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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Performance Evaluation of Weather@home2 Simulations over West African Region

Weather and climate forecasting, using climate models, have become essential tools and life-savers in the West African region; in spite of the fact that climate models do not fully comply with attributes of forecast qualities—RASAP: reliability, association, skill, accuracy, and precision. The objective of this paper is to quantitatively evaluate, in comparison to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modeling system (w@h2). Findings from some statistical evaluations show that, to a moderately significant extent, w@h2 model provides useful information during the monsoon seasons; skills to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season; ability to reproduce all the annual characteristics of the surface maximum air temperature over the region; as well as skill to detect heat waves that usually ravage West Africa during the boreal spring. The model displays traces of attributes that are needed for seasonal climate predictions and applications. Deficiencies in the quantitative reproducibility point to the facts that the model does provide a reliability akin to that of regional climate models. This paper further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application.

West Africa↗
DOE OSTI2021

Short-term impacts of 2017 western North American wildfires on meteorology, the atmosphere’s energy budget, and premature mortality

Abstract Western North American fires have been increasing in magnitude and severity over the last few decades. The complex coupling of fires with the atmospheric energy budget and meteorology creates short-term feedbacks on regional weather altering the amount of pollution to which Americans are exposed. Using a combination of model simulations and observations, this study shows that the severe fires in the summer of 2017 increased atmospheric aerosol concentrations leading to a cooling of the air at the surface, reductions in sensible heat fluxes, and a lowering of the planetary boundary layer height over land. This combination of lower-boundary layer height and increased aerosol pollution from the fires reduces air quality. We estimate that from start of August to end of October 2017, ∼400 premature deaths occurred within the western US as a result of short-term exposure to elevated PM 2.5 from fire smoke. As North America confronts a warming climate with more fires the short-term climate and pollution impacts of increased fire activity should be assessed within policy aimed to minimize impacts of climate change on society.

Bernstein, Diana N. (ORCID:0000000308279336)↗
DOE OSTI2025

Enhancing Short-Range Weather Forecasts through Temporal Variation Encoding: A Multiperiod Embedding Approach

Machine learning (ML) techniques have emerged as promising approaches to improve regional weather forecast accuracy and reliability through data-driven methods. We propose a novel ML-based weather forecasting model, the Multiperiod Embed Net (MPENet). A key distinguishing feature of MPENet is its explicit utilization of the inherent cyclic nature in weather dynamics, unlike the autoregressive strategies commonly used in other ML weather forecasting approaches. Critical cyclic structures are identified via Fourier analyses of dynamic time series. Cyclicity in the convolutional representation is achieved by transforming one-dimensional time series of meteorological variables into two-dimensional tensors based on identified periods. This approach enables the model to leverage intrinsic weather patterns, enhancing regional forecast performance. To demonstrate the effectiveness of MPENet, we conduct a comparative analysis with Nvidia’s FourCastNet. Both models are trained on High-Resolution Rapid Refresh (HRRR) data from 2015 to 2022, over a 192 km × 192 km region in Tennessee. The comparisons are performed locally at two specific locations known to have different weather dynamics due to orographic effects: Crossville, on the relatively flat Cumberland Plateau with fewer topographic airflow disruptions, and Oak Ridge, in the ridge-and-valley region, where airflow is heavily influenced by surrounding valleys and mountains. Our results indicate that FourCastNet achieves strong accuracy at very short lead times, while MPENet maintains competitive skill and shows advantages in capturing temporal evolution over longer periods. Cross-correlation analyses of MPENet and FourCastNet predictions with the HRRR data suggest that encoding critical cyclicity into the network architecture leads to improvements in the forecasting skill.

Artificial intelligence↗
DOE OSTI2018

Wind energy variability and links to regional and synoptic scale weather

The accurate characterization of seasonal and inter-annual site-level wind energy variability is essential during wind project development. Understanding the features and probability of low-wind years is of particular interest to developers and financers. However, a dearth of long-term, hub-height wind observations makes these characterizations challenging, and thus techniques to improve these characterizations are of great value. To improve resource characterization, we explicitly link wind resource variability (at hub-height, and at specific sites) to regional and synoptic scale wind regimes. Our approach involves statistical clustering of high-resolution modeled wind data, and is applied to California for a period covering 1980–2015. With this approach, we investigate the unique meteorological patterns driving low and high wind years at five separate wind project sites. We also find wind regime changes over the 36-year period consistent with global warming: wind regimes associated with anomalously hot summer days increased at half a day per year and stagnant conditions increased at one-third days per year. Despite these changes, the average annual resource potential remained constant at all project sites. Additionally, we identify correlations between climate modes and wind regime frequency, a linkage valuable for resource characterization and forecasting. Our general approach can be applied in any location and may benefit many aspects of wind energy resource evaluation and forecasting.

17 WIND ENERGY↗
DOE OSTI2022

Limitations of reanalysis data for wind power applications

Wind energy resource estimates commonly depend on simulated wind speed profiles generated by reanalysis or weather models due to the lack of long time series measurements with sufficient coverage at relevant heights (roughly 90 m above ground). However, modeled data, including reanalyses, can be noisy and display a wide range of biases and errors, variously attributed to terrain effects, poor coverage of assimilated inputs, and model resolution. Wind generation records, if available at high temporal and geographical resolution, can provide a proxy for wind measurements and allow for evaluation of reanalyses and weather model wind time series. We use a 7-year-long data set of hourly, plant-level generation records from over 100 wind plants across Texas to evaluate two commonly used reanalysis data sets (MERRA2 and ERA5). Additionally, we use 1-year of records (2019) to evaluate an operational, high-resolution regional weather modeling product (HRRR v3). We find that across the region, and across all modeling products, the modeled representation of wind generation (i.e., wind speeds at hub heights passed through a power curve) has relatively small mean errors when aggregated daily, but that accuracy and hourly correlation have a strong diurnal sensitivity. Accuracy and correlation systematically decline through the evening and markedly improve after sunrise. These diurnal patterns persist even in the highest resolution model tested (HRRR v3). We hypothesize the nighttime decline in accuracy is mostly due to poorly represented boundary layer conditions, perhaps related to model representation of stability, while other uncertainties (such as wake effects) play a secondary role.

17 WIND ENERGY↗
DOE OSTI2017

Daily-scale planetary wave patterns and the modulation of cold season weather in the northern extratropics

Here, tropospheric planetary waves, often linked to asymmetries in lower boundary forcing,significantly modulate atmospheric blocking and storm track structures that are, in turn, linked to extremesurface weather events. Day-to-day variability in the planetary scale circulation, taken as wave numbers 1 to 5in the daily 500 hPa geopotential heights, and the associated impact on storm tracks and regional weather arestudied for the period 1950–2005. Six boreal cold-season distinct planetary wave patterns are identified viahierarchical cluster analysis. The first, second, and sixth patterns feature a prominent zonal wave number 1structure, while the fourth and fifth patterns resemble the negative and positive phases of northern annularmode, respectively. The second pattern represents an amplification of the climatological mean wavestructure, while the third pattern resembles the zonal wave number 3 pattern. A multitaper spectral analysisof the daily projection indices indicates that the planetary wave patterns are primarily intraseasonal innature. The first (sixth) pattern combines the positive (negative) phase of the Pacific-North Americanteleconnection pattern and negative (positive) phase of the North Atlantic Oscillation, inducing poleward(equatorward) shifts in the Pacific storm track and a weakened (strengthened) Atlantic storm track. Incontrast, the fourth (fifth) pattern results in a simultaneous equatorward (poleward) displacement of bothstorm tracks. Extreme cold waves over the continental United States (U.S.) are favored during occurrences ofthe fourth and sixth patterns. During episodes of the first pattern, increased rainfall prevails over much ofthe U.S., while precipitation anomalies induced by the other patterns are more regional in nature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
DOE OSTI2022

Mineralogical, magnetic and geochemical data constrain the pathways and extent of weathering of mineralized sedimentary rocks

The oxidative weathering of sulfidic rock can profoundly impact watersheds through the resulting export of acidity and metals. Weathering leaves a record of mineral transformation, particularly involving minor redox-sensitive phases, that can inform the development of conceptual and quantitative models. In sulfidic sedimentary rocks, however, variations in depositional history, diagenesis and mineralization can change or overprint the distributions of these trace minerals, complicating the interpretation of weathering signatures. Here we show that a combination of bulk mineralogical and geochemical techniques, micrometer-resolution X-ray fluorescence microprobe analysis and rock magnetic measurements, applied to drill core samples and single weathered fractures, can provide data that enable the development of a geochemically consistent weathering model. This work focused on one watershed in the Upper Colorado River Basin sitting within the Mesaverde Formation, a sedimentary sandstone bedrock with disseminated sulfide minerals, including pyrite and sphalerite, that were introduced during diagenesis and subsequent magmatic-hydrothermal mineralization. Combined analytical methods revealed the pathways of iron (Fe), carbonate and silicate mineral weathering and showed how pH controls element retention or release from the actively weathering fractured sandstone. Drill core logging, whole rock X-ray diffraction, and geochemical measurements document the progression from unweathered rock at depth to weathered rock at the surface. X-ray microprobe analyses of a 1-cm size weathering profile along a fracture surface are consistent with the mobilization of Fe(II) and Fe(III) into acidic pore water from the dissolution of primary pyrite, Fe-sphalerite, chlorite, and minor siderite and pyrrhotite. These reactions are followed by the precipitation of secondary minerals such as of goethite and jarosite, a Fe-(oxyhydr)oxide and hydrous Fe(III) sulfate, respectively. Microscale analyses also helped explain the weathering reactions responsible for the mineralogical transformations observed in the top and most weathered section of the drill core. For example, dissolution of feldspar and chlorite neutralizes the acidity generated by Fe and sulfide mineral oxidation, oversaturating the solution in both Fe-oxides. The combination of X-ray spectromicroscopy and magnetic measurements show that the Fe(III) product is goethite, mainly present either as a coating on fracture surfaces in the actively weathering region of the core or more homogeneously contained within the unconsolidated regolith at the top of the core. Low-temperature magnetic data reveal the presence of ferromagnetic Fe-sulfide pyrrhotite that, although it occurs at trace concentrations, could provide a qualitative proxy for unweathered sulfide minerals because the loss of pyrrhotite is associated with the onset of oxidative weathering. Pyrrhotite loss and goethite formation are detectable through room-temperature magnetic coercivity changes, suggesting that rock magnetic measurements can determine weathering intensity in rock samples at many scales. In conclusion, this work contributes evidence that the weathering of sulfidic sedimentary rocks follows a geochemical pattern in which the abundance of sulfide minerals controls the generation of acidity and dissolved elements, and the pH-dependent mobility of these elements controls their export to the ground- and surface-water.

58 GEOSCIENCES↗
DOE OSTI2026

Evaluating technology upgrades as a complement to traditional bill assistance programs

State programs to improve energy affordability and reduce energy burden (the share of income spent on energy) could mitigate concerns about rising electricity prices. Many states offer bill assistance and rebates for weatherization and rooftop solar to income-qualifying households. Here, we analyse how these approaches may complement one another to improve energy affordability. Results illustrate trade offs between program costs and energy burden reduction, as well as between a program’s upfront and ongoing costs. Generally, the three strategies complement one another to improve energy affordability at lower net present cost than bill assistance alone, with varying effects across regions. Weatherization can reduce the solar installation capacity needed, and both together can reduce or eliminate ongoing reliance on bill assistance. Under full uptake among cost-effective households, fully rebated weatherization and solar rebated at $0.48/Watt, combined with bill assistance, yield the same modelled net present cost as bill assistance alone while reducing the share of low-income owner-occupied households with high energy burdens from 66% to 19%, compared with 34% under bill assistance alone. Absent tax credits, weatherization still reduces energy burden and bill assistance program costs, whereas solar may not be cost-competitive.

Forrester, Sydney P↗
DOE OSTI2017

Potential impacts of climate change on the built environment: ASHRAE climate zones, building codes and national energy efficiency

Statement of the Problem: ASHRAE releases updates to 90.1 “Energy Standard for Buildings except Low-Rise Residential Buildings” every three years resulting in a 3.7%-17.3% increase in energy efficiency for buildings with each release. This is adopted by or informs building codes in nations across the globe, is the National Standard for the US, and individual states elect which release year of the standard they will enforce. These codes are built upon Standard 169 “Climatic Data for Building Design Standards,” the latest 2017 release of which defines climate zones based on 8, 118 weather stations throughout the world and data from the past 8-25 years. This data may not be indicative of the weather that new buildings built today, will see during their upcoming 30-120 year lifespan. Methodology & Theoretical Orientation: Using more modern, high-resolution datasets from climate satellites, IPCC climate models (PCM and HadGCM), high performance computing resources (Titan) and new capabilities for clustering and optimization the authors briefly analyzed different methods for redefining climate zones. Using bottom-up analysis of multiple meteorological variables which were the subject matter, experts selected as being important to energy consumption, rather than the heating/cooling degree days currently used. Findings: We analyzed the accuracy of redefined climate zones, compared to current climate zones and how the climate zones moved under different climate change scenarios, and quantified the accuracy of these methods on a local level, at a national scale for the US. Conclusion & Significance: There is likely to be a significant annual, national energy and cost (billions USD) savings that could be realized by adjusting climate zones to take into account anticipated trends or scenarios in regional weather patterns.

New, Joshua Ryan↗
DOE OSTI2023

Evaluating the Representations of Atmospheric Rivers and Their Associated Precipitation in Reanalyses With Satellite Observations

Atmospheric rivers (ARs) are filaments of enhanced horizontal moisture transport in the atmosphere. Due to their prominent role in the meridional moisture transport and regional weather extremes, ARs have been studied extensively in recent years. Yet, the representations of ARs and their associated precipitation on a global scale remains largely unknown. In this study, we developed an AR detection algorithm specifically for satellite observations using moisture and the geostrophic winds derived from 3D geopotential height field from the combined retrievals of the Atmospheric Infrared Sounder and the Advanced Microwave Sounding Unit on NASA Aqua satellite. This algorithm enables us to develop the first global AR catalog based solely on satellite observations. The satellite–based AR catalog is then combined with the satellite–based precipitation (Integrated Muti–SatellitE Retrievals for GPM) to evaluate the representations of ARs and AR–induced precipitation in reanalysis products. Here our results show that the spreads in AR frequency and AR length distribution are generally small across data sets, while the spread in AR width is relatively larger. Reanalysis products are found to consistently underestimate both mean and extreme AR–related precipitation. However, all reanalyses tend to precipitate too often under AR conditions, especially over low latitude regions. This finding is consistent with the “drizzling” bias which has plagued generations of climate models. Overall, the findings of this study can help to improve the representations of ARs and associated precipitation in reanalyses and climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High resolution variability in wet deposition in the southeastern United States

Rainwater chemistry is determined by atmospheric pollutants and particles which vary spatially and temporally. Industrial and agricultural activities and meteorological events (e.g. sea breezes, severe weather, blowing dust) alter atmospheric particle and trace gas compositions. These gases and particles are scavenged by cloud and rain droplets that drive wet deposition. During an Intensive Operation Period (IOP) from April to October 2021, rainwater was collected at higher frequency intervals, usually daily, after precipitation events at three locations on the Savannah River Site (SRS). The farthest locations were separated by approximately 20 km. The mean concentration (μeq/L) of seven ions followed the Cl⁻ > SO 4 2− > Na⁺ > NO 3 ⁻ > K⁺ > Mg 2+ > Ca 2+ downward trend. Ion concentrations were compared to background ion concentrations from the National Atmospheric Deposition Program (NADP). The high frequency monthly averaged SRS data compared well with the monthly averaged NADP background but demonstrated extensive variability. In some months in 2021, the high frequency data compared better to the NADP site near the coast while in other months inland sites compared better. Strong spatial variability for ion concentrations was observed across SRS which was attributed to localized impacts in rainfall spatial variability. High frequency measurements allowed for comparison to regional weather patterns indicating influences from the Atlantic Ocean, Gulf of Mexico, and cities. This can account for spatial variability in the wet deposition flux. Sea breezes, Saharan dust, and anthropogenic sources were shown to impact wet deposition flux variability. Higher frequency precipitation chemistry sampling at numerous locations better captures ion concentration variability and improves measurement representativeness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Responses of summer mesoscale convective systems to irrigation over the North China Plain based on convection-permitting model simulations

Extensive irrigation activities in the North China Plain (NCP) significantly influence regional weather and climate. However, previous studies focusing on the NCP were primarily based on coarse-resolution models, which are unable to explicitly resolve convection systems, causing large uncertainty in precipitation simulations. In this study, a convection-permitting model coupled with a dynamic irrigation scheme is utilized to investigate the impacts of irrigation on summertime mesoscale convective systems (MCSs) over the NCP. Sensitivity experiments with irrigation off and on are conducted for 5 summers and an MCS identification and tracking algorithm is applied to both satellite observations and model simulations. We find that incorporating irrigation in the model increases MCS precipitation, which agrees more with observations. The probability distributions of MCS lifetime, area, propagation speed, and intensity are all better simulated with irrigation. Irrigation increases the occurrence frequency of MCSs throughout the entire day. The nighttime increase is partly because of more frequent local initiation of MCS developed from isolated deep convection, while the daytime increase is mainly attributed to the changes in MCSs initiating elsewhere and then propagating to the NCP. On average, irrigation induces additional moisture that is more thermodynamically favorable for precipitation, but this effect is partially offset by the weakened ascending air motion primarily caused by irrigation surface cooling. Compared to weak MCS precipitation events, strong MCS precipitation events experience greater enhancement in precipitation intensity when including irrigation because the offset effect from the change in large-scale ascending air motion is insignificant. In addition, irrigation makes the variation of MCS precipitation intensity more correlated with the variation in ascending motion but less correlated with that in atmospheric moisture. Our results suggest the pronounced impacts of irrigation on MCSs over the NCP which should be included in numerical models to improve regional precipitation simulation and prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Polymers in direct air capture: a mini review

The urgent need to mitigate climate change has intensified interest in direct air capture (DAC) technology, which targets extracting carbon dioxide (CO2) directly from the atmosphere. Among the various sorbents used in DAC, polymers have emerged as a promising solution, either as active sorbents or as structural supports for active DAC materials, due to their customizable properties, scalability and low cost. This mini-review investigates the latest trends in polymer-based materials for DAC and identifies critical research gaps, such as the need for thorough lifecycle assessments and in-depth studies on the degradation of polymeric materials. It also outlines future directions, emphasizing the importance of developing cost-effective, scalable and durable polymers that can perform efficiently across diverse climatic conditions, including the unique challenges presented by cold weather regions abundant in renewable energy. This mini-review aims to inform ongoing efforts in the design and utilization of polymeric sorbents, providing insights that could guide the development of economically viable and environmentally sustainable DAC technologies.

climate change↗
DOE OSTI2019

Modeling Analysis of the Swell and Wind-Sea Climate in the Salish Sea

Accurate model hindcast of wave climate in complex estuarine systems is challenging because high-resolution wave model and wind forcing are required. In this study, a modeling approach using the unstructured-grid Simulating WAves Nearshore and wind product from a high-resolution regional Weather Research and Forecasting hindcast was used to simulate the swell and wind-sea climate in the Salish Sea, a large estuary with many interconnected waterways on the Pacific Northwest coast of North America. The model hindcast was validated with observed data at four wave buoys in the Salish Sea. Spatial distribution and seasonal variations of wave climate in the Salish Sea were analyzed. Of the three major basins in the Salish Sea, the Strait of Juan de Fuca has the largest waves and is dominated by swells propagated from the Pacific Ocean. Significant wave heights in the Strait of Georgia have spatial and seasonal distribution patterns similar to those found in the Strait of Juan de Fuca. Waves in Puget Sound are small and primarily dominated by the wind-sea climate. Strong seasonal variations are observed in the Strait of Juan de Fuca and Strait of Georgia, but there is little seasonality of wave climate in Puget Sound. The high-resolution wave hindcast conducted in this study provides a comprehensive and important data set for better understanding the role of wave climate in coastal processes and natural hazards assessment in the Salish Sea.

wave climate, salish sea, modeling, swell, sea sta↗
DOE OSTI2024

Systematic Underestimation of Canopy Conductance Sensitivity to Drought by Earth System Models

The response of vegetation canopy conductance (g c ) to changes in moisture availability ($γ^{m}_{gc}$) is a major source of uncertainty in climate projections. While vegetation typically reduces stomatal conductance during drought, accurately modeling how and to what degree stomata respond to changes in moisture availability at global scales is particularly challenging, because no global scale g c observations exist. Here, we leverage a collection of satellite, reanalysis and station-based near-surface air and surface temperature estimates, which are physically and statistically linked to $γ^{m}_{gc}$ due to the local cooling effect of g c through transpiration, to develop a novel emergent constraint of $γ^{m}_{gc}$ in an ensemble of Earth System Models (ESMs). We find that ESMs systematically underestimate $γ^{m}_{gc}$ by ~33%, particularly in grasslands, croplands, and savannas in semi-arid and bordering regions of the Central United States, Central Europe, Southeastern South America, Southern Africa, Eastern Australia, and parts of East Asia. We show that this underestimation occurs because ESMs inadequately reduce g c when soil moisture decreases. As g c controls carbon, water and energy fluxes, the misrepresentation of modeled $γ^{m}_{gc}$ contributes to biases in ESM projections of gross primary production, transpiration, and temperature during droughts. Our results suggest that the severity and duration of droughts may be misrepresented in ESMs due to the impact of sustained g c on both soil moisture dynamics and the biosphere-atmosphere feedbacks that affect local temperatures and regional weather patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Application of Site Controllers for Electrification of Commercial Fleet Vehicles

Electrification of transportation fleets presents a significant challenge for commercial customers. These challenges can be specific to region, weather, operating schedule, charging infrastructure, and other factors. This paper presents the value of integrating a site controller to monitor the health of assets and co-optimize the operation of commercial sites with multiple distributed energy resource technologies and electric vehicle fleets. The tests demonstrate smart-charging and vehicle-to-building uses compared to business-as-usual cases. The secondary objectives of power management for the customer vehicle are optimized by a planning tool (REopt) and integrated using the site controller. Any deviations from the planned dispatch are addressed by the real-time controllers offering tertiary controls, such as energy management, and limiting the reverse power flow (back into the grid). The results indicate that site controllers offer an efficient solution to manage the health of the connected assets and a scalable means to optimize the operations of a commercial customer with electrified transportation fleets.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2021

Climate Extremes and Variability Surrounding Chesapeake Bay: Past, Present, and Future

Measures of extreme climate variability around Chesapeake Bay have changed over the past century (1895–2014), resulting in the need to establish new baselines for understanding future change. Here, observed climate variability is compared with Coupled Model Intercomparison Project fifth assessment climate models to evaluate ensemble model skill in this region. Observed trends include annual and seasonal declines in the percentage of cold days. Similarly, increases in the annual and seasonal percentages of warm days occurred in all seasons of the North Chesapeake (>38.2°N) but were only significant in spring and summer in the South (<38.2°N) demonstrating regional differences even at local scales. Precipitation intensity increased over the past century. Models using emissions scenarios RCP4.5 and 8.5 project these trends will continue, though they have little skill in precipitation extremes. Pacific and Atlantic climate modes are generally more correlated with climate extremes than mean temperature and precipitation suggesting potential predictability in the synoptic patterns underlying the extremes. However, they also drive the need for time series at least 60-years long for establishing climate trends. This local analysis differs from regional, state level, and local 2.5° × 3.75° grid analyses, highlighting the importance of local climate assessments that consider topographic and regional weather patterns.

54 ENVIRONMENTAL SCIENCES↗