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NASA NTRS1993

The effect of dissipative inhomogeneous medium on the statistics of the wave intensity

One of the main theoretical points in the theory of wave propagation in random medium is the derivation of closed form equations to describe the statistics of the propagating waves. In particular, in one dimensional problems, the closed form representation of the multiple scattering effects is important since it contributes in understanding such problems like wave localization, backscattering enhancement, and intensity fluctuations. In this the propagation of plane waves in a layer of one-dimensional dissipative random medium is considered. The medium is modeled by a complex permittivity whose real part is a constant representing the absorption. The one dimensional problem is mathematically equivalent to the analysis of a transmission line with randomly perturbed distributed parameters and a single mode lossy waveguide and the results can be used to study the propagation of radio waves through atmosphere and the remote sensing of geophysical media. It is assumed the scattering medium consists of an ensemble of one-dimensional point scatterers randomly positioned in a layer of thickness L with diffuse boundaries. A Poisson impulse process with density lambda is used to model the position of scatterers in the medium. By employing the Markov properties of this process an exact closed form equation of Kolmogorov-Feller type was obtained for the probability density of the reflection coefficient. This equation was solved by combining two limiting cases: (1) when the density of scatterers is small; and (2) when the medium is weakly dissipative. A two variable perturbation method for small lambda was used to obtain solutions valid for thick layers. These solutions are then asymptotically evaluated for small dissipation. To show the effect of dissipation, the mean and fluctuations of the reflected power are obtained. The results were compared with a lossy homogeneous medium and with a lossless inhomogeneous medium and the regions where the effect of absorption is not essential were discussed.

Saatchi, Sasan S.↗

NASA NTRS2014

A Practical Philosophy of Complex Climate Modelling

We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

complex simulation↗

NASA NTRS2021

Methodology to Assess the Changing Risk of Yield Failure Due to Heat and Drought Stress Under Climate Change

While the understanding of average impacts of climate change on crop yields is improving, few assessments have quantified expected impacts on yield distributions and the risk of yield failures. Here we present the relative distribution as a method to assess how the risk of yield failure due to heat and drought stress (measured in terms of return period between yields falling 15% below previous five year Olympic average yield) responds to changes of the underlying yield distributions under climate change. Relative distributions are used to capture differences in the entire yield distribution between baseline and climate change scenarios, and to further decompose them into changes in the location and shape of the distribution. The methodology is applied here for the case of rainfed wheat and grain maize across Europe using an ensemble of crop models under three climate change scenarios with simulations conducted at 25 km resolution. Under climate change, maize generally displayed shorter return periods of yield failures (with changes under RCP 4.5 between −0.3 and 0 years compared to the baseline scenario) associated with a shift of the yield distribution towards lower values and changes in shape of the distribution that further reduced the frequency of high yields. This response was prominent in the areas characterized in the baseline scenario by high yields and relatively long return periods of failure. Conversely, for wheat, yield failures were projected to become less frequent under future scenarios (with changes in the return period of −0.1 to +0.4 years under RCP 4.5) and were associated with a shift of the distribution towards higher values and a change in shape increasing the frequency of extreme yields at both ends. Our study offers an approach to quantify the changes in yield distributions that drive crop yield failures. Actual risk assessments additionally require models that capture the variety of drivers determining crop yield variability and scenario climate input data that samples the range of probable climate variation.

Climate risk assessment↗

NASA NTRS2009

Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

De Lannoy, Gabrielle J.M.↗

NASA NTRS2018

Exoplanet Biosignatures: Future Directions

We introduce a Bayesian method for guiding future directions for detection of life on exoplanets. We describe empirical and theoretical work necessary to place constraints on the relevant likelihoods, including those emerging from better understanding stellar environment, planetary climate and geophysics, geochemical cycling, the universalities of physics and chemistry, the contingencies of evolutionary history, the properties of life as an emergent complex system, and the mechanisms driving the emergence of life. We provide examples for how the Bayesian formalism could guide future search strategies, including determining observations to prioritize or deciding between targeted searches or larger lower resolution surveys to generate ensemble statistics and address how a Bayesian methodology could constrain the prior probability of life with or without a positive detection.

Bayesian analysis↗

NASA NTRSDate not supplied

Simulation of Radiation-Induced DNA Damage With the Code RITRACKS

INTRODUCTION DNA damage is one of the most physiologically important effects of ionizing radiation. Clustered DNA damage events, like double-strand breaks (DSBs), have the most notable biological consequences. DNA damage types depend on both the track structure of the radiation and the spatial organization of the DNA. High linear energy transfer (LET) charged nuclei, found in galactic cosmic rays (GCR), are known to produce large numbers of complex DNA damage events. The human genome is packaged into chromatin, which can take on locus-dependent and cell type-dependent spatial conformations that correspond to epigenetic states, such as more open, extended structures in transcriptionally active chromatin. These epigenetic differences can affect DNA break patterns in response to ionizing radiation, potentially creating distinct DNA repair and signaling outcomes across the genome in different cells. MATERIAL AND METHODS The code RITRACKS (Relativistic Ion Tracks), which simulates stochastic radiation track structures and radiation chemistry, was used to model damage on isolated and histone-bound DNA by various types of ions and photons. The changes made to the code to perform radiation-induced DNA damage, and simulation results on single nucleosomes are given in our recent paper. In this work, the DNA building capabilities of RITRACKS have been extended to simulate more complex DNA structures build on the coarse-grain simulation framework meso-WLCsim. This code can sample generic chromatin fiber conformation ensembles based on the geometry of nucleosomes and mechanical properties of DNA. Using RITRACKS, we simulated the fragment length distributions (FLD) of irradiated DNA structures built using the chromatin conformations of WLCsim and obtained results representative of those obtained with Radiation-Induced Correlated Cleavage with sequencing (RICC-Seq) experiments [6]. We have also performed Fe ion and photon irradiations of K562, IMR90, BJ and RPE-1 cells at NSRL to experimentally validate results. Sample processing and data analysis are in progress and any available preliminary results will be discussed. DISCUSSION The recent updates in the code RITRACKS allow the calculation of several quantities such as the DNA damage yield and the FLD. This approach can be used to model epigenetic state-specific chromatin structure parameters to leverage the epigenetic state data available for many human cell types to infer relative DNA damage sensitivity among genomic loci.

I Plante↗

NASA NTRS1987

Scattering parameters for aspherical hydrometeors at microwave frequencies

Scattering parameters for ensembles of aspherical ice and liquid hydrometeors were calculated at Psi = 50 deg for frequencies of 37.0, 50.3, and 85.6 GHz. Hydrometeors were assumed to be oblate spheroids whose semiminor axes were aligned at Psi = 0 deg. The angle of 50 deg is determined by the viewing angle of recent satellite-borne radiometers. Backscattering phase functions and extinction coefficients at Psi = 0 deg were also computed at 18.0, 37.0, and 85.6 GHz to provide information for future nadir scanning radars. The hydrometeors were assumed to be characterized by Marshall-Palmer (1948) size distributions. The extended boundary condition method was used to calculate the extinction and backscattering coefficients as well as the albedo for single scattering and the asymmetry factor of the phase function. Results are fitted to simple functions of the rainfall rate. Some comparisons intended to illustrate the differences and similarities of these results with those obtained from equal volume spheres are also presented.

Kummerow, C.↗

NASA NTRS2000

Overcoming Dynamic Disturbances in Imaging Systems

We develop and discuss a methodology with the potential to yield a significant reduction in complexity, cost, and risk of space-borne optical systems in the presence of dynamic disturbances. More robust systems almost certainly will be a result as well. Many future space-based and ground-based optical systems will employ optical control systems to enhance imaging performance. The goal of the optical control subsystem is to determine the wavefront aberrations and remove them. Ideally reducing an aberrated image of the object under investigation to a sufficiently clear (usually diffraction-limited) image. Control will likely be distributed over several elements. These elements may include telescope primary segments, telescope secondary, telescope tertiary, deformable mirror(s), fine steering mirror(s), etc. The last two elements, in particular, may have to provide dynamic control. These control subsystems may become elaborate indeed. But robust system performance will require evaluation of the image quality over a substantial range and in a dynamic environment. Candidate systems for improvement in the Earth Sciences Enterprise could include next generation Landsat systems or atmospheric sensors for dynamic imaging of individual, severe storms. The technology developed here could have a substantial impact on the development of new systems in the Space Science Enterprise; such as the Next Generation Space Telescope(NGST) and its follow-on the Next NGST. Large Interferometric Systems of non-zero field, such as Planet Finder and Submillimeter Probe of the Evolution of Cosmic Structure, could benefit. These systems most likely will contain large, flexible optomechanical structures subject to dynamic disturbance. Furthermore, large systems for high resolution imaging of planets or the sun from space may also benefit. Tactical and Strategic Defense systems will need to image very small targets as well and could benefit from the technology developed here. We discuss a novel speckle imaging technique with the potential to separate dynamic aberrations from static aberrations. Post-processing of a set of image data, using an algorithm based on this technique, should work for all but the lowest light levels and highest frequency dynamic environments. This technique may serve to reduce the complexity of the control system and provide for robust, fault-tolerant, reduced risk operation. For a given object, a short exposure image is "frozen" on the focal plane in the presence of the environmental disturbance (turbulence, jitter, etc.). A key factor is that this imaging data exhibits frame-to-frame linear shift invariance. Therefore, although the Point Spread Function is varying from frame to frame, the source is fixed; and each short exposure contains object spectrum data out to the diffraction limit of the imaging system. This novel speckle imaging technique uses the Knox-Thompson method. The magnitude of the complex object spectrum is straightforward to determine by well-established approaches. The phase of the complex object spectrum is decomposed into two parts. One is a single-valued function determined by the divergence of the optical phase gradient. The other is a multi-valued function determined by the circulation of the optical phase gradient-"hidden phase." Finite difference equations are developed for the phase. The novelty of this approach is captured in the inclusion of this "hidden phase." This technique allows the diffraction-limited reconstruction of the object from the ensemble of short exposure frames while simultaneously estimating the phase as a function of time from a set of exposures.

Young, Eric W.↗

NASA NTRS2000

Overcoming Dynamic Disturbances in Imaging Systems

We develop and discuss a methodology with the potential to yield a significant reduction in complexity, cost, and risk of space-borne optical systems in the presence of dynamic disturbances. More robust systems almost certainly will be a result as well. Many future space-based and ground-based optical systems will employ optical control systems to enhance imaging performance. The goal of the optical control subsystem is to determine the wavefront aberrations and remove them. Ideally reducing an aberrated image of the object under investigation to a sufficiently clear (usually diffraction-limited) image. Control will likely be distributed over several elements. These elements may include telescope primary segments, telescope secondary, telescope tertiary, deformable mirror(s), fine steering mirror(s), etc. The last two elements, in particular, may have to provide dynamic control. These control subsystems may become elaborate indeed. But robust system performance will require evaluation of the image quality over a substantial range and in a dynamic environment. Candidate systems for improvement in the Earth Sciences Enterprise could include next generation Landsat systems or atmospheric sensors for dynamic imaging of individual, severe storms. The technology developed here could have a substantial impact on the development of new systems in the Space Science Enterprise; such as the Next Generation Space Telescope(NGST) and its follow-on the Next NGST. Large Interferometric Systems of non-zero field, such as Planet Finder and Submillimeter Probe of the Evolution of Cosmic Structure, could benefit. These systems most likely will contain large, flexible optormechanical structures subject to dynamic disturbance. Furthermore, large systems for high resolution imaging of planets or the sun from space may also benefit. Tactical and Strategic Defense systems will need to image very small targets as well and could benefit from the technology developed here. We discuss a novel speckle imaging technique with the potential to separate dynamic aberrations from static aberrations. Post-processing of a set of image data, using an algorithm based on this technique, should work for all but the lowest light levels and highest frequency dynamic environments. This technique may serve to reduce the complexity of the control system and provide for robust, fault-tolerant, reduced risk operation. For a given object, a short exposure image is "frozen" on the focal plane in the presence of the environmental disturbance (turbulence, jitter, etc.). A key factor is that this imaging data exhibits frame-to-frame linear shift invariance. Therefore, although the Point Spread Function is varying from frame to frame, the source is fixed; and each short exposure contains object spectrum data out to the diffraction limit of the imaging system. This novel speckle imaging technique uses the Knox-Thompson method. The magnitude of the complex object spectrum is straightforward to determine by well-established approaches. The phase of the complex object spectrum is decomposed into two parts. One is a single-valued function determined by the divergence of the optical phase gradient. The other is a multi-valued function determined by, the circulation of the optical phase gradient-"hidden phase." Finite difference equations are developed for the phase. The novelty of this approach is captured in the inclusion of this "hidden phase." This technique allows the diffraction-limited reconstruction of the object from the ensemble of short exposure frames while simultaneously estimating the phase as a function of time from a set of exposures.

Young, Eric W.↗

NASA NTRS2023

Impact of Design Factors for ESA CCI Satellite Soil Moisture Data Assimilation over Europe

In this study, soil moisture retrievals of the combined active–passive ESA Climate Change Initiative (CCI) soil moisture product are assimilated into the Noah-MP land surface model over Europe using a one-dimensional ensemble Kalman filter and an 18-yr study period. The performance of the data assimilation (DA) system is evaluated by comparing it with a model-only experiment (at in situ sites) and by assessing statistics of innovations and increments as DA diagnostics (over the entire domain). For both assessments, we explore the impact of three design choices, resulting in the following insights. 1) The magnitude of the assumed observation errors strongly affects the skill improvements evaluated against in situ stations and internal diagnostics. 2) Choosing between climatological or monthly cumulative distribution function matching as the observation bias correction method only has a marginal effect on the in situ skill of the DA system. However, the internal diagnostics suggest a more robust system parameterization if the observations are rescaled monthly. 3) The choice of atmospheric reanalysis dataset to force the land surface model affects the model-only skill and the DA skill improvements. The model-only skill is higher with input from the MERRA-2 than with input from the ERA5 reanalysis, resulting in larger DA skill improvements for the latter. Additionally, we show that the added value of the DA strongly depends on the quality of the satellite retrievals and land cover, with the most substantial soil moisture skill improvements occurring over croplands and skill degradation occurring over densely forested areas.

Soil moisture↗

NASA NTRS2020

The Global Methane Budget 2000–2017

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4/yr (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4/yr or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4/yr or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4/yr larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4/yr larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4/yr, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30° N) compared to mid-latitudes (∼ 30 %, 30–60° N) and high northern latitudes (∼ 4 %, 60–90° N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4/yr lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4/yr by 8 Tg CH4/yr, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.

methane budget↗

NASA NTRS1993

A small-scale turbulence model

A previously derived analytical model for the small-scale structure of turbulence is reformulated in such a way that the energy spectrum may be computed. The model is an ensemble of two-dimensional (2D) vortices with internal spiral structure, each stretched by an axially symmetric strain flow. Stretching and differential rotation produce an energy cascade to smaller scales in which the stretching represents the effect of instabilities and the spiral structure is the source of dissipation at the end of the cascade. The energy spectrum of the resulting flow may be expressed as a time integration involving only the enstrophy spectrum of the time evolving 2D cross section flow, which may be obtained numerically. Examples are given in which a k exp -5/3 spectrum is obtained by this method. The k exp -5/3 inertial range spectrum is shown to be related to the existence of a self-similar enstrophy preserving range in the 2D enstrophy spectrum. The results are found to be insensitive to time dependence of the strain rate, including even intermittent on-or-off strains.

Lundgren, T. S.↗

NASA NTRS2003

Spectral Retrieval of Latent Heating Profiles from TRMM PR Data: Comparison of Look-Up Tables

The primary goal of the Tropical Rainfall Measuring Mission (TRMM) is to use the information about distributions of precipitation to determine the four dimensional (i.e., temporal and spatial) patterns of latent heating over the whole tropical region. The Spectral Latent Heating (SLH) algorithm has been developed to estimate latent heating profiles for the TRMM Precipitation Radar (PR) with a cloud- resolving model (CRM). The method uses CRM- generated heating profile look-up tables for the three rain types; convective, shallow stratiform, and anvil rain (deep stratiform with a melting level). For convective and shallow stratiform regions, the look-up table refers to the precipitation top height (PTH). For anvil region, on the other hand, the look- up table refers to the precipitation rate at the melting level instead of PTH. For global applications, it is necessary to examine the universality of the look-up table. In this paper, we compare the look-up tables produced from the numerical simulations of cloud ensembles forced with the Tropical Ocean Global Atmosphere (TOGA) Coupled Atmosphere-Ocean Response Experiment (COARE) data and the GARP Atlantic Tropical Experiment (GATE) data. There are some notable differences between the TOGA-COARE table and the GATE table, especially for the convective heating. First, there is larger number of deepest convective profiles in the TOGA-COARE table than in the GATE table, mainly due to the differences in SST. Second, shallow convective heating is stronger in the TOGA COARE table than in the GATE table. This might be attributable to the difference in the strength of the low-level inversions. Third, altitudes of convective heating maxima are larger in the TOGA COARE table than in the GATE table. Levels of convective heating maxima are located just below the melting level, because warm-rain processes are prevalent in tropical oceanic convective systems. Differences in levels of convective heating maxima probably reflect differences in melting layer heights. We are now extending our study to simulations of other field experiments (e.g. SCSMEX and ARM) in order to examine the universality of the look-up table. The impact of look-up tables on the retrieved latent heating profiles will also be assessed.

Shige, Shoichi↗

NASA NTRS1994

A comparison of CO(J = 1 yields 0) and CO(J = 2 yields 1) emission in the Milky Way molecular ring

We have carried out a CO (J = 2 right arrow 1) survey of the Scutum Arm region of the Milky Way molecular ring. Our goals are to compare CO (J = 2 right arrow 1) maps of individual Galactic clouds with the large-scale CO (J = 2 right arrow 1) emission from the Galactic plane, and to predict the CO (J = 2 right arrow 1) appearance of a Galactic cloud ensemble in an external galaxy. The angular resolution and spatial coverage of our survey are compatible with the existing CO (J = 1 right arrow 0) survey of this region by Sanders et al., which we use for comparison. We identify 34 molecular clouds in our map region; their relationships between size and line width and between virial mass and luminosity are consistent with the relationships seen in CO (J = 1 right arrow 0) emission. However, we note that previous studies have shown considerable variation in these relationships; we attribute much of this variation to differences in their cloud definition algorithm and statistical method. We find that the median ratio of integrated emission in the two lowest CO transitions for the clouds in our sample is I(2 right arrow 1)/ I(1 right arrow 0) = 0.69, implying that the typical emitting region in the line of sight contains cold gas that is not actively star-forming. Our conclusion that the molecular ring emission is not dominated by star-forming regions is consistent with other large-scale studies of the Milky Way. Our distributions of cloud size and temperature also imply that relatively massive molecular clouds that lac k star formation, such as Maddalena's cloud, are not rare in the inner Galaxy.

Chiar, Jean E.↗

NASA NTRS1993

Using x ray images to detect substructure in a sample of 40 Abell clusters

Using a method for constraining the dynamical state of a galaxy cluster by examining the moments of its x-ray surface brightness distribution, we determine the statistics of cluster substructure for a sample of 40 Abell clusters. Using x-ray observations from the Einstein Observatory Imaging Proportional Counter (IPC), we measure the first moment M1(r), the ellipsoidal orientation angle theta2(r), and the axial ratio eta(r) at several different radii in the cluster. We determine the effects of systematics such as x-ray point source emission, telescope vignetting, Poisson noise, and characteristics of the IPC by measuring the same parameters on an ensemble of simulated cluster images. Due to the small band-pass of the IPC, the ICM emissivity is nearly independent of temperature so the intensity at each point in the IPC images is simply proportional to the emission measure calculated along the line of sight through the cluster (e.g. Fabricant et al. 1980). Therefore, barring a change superposition of two x-ray emitting clusters, a significant variation in the image centroid M1(r) as a function of radius indicates that the center of mass of the intra-cluster medium (ICM) varies with radius. We argue that such a configuration (essentially an m = 1 component in the ICM density distribution) is a non-equilibrium component; it results from an off-center subclump or a recent merger in the ICM.

Mohr, J. J.↗

NASA NTRS2013

Synthetic Foveal Imaging Technology

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

Monacos, Steve P.↗

NASA NTRS2015

RACORO Continental Boundary Layer Cloud Investigations: 1. Case Study Development and Ensemble Large-Scale Forcings

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60 h case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in situ measurements from the Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) CLOWD (Clouds with Low Optical Water Depth) Optical Radiative Observations (RACORO) field campaign and remote sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, kappa, are derived from observations to be approximately 0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing data sets are derived from the ARM variational analysis, European Centre for Medium-Range Weather Forecasts, and a multiscale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in "trial" large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

Boundary layers↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗