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At least 253 records · Page 14

Observations and Modeling of the Onset of Fast Reconnection in the Solar Transition Region

Magnetic reconnection is a fundamental plasma process that plays a critical role not only in energy release in the solar atmosphere, but also in fusion, astrophysics, and other space plasma environments. One of the challenges in explaining solar observations in which reconnection is thought to play a critical role is to account for the transition of the dynamics from a slow quasi-continuous phase to a fast and impulsive energetic burst of much shorter duration. Despite the theoretical progress in identifying mechanisms that might lead to rapid onset, a lack of observations of this transition has left models poorly constrained. High-resolution spectroscopic observations from NASA's Interface Region Imaging Spectrograph now reveal tell-tale signatures of the abrupt transition of reconnection from a slow phase to a fast, impulsive phase during UV bursts or explosive events in the Sun's atmosphere. Our observations are consistent with numerical simulations of the plasmoid instability, and provide evidence for the onset of fast reconnection mediated by plasmoids and new opportunities for remote-sensing diagnostics of reconnection mechanisms on the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗

Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)

In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.

03 NATURAL GAS↗

Observations and Models of the Lunar Sodium Exosphere 1988 - 1999

Sodium in the lunar exosphere is easily observed from the Earth's surface due to its strong resonance emission lines in the visible region of the spectrum. Although sodium is a trace element, it is easily ejected from the surface by a number of processes. The variation of this exospheric constituent both spatially and temporally can help to constrain these sources and the loss processes and their timescales. Due to a revival of interest in the Moon and its volatiles, observations of the lunar exosphere obtained at the McMath-Pierce solar telescope in 1998 and 1999 have recently been reduced and analyzed. In addition, observations of the lunar sodium exosphere obtained with the Mt. Lemmon Lunar Coronagraph on Mt. Lemmon, Arizona, have also been published. We combine these new data with data previously published and reanalyzed by Sarantos et al. This comprehensive data set will be modeled using both a simple Chamberlain exosphere model and a comprehensive Monte Carlo model.

Killen, Rosemary↗

A comparison of high-temperature flare models with observations and implications for the low-temperature flare

EUV data from the Harvard College Observatory and Naval Research Laboratory instruments on board the Skylab Apollo telescope mount, together with SOLRAD 9 X-ray data, are analyzed in order to empirically deduce the variation of emission measure with temperature in the atmosphere of a number of solar flares. A 'mean' differential emission measure profile Q(T) for a flare is constructed which is then compared with the profile predicted by a number of theoretical models. It is found that realistic flare models must include both conductive and radiative terms in the energy equation, and that hydrodynamic terms may be important at low temperatures. The implications of the results obtained are discussed for flare models in general and it is shown that the inclusion of the conductive term into models which have hitherto neglected it can perhaps resolve some of the observational difficulties with such models.

Machado, M. E.↗

Exposing Process‐Level Biases in a Global Cloud Permitting Model With ARM Observations

The emergence of global convective‐permitting models (GCPMs) represents a significant advancement in climate modeling, offering improved representation of deep convection and complex precipitation patterns. In this study, we evaluate the performance of the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) using its doubly periodic configuration (DP‐SCREAM) against large eddy simulations and modern observational data sets from the Atmospheric Radiation Measurement program. We introduce several new transitional cloud regime cases, such as the transition from shallow to deep convection and from stratocumulus to cumulus, as well as cold‐air outbreak scenarios. The results reveal both strengths and limitations of SCREAM, particularly in the accurate simulation of cloud transitions and midlevel convection, with varying degrees of sensitivity to horizontal and vertical resolution. Despite improvements at higher resolutions, key biases remain, including the abrupt transition from shallow to deep convection and the lack of congestus clouds. These findings underscore the need for further refinement in turbulence parameterizations and vertical grid resolution in GCPMs.

Bogenschutz, Peter A. [Lawrence Livermore National↗

On the state estimation of structures with second order observers

The use of Linear Quadratic Regulator (LQR) control synthesis techniques implies the availability of full state feedback. For vibration control of structures, usually only a limited number of states are measured from which an observer model reconstructs the full state. It is shown that using second order observers is a viable technique for reconstructing the unmeasured states of structures under mildly restrictive conditions. Moreover, the computational advantages of the second order observer as compared to a first order observer indicate that significantly larger observer models may be utilized. Numerical examples are used to demonstrate the performance of second order observers. The implications of second order observers in the development of Controls-Structures Interaction (CSI) technology is discussed.

Belvin, W. Keith↗

Observations and Modeling of Thermal Structure in the Lower Atmosphere and the Upward Propagation of Tides into the Thermosphere

Thermal tides are the atmospheric response to diurnally varying thermal forcing resulting from radiative and convective heat transfer from the surface and from aerosol and gaseous heating within the atmosphere. Tides include sun-synchronous (migrating) waves driven in response to solar heating and additional non-migrating waves resulting from longitudinal variations in the distributions of topography, dust aerosol and water ice clouds. The systematic spatial mapping of temperature over 5 Mars years by the Mars Climate Sounder (MCS) has yielded a well-defined climatology of seasonally-varying temperature structures in the lower atmosphere, from 5 to ~80 km. Tide theory and Mars global circulation model (MGCM) simulations are a fruitful framework for relating temperature observations to thermal forcing by aerosol fields [1]. The analysis of density and temperature fields derived from MAVEN IUVS and NGIMS observations have revealed the presence of predominantly zonal wave 2 and 3 features at altitudes of 100-170 km that are almost certainly non-migrating tides propagating upward from the lower atmosphere [2,3]. In this presentation we will use the MCS climatology and MGCM simulations to relate the density variations seen by MAVEN with the seasonally varying tide activity in the lower atmosphere. Large amplitude perturbations in density are most sensitive to the tide components with the longest vertical wavelengths in temperature, which are well resolved in MCS observations.

Mars Climate Sounder (MCS)↗

Nightside plasmapause positions observed by DE-1 as a function of geomagnetic indices - Comparison with whistler observations and model calculations

The paper analyzes 28 plasmapause crossings made by the DE1 satellite in the night local time sector (from January to March 1982). Different signatures obtained by the Retarding Ion Mass Spectrometer instrument have been used for this analysis. The observed plasmapause positions (Lpp) have been organized as a function of geomagnetic indices. They are compared with the empirical relationship deduced by Carpenter and Parks (1973) from whistler observations. Moreover, the dependence of Lpp versus Kp has been inferred from model calculations using Kp dependent electric and magnetic fields derived from McIlwain's (1974) E3H electric field model and M2 magnetic field model respectively. Stationary models as well as time dependent ones, have been used to determine the positions of the plasmapause. The results of the model calculations are compared to the observations.

Decreau, P. M. E.↗

A comparison of observed and model energy balance for an extratropical cyclone system

Eddy kinetic energy budgets are presented for both moist and dry 48 h forecasts and corresponding observations of a developing winter extratropical cyclone. A diagnosis of observational data energetics is presented and compared with model results for an intense, occluding winter cyclone associated with a strong, well-developed jet stream. The nature of the eddy kinetic energy sources and sinks associated with the strong baroclinic development occurring in this cyclonic system is examined, and the extent to which to observed energy sources and sinks are present in the numerical predictions is addressed. The possibility of explaining differences between the observed and predicted cyclone systems by analyzing these kinetic energy properties is considered.

Dare, P. M.↗

Nanoflare Properties throughout Active Regions: Comparing SDO/AIA Observations with Modeled Active Region Light Curves

Coronal plasma in active regions is typically measured to be at temperatures near ~1-3 MK. Is the majority of the coronal plasma in hydrostatic equilibrium, maintained at these temperatures through a form of quasi-steady heating, or is this simply a measure of the average temperature of widely varying, impulsively heated coronal plasma? Addressing this question is complicated by the fact that the corona is optically thin: many thousands of flux tubes which are heated completely independently are contributing to the total emission along a given line of sight. There is a large body of work focused on the heating of isolated features - coronal loops - which are impulsively heated, however it is the diffuse emission between loops which often comprises the majority of active region emission. Therefore in this study we move beyond isolated features and analyze all of the emission in an entire active region from all contributing flux tubes. We investigate light curves systematically using SDO/AIA observations. We also model the active region corona as a line-of-sight integration of many thousands of completely independently heated flux tubes. The emission from these flux tubes may be time dependent, quasi-steady, or a mix of both, depending on the cadence of heat release. We demonstrate that despite the superposition of randomly heated flux tubes, different distributions of nanoflare cadences produce distinct signatures in light curves observed with multi-wavelength and high time cadence data, such as those from SDO/AIA. We conclude that the majority of the active region plasma is not maintained in hydrostatic equilibrium, rather it is undergoing dynamic heating and cooling cycles. The observed emission is consistent with heating through impulsive nanoflares, whose energy is a function of location within the active region.

Viall, Nicholeen↗

Predictability of the Minimum Sea Ice Extent from Winter Fram Strait Ice Area Export: Model vs Observations

Observations show predictive skill of the minimum sea ice extent (Min SIE) from late winter anomalous off-shore ice drift along the Eurasian coastline – leading to local ice thickness anomalies at the onset of the melt season – a signal then amplified by the ice-albedo feedback. We assess whether the observed seasonal predictability of September sea ice extent (Sept SIE) from Fram Strait Ice Area Export (FSIAE, a proxy for Eurasian coastal divergence) is present in Global Climate Model (GCM) large ensembles, namely the CESM2-LE, GISS-E2.1-G, FLOR-LE, CNRM-CM6-1, and CanESM5. All models show distinct periods where winter FSIAE anomalies are negatively correlated with the May sea ice thickness (May SIT) anomalies along the Eurasian coastline, and the following Sept Arctic SIE, as in observations. Counter-intuitively, several models show occasional periods where winter FSIAE anomalies are positively correlated with the following Sept SIE anomalies when the mean ice thickness is large or late in the simulation when the sea ice is thin, and/or when internal variability increases. More importantly, periods with weak correlation between FSIAE and the Sept SIE dominate, suggesting that summer melt processes dominate over late winter preconditioning and May SIT anomalies. In general, we find that the coupling between the FSIAE and ice thickness anomalies along the Eurasian coastline is an ubiquitous feature of GCMs and that the relationship with the following Sept SIE is dependent on the mean Arctic sea ice thickness.

off-shore ice drift↗

On the state estimation of structures with second order observers

The use of the linear quadratic regulator control synthesis techniques implies the availability of full state feedback. For vibration control of structures, usually only a limited number of states are measured from which an observer model reconstructs the full state. This paper shows that using second-order observers is a viable technique for reconstructing the unmeasured states of structures under mildly restrictive conditions. Moreover, the computational advantages of the second-order observer, as compared to a first-order observer, indicate that significantly larger observer models may be utilized. Numerical examples are used to demonstrate the performance of second-order observers. The implications of second-order observers in the development of the control/structures interaction technology is discussed.

Belvin, W. Keith↗

The quiescent chromospheres and transition regions of active dwarf stars - What are we learning from recent observations and models?

Progress in understanding active dwarf stars based on recent IUE, Einstein, and ground-based observations is reviewed. The extent of magnetic field control over nonflare phenomena in active dwarf stars is considered, and the spatial homogeneity and time variability of active dwarf atmospheres is discussed. The possibility that solar like flux tubes can explain enhanced heating in active dwarf stars in examined, and the roles of systematic flows in active dwarf star atmospheres are considered. The relation between heating rates in different layers of active dwarf stars is summarized, and the mechanism of chromosphere and transition region heating in these stars are discussed. The results of one-component and two-component models of active dwarf stars are addressed.

Linsky, J. L.↗

Machine learning feature analysis illuminates disparity between E3SM climate models and observed climate change

In September of 2020, Arctic sea ice extent was the second-lowest on record. State of the art climate prediction uses Earth system models (ESMs), driven by systems of differential equations representing the laws of physics. Previously, these models have tended to underestimate Arctic sea ice loss. The issue is grave because accurate modeling is critical for economic, ecological, and geopolitical planning. We use machine learning techniques, including random forest regression and Gini importance, to show that the Energy Exascale Earth System Model (E3SM) relies too heavily on just one of the ten chosen climatological quantities to predict September sea ice averages. Furthermore, E3SM gives too much importance to six of those quantities when compared to observed data. Finally, identifying the features that climate models incorrectly rely on should allow climatologists to improve prediction accuracy.

54 ENVIRONMENTAL SCIENCES↗

Growing wheat in Biosphere 2 under elevated CO2: observations and modeling

Spring wheat (Triticum aestivum L., cv. Yecora Rojo) was grown in the intensive agricultural biome (IAB) of Biosphere 2 during the l995-l996 winter/spring season. Environmental conditions were characterized by a day/night temperature regime of 27/17 degrees C, relative humidity (RH) levels around 45%, mean atmospheric CO2 concentration of 450 ppmv, and natural light conditions with mean intensities about half of outside levels. Weekly samples of above-ground plant matter were collected throughout the growing season and phenological events recorded. A computer model, CERES-Wheat, previously tested under both field and controlled conditions, was used to simulate the observed crop growth and to help in data analysis. We found that CERES-Wheat simulated the data collected at Biosphere 2 to within 10% of observed, thus suggesting that wheat growth inside the IAB was comparable to that documented in other environments. The model predicts phenological stages and final dry matter (DM) production within l0% of the observed data. Measured DM production rates, normalized for light absorbed by the crop. suggested photosynthetic efficiencies intermediate between those observed under optimal field conditions and those recorded in NASA-Controlled Ecological Life-Support Systems (CELSS). We suggest that such a difference can be explained primarily in terms of low light levels inside the IAB, with additional effects due to elevated CO2 concentrations and diffuse light fractions.

Non-NASA Center↗

Current Limitations on VLBI Accuracy

The contribution of VLBI to geophysics and geodesy arises from its ability to measure distances between stations in a network and to determine the orientation of stations in the network as well as the orientation of the network with respect to the external reference frame of extragalactic radio objects. Integrating nearly two decades of observations provides useful information about station positions and velocities and the orientation of the Earth, but the complications of the real world and the limitations of observing, modeling and analysis prevent recovery of all effects. Of the factors that limit the accuracy of seemingly straightforward geodetic parameters, the neutral propagation medium has been subject to the greatest scrutiny, but the treatment of the mapping function, the wet component and spatial/temporal inhomogeneities is still improving. These affect both the terrestrial scale and consistency over time. The modeling of non-secular site motions (tides and loading) has increased in sophistication, but there are some differences between the models and the observations. VLBI antennas are massive objects, so their behavior is quite unlike GPS monuments, but antenna deformations add some (generally) unmodeled signal. Radio sources used in geodetic VLBI observations are selected for strength and (relative) absence of structure, but apparent changes in position can leak into geodetic parameters. A linear rate of change of baseline or site parameters is the simplest model and its error improves with time span. However, in most cases the VLBI data distribution is insufficient to look for real non-linear behavior that might affect the average rate. A few sites have multiple VLBI antennas, and some show small differences in rate. VLBI intrinsically measures relative positions and velocities, but individual site positions and velocities are generally more useful. The creation of the VLBI terrestrial reference frame, which transforms relative information into individual results, is an empirical process that has intrinsic errors. While UT1 is uniquely measured by VLBI, the geographical distribution and availability of VLBI stations, especially in the southern hemisphere, and the consistency of the VLBI terrestrial reference frame may limit the accuracy of Earth orientation measurements. The effects of particular error sources on geodetic and geophysical parameters derived from VLBI data will be illustrated.

Ma, Chopo↗

Modeling MESSENGER Observations of Calcium in Mercury's Exosphere

The Mercury Atmospheric and Surface Composition Spectrometer (MASCS) on the MESSENGER spacecraft has made the first high-spatial-resolution observations of exospheric calcium at Mercury. We use a Monte Carlo model of the exosphere to track the trajectories of calcium atoms ejected from the surface until they are photoionized, escape from the system, or stick to the surface. This model permits an exploration of exospheric source processes and interactions among neutral atoms, solar radiation, and the planetary surface. The MASCS data have suggested that a persistent, high-energy source of calcium that was enhanced in the dawn, equatorial region of Mercury was active during MESSENGER's three flybys of Mercury and during the first seven orbits for which MASCS obtained data. The total Ca source rate from the surface varied between 1.2x10(exp 23) and 2.6x10(exp 23) Ca atoms/s, if its temperature was 50,000 K. The origin of this high-energy, asymmetric source is unknown, although from this limited data set it does not appear to be consistent with micrometeoroid impact vaporization, ion sputtering, electron-stimulated desorption, or vaporization at dawn of material trapped on the cold nightside.

Messenger↗

Modeling and Observational Framework for Diagnosing Local Land-Atmosphere Coupling on Diurnal Time Scales

Land-atmosphere interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during field experiments in the U. S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to the Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. Within this framework, the coupling established by each pairing of the available PBL schemes in WRF with the LSMs in LIS is evaluated in terms of the diurnal temperature and humidity evolution in the mixed layer. The co-evolution of these variables and the convective PBL is sensitive to and, in fact, integrative of the dominant processes that govern the PBL budget, which are synthesized through the use of mixing diagrams. Results show how the sensitivity of land-atmosphere interactions to the specific choice of PBL scheme and LSM varies across surface moisture regimes and can be quantified and evaluated against observations. As such, this methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

Santanello, Joseph A., Jr.↗