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DOE OSTI2025

Atmospheric wind energization of ocean weather

Ocean weather comprises vortical and straining mesoscale motions, which play fundamentally different roles in the ocean circulation and climate system. Vorticity determines the movement of major ocean currents and gyres. Strain contributes to frontogenesis and the deformation of water masses, driving much of the mixing and vertical transport in the upper ocean. While recent studies have shown that interactions with the atmosphere damp the ocean’s mesoscale vortices O(100) km in size, the effect of winds on straining motions remains unexplored. Here, we derive a theory for wind work on the ocean’s vorticity and strain. Using satellite and model data, we discover that wind damps strain and vorticity at an equal rate globally, and unveil striking asymmetries based on their polarity. Subtropical winds damp oceanic cyclones and energize anticyclones outside strong current regions, while subpolar winds have the opposite effect. A similar pattern emerges for oceanic strain, where subtropical convergent flow is damped along the west-equatorward east-poleward direction and energized along the east-equatorward west-poleward direction. These findings reveal energy pathways through which the atmosphere shapes ocean weather.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

How do North American weather regimes drive wind energy at the sub-seasonal to seasonal timescales?

Abstract There has been an increasing need for forecasting power generation at the subseasonal to seasonal (S2S) timescales to support the operation, management, and planning of the wind-energy system. At the S2S timescales, atmospheric variability is largely related to recurrent and persistent weather patterns, referred to as weather regimes (WRs). In this study, we identify four WRs that influence wind resources over North America using a universal two-stage procedure approach. These WRs are responsible for large-scale wind and power production anomalies over the CONUS at the S2S timescales. The WR-based reconstruction explains up to 40% of the monthly variance of power production over the western United States, and the explanatory power of WRs generally increases with the increase of timescales. The identified relationship between WRs and power production reveals the potential and limitations of the regional WR-based wind resource assessment over different regions of the CONUS across multiple timescales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Proactive Operations and Investment Planning via Stochastic Optimization to Enhance Power Systems’ Extreme Weather Resilience

We present scalable stochastic optimization approaches for improving power systems’ resilience to extreme weather events. We consider both proactive redispatch and transmission line hardening as alternatives for mitigating expected load shed due to extreme weather, resulting in large-scale stochastic linear programs (LPs) and mixed-integer linear programs (MILPs). We solve these stochastic optimization problems with progressive hedging (PH), a parallel, scenario-based decomposition algorithm. Our computational experiments indicate that our proposed method for enhancing power system resilience can provide high-quality solutions efficiently. With up to 128 scenarios on a 2,000-bus network, the operations (redispatch) and investment (hardening) resilience problems can be solved in approximately 6 min and 2 h of wall-clock time, respectively. Additionally, we solve the investment problems with up to 512 scenarios, demonstrating that the approach scales very well with the number of scenarios. Moreover, the method produces high quality solutions that result in statistically significant reductions in expected load shed. Our proposed approach can be augmented to incorporate a variety of other operational and investment resilience strategies, or a combination of such strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Notable impact of wildfires in the western United States on weather hazards in the central United States

Increased wildfire events constitute a significant threat to life and property in the United States. Wildfire impact on severe storms and weather hazards is another pathway that threatens society, and our understanding of which is very limited. Here, we use unique modeling developments to explore the effects of wildfires in the western US (mainly California and Oregon) on precipitation and hail in the central US. We find that the western US wildfires notably increase the occurrences of heavy precipitation rates by 38% and significant severe hail (≥2 in.) by 34% in the central United States. Both heat and aerosols from wildfires play an important role. By enhancing surface high pressure and increasing westerly and southwesterly winds, wildfires in the western United States produce ( 1 ) stronger moisture and aerosol transport to the central United States and ( 2 ) larger wind shear and storm-relative helicity in the central United States. Both the meteorological environment more conducive to severe convective storms and increased aerosols contribute to the enhancements of heavy precipitation rates and large hail. Moreover, the local wildfires in the central US also enhance the severity of storms, but their impact is notably smaller than the impact of remote wildfires in California and Oregon because of the lessened severity of the local wildfires. As wildfires are projected to be more frequent and severe in a warmer climate, the influence of wildfires on severe weather in downwind regions may become increasingly important.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Evaluating the carbon capture potential of industrial waste as a feedstock for enhanced weathering

Abstract Limiting anthropogenic global climate warming since the start of the industrial period to less than 2 °C will very likely require both deep and rapid reductions in anthropogenic greenhouse gas emissions and a range of approaches toward carbon dioxide removal (CDR). One prominent CDR approach is enhanced weathering (EW), in which crushed silicate rock is applied on land or in the open ocean to accelerate natural weathering processes that absorb carbon dioxide from Earth’s ocean–atmosphere system. However, in addition to a range of potential environmental, socioeconomic, and ethical issues associated with this pathway, bottlenecks in feedstock sourcing represent a key barrier for deployment of EW at scale. Here, we evaluate the potential of silicate wastes produced from industrial processes—such as steel slag and cement waste—as feedstocks for the EW process. An empirical model that links industrial alkaline waste production to gross domestic product at purchase power parity is developed to forecast waste production in the alternative futures described by the shared socioeconomic pathway (SSP) framework. By incorporating these results into an intermediate-complexity Earth system model, we also explore the impacts of EW using industrial waste on changes to global temperature, ocean pH, and ocean aragonite saturation state, while also quantifying overall CDR efficiency through the end of the century. We estimate a maximum cumulative end-of-century capture potential of ∼400 GtCO 2 for industrial waste, which could represent a significant fraction of the projected CDR requirement of many mitigation scenarios in the SSP framework. However, feedstock-dependent environmental impacts and the technoeconomics of feedstock redistribution may ultimately limit deployment scope.

Xu, Pengxiao (ORCID:0009000633724293)↗

DOE OSTI2023

Real-time attribution of the influence of climate change on extreme weather events: a storyline case study of Hurricane Ian rainfall

Abstract As the Earth continues to warm due to human greenhouse gas emissions, there is a growing need to efficiently communicate the effect that global warming has on individual extreme weather events. Using a storyline approach, we present a rapid attribution of the increase in rainfall over Florida during Hurricane Ian in 2022 due to climate change as a case study. We find that extreme accumulated rainfall amounts associated with Hurricane Ian increased by 18%, far in excess of what would be expected by Clausius–Clapeyron scaling. The study offers a blueprint for rapid operational climate change attribution statements about extreme storms and other very rare weather events.

Reed, Kevin A. (ORCID:0000000337417080)↗

DOE OSTI2021

Nanomechanical and Fluorescence Characterizations of Weathered PV Module Encapsulation

Nanoindentation and fluorescence spectroscopy provide spatially resolved mechanical and chemical characterization for degradation of poly (ethylene-co-vinyl acetate) (EVA) encapsulants aged under accelerated weathering and in field deployed photovoltaic (PV) modules. For the accelerated weathering tests, two different EVA formulations in the glass/EVA/glass-laminated coupons were exposed to ultraviolet (UV) light for 180 days at three different temperatures (40, 60, and 80 °C) and UV intensities (0.4, 2.2, and 2.9 W/m2/nm at 340 nm). The fluorescence spectra and moduli were uniform through the cross section of both EVA formulations at the lowest temperature and UV intensity; however, under the highest temperature and UV intensity, the UV irradiated sides showed lower moduli and higher fluorescence compared to the opposite sides. For EVA obtained from PV modules deployed 27 years in Sacramento, CA, USA, changes in fluorescence intensity across the thickness were relatively greater than changes in modulus. On the other hand, for EVA obtained from the same type of module stored in the shed for 27 years, no fluorescence was observed, and a uniform modulus was seen through the EVA layer, but with substantially higher values than those obtained from the field-deployed modules. The different extent of changes between laboratory and field exposures suggests the importance of considering effects of temperature and UV intensity for designing a reliable accelerated testing. This study uniquely demonstrates the capability of microscale characterization using nanoindentation and fluorescence microscopy to monitor mechanical and chemical degradation of EVA encapsulants in PV modules.

14 SOLAR ENERGY↗

DOE OSTI2024

Bilevel Nodal Behind-the-meter Solar Disaggregation Under Unexpected Extreme Weather Conditions

As the power grid undergoes significant paradigm shift due to the increasing penetration of renewable generation, the ever-growing installation of behind-the-meter (BTM) solar generation in the power grid also has a significant impact on nodal loads, posing challenges on transmission operators. Furthermore, increasing frequent and severe extreme weather events intertwine with ubiquitous BTM solar generations and have amplified the challenges of accurately model nodal load profiles, especially under the lack of ground-truth information for verification. To tackle these challenges, this paper introduces a bilevel model that utilizes year-long data (e.g., proxy solar, zonal load, and individual node load profiles) to disaggregate metered profiles into actual demand and BTM solar generation at each transmission node. The proxy solar not only scales the BTM solar generation of individual nodes but also create a compensation term for enhancing performance on days with unexpected extreme weather events. The proposed algorithm is validated with real-world PJM Interconnection data during unexpected events like the recent Winter Storm Elliott. For quantitative evaluations, a novel Score error is introduced, which is based on mean percentages and load scales and offers a universal assessment method suitable for all nodes and different data formats (e.g., normalized or raw values).

behind-the-meter solar, load disaggregations, load↗

DOE OSTI2018

Resilience Enhancement of Distribution Grids Against Extreme Weather Events

This paper proposes a resilience-oriented design (ROD) technique to protect distribution grids against high-impact but low-probability extreme weather events. The problem is formulated as a two-stage stochastic mixed integer problem. The first stage is to make ROD decisions, i.e., hardening existing distribution lines and deploying ROD resources such as back-up distributed generators and automatic switches. The second stage evaluates the system operation cost during a realized extreme weather event and repair cost after the event. A novel modeling strategy is proposed to deal with the decision-dependent uncertainty of distribution line damage status, which is affected by the first-stage hardening decisions. As both stages have binary variables, a modified and computationally efficient progressive hedging algorithm with scenario bundling is introduced. The algorithm performance is evaluated by calculating lower bounds of solutions. In conclusion, the proposed model and algorithms are demonstrated on 34-bus and 123-bus test feeders.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Data-Based Resilience Enhancement Strategies for Electric-Gas Systems Against Sequential Extreme Weather Events

Some extreme weather events, such as the hurricane, pass through an area sequentially and thus are called sequential extreme weather events (SEWEs). This paper proposes a data-based robust optimization (RO) model to enhance the resilience of the integrated electricity and gas system (IEGS) against SEWEs. Specifically, the SEWE strikes the IEGS sequentially. After each attack, the system state is adjusted immediately to minimize the maximized expected system cost caused by the SEWE. The attack-defense procedures are repeated alternatively during the SEWE. Preventive measures, hardening, are made in advance to reduce the impact of sequential attacks. The entire process is formulated as a multi-period RO model. Furthermore, it is proved that the most effective resilience enhancement strategies for this model are the same as those for a two-stage RO model, which can be solved by the nested column-and-constraint generation (C&CG) algorithm. In addition, the property of SEWEs, sequentially endangering limited regions of the IEGS, is incorporated to build a data-based uncertainty set and reduce its conservativeness. Simulation results on two IEGSs validate the effectiveness of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Deep abiotic weathering of pyrite

Pyrite is a ubiquitous iron sulfide mineral that is oxidized by trace oxygen. The mineral has been largely absent from global sediments since the rise in oxygen concentration in Earth’s early atmosphere. We analyzed weathering in shale, the most common rock exposed at Earth’s surface, with chemical and microscopic analysis. By looking across scales from 10 −9 to 10 2 meters, we determined the factors that control pyrite oxidation. Under the atmosphere today, pyrite oxidation is rate-limited by diffusion of oxygen to the grain surface and regulated by large-scale erosion and clast-scale fracturing. We determined that neither iron- nor sulfur-oxidizing microorganisms control global pyrite weathering fluxes despite their ability to catalyze the reaction. This multiscale picture emphasizes that fracturing and erosion are as important as atmospheric oxygen in limiting pyrite reactivity over Earth’s history.

58 GEOSCIENCES↗

DOE OSTI2023

Linking impact melt redox with crustal weathering regime

Abstract Impact melting and outgassing of impact melts were important processes shaping the crust and atmosphere of early Earth and Mars. The redox state of impact melts influences the gases they release, but the controls on impact melt redox are not well understood. Here, we present Fe micro–X-ray absorption near edge structure (μ-XANES) measurements of a suite of impact melt glasses from Lonar crater, India. As an impact into continental flood basalts, Lonar crater is an ideal analog for impacts into basaltic crust on early Earth and Mars. The Fe-μ-XANES technique permits robust characterization of the Fe3+/ΣFe ratio and therefore redox conditions in Lonar glasses. We found a range in Fe3+/ΣFe of 0.21–0.49 among Lonar glasses, including substantial intraclast variations. We conclude that a primary factor driving these variations was pre-impact oxidative weathering of target rocks. The coupling between crustal weathering regime and speciation of gases released from impact melts implies that impact melt outgassing could act as a feedback mechanism to reinforce prevailing surface redox conditions.

Geology↗

DOE OSTI2020

GHEP WIBT (Guidelines for Home Energy Professionals Weatherization Installer Badges Toolkit) [SWR-20-69]

The National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy's (DOE) Weatherization Assistance Program (WAP) are collaborating with the home energy retrofit industry to support the development of skilled workers. The Installer Badges Toolkit provides a flexible, customizable, and voluntary approach to training and skills recognition for WAP implementers, utility programs, private-sector workers, and contractors. In Fiscal Year 2018, DOE, along with the Crew Leader scheme committee, determined the Retrofit Installer Technician (RIT) Job Task Analysis (JTA) could be eliminated and its tasks inserted in the Crew Leader JTA. The RIT tasks became the basis of the Installer Badges. The Badges Toolkit was updated in 2020 to add licensing and copyright agreements. Users must cite the copyright information when using or distributing copies of the Badges Toolkit in any way. The technical content has remained unchanged from previous versions of the Badges Toolkit. The Toolkit for home retrofits consists of 25 Badges, each representing different energy efficiency tasks that an installer could perform on a home. Each Badge defines the desired outcome, criteria to verify, applicable material requirements, and references to Standard Work Specifications (SWS) or other relevant standards. The Badges provide a consistent approach to training by ensuring that installers in different regions are learning the same skills nationwide. Organizations can also customize the Toolkit by choosing only those Badges that are relevant to their program. The Badges Toolkit includes five pieces: "How to Use the Badges Toolkit" provides a brief overview of how a Grantee, Subgrantee, or training provider may approach using the toolkit. The "Badges Toolkit: Worksheet" includes what to consider when determining whether and how to best incorporate the Badges into a weatherization assistance program. The "Crew Leader Job Task Analysis Spreadsheet" indicates how the Badges align with specific areas of the JTA. The "Installer Badges Passport" features separate pages for each Badge, which include places for the installer and the supervisor/trainer to record the number of times a task has been successfully completed. The "Installer Badges Verification Criteria" includes sample inspection checklists for each Badge. These can be modified as needed based on approved variance requests or more stringent requirements. They also provide a basis for consistent inspections and awarding of Badges. Note: All elements of the Badges Toolkit are designed for use by potential program implementers. They are not off-the-shelf products intended for immediate deployment. Program implementers must review and modify as needed, revise verification criteria to match local requirements, complete worksheets, and otherwise define the parameters of their own badging program.

Desai, Jal↗

DOE OSTI2018

The Risks of Contracting the Acquisition and Processing of the Nation’s Weather and Climate Data to the Private Sector

Here, we are deeply concerned with the trend toward the purchase of commercial weather and climate data by the National Oceanic and Atmospheric Administration (NOAA) and other government agencies that may follow. One major concern is for the stability of both the raw and processed forms of these datasets as commercial enterprises come and go. Also of concern is the loss of free, publicly available data, which provide the backbone for much of the non-profit research at universities, government laboratories, and other nonprofit organizations. Related to this latter point is the questionable practice of private companies gaining the rights over data collected by instruments paid for by United States taxpayers. This letter highlights recent events that prompted our concerns and provides arguments in favor of maintaining an open and free data policy, which has established the United States as the global leader in supporting weather and climate operations, applications, basic research, and education.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Generalized Aerosol/Chemistry Interface (GIANT): A Community Effort to Advance Collaborative Science across Weather and Climate Models

Atmospheric aerosol and chemistry modules are key elements in Earth system models (ESMs), as they predict air pollutant concentrations and properties that can impact human health, weather, and climate. The current uncertainty in climate projections is partly due to the inaccurate representation of aerosol direct and indirect forcing. Aerosol/chemistry parameterizations used within ESMs and other atmospheric models span large structural and parameter uncertainties that are difficult to assess independently of their host models. Moreover, there is a strong need for a standardized interface between aerosol/chemistry modules and the host model to facilitate portability of aerosol/chemistry parameterizations from one model to another, allowing not only a comparison between different parameterizations within the same modeling framework, but also quantifying the impact of different model frameworks on aerosol/chemistry predictions. To address this need, we have initiated a new community effort to coordinate the construction of a Generalized Aerosol/Chemistry Interface (GIANT) for use across weather and climate models. We aim to organize a series of community workshops and hackathons to design and build GIANT, which will serve as the interface between a range of aerosol/chemistry modules and the physics and dynamics components of atmospheric host models. GIANT will leverage ongoing efforts at the U.S. modeling centers focused on building next-generation ESMs and the international AeroCom initiative to implement this common aerosol/chemistry interface. GIANT will create transformative opportunities for scientists and students to conduct innovative research to better characterize structural and parametric uncertainties in aerosol/chemistry modules, and to develop a common set of aerosol/chemistry parameterizations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Need for Caution in Interpreting Extreme Weather Statistics

Given the reality of anthropogenic global warming, it is tempting to seek an anthropogenic component in any recent change in the statistics of extreme weather. This paper cautions that such efforts may, however, lead to wrong conclusions if the distinctively skewed and heavy-tailed aspects of the probability distributions of daily weather anomalies are ignored or misrepresented. Departures of several standard deviations from the mean, although rare, are far more common in such a distinctively non-Gaussian world than they are in a Gaussian world. This further complicates the problem of detecting changes in tail probabilities from historical records of limited length and accuracy. A possible solution is to exploit the fact that the salient non-Gaussian features of the observed distributions are captured by so-called stochastically generated skewed (SGS) distributions that include Gaussian distributions as special cases. SGS distributions are associated with damped linear Markov processes perturbed by asymmetric stochastic noise and as such represent the simplest physically based prototypes of the observed distributions. The tails of SGS distributions can also be directly linked to generalized extreme value (GEV) and generalized Pareto (GP) distributions. The Markov process model can be used to provide rigorous confidence intervals and to investigate temporal persistence statistics. The procedure is illustrated for assessing changes in the observed distributions of daily wintertime indices of large-scale atmospheric variability in the North Atlantic and North Pacific sectors over the period 1872–2011. No significant changes in these indices are found from the first to the second half of the period.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Wave Events: Climatology, Trends, and Relationship to Northern Hemisphere Winter Blocking and Weather Extremes

Diagnostics of finite-amplitude local wave activity (LWA) are applied to the 500-hPa geopotential height field to diagnose persistent synoptic weather events of anomalously large wave activity in the Northern Hemisphere. By considering the cyclonic and anticyclonic components of LWA separately, persistent weather systems associated with large-amplitude troughs and ridges are detected. While anticyclonic wave events are predominantly found over Europe and Alaska, cyclonic wave events usually occur over East Asia and northeastern Canada. Those preferred regions correspond to the location of planetary-scale ridges and troughs, which contribute, together with transient anomalies, to the formation of wave events. Although wave events are not blocking events per definition, they are typically associated with increased blocking in their vicinity. Their spatial relationship to blocking, however, varies depending on their cyclonic or anticyclonic nature and the type of wave-breaking signatures. Wave events are also shown to be accompanied by warm or cold temperature extremes, whose spatial pattern depends on the type of events, cyclonic or anticyclonic, and the sector affected. Trends in the frequency of wave events indicate that cyclonic wave events and the associated cold extremes affecting East Asia have become more frequent in recent decades and could be linked to recent trends toward La Niña–like conditions in the Pacific and trends toward the negative phase of Arctic Oscillation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Seasonal and Geographical Variations in Fundamental Weather Patterns during Extreme Precipitation as Identified from Omega Equation Forcing

Abstract We investigate the large-scale weather patterns during extreme precipitation (PEx) events over the conterminous United States (CONUS) by applying a version of the quasigeostrophic (QG) omega equation. This work aims to develop a climatology of the weather patterns most related to PEx events during current climate. Extreme events are examined for each of seven regions defined by consistent annual cycles of precipitation and spanning the CONUS. For the CONUS we train several self-organizing maps (SOM) on a pressure–time series of vertical velocity from each of the advective forcing terms in the QG omega equation for each extreme event. The unsupervised learning of the SOM allows us to identify the most descriptive set of nine patterns in vertical velocity associated with precipitation extremes. This method finds multiple frontal- and cyclone-driven patterns while grouping primarily convective events into one pattern. Frontal events include a synoptic pattern consistent with West Coast atmospheric river events as well as pattern groups linked to developing and to mature (“occluded”) frontal cyclones. The primary patterns found during PEx events vary seasonally and geographically. Frontal cyclone patterns are most common during PEx events during summer in the part of the Great Plains and during winter for the Northeast, Southeast, Pacific Northwest, and Southwest. Convection is the most common pattern during summer in all regions. Except in the Southeast, the annual cycles of monthly number of PEx events and average precipitation match well, partially validating our choice of regions to aggregate PEx events.

Meteorology & Atmospheric Sciences↗