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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Summer Convective Precipitation Changes Over the Great Lakes Region Under a Warming Scenario

To understand future summer precipitation changes over the Great Lakes Region (GLR), we performed an ensemble of regional climate simulations through the Pseudo-Global Warming (PGW) approach. We found that different types of convective precipitation respond differently to the PGW signal. Isolated deep convection (IDC), usually concentrated in the southern domain, shows an increase in precipitation to the north of the GLR. Mesoscale convective systems (MCSs), usually concentrated upwind of the GLR, shift to the downwind region with increased precipitation. Thermodynamic variables such as convective available potential energy (CAPE) and convective inhibition energy (CIN) are found to increase across almost the entire studied domain, creating a potential environment more favorable for stronger convection systems and less favorable for weaker ones. Meanwhile, changes in the lifting condensation level (LCL) and level of free convection (LFC) show a strong correlation with variations in convective precipitation, highlighting the significance of these thermodynamic factors in controlling precipitation over the domain. Our results indicate that the decrease in LCL and LCF in areas with increased convective precipitation is mainly due to increased atmospheric moisture. In response to the prescribed warming perturbation, MCSs occur more frequently downwind, while localized IDCs exhibit more intense rain rates, longer durations, and larger rainfall area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Moisture Sources of Precipitation in the Great Lakes Region: Climatology and Recent Changes

Abstract Given the critical role of precipitation on hydroclimate, we quantified the contributions of moisture source regions to precipitation in the Great Lakes Region (GLR) using multiple reanalysis data sets. Results show that the Great Plains (GPs) and the GLR itself are the primary sources of moisture. The moisture sources for the double peaks in the GLR precipitation that occur in June and September are identified, which is caused by a shift in the peak timing of moisture contribution from the GLR and GPs. In particular, moisture from the GPs contributes more to the heavy precipitation, while moisture from the GLR contributes more to the light precipitation. We also found a statistically significant ( p < 0.05) increasing trend in the moisture contribution from the mid‐Pacific, caused by an intensified zonal moisture transport from the mid‐Pacific through changes in atmospheric circulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An Extension Industrial Assessment Center in Eastern Great Lakes Region

The extension IAC at CWRU is funded for 3 years to conduct 10 assessments of small and medium-sized manufacturing facilities each year in Eastern Great Lakes region. Total 30 assessments was proposed in the SOPO but due to the Covid-19 pandemic, the IAC program was suspended for 1.5 years. A total of 20 assessments was contracted to the extension IAC at CWRU which have been successfully accomplished. In the proposal, we proposed to train 18 students in the extension IAC program, and actually we selected and trained 19 students even though the IAC project was suspended during half of its project period.

42 ENGINEERING↗
DOE OSTI2022

Intercomparison of Dynamically and Statistically Downscaled Climate Change Projections over the Midwest and Great Lakes Region

Downscaling of global climate model (GCMs) simulations is a key element of regional-to-local-scale climate change projections that can inform impact assessments, long-term planning, and resource management in different sectors. Here, we conduct an intercomparison between statistically and dynamically downscaled GCMs simulations using the hybrid delta (HD) and the Weather Research and Forecast (WRF) Model, respectively, over the Midwest and Great Lakes region to 1) validate their performance in reproducing extreme daily precipitation (P) and daily maximum temperature (T max ) for summer and winter and 2) evaluate projections of extremes in the future. Our results show the HD statistical downscaling approach, which includes large-scale bias correction of GCM inputs, can reproduce observed extreme P and T max reasonably well for both summer and winter. However, raw historical WRF simulations show significant bias in both extreme P and T max for both seasons. Interestingly, the convection-permitting WRF simulation at 4-km grid spacing does not produce better results for seasonal extremes than the WRF simulation at 12 km using a parameterized convection scheme. Despite a broad similarity for winter extreme P projections, the projected changes in the future summer storms are quite different between downscaling methods; WRF simulations show substantial increases in summer extreme precipitation, while the changes projected by the HD approach exhibit moderate decreases overall. The WRF simulations at 4 km also show a pronounced decoupling effect between seasonal totals and extreme daily P for summer, which suggests that there could be more intense summer extremes at two different time scales, with more severe individual convective storms combined with longer summer droughts at the end of the twenty-first century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Comparative productivity of six bioenergy cropping systems on marginal lands in the Great Lakes Region, United States

Abstract Growing lignocellulosic crops on marginal lands is a promising solution for sustainable biofuel production. We evaluated the productivity of bioenergy cropping systems (switchgrass [ Panicum virgatum L., var. Cave‐In‐Rock], miscanthus [ Miscanthus × giganteus , ‘Illinois clone’], hybrid poplar [ Populus nigra × P. maximowiczii A. Henry ‘NM6’], native grasses [five species], early successional vegetation, and restored prairie vs. historical vegetation [as reference control]) with and without nitrogen fertilization on low‐fertility former cropland at five sites in the Great Lakes Region, United States. We reported biomass yields for the first 7 years after establishment. Switchgrass was most consistently productive across all sites but miscanthus was more productive at three of the five sites. When averaged across sites, years, and nitrogen (N) treatments, biomass yields followed the order miscanthus > switchgrass > hybrid poplar ≈ native grasses > restored prairie > early successional vegetation ≈ historical vegetation, but varied substantially by crop and site, with a significant crop by site interaction. Yields of miscanthus and switchgrass peaked after four–five growing seasons and declined thereafter, while yields of both native grasses and restored prairie increased throughout 6 years with no sign of follow‐on decline, suggesting that polycultures may outperform monocultures over the long term. Yields of early successional vegetation—similar in composition to historical vegetation at each site—did not improve with time. Nitrogen fertilization increased the yields of all cropping systems at all sites. Our results demonstrate the viability of low‐productivity former cropland for long‐term bioenergy production and suggest there is no single crop best suited for all low fertility soils.

Jayawardena, Dileepa M.↗
DOE OSTI2025

Rising Water Levels and Vegetation Shifts Drive Substantial Reductions in Methane Emissions and Carbon Dioxide Uptake in a Great Lakes Coastal Freshwater Wetland

ABSTRACT Coastal freshwater wetlands are critical ecosystems for both local and global carbon cycles, sequestering substantial carbon while also emitting methane (CH 4 ) due to anoxic conditions. Estuarine freshwater wetlands face unique challenges from fluctuating water levels, which influence water quality, vegetation, and carbon cycling. However, the response of CH 4 fluxes and their drivers to altered hydrology and vegetation remains unclear, hindering mechanistic modeling. To address these knowledge gaps, we studied an estuarine freshwater wetland in the Great Lakes region, where rising water levels led to a vegetation shift from emergent Typha dominance in 2015–2016 to floating‐leaved species in 2020–2022. Using eddy covariance flux measurements during the peak growing season (June–September) of both periods, we observed a 60% decrease in CH 4 emissions, from 81 ± 4 g C m −2 in 2015–2016 to 31 ± 3 g C m −2 in 2020–2022. This decline was driven by two main factors: (1) higher water levels, which suppressed ebullitive fluxes via increased hydrostatic pressure and extended CH 4 residence time, enhancing oxidation potential in the water column; and (2) reduced CH 4 conductance through plants. Net carbon dioxide (CO 2 ) uptake decreased by 90%, from −267 ± 26 g C m −2 in 2015–2016 to −27 ± 49 g C m −2 in 2020–2022. Additionally, diel CH 4 flux patterns shifted, with a distinct morning peak observed in 2015–2016 but absent in 2020–2022, suggesting changes in plant‐mediated transport and a potential decoupling from photosynthesis. The dominant factors influencing CH 4 fluxes shifted from water temperature and gross primary productivity in 2015–2016 to atmospheric pressure in 2020–2022, suggesting an increased role of ebullition as a primary transport pathway. Our results demonstrate that changes in water levels and vegetation can substantially alter CH 4 and CO 2 fluxes in coastal freshwater wetlands, underscoring the critical role of hydrological shifts in driving carbon dynamics in these ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Biogeochemistry of upland to wetland soils, sediments, and surface waters across Mid-Atlantic and Great Lakes coastal interfaces

Transferable and mechanistic understanding of cross-scale interactions is necessary to predict how coastal systems respond to global change. Cohesive datasets across geographically distributed sites can be used to examine how transferable a mechanistic understanding of coastal ecosystem control points is. To address the above research objectives, data were collected by the EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Consortium – a regionally distributed network of researchers that collaborated on experimental design, methodology, collection, analysis, and publication. The EXCHANGE Consortium collected samples from 52 coastal terrestrial-aquatic interfaces (TAIs) during Fall of 2021. At each TAI, samples collected include soils from across a transverse elevation gradient (i.e., coastal upland forest, transitional forest, and wetland soils), surface waters, and nearshore sediments across research sites in the Great Lakes and Mid-Atlantic regions (Chesapeake and Delaware Bays) of the continental USA. The first campaign measures surface water quality parameters, bulk geochemical parameters on water, soil, and sediment samples, and physicochemical parameters of sediment and soil.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Lake-Effect Snowstorm Events and Associated Snowfall Totals Integrated from NOAA Storm Reports, ERA5, and HRRR for the Laurentian Great Lakes (1997–2024)

Lake-effect snowstorms are localized, impactful winter weather phenomena that can generate substantial snowfall totals and pose significant challenges for forecasting, transportation, and regional infrastructure. To support the analysis and modeling of these events, this dataset compiles observational reports of lake-effect snowstorms alongside corresponding snowfall estimates derived from gridded atmospheric datasets. The observational component of the data originates from the National Weather Service (NWS) winter storm report, subset to lake-effect snow event type, covering 1997–2024. For each lake-effect snow event, this data provides the impacted county, event start and end datetimes at an hourly resolution, as well as relevant storm narratives. The complementary reanalysis-derived data is sourced from European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) and High-Resolution Rapid Refresh (HRRR) gridded data. For both gridded datasets, the maximum total snowfall (in units mm) was extracted, constrained by the county and datetimes specified by the observational report. ERA5 data covers the entire observational period (1997–2024), whereas HRRR data is only available from November 2016 – December 2024. Three CSV files are provided here: (1) the observational lake-effect snow event report, (2) ERA5 maximum snowfall detections for each event, and (3) HRRR maximum snowfall detections for each event. Relevant data from the observational files, such as impacted state and county, event datetimes, and event IDs, were included for convenience. Users can inspect and visualize the data using tools such as Microsoft Excel and Python pandas/matplotlib packages. This dataset may support a variety of applications, including climatological analyses of lake-effect snowfall, evaluation of snowfall representation in atmospheric datasets and numerical weather prediction models, and the development of machine learning approaches for detecting or predicting lake-effect snowfall events.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > SOLID↗
DOE OSTI2022

The Melampsora americana Population on Salix purpurea in the Great Lakes Region Is Highly Diverse with a Contributory Influence of Clonality

Shrub willows (Salix spp.) are emerging as a viable lignocellulosic, second-generation bioenergy crop with many growth characteristics favorable for marginal lands in New York State and surrounding areas. Willow rust, caused by members of the genus Melampsora, is the most limiting disease of shrub willow in this region and remains extremely understudied. In this study, genetic diversity, genetic structure, and pathogen clonality were examined in Melampsora americana over two growing seasons via genotyping-by-sequencing to identify single-nucleotide polymorphism markers. In conjunction with this project, a reference genome of rust isolate R15-033-03 was generated to aid in variant discovery. Sampling between years allowed regional and site-specific investigation into population dynamics, in the context of both wild and cultivated hosts within high-density plantings. This work revealed that this pathogen is largely panmictic over the sampled areas, with few sites showing moderate genetic differentiation. These data support the hypothesis of sexual recombination between growing seasons because no genotype persisted across the two years of sampling. Additionally, clonality was determined as a driver of pathogen populations within cultivated fields and single shrubs; however, there is also evidence of high genetic diversity of rust isolates in all settings. This work provides a framework for M. americana population structure in the Great Lakes region, providing crucial information that can aid in future resistance breeding efforts.

Plant Sciences↗
DOE OSTI2020

Physical drivers facilitating a toxigenic cyanobacterial bloom in a major Great Lakes tributary

The Maumee River is the primary source for nutrients fueling seasonal Microcystis -dominated blooms in western Lake Erie's open waters though such blooms in the river are infrequent. The river also serves as source water for multiple public water systems and a large food services facility in northwest Ohio. On 20 September 2017, an unprecedented bloom was reported in the Maumee River estuary within the Toledo metropolitan area, which triggered a recreational water advisory. Here we (1) explore physical drivers likely contributing to the bloom's occurrence, and (2) describe the toxin concentration and bacterioplankton taxonomic composition. A historical analysis using 10-years of seasonal river discharge, water level, and local wind data identified two instances when high-retention conditions occurred over ≥ 10 d in the Maumee River estuary: in 2016 and during the 2017 bloom. Observation by remote sensing imagery supported the advection of cyanobacterial cells into the estuary from the lake during 2017 and the lack of an estuary bloom in 2016 due to a weak cyanobacterial bloom in the lake. A rapid-response survey during the 2017 bloom determined levels of the cyanotoxins, specifically microcystins, in excess of recreational contact limits at sites within the lower 20 km of the river while amplicon sequencing found these sites were dominated by Microcystis . These results highlight the need to broaden our understanding of physical drivers of cyanobacterial blooms within the interface between riverine and lacustrine systems, particularly as such blooms are expected to become more prominent in response to a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Geospatial coherence of surface-atmosphere fluxes in the upper Great Lakes region

Surface-atmosphere fluxes are known to vary at multiple time scales, but uncertainty is high as to how fluxes change spatially within regions. With an increase in the number of eddy covariance towers, we are now able to examine the geospatial coherence of ecosystem fluxes, using time-series correlation. Eighteen sites from Michigan and Wisconsin were used in this study, ranging from 100 m to 600 km apart. Surface-atmosphere fluxes from a six-month period were used to quantify spatial coherence on a pair-wise basis. Using geospatial statistics, carbon and sensible heat (H) fluxes were found to be 95% correlated directly outside of their flux footprint and 56% correlated up to a distance of ~35 km. Latent (LE) and momentum (τ) fluxes were less correlated, 83% directly outside of their flux footprint and 40% at a distance of ~130 km albeit, at a much larger spatial distance than for the carbon and sensible heat fluxes. All fluxes showed strong spectral resonance at diel and seasonal timescales, with 1-, 2- and 3-month periods being common modes of variability among H, LE, and τ fluxes. Results based on Empirical Orthogonal Function show distinct transitions of net ecosystem exchange from fall to winter before photosynthesis or respiration while H and τ do not exhibit coherent trends. Here, this work demonstrates the potential of quantifying geospatial coherence of surface-atmosphere fluxes in the Midwestern United States, with the ability to predict fluxes beyond the spatial limit of a single flux tower footprint. Ultimately, expanding the flux measurements to larger scales would allow better spatial scaling of terrestrial surface-atmosphere fluxes between tower footprint and modeling or remote sensing scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modeled Surface-Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region Using Neural Networks

The eddy covariance (EC) method is one of the most widely used approaches to quantify surface-atmosphere fluxes. However, scaling up from a single EC tower to the landscape remains an open challenge. To address this, we used 63 site years of data to examine simulated annual and growing season sums of carbon fluxes from three paired land-cover type sites of corn, restored-prairie, and switchgrass ecosystems. This was also done across the landscape by modeling fluxes using different land-cover type input data. An artificial neural network (ANN) approach was used to model net ecosystem exchange (NEE), ecosystem respiration (R eco ), and gross primary production (GPP) at one paired site using environmental observations from the second site only. With a mean spatial separation of 11 km between paired sites, we were able to model annual sums of NEE, R eco , and GPP with uncertainties of 20%, 22%, and 8%, respectively, relative to observation sums. When considering the growing season only, model uncertainties were 17%, 22%, and 9%, respectively for the three flux terms. We also show that ANN models can estimate sums of R eco and GPP fluxes without needing the constraint of similar land-cover-type, with annual uncertainties of 12% and 10%. These results provide new insights to scaling up observations from one EC site beyond the footprint of the EC tower to multiple land-cover types across the landscape.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate Drives Modeled Forest Carbon Cycling Resistance and Resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond (resistance) and recover from (resilience) to rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the ED-2.2 model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900, and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes, and interacted with one another. We then calculated metrics of functional ecosystem stability. Modeled gross primary production exhibited a mean resistance of -0.13, -0.23, and -0.42 (unitless) in response to increasing disturbance severity of 45%, 65%, and 85% mortality, respectively; and resilience of 0.002, 0.004, 0.008 (yr-1) respectively. This pattern held true for other carbon fluxes, meaning that in general simulated GPP declined more initially but recovered more quickly from higher mortality. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

EXCHANGE Campaign 2 - Microbial Biomass Collapse (EC2-MBC): Carbon Availability Under Prolonged Flooding in Mid-Atlantic and Great Lakes Coastal Ecosystems

Our collective research focus is on investigating the interaction between carbon availability and microbial demands during prolonged flooding. Through laboratory experiments utilizing freshly collected soil samples from diverse transition zone environments, we aim to simulate flooding and understand the mechanisms governing carbon cycling under anoxic conditions. Our primary objective is to elucidate how carbon becomes available to microbes and how they utilize it, discerning between maintenance and investment processes. By examining soils from regions with differing native redox conditions, our aim is to gain comprehensive insights into carbon dynamics across various soil types. Future data types will be added to the ESS-DIVE data package as they are completed and will be version-controlled in the Change History section of EC2_MBC_README.pdf. This data package includes: EC2_MBC_README.pdf flmd.csv dd.csv EC2_SampleIdentificationKey.csv EC2_SoilMoistureKey.csv Processed_GHGFlux_Entisols.csv Processed_GHGFlux_Inceptisols.csv Processed_GHGFlux_Ultisols.csv Processed_Porewater_Iron_II.csv Processed_Porewater_Nutrients.csv Processed_Porewater_Sulfate.csv Processed_Probe_Measurements.csv Processed_Soil_HydrolyticEnzymes.csv Processed_Soil_MicrobialCN.csv Processed_Soil_NPOC_TN_SaltExtracted.csv Processed_Soil_NPOC_TN_WaterExtracted.csv Processed_Soil_Nutrients_OlsenPExtracted.csv Processed_Soil_Nutrients_SaltExtracted.csv Processed_Soil_Nutrients_WaterExtracted.csv Processed_DO_Probe.zip Processed_Temperature_Probe.zip

Carbon Cycling↗
DOE OSTI2026

EXCHANGE Campaign Degradation (ECD): Understanding Decomposition Dynamics Across Mid-Atlantic and Great Lakes Coastal Ecosystems

The EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Degradation Experiment (EXCHANGE-D) is an in situ experiment designed to assess organic matter decomposition rates across coastal terrestrial-aquatic interfaces (TAIs), from coastal uplands through transition zones to wetlands. Through a network of partner scientists and coastal sites, we are testing how environmental gradients shape decomposition and carbon dynamics across terrestrial-aquatic interfaces. Using standardized tea bag substrates deployed across a network of diverse coastal sites, we compare decomposition rates at different fresh- and salt-water TAIs to develop transferable knowledge that improves the representation of organic matter degradation in coastal ecosystem models. For more information, please see https://compass.pnnl.gov/FME/EXCHANGE. This is Version 1 of the data package, which includes: ecd_README.pdf flmd.csv dd.csv ecd_soil_weom_L2.csv ecd_soil_ph_conductivity_L2.csv ecd_soil_gwc_L2.csv ecd_soil_teabag_degradation_L2.csv ecd_readme.pdf

coastal soils↗
DOE OSTI2025

Data for "Implications of Zoning Ordinances for Rural Utility-Scale Solar Deployment and Power System Decarbonization in the Great Lakes Region".

This dataset includes the Energy Zoning Database and geographic shapefiles used to identify suitable rural areas for utility-scale solar development. Additionally, it contains the input data required for the capacity expansion model, including information on existing electric generators and their associated costs, solar resource potential, and transmission infrastructure data. These datasets collectively support the analysis presented in the paper, ensuring a comprehensive assessment of zoning regulations, land suitability, and the economic and technical feasibility of solar deployment in rural areas.

Owusu-Obeng, Papa Yaw (ORCID:0000000334385183)↗