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DOE OSTI2025

Establishing nationwide power system vulnerability index across US counties using interpretable machine learning

Power outages have become increasingly frequent, intense, and prolonged in the US due to climate change, aging electrical grids, and rising energy demand. However, largely due to the absence of granular spatiotemporal outage data, we lack data-driven evidence and analytics-based metrics to quantify power system vulnerability. This limitation has hindered the ability to effectively evaluate and address vulnerability to power outages in US communities. Here, in this work, we collected ∼179 million power outage records at 15-min intervals across 3022 US contiguous counties (96.15 % of the area) from 2014 to 2023. We developed a power system vulnerability assessment framework based on three dimensions (intensity, frequency, and duration) and applied interpretable machine learning models (XGBoost and SHAP) to compute Power System Vulnerability Index (PSVI) at the county level. Our analysis reveals a consistent increase in power system vulnerability across the US counties over the past decade. We identified 318 counties across 45 states as hotspots for high power system vulnerability, particularly in the West Coast (California and Washington), the East Coast (Florida and the Northeast area), the Great Lakes megalopolis (Chicago-Detroit metropolitan areas), and the Gulf of Mexico (Texas). Our heterogeneity analysis indicates that urban counties and those located along regional transmission boundaries tend to exhibit significantly higher vulnerability. Our results highlight the significance of the proposed PSVI for evaluating the vulnerability of communities to power outages. The findings underscore the widespread and pervasive impact of power outages across the country and offer crucial insights to support infrastructure operators, policymakers, and emergency managers in formulating policies and programs aimed at enhancing the resilience of the US power infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Vegetation Warming Experiment: Thaw depth and dGPS locations, Utqiagvik, Alaska, 2019

Thaw depth measurements within and around warming chambers, and in ambient plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Measurements were taken at the start and end of chamber deployment, and two intermediate times during the 2019 growth season. dGPS measurements of chamber and ambient plot locations are also included. The files included in this data package are in .csv format, and include 3 data files and 3 metadata files. This data was recorded as part of the Zero Power Warming (ZPW) vegetation warming experiment. See related data files for environmental conditions, leaf physiology, leaf traits, and landscape and plot phenocam images. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

Solar Forced Dansgaard/Oeschger Events?

Climate records for the last ice age (which ended 11,500 years ago) show enormous climate fluctuations in the North Atlantic region - the so-called Dansgaard/Oeschger events. During these events air temperatures in Greenland changed on the order of 10 degrees Celsius within a few decades. These changes were attributed to shifts in ocean circulation which influences the warm water supply from lower latitudes to the North Atlantic region. Interestingly, the rapid warmings tend to recur approximately every 1500 years or multiples thereof. This has led researchers to speculate about an external cause for these changes with the variable Sun being one possible candidate. Support for this hypothesis came from climate reconstructions, which suggested that the Sun influenced the climate in the North Atlantic region on these time scales during the last approximately 12,000 years of relatively stable Holocene climate. However, Be-10 measurements in ice cores do not indicate that the Sun caused or triggered the Dansgaard/Oeschger events. Depending on the solar magnetic shielding more or less Be-10 is produced in the Earth's atmosphere. Therefore, 10Be can be used as a proxy for solar activity changes. Since Be-10 can be measured in ice cores, it is possible to compare the variable solar forcing directly with the climate record from the same ice core. This removes any uncertainties in the relative dating, and the solar-climate link can be reliably studied. Notwithstanding that some Dansgaard/Oeschger warmings could be related to increased solar activity, there is no indication that this is the case for all of the Dansgaard/Oeschger events. Therefore, during the last ice age the Be-10 and ice core climate data do not indicate a persistent solar influence on North Atlantic climate.

Muscheler, R.↗

NASA NTRSDate not supplied

Towards a program of record of inland water quality: Exploiting present and heritage multispectral sensors for maximum information extraction

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This research exploits recent advancements in bio-optical modeling, cloud computing, and machine learning to enhance our capacity to leverage present and heritage satellite data. Recent research suggests that sensors with low spectral resolution, such as Sentinel 2 and Landsat missions, contain enough hidden spectral variation which can be exploited using data-driven approaches. The availability of three decades of archival imagery will open doors to discover global trends of eutrophication and increased cyanobacteria dominance and provide valuable insight to the development of predictive methodologies. Preliminary efforts in synthetic emulation of global natural inland waters will be discussed and contextualized against satellite radiometric measurement uncertainty, satellite data product uncertainties and causal signal ambiguity over the visible wavelength range, supported by high quality field and image data for selected inland aquatic sites. Insights on water quality estimation via data-driven machine learning models versus matrix inversions will be discussed, and how we can exploit spectral-spatial relationships in high spatial resolution data. A cross-sensor synergistic approach with detailed uncertainty analysis based on optical water types, will allow for unprecedented global snapshots of fine scale ecological dynamics of inland waters.

Inland↗

DOE OSTI2024

Using pollen in turbidites for vegetation reconstructions

Turbidites, deposited by sub-aqueous gravity flows, are common in sedimentary archives worldwide and present a unique challenge and opportunity when reconstructing past vegetation through pollen analysis. When sampling pollen from a sediment core for palaeovegetation records, it is common practice to target background sediments (i.e. pelagic sediment) and avoid sampling turbidites, as they are presumed to portray a misleading picture of past vegetation. This assumption stems from our limited understanding of pollen abundance and distribution through turbidites, meaning that palynologists overlook deposits that could potentially be used to reconstruct past vegetation and climate. We present pollen assemblage and sedimentological data from four recent (<150 years) deep marine turbidite deposits from the Hikurangi Subduction Margin, Aotearoa-New Zealand, with the aim of understanding the abundance and distribution of pollen in fine-grained turbidites. We find that pollen is diluted in the bases of turbidites, but despite this dilution, the proportions of different pollen taxa remain consistent through each turbidite. These results confirm that pollen can be sampled from turbidites for palaeovegetation reconstructions and that sampling the fine-grained upper parts of turbidites will provide the best pollen recovery.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2009

The Green Sahara: Climate Change, Hydrologic History and Human Occupation

Archaeology can provide insight into interactions of climate change and human activities in sensitive areas such as the Sahara, to the benefit of both disciplines. Such analyses can help set bounds on climate change projections, perhaps identify elements of tipping points, and provide constraints on models. The opportunity exists to more precisely constrain the relationship of natural solar and climate interactions, improving understanding of present and future anthropogenic forcing. We are beginning to explore the relationship of human occupation of the Sahara and long-term solar irradiance variations synergetic with changes in atmospheric-ocean circulation patterns. Archaeological and climate records for the last 12 K years are gaining adequate precision to make such comparisons possible. We employ a range of climate records taken over the globe (e.g. Antarctica, Greenland, Cariaco Basin, West African Ocean cores, records from caves) to identify the timing and spatial patterns affecting Saharan climate to compare with archaeological records. We see correlation in changing ocean temperature patterns approx. contemporaneous with drying of the Sahara approx. 6K years BP. The role of radar images and other remote sensing in this work includes providing a geographically comprehensive geomorphic overview of this key area. Such coverage is becoming available from the Japanese PALSAR radar system, which can guide field work to collect archaeological and climatic data to further constrain the climate change chronology and link to models. Our initial remote sensing efforts concentrate on the Gilf Kebir area of Egypt.

remote sensing↗

NASA NTRSDate not supplied

A NASA GISTEMP Observational Uncertainty Ensemble: Regional and Monthly Uncertainty

The historical global temperature record is an essential data product for quantifying the variability and change of the Earth system. In recent years, better characterization of observational uncertainty in global and hemispheric trends has become available, but the methodologies are not necessarily applicable to analyses at smaller regional areas, or monthly means, where station sparsity and other systematic issues contribute to greater uncertainty. This work details a gridded uncertainty ensemble of historical temperature anomalies from the Goddard Institute for Space Studies (GISS) Surface Temperature product (GISTEMP) product. This ensemble characterizes the complex spatial and temporal correlation structure of uncertainty in gridded historical temperature, enabling proper uncertainty propagation for climate and social science at regional and monthly scales. This work details the methodology for generating the uncertainty ensemble, key statistics of the uncertainty evolution over space and time, and provides best practices for using the uncertainty ensemble in future studies. Summary statistics from the uncertainty ensemble are in good agreement with production GISTEMP. Two applications of the uncertainty ensemble are also presented. First, the warmest year on record is shown to most likely be 2016 with a 53.2% chance and 2020 as the second most likely with a 44.4% chance. Second, it is shown that the arctic is warming 2.5 - 5 times faster than the globe, significantly faster than the regularly quoted twice as fast.

GISTEMP↗

NASA NTRS2004

Impact Crater Abundance of the Martian South Polar Layered Deposits from THEMIS Visible Imaging

The polar layered deposits (PLD) of Mars have attracted considerable attention since their identification in Mariner 9 images, largely due to the possibility that these finely layered, volatile-rich deposits hold a record of recent eras in Martian climate history. The PLD have been a target of imaging and other sensors in the last several decades, but only recently has it been possible to obtain a moderately high resolution image map, using the visible sensor on 2001 Mars Odyssey's Thermal Emission Imaging System (THEMIS). THEMIS has acquired a 36 meter/pixel contiguous single-band visible image data set of the south polar layered deposits (SPLD), during the southern spring in 2003. The data will undoubtedly be applied to many problems in Mars polar studies. We use these images to further characterize the population of impact craters on the SPLD, and the implications of the observed population for the age and evolution of the SPLD.

Plaut, J. J.↗

NASA NTRS2006

Does The Nile Reflect Solar Variability?

Historical records of the Nile water level provide a unique opportunity to investigate the possibility that solar variability influences the Earth's climate. Particularly important are the annual records of the water level, which are uninterrupted for the years 622-1470 A.D. These records are non-stationary, so that standard spectral analyses cannot adequately characterize them. Here the Empirical Mode Decomposition technique, which is designed to deal with nonstationary, nonlinear time series, becomes useful. It allows the identification of two characteristic time scales in the water level data that can be linked to solar variability: the 88 year period and a time scale of about 200 years. These time scales are also present in the concurrent aurora data. Auroras are driven by coronal mass ejections and the rate of auroras is an excellent proxy for solar variability. Analysis of auroral data contemporaneous with the Nile data shows peaks at 88 years and about 200 years. This suggests a physical link between solar variability and the low frequency variations of the Nile water level. The link involves the influence of solar variability on the North Annual Mode of atmospheric variability and its North Atlantic and Indian Oceans patterns that affect rainfall over Eastern Equatorial Africa where the Nile originates.

statistical methods↗

NASA NTRS2013

On the Impact Angle of Hurricane Sandy's New Jersey Landfall

Hurricane Sandy's track crossed the New Jersey coastline at an angle closer to perpendicular than any previous hurricane in the historic record, one of the factors contributing to recordsetting peak-water levels in parts of New Jersey and New York. To estimate the occurrence rate of Sandy-like tracks, we use a stochastic model built on historical hurricane data from the entire North Atlantic to generate a large sample of synthetic hurricanes. From this synthetic set we calculate that under long-term average climate conditions, a hurricane of Sandy's intensity or greater (category 1+) makes NJ landfall at an angle at least as close to perpendicular as Sandy's at an average annual rate of 0.0014 yr-1 (95% confidence range 0.0007 to 0.0023); i.e., a return period of 714 years (95% confidence range 435 to 1429).

hurricanes↗

NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global chemistry-climate models (CCMs) where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) CCM through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗

DOE OSTI2022

What We Learned From Analyzing 18 Million Rows of Commercial Buildings’ HVAC Fault Data

To achieve ambitious decarbonization goals it is critical that buildings operate to their full potential. Commercial HVAC systems, however, experience a wide range of operational faults, adversely affecting energy consumption, occupant comfort, and maintenance costs. Analytical tools such as fault detection & diagnostics (FDD) software identify and help diagnose these types of sensing, mechanical, or control-related faults. While significant energy savings has been documented for FDD, along with limited-scale studies on technical capabilities, there is a lack of empirical data on faults being reported by FDD tools. With FDD deployment accelerating significantly over the past decade there is an opportunity to gather and analyze data on commercial HVAC operational problems at an unprecedented scale. Such data could address many questions such as: [a] What faults are most commonly reported?; and [b] How does fault reporting vary by time of year and other possible drivers? A recent study into FDD fault reporting amassed the largest U.S. dataset of commercial HVAC air-side fault records, drawn from multi-year monitoring across over 60,000 pieces of HVAC equipment. The results of this study provide granular data on fault reporting for over 90 unique fault types. In this paper we provide an overview of the research process and highlight key findings and lessons learned. This study presents an extraordinary level of detail on FDD fault reporting characteristics across many climate zones and building types. Armed with these new insights, commercial building industry stakeholders can make better informed decisions when designing, configuring, and operating commercial HVAC systems.

Crowe, Eliot↗

DOE OSTI2025

A U.S. Scientific Community Vision for Sustained Earth Observations of Greenhouse Gases to Support Local to Global Action

Managing carbon stocks in the land, ocean, and atmosphere under changing climate requires a globally‐integrated view of carbon cycle processes at local and regional scales. The growing Earth Observation (EO) record is the backbone of this multi‐scale system, providing local information with discrete coverage from surface measurements and regional information at global scale from satellites. Carbon flux information, anchored by inverse estimates from spaceborne Greenhouse Gas (GHG) concentrations, provides an important top‐down view of carbon emissions and sinks, but currently lacks global continuity at assessment and management scales (<100 km). Partial‐column data can help separate signals in the boundary layer from the overlying atmosphere, providing an opportunity to enhance surface sensitivity and bring flux resolution down from that of column‐integrated data (100–500 km). Based on a workshop held in September 2024, the carbon cycle community envisions a carbon observation system leveraging GHG partial columns in the lower and upper troposphere to weave together information across scales from surface and satellite EO data, and integration of top‐down/bottom‐up analyses to link process understanding to global assessment.

Parazoo, Nicholas C. [California Institute of Tech↗

NASA NTRS2016

The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.

climate models↗

NASA NTRS2021

State of the Climate in 2020: Global Oceans

This chapter details 2020 global patterns in select observed oceanic physical, chemical, and biological variables relative to long-term climatologies, their differences between 2020 and 2019, and puts 2020 observations in the context of the historical record. In this overview we address a few of the highlights, first in haiku, then paragraph form: La Niña arrives, shifts winds, rain, heat, salt, carbon: Pacific—beyond. Compiled by NOAA’s National Centers for Environmental Information, "State of the Climate in 2020" is based on contributions from scientists from around the world. It provides a detailed update on global climate indicators, notable weather events, and other data collected by environmental monitoring stations and instruments located on land, water, ice, and in space. The full report is available from: https://doi.org/10.1175/2021BAMSStateoftheClimate.1.

Gregory C Johnson↗

DOE OSTI2025

Alteration history of aluminum-rich rocks at Jezero crater, Mars

Aluminum-rich clay minerals are detected across the ancient surface of Mars and record intervals of intense alteration by liquid water. On Earth, these clay minerals can form from hydrothermal alteration or rainfall-driven chemical weathering over thousands to millions of years, but how they formed on Mars remains a mystery. The Perseverance rover discovered light-toned, cobble-sized, aluminum-rich (30-45 wt% Al 2 O 3 ) “float” rocks (rock fragments), with some exhibiting spectral signatures of kaolinite, an aluminum-rich clay mineral. These rocks now enable an investigation into the ancient kaolinite-bearing terrains of Mars. To interpret their formation, we use data from the SuperCam and Mastcam-Z instruments onboard the rover to compare the chemistry and reflectance spectra of the float rocks with deeply weathered paleosols and hydrothermal kaolin deposits from Earth’s geological record. Aluminum and titanium enrichments coupled with depletion of iron and magnesium are unlike hydrothermal deposits and instead comparable to bleached horizons of paleosols that formed under high rainfall during past greenhouse climates on Earth. These rocks therefore likely represent some of the wettest intervals of Mars’ history.

58 GEOSCIENCES↗

NASA NTRS2014

Uncertainty Analysis for the Miniaturized Laser Heterodyne Radiometer (mini-LHR)

Presented here is a sensitivity analysis for the miniaturized laser heterodyne radiometer (mini-LHR). This passive, ground-based instrument measures carbon dioxide (CO2) in the atmospheric column and has been under development at NASA/GSFC since 2009. The goal of this development is to produce a low-cost, easily-deployable instrument that can extend current ground measurement networks in order to (1) validate column satellite observations, (2) provide coverage in regions of limited satellite observations, (3) target regions of interest such as thawing permafrost, and (4) support the continuity of a long-term climate record. In this paper an uncertainty analysis of the instrument performance is presented and compared with results from three sets of field measurements. The signal-to-noise ratio (SNR) and corresponding uncertainty for a single scan are calculated to be 329.4+/-1.3 by deploying error propagation through the equation governing the SNR. Reported is an absorbance noise of 0.0024 for 6 averaged scans of field data, for an instrument precision of approximately 0.2 ppmv for CO2.

carbon dioxide (CO2)↗

NASA NTRSDate not supplied

Examination of Regional Trends in Low Level Cloud Properties Found in the Aqua-MODIS Satellite Record

Clouds have a pronounced influence on the Earth?s climate. Relative to cloud free conditions, they cool the planet by increasing the amount of solar radiation reflected back to space and reducing the amount of sunlight reaching the surface, but they warm the planet by decreasing the amount of thermal infrared radiation escaping to space and increasing the amount reaching the surface (a greenhouse effect). The global mean net cloud radiative effect (CRE) is about -20 W/m2, a cooling effect at both the top-ofatmosphere and surface. Given the magnitude of CRE?s, it is expected that changes in cloud properties could be a significant factor in climate change due to anthropogenic forcing?s, yet cloud feedbacks are not well known and remain one of the largest uncertainties in climate prediction. This paper explores relationships between coincident observations of atmospheric aerosols, clouds and radiation derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and from the Clouds and the Earth?s Radiant Energy System (CERES) instruments on the Aqua satellite. We investigate several interesting regional trends that have emerged in the nearly 18-year satellite record that suggest correlation between changes in low-level cloud properties and changes in aerosol optical depth that may be associated with changes in pollution emissions and possibly with other factors. MERRA reanalysis of meteorological conditions and aerosol particulate species are investigated to help better understand the potential mechanisms responsible for the observed cloud property trends. Finally, we analyze a new CERES flux by cloud type dataset in order to try and isolate the associated trends in low-level cloud radiative effects. It is anticipated that this study using long-term observations of clouds, aerosols and radiative fluxes combined with model reanalysis data will contribute to an improved understanding of cloud climate feedbacks.

William L Smith Jr.↗