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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Interactive Photochemistry in Earth System Models to Assess Uncertainty in Ozone and Greenhouse Gases. Final report

Atmospheric chemistry controls the abundances and hence climate forcing of important greenhouse gases including N 2 O, CH 4 , HFCs, CFCs, and O 3 . Attributing climate change to human activities requires, at a minimum, accurate models of the chemistry and circulation of the atmosphere that relate emissions to abundances. This DOE-funded research provided realistic, yet computationally optimized and affordable, photochemical modules to the Community Earth System Model (CESM) that augment the CESM capability to explore the uncertainty in future stratospheric-tropospheric ozone, stratospheric circulation, and thus the lifetimes of chemically controlled greenhouse gases from climate simulations. To this end, we have successfully implemented Fast-J (radiation algorithm determining key chemical photolysis rates) and Linoz v3.0 (linearized photochemistry for interactive O 3 , N 2 O, NO y and CH 4 ) packages in LLNL-CESM and for the first time demonstrated how change in O2 photolysis rate within its uncertainty range can significantly impact on the stratospheric climate and ozone abundances. From the UCI side, this proposal also helped LLNL develop a CAM-Superfast Chemistry model that was implemented for the IPCC AR5 and contributed chemical-climate simulations to CMIP5.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

GCAP 2.0: A Global 3-D Chemical-Transport Model Framework for Past, Present, and Future Climate Scenarios

This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.

Global Change and Air Pollution (GCAP 2.0) model↗
DOE OSTI2022

Intrinsic Century-Scale Variability in Tropical Pacific Sea Surface Temperatures and Their Influence on Western US Hydroclimate

Hydroclimate variability of the southwest United States (SWUS) is influenced by the tropical Pacific Ocean, particularly through the teleconnection to El Nino/Southern Oscillation (ENSO), which is expected to be altered by climate change. Natural variability in this teleconnection has not been robustly quantified, complicating the detection of anthropogenic climate change. Here, we use a linear inverse model (LIM) to quantify natural variability in the ENSO-SWUS teleconnection. The LIM yields realistic teleconnection patterns with century-scale variability comparable to simulations from the Last Millennium Ensemble project and the Climate Model Intercomparison Project Phases 5 and 6. The variability quantified by the LIM illuminates two aspects of our understanding of ENSO and its impacts: the inherent statistics of the observable system can produce century-long periods with a wide range of correlations to SWUS hydroclimate, including nonsignificant correlations, and thus that detecting changes in ENSO-related hydroclimate variability is challenging in a changing climate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

Importance of Radiative Transfer Models in Atmospheric Remote Sensing

Radiative transfer models (RTMs) play a significant role in the development of satellite instruments for remote sensing applications. These models simulate electromagnetic radiation's propagation through the atmosphere, providing valuable insights into atmosphere-radiation interactions. RTMs facilitate the optimization of satellite instrument designs, ensuring their ability to measure targeted atmospheric and surface properties accurately. Moreover, they aid in simulating instrument’s measurements under various atmospheric conditions, enabling calibration and validation processes to enhance data quality and reliability. RTMs are extensively used in the Observing System Simulation Experiments (OSSE), to generate synthetic observations. By incorporating RTMs into OSSE, we can assess the potential impact of future satellite missions, sensor configurations, and data assimilation techniques. This approach allows for the optimization of satellite instruments and constellations and the evaluation of their influence on weather forecasting, climate monitoring, and other Earth science applications. Another crucial application area of RT models is data assimilation, where they play a fundamental role in combining satellite observations with numerical models to improve atmospheric and environmental predictions. RTMs provide the link between observed radiances and atmospheric parameters, enhancing the accuracy of numerical models and generating more reliable forecasts for weather events, air quality assessments, and climate projections. Moreover, adapting RT models to capture the intricate radiation interactions within the Planetary Boundary Layer will significantly contribute to improving weather forecasting and climate change projections. Current community radiative transfer (RT) models are primarily developed and optimized for operational data assimilation of satellite observations. These models excel at assimilating satellite data into numerical weather prediction models to improve forecast accuracy. However, their focus on data assimilation limits their suitability for other important applications, such as satellite instrument development, OSSE, and Planetary Boundary Layer (PBL) studies. Moreover, for PBL studies, RT models need to be adapted to capture the intricate radiation interactions within this crucial atmospheric layer. Developing RT models that can represent the PBL's unique characteristics, such as surface interactions, will contribute significantly to understanding and predicting weather phenomena, air quality, and climate dynamics. This abstract provides a comprehensive overview of the current status of RT models and highlights their limitations concerning satellite instrument development, OSSE, and PBL studies. Addressing these shortcomings requires concerted efforts to enhance RT models' capabilities and expand their applications beyond data assimilation. By investing in research and development to improve these

Isaac Moradi↗
DOE OSTI2018

A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios

Abstract. To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land-use and climate change on biodiversity and ecosystem services (i.e., nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) – SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6 – to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

58 GEOSCIENCES↗
NASA NTRS2024

The Economics of Farming Expansion in the Brazilian Cerrado Under Possible Effects of Climate Change

This analysis assesses the financial viability of legally investing in native Cerrado vegetation deforestation for crop production, considering climate change. The study uses data from twelve different crop models based on three different climate models to predict potential future crop yields in cleared land for growing soy and maize. The outcomes show that in many micro-regions, investments in clearing land for crop production would destroy economic value, that is, generate a negative net present value because of low/negative and volatile cashflows driven primarily by future yields as affected by climate. Our analysis was carried out based on present agricultural practices and technology. As climate changes, farmers may adapt their practices, which can lead to more resilient and productive crops, or grow different crops, which could provide better returns on investment in clearing land than the ones resulting from our analysis. Despite various uncertainties, farmers, policy makers and financial institutions should be aware of the climatic and financial risks associated with land clearing in Brazil, mainly in micro-regions in which all scenarios resulted in negative outcomes in the investment analysis.

agricultural expansion↗
DOE OSTI2023

Data from "The Influence of Climate Change on Flooding and Social Inequalities from Remnants of Hurricane Ida"

Previous research has demonstrated that tropical cyclone-related precipitation and flooding have been increased by anthropogenic global warming. Our work aims to quantify the contribution of climate change to the deadly flooding from the remnants of Hurricane Ida (2021) and its impact on human society. We developed an analysis framework that combines lessons from climate change attribution science, two-dimensional hydrodynamic modeling, and flood impact evaluation, including a social inequality index, to estimate remnants of Ida flooding and consequences responding to current (locally 1°C warmer) and future (another 1°C warmer) climate change. We find that an additional quarter to a half million people were exposed to flooding due to current and future climate change. The human influence on flood impacts was larger with deeper flood water depth (≥ 1 m) than with shallow depths. Socially vulnerable populations were found to be disproportionately more affected, and climate change exacerbates this inequality

Climate Change↗
DOE OSTI2017

Land management strategies for improving water quality in biomass production under changing climate

Here, the Corn Belt states are the largest corn-production areas in the United States because of their fertile land and ideal climate. This attribute is particularly important as the region also plays a key role in the production of bioenergy feedstock. In much of the nation, agricultural nutrients are a primary cause of water quality degradation. This study focuses on potential change in streamflow, sediment, nitrogen, and phosphorus due to climate change and land management practices in the South Fork Iowa River (SFIR) watershed, Iowa. Thirty-six projections from select Regional Climate Models (RCM) for Representative Concentration Pathways (RCP) 2.5, 4.5, and 8.5 were used to develop climate change scenarios for the SFIR watershed and incorporated into the Soil and Water Assessment Tool (SWAT). The watershed is covered primarily with annual crops (corn and soybeans). Three scenarios of land use change and conservation practices were further developed to examine their impacts on water quality under historical and modeled future climate. With cropland conversion to switchgrass, stover harvest, and best management practices (BMPs) (such as establishing riparian buffers and applying cover crops) significant reductions in nutrients were observed in the SFIR watershed under historical climate and future climate scenarios. Under historical climate, suspended sediment (SS), total nitrogen (N), and phosphorus (P) at the outlet point of the SFIR watershed could decrease by up to 56.7%, 32.0%, and 16.5%, respectively, compare with current land use when a portion of the cropland is converted to switchgrass and cover crop is in place. Climate change could cause an increase in 12.0% (SS), 4.7% (N), and 7.7% (P) from current land use. This increase could be mitigated through land management and practices by 53.6% (SS), 27.8 (N), and 7.0% (P). Climate change reduced crop yield. Nutrient and sediments loadings distributed heterogeneously across the watershed. Water footprint analysis further revealed changes in green water that are highly dependent on land management scenarios. The study highlights the versatile approaches in landscape management that are available to address climate change adaptation and acknowledged the complex nature of different perspectives in water sustainability. Further study involving implementing landscape design and management using long-term field to watershed water monitoring data is necessary to verify the findings and moving towards watershed specific regional programs for climate adaptation.

09 BIOMASS FUELS↗
DOE OSTI2021

An evaluation of size-resolved cloud microphysics scheme numerics for use with radar observations Part II: Condensation and evaporation

Accurate numerical modeling of clouds and precipitation is essential for weather forecasting and climate change research. While size-resolved (bin) cloud microphysics models predict particle size distributions without imposing shapes, results are subject to artificial size distribution broadening owing to numerical diffusion associated with various processes. Whereas Part I of this study addressed collision–coalescence, here we investigate numerical diffusion that occurs in solving condensation and evaporation. In a parcel model framework, all of the numerical schemes examined converge to one solution of condensation and evaporation as the mass grid is refined, and the advection-based schemes are recommended over the reassigning schemes. Including Eulerian vertical advection in a column limits the convergence to some extent, but that limitation occurs at a sufficiently fine mass grid, and the number of iterations in solving vertical advection should be minimized to reduce numerical diffusion. Insubstantial numerical diffusion in solving condensation can be amplified if collision–coalescence is also active, which in turn can be substantially diminished if turbulence effects on collision are incorporated. Here, large-eddy simulations of a drizzling stratocumulus field reveal that changes in moments of Doppler spectra obtained using different mass grids are consistent with those obtained from the simplified framework, and that spectral moments obtained using a mass grid designed to effectively reduce numerical diffusion are generally closer to observations. Notable differences between the simulations and observations still exist, and our results suggest a need to consider whether factors other than numerical diffusion in the fundamental process schemes employed can cause such differences.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

An Evaluation of Size-Resolved Cloud Microphysics Scheme Numerics for use with Radar Observations Part II: Condensation and Evaporation

Accurate numerical modeling of clouds and precipitation is essential for weather forecasting and climate change research. While size-resolved (bin) cloud microphysics models predict particle size distributions without imposing shapes, results are subject to artificial size distribution broadening owing to numerical diffusion associated with various processes. Whereas Part 1 addressed collision-coalescence, here we investigate numerical diffusion that occurs in solving condensation and evaporation. In a parcel model framework, all of the numerical schemes examined converge to one solution of condensation and evaporation as the mass grid is refined, and the advection-based schemes are recommended over the reassigning schemes. Including Eulerian vertical advection in a column limits the convergence to some extent, but that limitation occurs at a sufficiently fine mass grid, and the number of iterations in solving vertical advection should be minimized to reduce numerical diffusion. Insubstantial numerical diffusion in solving condensation can be amplified if collision-coalescence is also active, which in turn can be substantially diminished if turbulence effects on collision are incorporated. Large-eddy simulations of a drizzling stratocumulus field reveal that changes in moments of Doppler spectra obtained using different mass grids are consistent with those obtained from the simplified framework, and that spectral moments obtained using a mass grid designed to effectively reduce numerical diffusion are generally closer to observations. Notable differences between the simulations and observations still exist, and our results suggest a need to consider whether factors other than numerical diffusion in the fundamental process schemes employed can cause such differences.

Cloud microphysics↗
DOE OSTI2015

Increasing water cycle extremes in California and relation to ENSO cycle under global warming

California has experienced its most severe drought in recorded history since the winter of 2013-2014. The long duration of drought has stressed statewide water resources and the economy, while fueling an extraordinary increase in wildfires. The effects of global warming on the regional climate include a hotter and drier climate, as well as earlier snowmelt, both of which exacerbate drought conditions. However, connections between a changing climate and how climate oscillations modulate regional water cycle extremes are not well understood. Here we analyze large-ensemble simulations of future climate change in California using the Community Earth System Model version 1 (CESM1) and multiple climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Both intense drought and excessive flooding are projected to increase by at least 50% toward the end of the 21st century. Furthermore, the projected increase in water cycle extremes is associated with tighter relation to El Niño and Southern Oscillation (ENSO), particularly extreme El Niño and La Niña events, which modulates California’s climate not only through its warm and cold phases, but also ENSO’s precursor patterns.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Creating Gridded Fire Probability Maps using NASA Data

Fire is a nationally and globally significant process that strongly affects human–dominated and wild landscapes. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop the world's first grid-based wildfire probability product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use multiple satellites and ancillary data to weigh the likelihood of fire, based on a number of sources that verify a fire burning in a grid cell and the level of confidence in the data source. For example, Sentinel-2 vegetation-change indices have a higher level of confidence than VIIRS (Visible Infrared Imaging Radiometer Suite) active-fire detection data; and VIIRS active-fire detection data have a higher-level of confidence than MODIS (Moderate Resolution Imaging Spectroradiometer) active-fire detection data. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗
NASA NTRSDate not supplied

Creating IR-verified Gridded Fire Burn Maps using Public NASA and Satellite Data

Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop a high-confidence grid-based wildfire burn product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This product will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use VIIRS (Visible Infrared Imaging Radiometer Suite) 375 m fire detections and Sentinel-2 10 m satellite imagery to create a 20-m gridded fire burn product. Our process is based on the level of confidence in the data source and takes into account vegetation change throughout the life of the fire. For example, Sentinel-2 vegetation-change indices have a higher level of confidence when congruent with VIIRS active-fire detection data, rather than VIIRS detections alone. We have also verified our fire burn product against MODIS/ASTER Airborne Simulator (MASTER) Infrared (IR) data from the Fire Influence on Regional to Global Environments Experiment - Air Quality (FIREX-AQ) 2019 campaign, with 88% overall agreement. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗
NASA NTRS1987

Condensate phenomena in the polar regions of Mars

Models used to study the changes in Martian climate must of necessity adequately describe the current volatile cycles. The focus is on mathematical modeling of current volatile cycles and modest extrapolation to past regimes. Water cycle, dust storms, polar variabilty, and north polar clouds data were compared to the model predictions.

James, Philip B.↗
NASA NTRS2016

A Global Repository for Planet-Sized Experiments and Observations

Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP) output used by the Intergovernmental Panel on Climate Change assessment reports. Data served by ESGF not only include model output (i.e., CMIP simulation runs) but also include observational data from satellites and instruments, reanalyses, and generated images. Metadata summarize basic information about the data for fast and easy data discovery.

Earth Systems Grid Federation (ESGFC)↗
NASA NTRS2004

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers.

optical depth↗
NASA NTRS2010

Projecting the Local Impacts of Climate Change on a Central American Montane Avian Community

Significant changes in the climates of Central America are expected over the next century. Lowland rainforests harbor high alpha diversity on local scales (<1 km2), yet montane landscapes often support higher beta diversity on 10-100 km2 scales. Climate change will likely disrupt the altitudinal zonation of montane communities that produces such landscape diversity. Projections of biotic response to climate change have often used broad-scale modelling of geographical ranges, but understanding likely impacts on population viability is also necessary for anticipating local and global extinctions. We model species abundances and estimate range shifts for birds in the Tilaran Mountains of Costa Rica, asking whether projected changes in temperature and rainfall could be sufficient to imperil high-elevation endemics and whether these variables will likely impact communities similarly. We find that nearly half of 77 forest bird species can be expected to decline in the next century. Almost half of species projected to decline are endemic to Central America, and seven of eight species projected to become locally extinct are endemic to the highlands of Costa Rica and Panam . Logistic-regression modelling of distributions and similarity in projections produced by temperature and rainfall models suggest that changes in both variables will be important. Although these projections are probably conservative because they do not explicitly incorporate biological or climate variable interactions, they provide a starting point for incorporating more realistic biological complexity into community-change models. Prudent conservation planning for tropical mountains should focus on regions with room for altitudinal reorganization of communities comprised of ecological specialists.

Gasner, Matthew R.↗
DOE OSTI2013

Source Characterization and Temporal Variation of Methane Seepage from Thermokarst Lakes on the Alaska North Slope in Response to Arctic Climate Change

The goals of this research were to characterize the source, magnitude and temporal variability of methane seepage from thermokarst lakes (TKL) within the Alaska North Slope gas hydrate province, assess the vulnerability of these areas to ongoing and future arctic climate change and determine if gas hydrate dissociation resulting from permafrost melting is contributing to the current lake emissions. Analyses were focused on four main lake locations referred to in this report: Lake Qalluuraq (referred to as Lake Q) and Lake Teshekpuk (both on Alaska's North Slope) and Lake Killarney and Goldstream Bill Lake (both in Alaska's interior). From analyses of gases coming from lakes in Alaska, we showed that ecological seeps are common in Alaska and they account for a larger source of atmospheric methane today than geologic subcap seeps. Emissions from the geologic source could increase with potential implications for climate warming feedbacks. Our analyses of TKL sites showing gas ebullition were complemented with geophysical surveys, providing important insight about the distribution of shallow gas in the sediments and the lake bottom manifestation of seepage (e.g., pockmarks). In Lake Q, Chirp data were limited in their capacity to image deeper sediments and did not capture the thaw bulb. The failure to capture the thaw bulb at Lake Q may in part be related to the fact that the present day lake is a remnant of an older, larger, and now-partially drained lake. These suggestions are consistent with our analyses of a dated core of sediment from the lake that shows that a wetland has been present at the site of Lake Q since approximately 12,000 thousand years ago. Chemical analyses of the core indicate that the availability of methane at the site has changed during the past and is correlated with past environmental changes (i.e. temperature and hydrology) in the Arctic. Discovery of methane seeps in Lake Teshekpuk in the northernmost part of the lake during 2009 reconnaissance surveys provided a strong impetus to visit this area in 2010. The seismic methods applied in Lake Teshekpuk were able to image pockmarks, widespread shallow gas in the sediments, and the relationship among different sediment packages on the lake's bottom, but even boomer seismics did not detect permafrost beneath the northern part of the lake. By characterizing the biogeochemistry of shallow TKL with methane seeps we showed that the radical seasonal shifts in ice cover and temperature. These seasonal environmental differences result in distinct consumption and production processes of biologically-relevant compounds. The combined effects of temperature, ice-volume and other lithological factors linked to seepage from the lake are manifest in the distribution of sedimentary methane in Lake Q during ice-covered and ice-free conditions. The biogeochemistry results illustrated very active methanotrophy in TKLs. Substantial effort was subsequently made to characterize the nature of methanotrophic communities in TKLs. We applied stable isotope probing approaches to genetically characterize the methanotrophs most active in utilizing methane in TKLs. Our study is the first to identify methane oxidizing organisms active in arctic TKLs, and revealing that type I methanotrophs and type II methanotrophs are abundant and active in assimilating methane in TKLs. These organisms play an important role in limiting the flux of methane from these sites. Our investigations indicate that as temperatures increase in the Arctic, oxidation rates and active methanotrophic populations will also shift. Whether these changes can offset predicted increases in methanogenesis is an important question underlying models of future methane flux and resultant climate change. Overall our findings indicate that TKLs and their ability to act as both source and sink of methane are exceedingly sensitive to environmental change.

03 NATURAL GAS↗