Results for “FLUX” — Page 33

NASA NTRS2015

An Inversion Analysis of Recent Variability in Natural CO2 Fluxes Using GOSAT and In Situ Observations

About one-half of the global CO2 emissions from fossil fuel combustion and deforestation accumulates in the atmosphere, where it contributes to global warming. The rest is taken up by vegetation and the ocean. The precise contribution of the two sinks, and their location and year-to-year variability are, however, not well understood. We use two different approaches, batch Bayesian synthesis inversion and variational data assimilation, to deduce the global spatiotemporal distributions of CO2 fluxes during 2009-2010. One of our objectives is to assess different sources of uncertainties in inferred fluxes, including uncertainties in prior flux estimates and observations, and differences in inversion techniques. For prior constraints, we utilize fluxes and uncertainties from the CASA-GFED model of the terrestrial biosphere and biomass burning driven by satellite observations and interannually varying meteorology. We also use measurement-based ocean flux estimates and two sets of fixed fossil CO2 emissions. Here, our inversions incorporate column CO2 measurements from the GOSAT satellite (ACOS retrieval, filtered and bias-corrected) and in situ observations (individual flask and afternoon-average continuous observations) to estimate fluxes in 108 regions over 8-day intervals for the batch inversion and at 3 x 3.75 weekly for the variational system. Relationships between fluxes and atmospheric concentrations are derived consistently for the two inversion systems using the PCTM atmospheric transport model driven by meteorology from the MERRA reanalysis. We compare the posterior fluxes and uncertainties derived using different data sets and the two inversion approaches, and evaluate the posterior atmospheric concentrations against independent data including aircraft measurements. The optimized fluxes generally resemble those from other studies. For example, the results indicate that the terrestrial biosphere is a net CO2 sink, and a GOSAT-only inversion suggests a shift in the global sink from the tropics south to the north relative to the prior and to an in-situ-only inversion. We also find a smaller terrestrial sink in higher-latitude northern regions in boreal summer of 2010 relative to 2009.

Carbon dioxide↗

NASA NTRS2018

The Cause of Faint Coronal Jets from Emerging-Flux Regions in Solar Coronal Holes

Coronal jets are transient thin bursts of magnetically channeled solar material from the surface into the corona. They are brightest at their base, with a bright point (jet bright point, JBP) at an edge of the base. Early studies (Shibata et al. 1992) suggested that jets result from magnetic flux emergence: a small bipole emerges into unipolar ambient field, driving the jet and forming the JBP via interchange reconnection. More recent studies, using higher-cadence, higher-resolution, and broader wavelength coverage than before, show that prominent coronal jets are usually driven by a minifialment eruption (Sterling et al. 2015), and that, rather than flux emergence, flux cancelation usually prepares and triggers the eruption (Panesar et al. 2016). Here, we analyzed eight emerging flux regions to determine whether the emerging flux directly drove any coronal jets. We used EUV images from the Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) (in 304, 171, 211, 193, and 94 Å channels), and magnetograms from SDO/Helioseismic & Magnetic Imager (HMI). All eight regions produced jet-like features that were weak in intensity (“faint jets’’), by which we mean they were so faint that we likely would not have identified them as jets had we initially searched for jets in AIA movies alone (as in, e.g., Panesar et al. 2016, Moore et al. 2013) without knowing whether the base was an emerging bipole. In seven of the eight regions, all jets (faint or prominent) erupted from locations where one leg of the emerging bipole was evidently canceling with an ambient opposite-polarity flux clump. The eighth case, the one that had the fastest flux emergence, possibly made faint jets by the flux-emergence mechanism, but these too might instead have resulted from flux cancelation.

Harden, Abigail R.↗

NASA NTRS2018

Improving NASA GEOS Atmospheric CO2 Simulations by Calibrating CASA Surface Fluxes with an Empirical Sink

With the adoption of the Paris climate accord, efforts to monitor and understand both anthropogenic and natural carbon sources and sinks are increasing across the world. Given their low latency and global coverage, satellite observations of atmospheric carbon dioxide (CO2) are poised to make important contributions to this field. The combination of satellite data and high resolution global models can be used to monitor changes in carbon fluxes and to evaluate the consistency of nationally reported emissions estimates in support of multiple stakeholder communities. However, a consistent challenge to such work has been the high latency of surface carbon flux estimates, which are often not available for a year or more. This presentation describes the construction of surface carbon flux estimates meant to improve the near real time simulation of atmospheric CO2 with NASA's Goddard Earth Observing System (GEOS) general circulation model. The surface flux estimates begin with a collection of bottom-up fluxes which incorporate satellite measurements in their construction, e.g. vegetation indices in the Carnegie-Ames-Stanford Approach (CASA) and nighttime lights in the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). From there, we take the additional step of using an empirical sink to calibrate terrestrial net biospheric exchange (NBE) to estimated values from atmospheric inversion systems. This approach removes a known, systematic bias in predicted atmospheric mixing ratios. Using these fluxes in a free running simulation, the model is able to reproduce in situ measurements with the same skill as when it uses gridded fluxes from a flux inversion system. Using these fluxes as a prior in an assimilation system, e.g. one incorporating retrievals of column CO2 from the Orbiting Carbon Observatory 2 (OCO-2), allows the analysis to capture variability in CO2 on scales that would be missed otherwise. This approach supports NASA's capability to forecast atmospheric CO2 up to two weeks in advance by leveraging a GEOS system used to produce quasi-operational weather analyses and forecasts, providing a valuable new tool to the carbon monitoring research and applications communities.

Weir, B.↗

NASA NTRS2021

East–West Proton Flux Anisotropy Observed with the PAMELA Mission

We present a study of the east–west anisotropy of trapped-proton fluxes in low-Earth orbit based on the measurements of the Payload for Antimatter Matter Exploration and Light-nuclei Astrophysics(PAMELA)experiment. The differential intensities of eastward- and westward-traveling protons detected in the South Atlantic Anomaly region were estimated as a function of equatorial pitch angle and drift shell, for six energy bins between80 MeV and 2 GeV. We found that, as a consequence of the strong atmospheric gradient coupled with the large gyro radius in this energy range, the intensities of eastward fluxes exceed those of westward fluxes by a factor of∼10–20. However, the reported directional asymmetry also depends on the sign of the local flux gradient, resulting in more intense westward fluxes beyond the radial distances where the inner belt peaks. PAMELA observations can be used to improve the description of the near-Earth radiation environment at lowest altitudes and highest trapping energies, where current theoretical and empirical models are affected by the largest uncertainties. Unified Astronomy Thesaurus concepts: Cosmic rays(329);Van Allen radiation belts(1758)1. Introduction Low-altitude inner-belt protons are strongly influenced by the density distribution of Earth’s atmosphere, mostly through interactions with its neutral constituents, which induce significant flux anisotropies. In prim is, the atmospheric loss cone results in a steep pitch-angle distribution, which becomes narrower for lower drift shells. A further, azimuthal anisotropy originates from finite gyro radius effects at proton energies in excess of a few tens of MeV(Haerendel1962; Lenchek & Singer1962). In fact, for a given spacecraft position, protons with the same pitch angle but different gyro phase—the azimuth angle associated with the gyration motion—have their guiding centers on different drift shells. In particular, protons from the west and from the east gyrate around magnetic field lines located at higher and lower altitudes, respectively. The guiding-center separationΔhincreaseswith increasing energy, so that protons moving eastward will encounter progressively lower drift-averaged densities, thus experiencing less atmospheric absorption; the opposite situation will occur for protons traveling westward, resulting in an east–west asymmetry of flux intensities whenΔhbecomes comparable to or larger than the flux scale height(Garmire1963; Heckman &Nakano1963).The trapped-flux anisotropy is a relevant aspect of the modeling of the low Earth orbit(LEO)radiation environment, given the significant engineering implications, especially for The Astrophysical Journal,919:114(6pp), 2021 October 1https://doi.org/10.3847/1538-4357/ac1677© 2021. The American Astronomical Society.

A. Bruno↗

NASA NTRSDate not supplied

CERES FluxByCldTyp NB2BB Fluxes Improvement based on Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

NASA NTRS2022

Identification of Flux Rope Orientation via Neural Networks

Geomagnetic disturbance forecasting is based on the identification of solar wind structures and accurate determination of their magnetic field orientation. For nowcasting activities, this is currently a tedious and manual process. Focusing on the main driver of geomagnetic disturbances, the twisted internal magnetic field of interplanetary coronal mass ejections (ICMEs), we explore a convolutional neural network’s (CNN) ability to predict the embedded magnetic flux rope’s orientation once it has been identified from in situ solar wind observations. Our work uses CNNs trained with magnetic field vectors from analytical flux rope data. The simulated flux ropes span many possible spacecraft trajectories and flux rope orientations. We train CNNs first with full duration flux ropes and then again with partial duration flux ropes. The former provides us with a baseline of how well CNNs can predict flux rope orientation while the latter provides insights into real-time forecasting by exploring how accuracy is affected by percentage of flux rope observed. The process of casting the physics problem as a machine learning problem is discussed as well as the impacts of different factors on prediction accuracy such as flux rope fluctuations and different neural network topologies. Finally, results from evaluating the trained network against observed ICMEs from Wind during 1995–2015 are presented.

Thomas Narock↗

NASA NTRSDate not supplied

Flux Improvement based on Machine Learning for the CERES FluxByCldTyp Data Product

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

NASA NTRSDate not supplied

Improvement of Radiative Fluxes for the CERES FluxByCldTyp Data Product Based on Machine Learning Technique

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere and surface flux data for climate studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models. The FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate their broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Preliminary results show significant LW improvement.

Sun, Moguo↗

NASA NTRSDate not supplied

Improvement of Radiative Fluxes for the CERES FluxByCldTyp Data Product Based on Machine Learning Technique

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

NASA NTRSDate not supplied

Improving Radiative Fluxes for the CERES FluxByCldTyp Data Product Using Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Preliminary results show significant LW improvement.

Sun, Moguo↗

DOE OSTI2015

Laboratory Study of the Equilibrium and Eruption of Line-Tied Magnetic Flux Ropes in the Solar Corona

Ideal magnetohydrodynamic (MHD) instabilities such as the kink instability and the torus instability are leading candidates to explain the sudden onset of eruptive events in the solar corona. These instabilities act on line-tied magnetic flux ropes--long-lived arched structures anchored to the solar surface. In spite of substantial observational and numerical research, however, the role of these instabilities in the corona remains a subject of intense debate. For this thesis, we have constructed and operated a new line-tied flux rope experiment that permits for the first time the study of both the kink and torus instabilities in the laboratory. This experiment has the following key features: (1) the arched flux rope is line-tied to two conducting footpoints; (2) the system is magnetically dominated (low-beta) with significant stored energy; (3) the system is driven quasi-statically, producing a long-lived equilibrium; and (4) the flux rope is generated within a potential (vacuum) magnetic field arcade whose decay index--the predicted torus instability control parameter--can be externally controlled. The flux ropes are diagnosed using a two-dimensional in situ magnetic probe array whose cross-section covers a substantial portion of the plasma. The central result of this thesis is that toroidal field forces, which are traditionally neglected in the analysis of coronal flux ropes, are identified for the first time as an essential contributor to both the equilibrium and the stability of line-tied flux ropes. Most importantly, experimental measurements show that a tension force derived from a self-generated paramagnetic toroidal field exerts a restoring force on the line-tied plasma and suppresses eruptive behavior in a significant portion of the parameter space. This suppression extends to regimes that are both kink and torus unstable. We find that, in order to explain the measured tension force, low aspect ratio and line-tying effects must be considered. Finally, flux rope eruptions are observed in these experiments, but only in regimes with sufficiently low external toroidal field where the tension force is reduced. These results constitute a new condition for the prediction of line-tied magnetic flux rope eruptions: that of low external toroidal field.

Magnetic Fields↗

DOE OSTI2022

Requirements for Soldering Fluxes Research using the B-53 Test Board

IPC J-STD-004B standard prescribes general requirements for the classification and testing of soldering flux for high qualify interconnections. This standard defines the classification of soldering materials through specifications of test methods and inspection criteria. The materials include liquid flux, paste flux, solderpaste flux, solder preform flux, and flux-cored solder. This research will use the proposed IPC-53 Surface Insulation Resistance (SIR) test patterns by means of an open comb (2D) and closed comb (3D to simulate a component over the comb pattern). The 2D open comb has uniformity of conductor spacing, sheet resistance, and flux outgassing. The 3D-closed comb simulates the effect of leadless or bottom-terminated components, which have non-uniform sheet resistance and flux outgassing. The response variables will include SIR testing and visual imaging. The objective is to investigate IPC test method improvements for characterizing soldering fluxes when using leadless components with narrow pad-to-pad spacing.

Diamond, Louis↗

DOE OSTI2021

Long-term dynamics of soil, tree stem and ecosystem methane fluxes in a riparian forest

The carbon (C) budgets of riparian forests are sensitive to climatic variability. Therefore, riparian forests are hot spots of C cycling in landscapes. Only a limited number of studies on continuous measurements of methane (CH 4 ) fluxes from riparian forests is available. Here, in this work, we report continuous high-frequency soil and ecosystem (eddy-covariance; EC) measurements of CH 4 fluxes with a quantum cascade laser absorption spectrometer for a 2.5-year period and measurements of CH 4 fluxes from tree stems using manual chambers for a 1.5 year period from a temperate riparian Alnus incana forest. The results demonstrate that the riparian forest is a minor net annual sink of CH 4 consuming 0.24 kg CH 4 -C ha –1 y –1 . Soil water content is the most important determinant of soil, stem, and EC fluxes, followed by soil temperature. There were significant differences in CH 4 fluxes between the wet and dry periods. During the wet period, 83% of CH 4 was emitted from the tree stems while the ecosystem-level emission was equal to the sum of soil and stem emissions. During the dry period, CH 4 was substantially consumed in the soil whereas stem emissions were very low. A significant difference between the EC fluxes and the sum of soil and stem fluxes during the dry period is most likely caused by emission from the canopy whereas at the ecosystem level the forest was a clear CH 4 sink. Our results together with past measurements of CH 4 fluxes in other riparian forests suggest that temperate riparian forests can be long-term CH 4 sinks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Spatial Variation of Soil CO 2 , CH 4 and N 2 O Fluxes Across Topographical Positions in Tropical Forests of the Guiana Shield

The spatial variation of soil greenhouse gas fluxes (GHG; carbon dioxide—CO 2 , methane—CH 4 and nitrous oxide—N 2 O) remains poorly understood in highly complex ecosystems such as tropical forests. Here, we used 240 individual flux measurements of these three GHGs from different soil types, at three topographical positions and in two extreme hydric conditions in the tropical forests of the Guiana Shield (French Guiana, South America) to (1) test the effect of topographical positions on GHG fluxes and (2) identify the soil characteristics driving flux variation in these nutrient-poor tropical soils. Surprisingly, none of the three GHG flux rates differed with topographical position. CO 2 effluxes covaried with soil pH, soil water content (SWC), available nitrogen and total phosphorus. The CH 4 fluxes were best explained by variation in SWC, with soils acting as a sink under drier conditions and as a source under wetter conditions. Unexpectedly, our study areas were generally sinks for N 2 O and N 2 O fluxes were partly explained by total phosphorus and available nitrogen concentrations. This initial work describing the spatial variation of soil fluxes of the three main GHGs measured simultaneously in forests of the Guiana Shield lays the foundation for specific studies of the processes underlying the observed patterns.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Estimating source-sink distributions and fluxes of reactive nitrogen and sulfur within a mixed forest canopy

The vertical source-sink distribution of air pollutants within and above forested canopies is necessary for describing the biological, physical, and chemical processes influencing the soil-vegetation-atmosphere exchange. Here, this study implemented inverse modeling methods to estimate the source-sink and flux profiles of reactive nitrogen (N) and sulfur (S) compounds from measurements of the mean concentration profiles of ammonia (NH 3 ), nitric acid (HNO 3 ), sulfur dioxide (SO 2 ), and particulate ammonium (NH 4 + ), nitrate (NO 3 − ), and sulfate (SO 4 2− ) at a forest site in the southern Appalachian Mountains. Three inverse approaches utilizing different approximations to scalar transport within the canopy were developed and evaluated against sensible heat flux measurements. The Eulerian model (EUL), which incorporates vertical velocity skewness, performed well in reproducing the turbulent heat fluxes and was subsequently used to calculate the chemical source-sink and flux profiles. Above-canopy fluxes of NH 3 were downward, indicating that the forest was a net sink of NH 3 . The soil/litter layer was both a source and a sink for NH 3 but the exchange rate at the forest floor was small. Fluxes of HNO 3 , SO 2 , NO 3 − , NH 4 + , and SO 4 2- were uni-directional (deposition only) between the air and the canopy/ground and increased monotonically from the forest floor to the canopy top. Crown foliage dominated the uptake of reactive N and S during the growing season, accounting for 80–90% of the total canopy-scale flux. Fluxes and canopy-ground partitioning estimated using the resistance-based Surface Tiled Aerosol and Gas Exchange (STAGE) model were generally comparable to EUL. The comparison highlights the need for improved parameterizations of litter exchange and NH 3 compensation points in resistance models for forest ecosystems. The findings here benefit the application of critical loads in forest ecosystems and guide further development of resistance-based exchange models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Mechanistic Modeling of Microtopographic Impacts on CO 2 and CH 4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO 2 and CH 4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO 2 and CH 4 fluxes across seven landscape types in Utqia&#289vik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO 2 and CH 4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH 4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO 2 + H 2 ) is the most important factor determining CH 4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH 4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH 4 fluxes. The model underestimated the EC-measured CH 4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH 4 flux. The strong microtopographic impacts on CO 2 and CH 4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2011

WHAT DOES A SUBMILLIMETER GALAXY SELECTION ACTUALLY SELECT? THE DEPENDENCE OF SUBMILLIMETER FLUX DENSITY ON STAR FORMATION RATE AND DUST MASS

We perform three-dimensional dust radiative transfer (RT) calculations on hydrodynamic simulations of isolated and merging disk galaxies in order to quantitatively study the dependence of observed-frame submillimeter (submm) flux density on galaxy properties. We find that submm flux density and star formation rate (SFR) are related in dramatically different ways for quiescently star-forming galaxies and starbursts. Because the stars formed in the merger-induced starburst do not dominate the bolometric luminosity and the rapid drop in dust mass and more compact geometry cause a sharp increase in dust temperature during the burst, starbursts are very inefficient at boosting submm flux density (e.g., a {approx}> 16 Multiplication-Sign boost in SFR yields a {approx}< 2 Multiplication-Sign boost in submm flux density). Moreover, the ratio of submm flux density to SFR differs significantly between the two modes; thus one cannot assume that the galaxies with highest submm flux density are necessarily those with the highest bolometric luminosity or SFR. These results have important consequences for the bright submillimeter-selected galaxy (SMG) population. Among them are: (1) The SMG population is heterogeneous. In addition to merger-driven starbursts, there is a subpopulation of galaxy pairs, where two disks undergoing a major merger but not yet strongly interacting are blended into one submm source because of the large ({approx}> 15'' or {approx}130 kpc at z = 2) beam of single-dish submm telescopes. (2) SMGs must be very massive (M{sub *} {approx}> 6 Multiplication-Sign 10{sup 10} M{sub Sun }). (3) The infall phase makes the SMG duty cycle a factor of a few greater than what is expected for a merger-driven starburst. Finally, we provide fitting functions for SCUBA and AzTEC submm flux densities as a function of SFR and dust mass and bolometric luminosity and dust mass; these should be useful for calculating submm flux density in semi-analytic models and cosmological simulations when performing full RT is computationally not feasible.

79 ASTRONOMY AND ASTROPHYSICS↗