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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Modeling CO 2 emissions from A rctic lakes: Model development and site‐level study

Abstract Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one‐dimensional process‐based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO 2 fluxes from the study Arctic lakes. The simulated area‐weighted CO 2 fluxes from yedoma thermokarst lakes, nonyedoma thermokarst lakes, and glacial lakes are 29.5, 13.0, and 21.4 g C m −2 yr −1 , respectively, close to the observed values (31.2, 17.2, and 16.5 ± 7.7 g C m −2 yr −1 , respectively). The simulations show that the high CO 2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight‐induced organic carbon degradation is more important for shallow nonyedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM can simulate the whole‐lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Lake Huron Enhances Snowfall Downwind of Lake Erie: A Modeling Study of the 2010 New Year’s Lake Effect Snowfall Event

In the Northeast and Great Lakes regions of the United States, the influence of multiple lakes on the overlying air can greatly affect lake-effect snowfall over downwind communities. To assess the impact of Lake Huron on snowfall downwind of Lake Erie, we simulated a lake-effect snow event which occurred from 1 to 6 January 2010 using the Regional Atmospheric Modeling System (RAMS). We found that the presence of Lake Huron enhances snowfall downwind of Lake Erie by almost 20% and leads to much heavier local snowfall totals than when Lake Huron is not present. This increase in snowfall is due to a lake-to-lake (L2L) convective band, as secondary circulations associated with lake-effect convection form over Lake Huron and persist overland between the lakes before reintensifying over Lake Erie. As these secondary circulations move over Lake Erie, lifting within the upward branch of the circulations accelerates the development of convection within the L2L band. Surface fluxes and convection over Lake Huron deepen the boundary layer, promoting deeper vertical development of this L2L band over Lake Erie. However, although this boundary layer modification strengthens the L2L band, we found that it actually reduced lake-effect snowfall produced by wind-parallel bands (WPB) in other parts of the lake. This indicates that boundary layer modification from upstream lakes may impact L2L bands differently than WPB which are not connected to upstream secondary circulations.

Lake effects↗
DOE OSTI2010

Lake Granbury and Lake Whitney Assessment Initiative Final Scientific/Technical Report Summary

A team of Texas AgriLife Research, Baylor University and University of Texas at Arlington researchers studied the biology and ecology of Prymnesium parvum (golden algae) in Texas lakes using a three-fold approach that involved system-wide monitoring, experimentation at the microcosm and mesocosm scales, and mathematical modeling. The following are conclusions, to date, regarding this organism's ecology and potential strategies for mitigation of blooms by this organism. In-lake monitoring revealed that golden algae are present throughout the year, even in lakes where blooms do not occur. Compilation of our field monitoring data with data collected by Texas Parks and Wildlife and Brazos River Authority (a period spanning a decade) revealed that inflow and salinity variables affect bloom formations. Thresholds for algae populations vary per lake, likely due to adaptations to local conditions, and also to variations in lake-basin morphometry, especially the presence of coves that may serve as hydraulic storage zones for P. parvum populations. More specifically, our in-lake monitoring showed that the highly toxic bloom that occurred in Lake Granbury in the winter of 2006/2007 was eliminated by increased river inflow events. The bloom was flushed from the system. The lower salinities that resulted contributed to golden algae not blooming in the following years. However, flushing is not an absolute requirement for bloom termination. Laboratory experiments have shown that growth of golden algae can occur at salinities ~1-2 psu but only when temperatures are also low. This helps to explain why blooms are possible during winter months in Texas lakes. Our in-lake experiments in Lake Whitney and Lake Waco, as well as our laboratory experiments, revealed that cyanobacteria, or some other bacteria capable of producing algicides, were able to prevent golden algae from blooming. Identification of this organism is a high priority as it may be a key to managing golden algae blooms. Our numerical modeling results support the idea that cyanobacteria, through allelopathy, control the timing of golden algae blooms in Lake Granbury. The in-lake experiments in Lake Whitney and Lake Waco also revealed that as golden algae blooms develop, there are natural enemies (a species of rotifer, and a virus) that help slow the population growth. Again, better characterization of these organisms is a high priority as it may be key to managing golden algae blooms. Our laboratory and in-lake experiments and field monitoring have shown that nutrient additions will remove toxicity and prevent golden algae from blooming. In fact, other algae displace the golden algae after nutrient additions. Additions of ammonia are particularly effective, even at low doses (much lower than what is employed in fish hatchery ponds). Application of ammonia in limited areas of lakes, such as in coves, should be explored as a management option. The laboratory experiments and field monitoring also show that the potency of toxins produced by P. parvum is greatly reduced when water pH is lower, closer to neutral levels. Application of mild acid to limited areas of lakes (but not to a level where acidic conditions are created), such as in coves, should be explored as a management option. Finally, our field monitoring and mathematical modeling revealed that flushing/dilution at high enough levels could prevent P. parvum from forming blooms and/or terminate existing blooms. This technique could work using deeper waters within a lake to flush the surface waters of limited areas of the same lakes, such as in coves and should be explored as a management option. In this way, water releases from upstream reservoirs would not be necessary and there would be no addition of nutrients in the lake.

58 GEOSCIENCES↗
DOE OSTI2022

A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

Abstract. Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

58 GEOSCIENCES↗
DOE OSTI2022

Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model

Abstract. Lakes in the Arctic are important reservoirs of heat with much lower albedo in summer and greater absorption of solar radiation than surrounding tundra vegetation. In the winter, lakes that do not freeze to their bed have a mean annual bed temperature >0 ∘C in an otherwise frozen landscape. Under climate warming scenarios, we expect Arctic lakes to accelerate thawing of underlying permafrost due to warming water temperatures in the summer and winter. Previous studies of Arctic lakes have focused on ice cover and thickness, the ice decay process, catchment hydrology, lake water balance, and eddy covariance measurements, but little work has been done in the Arctic to model lake heat balance. We applied the LAKE 2.0 model to simulate water temperatures in three Arctic lakes in northern Alaska over several years and tested the sensitivity of the model to several perturbations of input meteorological variables (precipitation, shortwave radiation, and air temperature) and several model parameters (water vertical resolution, sediment vertical resolution, depth of soil column, and temporal resolution). The LAKE 2.0 model is a one-dimensional model that explicitly solves vertical profiles of water state variables on a grid. We used a combination of meteorological data from local and remote weather stations, as well as data derived from remote sensing, to drive the model. We validated modeled water temperatures with data of observed lake water temperatures at several depths over several years for each lake. Our validation of the LAKE 2.0 model is a necessary step toward modeling changes in Arctic lake ice regimes, lake heat balance, and thermal interactions with permafrost. The sensitivity analysis shows us that lake water temperature is not highly sensitive to small changes in air temperature or precipitation, while changes in shortwave radiation and large changes in precipitation produced larger effects. Snow depth and lake ice strongly affect water temperatures during the frozen season, which dominates the annual thermal regime of Arctic lakes. These findings suggest that reductions in lake ice thickness and duration could lead to more heat storage by lakes and enhanced permafrost degradation.

Clark, Jason A. (ORCID:0000000248105261)↗
DOE OSTI2022

Climate projections over the Great Lakes Region: using two-way coupling of a regional climate model with a 3-D lake model

Abstract. Warming trends in the Laurentian Great Lakes and surrounding areas have been observed in recent decades, and concerns continue to rise about the pace and pattern of future climate change over the world's largest freshwater system. To date, most regional climate models used for Great Lakes projections either neglected the lake-atmosphere interactions or are only coupled with a 1-D column lake model to represent the lake hydrodynamics. This study presents a Great Lakes climate change projection that has employed the two-way coupling of a regional climate model with a 3-D lake model (GLARM) to resolve 3-D hydrodynamics essential for large lakes. Using the three carefully selected Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs), we show that the GLARM ensemble average substantially reduces surface air temperature and precipitation biases of the driving GCM ensemble average in present-day climate simulations. The improvements are not only displayed from an atmospheric perspective but are also evident in the accurate simulations of lake temperature and ice coverage. We further present the GLARM projected climate change for the mid-21st century (2030–2049) and the late 21st century (2080–2099) in the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. Under RCP 8.5, the Great Lakes basin is projected to warm by 1.3–2.1 ∘C by the mid-21st century and 4.1–5.0 ∘C by the end of the century relative to the early century (2000–2019). Moderate mitigation (RCP 4.5) reduces the mid-century warming to 0.8–1.8 ∘C and late-century warming to 1.8–2.7 ∘C. Annual precipitation in GLARM is projected to increase for the entire basin, varying from 0 % to 13 % during the mid-century and from 9 % to 32 % during the late century in different scenarios and simulations. The most significant increases are projected in spring and fall when current precipitation is highest and a minimal increase in winter when it is lowest. Lake surface temperatures (LSTs) are also projected to increase across the five lakes in all of the simulations, but with strong seasonal and spatial variability. The most significant LST increases occur in Lakes Superior and Ontario. The strongest warming is projected in spring that persists into the summer, resulting from earlier and more intense stratification in the future. In addition, diminishing winter stratification in the future suggests the transition from dimictic lakes to monomictic lakes by the end of the century. In contrast, a relatively smaller increase in LSTs during fall and winter is projected with heat transfer to the deep water due to the strong mixing and energy required for ice melting. Correspondingly, the highest monthly mean ice cover is projected to reduce to 3 %–15 % and 10 %–40 % across the lakes by the end of the century in RCP 8.5 and RCP 4.5, respectively. In the coastal regions, ice duration is projected to decrease by up to 60 d.

Xue, Pengfei (ORCID:000000025702421X)↗
DOE OSTI2020

Validation and Sensitivity Analysis of a 1-D Lake Model Across Global Lakes

Lakes have important influence on weather and climate from local to global scales. However, their prediction using numerical models is notoriously difficult because lakes are highly heterogeneous across the globe, but observations are sparse. In this study, we assessed the performance of a 1-D lake model in simulating the thermal structures of 58 lakes with diverse morphometric and geographic characteristics by following the phase 2a local lake protocol of the Inter-sectoral Impact Model Intercomparison Project (ISIMIP2a). After calibration, the root-mean-square errors (RMSE) were below 2 °C for 70% and 75% of the lakes for epilimnion and full-profile temperature simulations, with an average of 1.71 °C and 1.43 °C, respectively. The model performance mainly depended on lake shape rather than location, supporting the possibility of grouping model parameters by lake shape for global applications. Furthermore, through machine-learning based parameter sensitivity tests, we identified turbulent heat fluxes, wind-driven mixing and water transparency as the major processes controlling lake thermal and mixing regimes. Snow density was also important for modeling the ice phenology of high-latitude lakes. The relative influence of the key processes and the corresponding parameters mainly depended on lake latitude and depth. Turbulent heat fluxes showed a decreasing importance in affecting epilimnion temperature with increasing latitude. Wind-driven mixing was less influential to lake stratification for deeper lakes while the impact of light extinction, on the contrary, showed a positive correlation with depth. Our findings may guide improvements in 1-D lake model parameterizations to achieve higher fidelity in simulating global lake thermal dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Insights on Simulating Summer Warming of the Great Lakes: Understanding the Behavior of a Newly Developed Coupled Lake-Atmosphere Modeling System

The Laurentian Great Lakes are the world's largest freshwater system and regulate the climate of the Great Lakes region, which has been increasingly experiencing climatic, hydrological, and ecological changes. An accurate mechanistic representation of the Great Lakes thermal structure in Regional Climate Models (RCMs) is paramount to studying the climate of this region. Currently, RCMs have primarily represented the Great Lakes through coupled one-dimensional (1D) column lake models; this approach works well for small inland lakes but is unable to resolve the realistic hydrodynamics of the Great Lakes and leads to inaccurate representations of lake surface temperature (LST) that influence regional climate and weather patterns. This work overcomes this limitation by developing a fully two-way coupled modeling system using the Weather Research and Forecasting model and a three-dimensional (3D) hydrodynamic model. The coupled model system resolves the interactive physical processes between the atmosphere, lake, and surrounding watersheds; and validated against a range of observational data. The model is then used to investigate the potential impacts of lake-atmosphere coupling on the simulated summer LST of Lake Superior. By evaluating the difference between our two-way coupled modeling system and our observation-driven modeling system, we find that coupled-lake atmosphere dynamics can lead to a higher LST during June-September through higher net surface heat flux entering the lake in June and July and a lower net surface heat flux entering the lake in August and September. The unstratified water in June distributes the entering surface heat flux throughout the water column leading to a minor LST increase, while the stratified waters of July create a conducive thermal structure for the water surface to warm rapidly under the higher incoming surface heat flux. This research provides insight into the coupled modeling system behavior, which is critical for enhancing our predictive understanding of the Great Lakes climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Detoured flight direction responses along the southwest coast of Lake Erie by night-migrating birds

Abstract Migratory birds encounter the Great Lakes while moving through eastern North America toward breeding grounds to the North, which offers a good opportunity to study variation in migratory behavior as birds face a potentially influencing topographical feature. Using passive infrared technology, we documented the direction of relatively low-flying, nocturnal, mostly passerine migration in spring along the southern coast of Lake Erie’s western basin. We examined the extent to which spring migrants flew across Lake Erie as a continuation of the inland, northeasterly broad front migratory direction, as determined by weather radar and infrared observations, or displayed a tendency to deviate to more closely follow the direction of the coastline. We found that an estimated 62% of all low-flying migrants deviated their flight directions toward the coast of Lake Erie at 2 coastal sites, Cedar Point and Ottawa, which were characterized by northwest–southeast oriented coastlines. Migrants at a third coastal location, Maumee Bay, which has a more east–west oriented coastline, did not display similarly deviated flight directions. We found that even when winds were energetically favorable for a lake crossing, many migrants still routinely displayed deviated flight directions that approached paralleling the coastline. Further, the mean flight direction at one site, Ottawa, shifted more in the direction of the coastline as the night progressed, suggesting that time of night could influence the shift to a more coastal flight direction. The data indicate that the western basin of Lake Erie acts as a salient topographical feature influencing the flight directions of nocturnal migrants. The data further suggest that birds are making active decisions while in flight, based on current environmental and physiological conditions, about whether to continue to cross Lake Erie or take a coastal detour.

Zoology↗
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 OSTI2017

Nearly a decade-long repeatable seasonal diversity patterns of bacterioplankton communities in the eutrophic Lake Donghu (Wuhan, China)

Uncovering which environmental factors have the greatest influence on community diversity patterns and how ecological processes govern community turnover are key questions related to understanding community assembly mechanisms. Although we have good understanding of plant and animal community assembly, the mechanisms regulating diversity patterns of aquatic bacterial communities in lake ecosystems remains poorly understood. Here we present nearly a decade-long time-series study of bacterioplankton communities from the eutrophic Lake Donghu (Wuhan, China) using 16S rRNA gene amplicon sequencing. We found strong repeatable seasonal patterns for the overall community, common (detected in more than 50% samples) and dominant bacterial taxa (relative abundance > 1%). Moreover, community composition tracked the seasonal temperature gradient, indicating that temperature is an important environmental factor controlling observed diversity patterns. Total phosphorus also contributed significantly to the seasonal shifts in bacterioplankton composition. However, any spatial pattern across the main lake areas was overwhelmed by temporal variability in this eutrophic lake system. Phylogenetic analysis further indicated that 75%-82% of community turnover was governed by homogeneous selection, suggesting that the bacterioplankton communities are mainly controlled by niche-based processes. However, dominant niches available within seasons might be occupied by similar combinations of bacterial taxa with modest dispersal rates throughout this lake system. This study gives us important insights into community assembly and seasonal turnover of lake bacterioplankton, it may be also useful to predict temporal patterns of other planktonic communities.

16S rRNA amplicon sequencing↗
DOE OSTI2021

The LAKE model input dataset for three Arctic lakes

This dataset contains meteorological data collected for three Arctic lakes and compiled to satisfy input requirements of the LAKE 2.0 model. The dataset was generated to act as a benchmarking dataset for future model-data inter-comparisons. The LAKE 2.0 model simulates temperatures within the water later and the sedimentary layer of a lake. The LAKE2.0. is an open-source code and available to download via this weblike http://tesla.parallel.ru/Viktor/LAKE/-/wikis/LAKE-model (last visit July 14, 2021). The meteorological data are required to simulate the surface energy balance at the surface of a lake. This dataset includes a compilation of the meteorological data pulled from multiple data streams, including National Oceanic and Atmospheric Administration (NOAA) climate data, Circumarctic Lakes Observation Network (CALON) data, and the United States Geological Survey (USGS) data. The data were compiled for three Arctic lakes: FoxDen (66.55877, -164.45670), Atqasuk (70.452497, -156.951984), and Toolik (68.63150, -149.60740). Each meteorological data is in comma-delimited format (file extension ‘.dat’) and includes eight columns: Temperature [K], Pressure [Pa], longwave downward radiation [W/m2], shortwave downward radiation [W/m2], “U” wind speed [m/s], ”V” wind speed [m/s], humidity [kg/kg], precipitation [m/s]. In addition to the meteorological data file, we included setup and driver files. The Toolik lake is the deepest out of three lakes and has inflowing and outflowing groundwater data. InflowOutflowREADME.txt has more information about inflow and outflow flies. The other two lakes are much shallower and modeled as a closed system (i.e. no water inflow or outflow).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Coupled Lake‐Atmosphere‐Land Physics Uncertainties in a Great Lakes Regional Climate Model

Abstract This study develops a surrogate‐based method to assess the uncertainty within a convective permitting integrated modeling system of the Great Lakes region, arising from interacting physics parameterizations across the lake, atmosphere, and land surface. Perturbed physics ensembles of the model during the 2018 summer are used to train a neural network surrogate model to predict lake surface temperature (LST) and near‐surface air temperature (T2m). Average physics uncertainties are determined to be 1.5C for LST and T2m over land, and 1.9C for T2m over lake, but these have significant spatiotemporal variations. We find that atmospheric physics parameterizations alone are the dominant sources of uncertainty (45%–53%), while lake and land parameterizations account for 33% and 38% of the uncertainty of LST and T2m over land respectively. Interactions of atmosphere physics parameterizations with those of the land and lake contribute to an additional 13%–17% of the total variance. LST and T2m over the lake are more uncertain in the deeper northern lakes, particularly during the rapid warming phase that occurs in late spring/early summer. The LST uncertainty increases with sensitivity to the lake model's surface wind stress scheme. T2m over land is more uncertain over forested areas in the north, where it is most sensitive to the land surface model, than the more agricultural land in the south, where it is most sensitive to the atmospheric planetary boundary and surface layer scheme. Uncertainty also increases in the southwest during multiday temperature declines with higher sensitivity to the land surface model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Methane emissions from pan-Arctic lakes during the 21st century: An analysis with process-based models of lake evolution and biogeochemistry

The importance of methane emissions from pan-Arctic lakes in the global carbon cycle has been suggested by recent studies. These studies indicated that climate change influences this methane source mainly in two ways: the warming of lake sediments and the evolution of thermokarst lakes. Few studies have been conducted to quantify the two impacts together in a unified modeling framework. Here we adapt a region-specific lake evolution model to the pan-Arctic scale and couple it with a lake methane biogeochemical model to quantify the change of this freshwater methane source in the 21st century. Our simulations show that the extent of thaw lakes will increase throughout the 21st century in the northern lowlands of the pan-Arctic where the reworking of epigenetic ice in drained lake basins will continue. The projected methane emissions by 2100 are 28.3 ± 4.5 Tg CH 4 yr -1 under a low warming scenario (Representative Concentration Pathways (RCPs) 2.6) and 32.7±5.2 Tg CH 4 yr -1 under a high warming scenario (RCP 8.5), which are about 2.5 and 2.9 times the simulated present-day emissions. Most of the emitted methane originates from nonpermafrost carbon stock. For permafrost carbon, the methanogenesis will mineralize a cumulative amount of 3.4 ± 0.8 Pg C under RCP 2.6 and 3.9 ± 0.9 Pg C under RCP 8.5 from 2006 to 2099. The projected emissions could increase atmospheric methane concentrations by 55.0–69.3 ppb. In conclusion, this study further indicates that the warming of lake sediments dominates the increase of methane emissions from pan-Arctic lakes in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Shallow Water Offshore Wind Optimization for the Great Lakes (DE-FOA-0000415) Final Report: A Conceptual Design for Wind Energy in the Great Lakes

The primary objective of the project was to develop a innovative Gravity Base Foundation (GBF) concepts, including fabrication yards, launching systems and installation equipment, for a 500MW utility scale project in the Great Lakes (Lake Erie). The goal was to lower the LCOE by 25%. The project was the first to investigate an offshore wind project in the Great Lakes and it has furthered the body of knowledge for foundations and installation methods within Lake Erie. The project collected historical geotechnical information for Lake Erie and also used recently obtained data from the LEEDCo Icebreaker Project (FOA DE-EE0005989) geotechnical program to develop the conceptual designs. Using these data-sets, the project developed design wind and wave conditions from actual buoy data in order to develop a concept that would de-risk a project using a GBF. These wind and wave conditions were then utilized to create reference designs for various foundations specific to installation in Lake Erie. A project partner on the project (Weeks Marine) provided input for construction and costing the GBF fabrication and installation. By having a marine contractor with experience with large marine projects as part of the team provides credibility to the LCOE developed by NREL. NREL then utilized the design and construction costing information as part of the LCOE model. The report summarizes the findings of the project; Developed a cost model and “baseline” LCOE; Documented Site Conditions within Lake Erie; Developed Fabrication, Installation and Foundations Innovative Concept Designs; Evaluated LCOE Impact of Innovations; Developed Assembly line “Rail System” for GBF Construction and Staging; Developed Transit-Inspired Foundation Designs which incorporated: Semi-Floating Transit with Supplemental Pontoons Barge mounted Winch System; Developed GBF with “Penetration Skirt”; Developed Integrated GBF with Turbine Tower; Developed Turbine, Plant Layout and O&M Strategies. The report details lowering LCOE by 22.3% and identified additional strategies that could further lower LCOE when building an utility scale wind farm in the Great Lakes.

17 WIND ENERGY↗
DOE OSTI2022

Impacts of Lake Surface Temperature on the Summer Climate Over the Great Lakes Region

The surface of the Great Lakes interacts with the atmosphere, influencing the weather and climate over the Great Lakes Region (GLR). However, most climate models were not designed with sufficient emphasis on lake–atmosphere interactions, which could potentially cause model biases over the GLR. To understand how lake surface temperature (LST) affects the regional summer climate over the GLR, we conducted twin experiments using the Weather Research and Forecasting model at a spatial resolution of 4 km using two different LST data sets as the bottom boundary condition over the Great Lakes. In this work, our simulations include 10 ensemble members for the summer of 2018 and a single multiyear run for the summers of 2014–2020. Results show that variations in LST influence atmospheric temperature and moisture at a local scale—while affecting the convective environment and precipitation processes over a much larger spatial scale. In particular, an LST that is only 1°C–3°C warmer (depending on the lake) increases near-surface air temperature by 1.93°C and 0.97°C over Lake Superior and Lake Erie, respectively, and increases evaporation over the lakes by 0.23 and 1.1 mm day –1 . The warmer LST reduces mesoscale convective precipitation upstream of the GLR; however, it increases isolated deep convective precipitation and nonconvective precipitation downstream of GLR due to increased local instability and enhancement of moisture transport. Our analyses confirm the robustness of these impacts, which is at least 2 times larger than the model internal variability and is seen across all simulated summer seasons.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Stable Methane Isotopologues From Northern Lakes Suggest That Ebullition Is Dominated by Sub‐Lake Scale Processes

Abstract Stable isotopes have emerged as popular study targets when investigating emission of methane (CH 4 ) from lakes. Yet little is known on how isotopic patterns conform to variations in emission magnitudes—a highly relevant question. Here, we present a large multiyear data set on stable isotopes of CH 4 ebullition (bubbling) from three small adjacent subarctic lakes. The δ 13 C‐CH 4 and δD‐CH 4 range from −78.4‰ to −53.1‰ and from −369.8‰ to −218.8‰, respectively, and vary greatly among the lakes. The signatures suggest dominant hydrogenotrophic methanogenesis, particularly in the deep zones, but there are also signals of seemingly acetoclastic production in some high fluxing shallow areas, possibly fueled by in situ vegetation, but in‐sediment anaerobic CH 4 oxidation cannot be ruled out as an alternative cause. The observed patterns, however, are not consistent across the lakes. Neither do they correspond to the spatiotemporal variations in the measured bubble CH 4 fluxes. Patterns of acetoclastic and hydrogenotrophic production plus oxidation demonstrate that gains and losses of sediment CH 4 are dominated by sub‐lake scale processes. The δD‐CH 4 in the bubbles was significantly different depending on measurement month, likely due to evaporation effects. On a larger scale, our isotopic data, combined with those from other lakes, show a significant difference in bubble δD‐CH 4 between postglacial and thermokarst lakes, an important result for emission inventories. Although this characteristic theoretically assists in source partitioning studies, most hypothetical future shifts in δD‐CH 4 due to high‐latitude lake area or production pathway are too small to lead to atmospheric changes detectable with current technology.

54 ENVIRONMENTAL SCIENCES↗