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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

MSD CoP Webinar: AI and Extreme Events - Overcoming Data Challenges for Improved Characterization of Climate Extremes

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Artificial Intelligence (AI) models require large volumes of data for training and testing. Data requirements present challenges for using AI to explore extreme events with limited observational data. This webinar will showcase two innovative methods developed by part of the European Climate Intelligence (CLINT) project to overcome data challenges and harness AI to improve our understanding of climate extremes. Dr. Ascenso will present his research on data augmentation methods to improve estimates of tropical cyclones using satellite data. His presentation will review established methods for data augmentation and explore opportunities and challenges for using generative AI to generate images of extreme, life-threatening tropical cyclones. Next, Dr. Plesiat will present his research on deep learning techniques to overcome limited observational data sets. His presentation will illustrate deep learning methods to develop AI reconstructions of four climate indices across Europe. Presenters : Dr. Guido Ascenso (post-doctoral researcher, Politecnico di Milano); Dr. Étienne Plésiat (German Climate Computing Centre - DKRZ) Moderator(s): Stefano Galelli (MSD CoP WG Co-Lead), David Gold (MSD CoP WG Co-Lead), Jillian Sturtevant (MSD CoP WG Communications Officer), Matteo Giuliani (Politecnico di Milano, MSD CoP WG Member, Moderator and Organizer) This webinar was held on: October 11, 2024 from 11AM - 1PM ET

AI↗
DOE OSTI2024

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.↗
DOE OSTI2025

Extreme Ultraviolet and Beyond Extreme Ultraviolet Lithography Using Amorphous Zeolitic Imidazolate Resists Deposited by Atomic/Molecular Layer Deposition

Amorphous zinc-imidazolate (aZnMIm) resists show potential to meet the demands for next-generation high-numerical aperture (high-NA) metal-containing extreme ultraviolet (EUV) resist materials, given their ease of deposition by atomic/molecular layer deposition (ALD/MLD) at thicknesses of 20 nm and below. Here, this study demonstrates that aZnMIm thin films, previously identified as high-resolution electron beam resists, can also function as negative-tone EUV photoresists. Water development achieves high sensitivity (5 mJ/cm 2 ) but leaves significant residue, while acetic acid development results in poor contrast. A hybrid approach─water followed by acetic acid─enables residue-free development with a sensitivity of 181 mJ/cm 2 . Dry development using 1,1,1,5,5,5-hexafluoroacetylacetone (hfacH) is also possible but shows lower sensitivity (375 mJ/cm 2 ) compared to wet development methods. EUV photoelectron spectroscopy (PES), reflectometry/EUV absorption, total electron yield (TEY), residual gas analysis (RGA), and time-of-flight secondary ion mass spectrometry (TOF-SIMS) were used to investigate the effects of EUV irradiation on aZnMIm resists. Reflectometry experiments reveal an aZnMIm EUV absorption coefficient of 6.2 μm –1 , while PES and TEY analyses show that, compared to poly(4-hydroxystyrene) (PHS), a polymer-based reference resist, aZnMIm emits more primary and secondary electrons but generates fewer slow electrons relative to its primary electron emission; its total electron yield is similar to that of poly(methyl methacrylate) (PMMA) resists. When exposed to EUV, aZnMIm predominantly outgasses H 2 , as determined by RGA. TOF-SIMS measurements demonstrate that high-dose EUV exposure only partially fragments the 2-methylimidazole (2MIm) organic linkers, unlike high-dose electron beam exposure, which is known to completely degrade them. Additionally, aZnMIm resists show promise for potential beyond EUV lithography (BEUVL) due to the presence of Zn, which provides higher sensitivity at a wavelength of 6.7 nm compared to other metal ions, such as Sn, that are currently used in the best-performing EUV metal–organic resists. TEY measurements demonstrate that aZnMIm emits nearly twice as many electrons as PHS at 6.7 nm. The BEUV TEY of aZnMIm also surpasses that of PMMA, poly(pentafluorostyrene), and poly(4-iodostyrene), with the latter two being known for their high EUV TEYs. This work provides insight into zeolitic imidazolate framework (ZIF)-based EUV and BEUV resists and highlights their potential for both wet and dry development.

lithography↗
DOE OSTI2026

A worldwide climatology of extreme air masses

Extreme temperature events are among the most damaging weather phenomena. In a warming world, more heat extremes and fewer cold extremes are expected in most regions in the future, a trade-off that warrants further understanding of such events. Here, we track and analyze large, persistent areas of hot and cold extreme temperatures in parallel, relative to the location and time of year, to quantify overall regional exposure to extreme temperatures. To accomplish this, we compare the frequencies, movements, trends, and sources/sinks in each type of extreme air mass, calling them extreme cold or extreme hot air masses (ECAMs/EHAMs). For most land regions, ECAMs occur more often than EHAMs, and ECAMs are more common in each hemisphere’s winter, when cold-air advection is strongest and most widespread. Average movement of ECAMs has a stronger equatorward component in winter than in summer, while movement of EHAMs is eastward all year, with less meridional movement than ECAMs. EHAMs have become more common almost everywhere on land, and the reverse is true for ECAMs, with the strongest trends in the northern hemisphere occurring in autumn, especially in the Arctic. The number of EHAMs around the world is increasing at a higher rate (+ 2.32 events/year) than ECAM numbers are decreasing (-1.27 events/year), causing a net increase in extremes, especially in some midlatitude regions. These results help to document the different processes driving hot and cold extremes, and thus the asymmetric and regionally varying trends in frequency for extreme air masses.

Ryan, James M↗
DOE OSTI2024

Trends and meteorological drivers of extreme daily reservoir evaporation events in the western United States

Extreme daily evaporation from reservoir surfaces can lead to significant short-term water losses, affecting water quality, water supply, and reservoir operation strategies. Historical trends in daily reservoir evaporation events have eluded the scientific and operational communities, largely due to a lack of long-term, consistent data record. This study quantifies trends in extreme daily reservoir evaporation events at 165 major reservoirs located in the western U.S. Here, we use the place-based energy balance and aerodynamic Daily Lake Evaporation Model (DLEM) driven by multiple meteorological data products (RTMA, gridMET, Daymet) to estimate daily evaporation rates at these reservoirs from 1981 to 2022. The results—while are based on different meteorological forcing datasets—consistently indicate that the California, Lower Colorado, and Rio Grande hydrologic regions are more prone to higher daily evaporation extremes. Compared to the rest of western U.S, these three regions also experience a more pronounced increasing trend in the annual maximum daily evaporation rate, at about 0.3 mm day -1 decade -1 during 1981-2022. The results show that heat and dryness are the main drivers to the increasing trend of extreme evaporation, while extreme wind speed is the primary contributor to exceptionally high daily evaporation events across all regions. This phenomenon is particularly prominent in the arid Lower Colorado region, but less significant in the cold and humid Pacific Northwest region. We also find that the correlation between extreme wind speed and extreme evaporation degrades as the time scale increases from daily, to monthly and seasonal. Our findings have strong implications for the pattern and distribution of extreme evaporation events at the western U.S. reservoirs, and illustrate how various drivers influence extreme evaporation across different time scales.

13 HYDRO ENERGY↗
DOE OSTI2025

Aerosol Decline Accelerates the Increasing Extreme Precipitation in China

Extreme precipitation is becoming more intense and frequent. The increasing trends in extreme precipitation in China in warm season related to changes in aerosols and greenhouse gases (GHGs) are investigated using observations, reanalysis data and model simulations. A significant accelerating increase in extreme precipitation occurred around 2010, with the trend in accumulated extreme rainfall amount (R95pTOT) increasing from 2.88 mm per decade during 2000–2010 to 22.88 mm per decade during 2010–2023. The sudden acceleration of the increasing extreme precipitation is largely attributed to the reverse in aerosol trends associated with China’s clean air actions, which affects extreme precipitation through perturbing cloud microphysics and atmospheric dynamics, accounting for half of the change in R95pTOT trends. Future aerosol reduction to achieve carbon neutrality is shown to continue to intensify the extreme precipitation, which overweighs the effect induced by GHGs, highlighting the importance of aerosol changes in modulating future climate and weather extremes.

58 GEOSCIENCES↗
DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗
DOE OSTI2024

Extreme Precipitation Over the Southern Slope of the Tibetan Plateau and the Associated Atmospheric Circulation Anomalies

The southern slope of the Tibetan Plateau (SSTP) is one of the rainiest regions in the world where geological hazards caused by extreme precipitation often occur. This study investigates the characteristics and mechanisms of extreme precipitation over SSTP from June to September during 2001–2020 using Global Precipitation Measurement satellite observation. The extreme precipitation days are defined as the days with top 5% of regional-mean daily precipitation over SSTP in this period, which has an average precipitation of 27.2 mm/d. Averaging over the extreme precipitation days, precipitation peaks at an altitude of about 300 m, coinciding with the climatological maximum precipitation, but with a much larger value of 37.2 mm/d than the climatology of 11.9 mm/d. Composite analysis of circulations on extreme days reveals significant circulation anomalies in both the lower and upper troposphere. Specifically, the lower-tropospheric circulations are characterized by significant westerly anomalies over northern India, and the upper-tropospheric circulations are characterized by northerly anomalies over the central Tibetan Plateau, which are statistically independent. The lower-tropospheric westerly anomalies blowing toward SSTP are blocked by the topography, favoring extreme precipitation over SSTP. The upper-tropospheric northerly anomalies, on the other hand, correspond to anomalous northeasterlies north of SSTP in the middle troposphere and southeasterlies to the south in the lower troposphere, and the convergence of these circulation anomalies favors extreme precipitation over SSTP. Lastly, the lower-tropospheric westerly and upper-tropospheric northerly anomalies, respectively, correspond to less precipitation over the South Asian monsoon region and the Tibetan Plateau.

Extreme precipitation, Tibetan Plateau↗
DOE OSTI2024

Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Abstract Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Advancing extreme pulsed lasers through measurements: summary of the pulsed laser metrology workshop

In this report we present consensus findings produced during the pulsed laser metrology (PLM) workshop (Boulder, CO, USA, August 2025). The workshop was a meeting of 35 scientists from private industry, academia, and U.S. government to compile a list of the metrology needs to support extreme pulsed laser development and implementation. We define ‘extreme pulsed lasers’ loosely as those with peak powers above 1 TW or multi-Joule pulse energies. Such lasers are being increasingly used and investigated for use in high energy particle acceleration, short wavelength radiation generation, laser-based fusion, etc. The rapid growth of these fields and the proliferation of extreme lasers for these applications, coupled with the extreme electric fields they generate and relative scarcity of such lasers, presents unique challenges to accuracy in their measurement. The PLM workshop was a two-day event designed to hear from users, developers, and researchers on the current state of optical metrology associated with these extreme pulsed lasers. The goal was to identify the most important measurement challenges limiting development and implementation of these lasers in practical applications. We report here the conclusions and recommendations of this workshop. The hope is that this document will become the first of many iterations which track the status of measurement needs supporting extreme pulsed lasers.

Lasers↗
DOE OSTI2024

Light rain exacerbates extreme humid heat

Abstract Humid heat waves pose significant risks to human health and the ecosystem. Intuitively, rainfall often alleviates extreme humid heat. However, here we show that light rain often accompanies extreme humid heat, exacerbating its frequency and intensity, especially over arid and semi-arid regions compared to no rain and moderate-to-heavy rain cases. This is because light rain does not dramatically reduce solar radiation but increases near-surface humidity through enhanced surface evaporation. The water replenishment from light rain as well as a shallower planetary boundary layer is crucial for consecutive extremes where there are commonly sporadic drizzle days amidst several rain-free days. These extremes last longer than rain-free extremes. Current global climate models (GCMs) overestimate light rain. After reducing this bias in a GCM, underestimations of humid heat waves in energy-limited regions and overestimations in water-limited regions are largely alleviated. These findings underscore the underappreciated impact of light rain on extreme humid heat.

Science & Technology - Other Topics↗
DOE OSTI2025

Weather and climate extremes in a changing Arctic

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.

atmospheric dynamics↗
DOE OSTI2025

Variational AutoEncoders Reveal Intensifying GPP Extremes in Continental United States based on CESM2 Simulations

Climate extremes significantly impact terrestrial carbon cycle dynamics, necessitating robust methods for detecting and analyzing anomalous behavior in plant productivity. This study presents a novel application of variational autoencoders (VAE) for identifying extreme events in gross primary productivity (GPP) from Community Earth System Model version 2 simulations across four AR6 regions in the Continental United States. We compare VAE-based anomaly detection with traditional singular spectral analysis (SSA) methods across three time periods: 1850-80, 1950-80, and 2050-80 under SSP5-8.5 scenario. The VAE architecture employs three dense layers and a latent space with input sequence length of 12 months, training on normalized GPP time series to reconstruct the GPP and identify anomalies based on reconstruction errors. Extreme events are defined using 5th percentile thresholds applied to both VAE and SSA anomalies. Results demonstrate strong regional agreement between VAE and SSA methods in spatial patterns of extreme event frequencies, despite VAE consistently producing higher threshold values (179-756 GgC for VAE vs. 100-784 GgC for SSA across regions and periods). Both methods reveal increasing magnitudes and frequencies of negative carbon cycle extremes toward 2050-80, particularly in Western and Central North America. The VAE approach shows comparable performance to established SSA techniques while offering computational advantages and enhanced capability for capturing non-linear temporal dependencies in carbon cycle variability. This research demonstrates the potential of deep learning approaches for extremes detection and provides a foundation for improved understanding of future carbon cycle risks under future conditions.

Sharma, Bharat [ORNL] (ORCID:0000000266982487)↗
DOE OSTI2024

On the relationship between precipitation extreme and local temperature over eastern China based on convection permitting simulations: roles of different moisture processes and precipitation types

The Clausius–Clapeyron (CC) scaling, which indicates a roughly 7% increase in saturated water vapor per 1 °C increase in temperature, can serve as a strong constraint linking the intensity of precipitation extremes and local temperature. However, the relationship between precipitation extreme and local temperature (referred to as the PE-T relationship) does not always follow the CC scaling and is highly dependent on climate regimes. In this study, we investigated the impacts of different moisture processes and precipitation types on the PE-T relationship over eastern China during the summertime based on convection-permitting model simulations. Consistent with observations, the simulated intensity of precipitation extremes increases with temperature at a rate close to CC (double-CC) scaling below (above) 20 °C. When the temperature exceeds 25 °C, precipitation intensity starts to drop. Precipitation extremes are mainly contributed by the stratiform, MCS (i.e., mesoscale convective system) convective, and non-MCS convective precipitation at low (< 20 °C), medium (20–25 °C), and high (> 25 °C) temperatures, respectively, suggesting that the double-CC scaling occurs when convective types become dominant, while the negative scaling at high temperatures is attributed to the reduced horizontal scale of convection. Corresponding to the reduced intensity of precipitation at high temperatures, there are stronger divergence and subsidence in the low-level atmosphere, which is probably caused by the net cooling associated with the enhanced melting and evaporation of falling hydrometeors due to the lower relative humidity in the low-level atmosphere. Overall, our findings contribute to a deeper understanding of the temperature dependence of precipitation extremes in eastern China.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Extreme hydroclimates amplify the biophysical effects of advanced green-up in temperate China

Vegetation phenology modulates climate by altering energy and water exchange between the land and atmosphere. However, how extreme hydroclimatic conditions modify these phenology-climate feedbacks is still poorly understood. Here, in this study, we used a land–atmosphere-coupled Weather Research and Forecasting model to explore the impacts of advanced green-up on air temperature under different hydroclimate conditions across temperate China and to Mechanistic analysis elucidate the underlying biophysical mechanisms. By imposing a 14-day earlier green-up in line with recent satellite observations, we found that under mean climate conditions, an earlier leaf-out induces immediate surface cooling of 0.14 °C during green-up and a lagging 0.02 °C warming during senescence averaged for temperate China. Extremely humid conditions amplify the cooling effects to 0.18 °C during green-up, extending this cooling into the senescence period. Conversely, under extremely arid conditions, earlier green-up cools air temperature by 0.09 °C, and amplified senescence warming to 0.16 °C. Mechanism analysis revealed that evapotranspiration-dominated non-radiative processes drive immediate cooling during green-up while radiation and circulation process dominates the delayed but opposite warming/cooling effects during senescence in extremely arid/humid hydroclimates. Given the projected continuation of warming trends and increased frequency of extreme climatic events, it is imperative to incorporate the biophysical effects of vegetation phenology into local climate adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Data-Driven Method for Synthetic Extreme Weather Generation and Solar Impact Assessment: Preprint

High-resolution, high-fidelity weather datasets are essential for testing and evaluating the resilience of power systems, particularly under extreme weather conditions. However, existing extreme weather datasets are typically derived from historical events that are localized and may lack the spatial and temporal resolution or scenario diversity needed to test largescale power systems. In this work, we propose a synthetic extreme weather simulation approach capable of generating targeted extreme events, such as hurricanes, using publicly available data sources. Preliminary results demonstrate the impact of a simulated Category 1 hurricane on renewable generation and critical infrastructure in California. The work aims to provide a flexible approach for creating multiple types of extreme weather scenarios across different regions, enabling comprehensive system stress testing, training, and resilience assessment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Leveraging Extremal Dependence to Better Characterize the 2021 Pacific Northwest Heatwave

Abstract In late June, 2021, a devastating heatwave affected the US Pacific Northwest and western Canada, breaking numerous all-time temperature records by large margins and directly causing hundreds of fatalities. The observed 2021 daily maximum temperature across much of the U.S. Pacific Northwest exceeded upper bound estimates obtained from single-station temperature records even after accounting for anthropogenic climate change, meaning that the event could not have been predicted under standard univariate extreme value analysis assumptions. In this work, we utilize a flexible spatial extremes model that considers all stations across the Pacific Northwest domain and accounts for the fact that many stations simultaneously experience extreme temperatures. Our analysis incorporates the effects of anthropogenic forcing and natural climate variability in order to better characterize time-varying changes in the distribution of daily temperature extremes. We show that greenhouse gas forcing, drought conditions and large-scale atmospheric modes of variability all have significant impact on summertime maximum temperatures in this region. Our model represents a significant improvement over corresponding single-station analysis, and our posterior medians of the upper bounds are able to anticipate more than 96% of the observed 2021 high station temperatures after properly accounting for extremal dependence. Supplementary materials accompanying this paper appear online.

Zhang, Likun (ORCID:0000000154584556)↗