes and human-Earth system interactions. A literature review, multi-day community workshop, and external input were used to develop this scoping study report. The report first summarizes scientific understanding and knowledge gaps associated with major regional systems, including atmosphere and climate, the land surface, coastal and marine processes, and human systems, as well as how these systems are changing over time. It then highlights some of the most notable extreme events in the region, including heat waves, atmospheric rivers, droughts, and wildfires. Finally, key research opportunities for Earth and environmental systems modeling in, above, and around Puget Sound are highlighted.
Weather and climate extremes are increasingly occurring in the Arctic. Here, in this Review, we evaluate historical and projected changes in rare Arctic extremes across the atmosphere, cryosphere and ocean and elucidate their driving mechanisms. Clear shifts occur in mean and extreme distributions after ~2000. For instance, pre-2000 to post-2000 observational probabilities of 1.5 standard deviation events increase by 20% for atmospheric heat waves, 76.7% for Atlantic layer warm events, 83.5% for Arctic sea ice loss and 62.9% for Greenland Ice Sheet melt extent — in many cases, low probability, rare extreme events in the early period become the norm in the latter period. These observed changes can be explained using a ‘pushing and triggering’ concept, representing interplay between external forcing and internal variability: long-term warming destabilizes the climate system and ‘pushes’ it to a new state, allowing subsequent variability associated with large-scale atmosphere–ocean–ice interactions and synoptic systems to ‘trigger’ extreme events over different timescales. Ongoing anthropogenic warming is expected to further increase the frequency and magnitude of extremes, such that simulated probabilities of 1.5 standard deviation events increase by 72.6% for atmospheric heat waves, 68.7% for Atlantic layer warm events and 93.3% for Greenland Ice Sheet melt rate between historic (1984–2014) and future (2069–2099) periods under a very high emission scenario. Future research should prioritize the development of physically based metrics, enhance high-resolution observation and modelling capabilities and improve understanding of multiscale Arctic climate drivers.
This dataset contains simple condensation mdoel output and CAM4 model output that were used to produce figures in the following paper: Wan, H., Woodward, C. S., Zhang, S., Vogl, C. J., Stinis, P., Gardner, D. J., Rasch, P. J., Zeng, X., Larson, V. E., and Singh, B. (2020): Improving time-step convergence in an atmosphere model with simplified physics: the impacts of closure assumption and process coupling, Journal of Advances in Modeling Earth Systems, https://doi.org/10.1029/2019MS001982
The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility supports atmospheric science through an integrated network of fixed and mobile observatories. These facilities collect continuous and campaign-based observations of atmospheric properties, with the goal of improving the representation of clouds, aerosols, precipitation, and radiation in Earth system models. The Bankhead National Forest (BNF) site, established as an ARM Mobile Facility (AMF) on 1 October 2024, is situated in a forested region of northern Alabama. Its strategic location in a southeastern U.S. environment characterized by complex terrain, diverse land cover, and frequent convective storms provides a valuable opportunity to examine coupled land-atmosphere processes under natural variability.
This mosaic of visible to shortwave infrared (VSWIR) data was derived from the assignable asset NEON AOP radiance data that was collected by LBNL’s Watershed Function SFA during the summer of 2018 (DOI: 10.15485/1617204). This atmospheric correction was completed to take into account site-specific terrain variability in the 334 km2 survey area centered around Crested Butte, CO. The atmospheric correction was completed using ACORN atmospheric correction software executed on 200 x 200 pixel kernels rather than line by line in order to capture local flight altitude conditions. Manual cloud delineation removed any small shaded areas that occurred within the data collection areas. Mosaics were developed based on preference for days that were in close timing proximity to the coincident ground campaign and with mosaicing criteria that minimized the angle between the sun and the sensor to retrieve the most consistent reflectance (min_phase_refl_tiled). Finally, we generated shade masks based on the geometry between the sun angle at time of flight, the ground surface, and the sensor. Here we provide the orthomosaiced estimated reflectance data (min_phase_refl_tiled.tif), canopy water content (wtrl), estimated atmospheric water vapor (wtrv), the observational data (obs) for this particular mosaic, the estimated visibility (vis), shade masks derived from the digital surface elevation model (shade) and the digital terrain model (shade_tch) added to the canopy height model (DOI: 10.15485/1617203), and a wavelength metadata file. Each image file is provided as a GeoTiff with internal tiling and LZW compression. These data can also be found on Google Earth Engine for extraction, download, and analysis of smaller extents (Google Earth Engine data is linked in external link table).
Mapping thermal anisotropy across global lands is critical for advancing a wide range of Earth science studies. However, a comprehensive understanding of global thermal anisotropy intensity (TAI) and its governing factors remains missing. We introduce a novel data-driven methodology to quantify global TAI exclusively using multi-angle MODIS land surface temperature time series observations. Our analysis reveals distinct seasonal and diurnal TAI patterns, with global mean summertime TAI exceeding 2.9°C. Furthermore, we identify strong associations between TAI and key surface and atmospheric parameters, such as leaf area index and downward shortwave radiation. Our findings advocate for a paradigm shift from model-based to data-driven approaches in correcting thermal anisotropy, thereby addressing a critical bottleneck in Earth observation.
This report describes the research results and products stemming from the funding award DE-SC0018221. The main goals of this project were to develop a quantitative understanding of the factors driving secondary organic aerosol (SOA) formation from biogenic volatile organic compounds, namely isoprene and monoterpenes, using a combination of laboratory measurements, field data analysis, and modeling. Specifically, we aimed to: 1) develop an observationally constrained volatility distribution of trace gases produced from the oxidation of biogenic hydrocarbons that can explain the formation of SOA from in situ observations made during DOE ASR/ARM field campaigns such as HI-SCALE and BAECC 2) use new and existing (e.g. DOE ASR funded SOAFFEE experiments) laboratory chamber experiments to develop detailed parameterizations of isoprene-derived epxoy diol (IEPOX) reactive uptake, including product branching, product volatility, and solubility constants, as well as SOA formation generally from the formation of highly oxygenated organic molecules (HOM) formed from isoprene and monoterpene photo-oxidation that can be directly incorporated into models. 3) collaborate with PNNL modeling teams to incorporate new parameterizations into detailed box models, such as MOSAIC, and regional or Earth System models such as WRF.
Fire is the primary form of terrestrial ecosystem disturbance on a global scale and an important Earth system process. Most Earth system models (ESMs) have incorporated fire modeling, with 19 of them submitting model outputs of fire-related variables to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study provides the first comprehensive evaluation of CMIP6 historical fire simulations by comparing them with multiple satellite-based products and charcoal-based historical reconstructions. Our results show that most CMIP6 models simulate the present-day global burned area and fire carbon emissions within the range of satellite-based products. They also capture the major features of observed spatial patterns and seasonal cycles, the relationship of fires with precipitation and population density, and the influence of the El Niño–Southern Oscillation (ENSO) on the interannual variability of tropical fires. Regional fire carbon emissions simulated by the CMIP6 models from 1850 to 2010 generally align with the charcoal-based reconstructions, although there are regional mismatches, such as in southern South America and eastern temperate North America prior to the 1910s and in temperate North America, eastern boreal North America, Europe, and boreal Asia since the 1980s. The CMIP6 simulations have addressed three critical issues identified in CMIP5: (1) the simulated global burned area being less than half of that of the observations, (2) the failure to reproduce the high burned area fraction observed in Africa, and (3) the weak fire seasonal variability. Furthermore, the CMIP6 models exhibit improved accuracy in capturing the observed relationship between fires and both climatic and socioeconomic drivers and better align with the historical long-term trends indicated by charcoal-based reconstructions in most regions worldwide. However, the CMIP6 models still fail to reproduce the decline in global burned area and fire carbon emissions observed over the past 2 decades, mainly attributed to an underestimation of anthropogenic fire suppression, and the spring peak in fires in the Northern Hemisphere midlatitudes, mainly due to an underestimation of crop fires. In addition, the model underestimates the fire sensitivity to wet–dry conditions, indicating the need to improve fuel wet-ness estimation. Based on these findings, we present specific guidance for fire scheme development and suggest a postprocessing methodology for using CMIP6 multi-model outputs to generate reliable fire projection products.
Africa is increasingly being exposed to the negative impacts of climate and environmental change, while having less capacity to respond compared to other continents. The vulnerability partially results from unprecedented demographic growth, urbanization, and industrialization. However, the continent has still largely been underserved by the broader Earth System Science (ESS) community, as evidenced by the limited amount of ESS data and research that cover Africa compared to other areas of the world. Here we present the recent University Corporation for Atmospheric Research (UCAR) Africa Initiative that aims to enhance environmental sustainability in Africa by fostering international collaborative research partnerships co-led by African scientists. Specifically, we outline urgent challenges and opportunities identified through an international workshop in six areas of ESS namely (1) air quality and health, (2) weather, (3) climate, (4) land and water, (5) social science perspectives, and (6) developing equitable collaboration and sustainable infrastructure. We highlight examples of successful partnerships and conclude with recommendations to advance collaborative, actionable ESS research that addresses Africa’s critical environmental challenges.
Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. Here, we found that higher values of RH (up to 40%) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30% maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physically-based predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling.
Earth’s energy imbalance (EEI), a key driver of climate change, has risen markedly over the last two decades. Greenhouse gas forcing, aerosol forcing, and cloud feedback all contribute to this increase. However, the role of aerosol forcing, particularly effective radiative forcing through aerosol-cloud interactions (ERF ACI ), remains highly uncertain and closely intertwined with cloud feedback. Here, we estimate shortwave ERF ACI using satellite observations and show its importance as a contributor to the EEI increase between 2003 and 2023. ERF ACI exhibits a significant increasing trend of 0.33 Wm −2 /decade averaged over oceans between 60°S and 60°N. The increasing trend of ERF ACI stems from a global decline in cloud droplet number concentration driven by decreasing anthropogenic aerosol emissions. It is of similar magnitude as the combined instantaneous forcing trend from greenhouse gases and aerosol-radiation interactions. Our results may reduce the gap between the simulated and observed shortwave contribution to EEI trends while implying a weak shortwave cloud feedback. They also suggest a stronger aerosol forcing than the multi-model mean.
Infrasonic signatures of meteoroid fragmentation are frequently ambiguous: do multiple arrivals signify a complex breakup or merely the distorting effects of a layered atmosphere? Resolving this ambiguity is critical for accurate energy estimates and source reconstruction. In this study, we address this challenge by analyzing a unique regional dataset of well-constrained meteoroid events observed by the Southern Ontario Meteor Network and the co-located Elginfield Infrasound Array. We employ pseudo-differential parabolic equation (PPE) simulations to quantify how fine-scale gravity-wave structures in the stratosphere and lower thermosphere modify acoustic waveforms at ranges <300 km. Our modeling reveals that while fine-scale layering can stretch signals and generate diffuse oscillatory tails, it does not produce discrete, high-amplitude pulse splitting at ranges below ∼140 km. By applying these results to the rare multi-arrival event 20060305, we demonstrate that its distinct double arrival at 100 km range is inconsistent with atmospheric multipathing and provides definitive evidence of separate fragmentation episodes. These findings establish new diagnostic criteria for separating source physics from propagation artifacts, improving the reliability of infrasound as a monitoring tool for natural bolides, space debris re-entries, and catastrophic launch failures.
SAND2023-05377O The Modal Aerosol Model with 4 fixed modes (MAM4xx) is a performance-portable, C++ implementation for modeling the chemical reactions of aerosols in the atmosphere. MAM4xx is part of the Energy Exascale Earth System Model (E3SM). The E3SM project is an ongoing Earth system modeling, simulation, and prediction project that optimizes the use of DOE laboratory resources to meet the science needs of the nation and the mission needs of DOE. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Motivated by the need to improve visualizations of Earth's complex water cycle, this team embarked on non-trivial tasks to push from traditional methods of viewing data from simulations as static line graphs and contour plots into new realms with multiple dimensions (three spatial dimensions and the time component) viewable at once. To do this, we chose to feature the extremes in the general circulation of the atmosphere because these Earth system elements are short-lived, but impactful events. We used simulation data produced by the Department of Energy's (DOE) Energy Exascale Earth System Model (E3SM),which is designed to answer DOE science questions using DOE computing facilities. The E3SM project includes three sets of simulation experiments: cryosphere, bio-geochemical cycles, and the water cycle. The water cycle experiment campaign includes a set of simulations designed to understand how the water cycle will change in coming decades under a changing climate.
Focal Area(s): This white paper responds to Focal Area #3: Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: This white paper addresses the water-cycle and data-model integration grand challenge. It leverages data from the Atmospheric Radiation Measurement (ARM) Climate Research Facility, and Next-Generation Ecosystem Experiment (NGEE), and Science Focus Area (SFA). The white paper focuses on controlling cloud, precipitation, and radiative properties as observed and simulated by the Earth System Models (ESM). The described framework can be readily applied to any other ensemble of instruments, including satellites and other ground-based networks.
Representing warm, shallow clouds is a challenge for Global Climate Models, which leads to uncertainty in model projections of future climate. Our study was particularly concerned with how climate models represent the effects of shallow, non-precipitating cumulus clouds. Climate models must make certain assumptions when representing low clouds such as how much dry air from outside the cloud is mixed into the warm, moist cloud updraft. This process is called “entrainment” and tends to weaken the cloud updraft and dry out the cloud, compared to a theoretical cloud with no mixing. This project was a joint observational and modeling study to derive estimates of entrainment from field observations and use high-resolution modeling to evaluate the assumptions used in climate model representations of shallow cumulus. Our research took advantage of a wide variety of Department of Energy measurements from fixed climate-monitoring locations over the Southern Great Plains of the U.S. and the in the Eastern North Atlantic, along with short-term field projects (MAGIC, CAP–MBL, ACE–ENA). During the project, the PI maintained regular collaborations with Department of Energy Scientists at Brookhaven and Argonne National Laboratories. The project funded two students, who both obtained their M.S. in Atmospheric Science and are currently in the Atmospheric Science Ph.D. program. Both were lead authors on research papers funded by this grant.
Intense winds associated with tropical cyclones (TCs) generate surface ocean cooling in their wakes, which can persist for several weeks in their aftermath. While multi-decadal observations of the sea surface have shown a substantial warming of the ocean, long-term changes in cold wake recovery time remain largely unknown. Here we find a trend toward faster recovery of TC cold wakes in the Atlantic main development region (MDR) since 2001. This is due primarily to a decrease in the strength of the North Atlantic trade winds, which reduces evaporative cooling of the ocean. The faster damping of TC cold wakes has led to a significant increase in the intensification of subsequent TCs that encounter lingering wakes from prior TCs, with a magnitude that is about 9% of that from long-term warming of the ocean. Finally, earth system model simulations indicate that the observed decrease in the cold wake recovery time will likely continue into the future.