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NASA NTRS2016

Energetic Electron Acceleration Observed by MMS in the Vicinity of an X-Line Crossing

During the first months of observations, the Magnetospheric Multiscale Fly's Eye Energetic Particle Spectrometer instrument has observed several instances of electron acceleration up to greater than 100 keV while in the vicinity of the dayside reconnection region. While particle acceleration associated with magnetic reconnection has been seen to occur up to these energies in the tail region, it had not yet been reported at the magnetopause. This study reports on observations of electron acceleration up to hundreds of keV that were recorded on 19 September 2015 around 1000 UT, in the midst of an X-line crossing. In the region surrounding the X-line, whistler-mode and broadband electrostatic waves were observed simultaneously with the appearance of highly energetic electrons which exhibited significant energization in the perpendicular direction. The mechanisms by which particles may be accelerated via reconnection-related processes are intrinsic to understanding particle dynamics among a wide range of spatial scales and plasma environments.

Jaynes, A. N.↗

NASA NTRS2021

First Attempt of Global-scale Assimilation of Subdaily Scale Soil Moisture Estimates from CYGNSS and SMAP into a Land Surface Model

Soil moisture performs a key function in the hydrologic process and understanding the global-scale water cycle. However, estimations of soil moisture taken from current sun-synchronous orbit (SSO) satellites are limited in that they are neither spatially nor temporally continuous. This limitation creates discontinuous soil moisture observation from space and hampers our understanding of the fundamental processes that control the surface hydrologic cycle across both time and space domains. Here, we propose to use frequent soil moisture observations from NASA’s constellation of eight micro-satellites called the Cyclone Global Navigation Satellite System(CYGNSS) together with the Soil Moisture Active Passive (SMAP) to assimilate subdaily-scale soil moisture intoa land surface model(LSM). Our results, which are based on triple collocation analysis(TCA), show how current scientific advances in satellite systems can fill previous gaps in soil moisture observations in subdaily scale bypast observations, and eventually adds value to improvements in global scale soil moisture estimates in LSMs. Overall, TCA-based fractional mean square errors (fMSE) of LSM soil moisture are improved by 61% with the synergetic assimilation of CYGNSS data with SMAP soil moisture observations. However, assimilating satellite-based soil moisture over dense vegetation areas can degrade the performance of LSMs as these areas propagate erroneous soil moisture information to LSMs. To our knowledge, this study isthe first global assimilation of GNSS-based soil moisture observations in land surface models.

Hyunglok Kim↗

NASA NTRSDate not supplied

Recent Advancements in Electrical Capacitance Mass Gauging for Cryogenic PropellantTanks

The current lack of unsettled mass gauging is a key roadblock for many space activities, such as orbital refueling, missions to the Moon and Mars, and nuclear thermal and nuclear electric propulsion technologies. Liquid can form any one of an infinite number of configurations in microgravity, such as floating in globs or accumulating on tank surfaces in discontiguous volumes, or both. Capacitive sensing requires no moving parts and dissipates close to zero heat, making it an ideal candidate for cryogenic fluid mass gauging in settled and unsettled configurations. Capacitive sensing has a history of proven use in space propellant tanks, including tanks on the space shuttle, Saturn V, and the Apollo Lunar Excursion Module. Modern capacitive sensor technology allows using the entire tank as the capacitor volume by placing electrodes on the tank walls and propellant management surfaces. Capacitance is directly related to density, and therefore to mass for fixed volumes. In this presentation, we discuss the concepts behind whole-tank capacitance mass gauging and associated engineering challenges. We describe recent efforts to develop a micro-g unsettled cryogenic mass gauge using whole-tank capacitance sensing, including the development of test beds, electronics, and algorithms. We describe several mathematical processing techniques, including empirical-based averaging, electrical capacitance volume tomography, and spatial regularization. A modeling study, performed using settled configurations in gravity and no gravity, and with a set of 100 random fluid configurations, has indicated that spatial regularization, in which capacitance measurements are weighted to account for non-uniform electric fields, yields a mass fraction accuracy of 8% for any fluid configuration. Such a sensor is expected to operate in real time with a sampling frequency of at least 1 kHz.

cryogenic↗

NASA NTRS2020

Identifying Hurricane Impacts on Barbuda Using Citizen Science Ground Observations, Drone Photography and Satellite Imagery

Barbuda is a low-lying leeward island in the West Indies. In September 2017 Hurricane Irma battered the island with 185 mph winds. Damage to housing and infrastructure was so extensive that all 1800 residents of the island were immediately evacuated post hurricane to the neighboring island of Antigua. Our research is focused on documenting and analyzing the landscape scale changes that took place on the island as a result of the hurricane using a nested methodology. Ground level observations were recorded using a beta version of the Global Learning and Observation to Benefit the Environment (GLOBE) Observer Land Cover tool. Aerial photographs provide medium scale landscape resolution. Satellite images were processed to provide NDVI values. We describe how nested data at several spatial scales enable detailed description of Hurricane Irma’s impact across the landscape of this 62 sq. mile island. Here we are connecting observations at different spatial scales, using citizen science observations, aerial drone photography and satellite imagery to document and analyze hurricane impacts on the island of Barbuda, eastern Caribbean.

Barbuda↗

NASA NTRSDate not supplied

Generating a 4D Global CH(4) Product by Assimilating TROPOMI column CH(4) in NASA’s GEOS GCM

Examination of temporal and spatial CH4 variability is crucial for better understanding the human and natural processes driving climate change and ultimately designing mitigation strategies. Here we present an analysis framework that uses NASA’s GEOS General Circulation Model (GCM) to construct a high-resolution, time varying picture of atmospheric CH4 consistent with measurements from a variety of platforms, both in situ and remotely sensed. The resulting time varying atmospheric CH4 product can (i) support interpretation of high-resolution point source detection approaches, (ii) provide reanalysis fields for CH4 and other greenhouse gases, and (iii) supply boundary conditions for regional models. Our approach starts with a set of CH4 emissions from various inventories that have been adjusted to match the global annual growth rate over recent decades. These emissions are transported by the GEOS GCM, which in turn is constrained by meteorology from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) product. The simulated atmospheric field is compared with CH4 measurements, such as those from the TROPOspheric Monitoring Instrument (TROPOMI), and adjustments calculated following a Bayesian protocol. The accuracy of the resultant optimal atmospheric CH4 field can be demonstrated by its improved agreement (compared to a direct simulation of the CH4 inventories) with a host of independent CH4 measurements, such as those from the Total Carbon Column Observation Network (TCCON) and in situ observations from surface and airborne platforms.

Nikolay V. Balashov↗

NASA NTRS2004

Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

Hood, Kenneth Brown↗

NASA NTRS2007

Method and system for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

Hood, Kenneth Brown↗

NASA NTRS1997

Laser-Induced Incandescence in Microgravity

Knowledge of soot concentration is important due to its presence and impact upon a wide range of combustion processes ranging from diffusion to premixed flames, laminar to turbulent processes and homogeneous to heterogeneous combustion. Measurement of soot volume fraction (f(sub v)) is essential to discerning its formation and growth. The presence of soot also affects other physical and chemical properties of combustion thereby affecting studies not directly concerned with either its formation or growth, such as radiative heat transfer, CO oxidation and fuel vaporization or pyrolysis rates. Microgravity offers unique opportunities for studying both soot growth and the effect of soot radiation upon flame structure and spread. Spatial scales and residence time scales are greatly extended in 0-g facilitating soot growth studies. With the varied geometries, short duration microgravity test times and time-varying processes there is a demand for measurement of f(sub v) with high spatial and temporal resolution. Laser-induced incandescence (LII) has advanced f(sub v) measurements in many 1-g combustion processes. To create laser-induced incandescence, a pulsed high intensity laser heats soot to incandescence temperatures. Using appropriate spectral and temporal detection conditions, the resulting incandescence can be selectively detected apart from the non-laser-heated soot and flame gases. Theoretical modelling and experiments have shown that the resulting incandescence is representative of f(sub v). Using an intensified array camera and a laser sheet for excitation, one- and two-dimensionally resolved LII images of f(sub v) have been obtained in 1-g. LII has been characterized and developed at NASA-Lewis for soot volume fraction determination in a wide range of 1-g combustion applications. Broadly grouped, the characterization work has included studies of excitation intensity, excitation wavelength and the optimum temporal and spectral detection conditions to enable an accurate representation of soot volume fraction by LII. Tests for special requirements imposed by different combustion processes have been performed in laminar and turbulent diffusion flames, rich sooting premixed flames, single droplet combustion, and other heterogeneous combustion. These studies demonstrated LII's high sensitivity, temporal and spatial capabilities and its geometric versatility. In contrast to the advantages offered to combustion studies by a microgravity environment, advanced diagnostics, specifically those requiring pulsed laser diagnostics have been limited due to the size, weight and power limitations in a low-gravity environment. Reported here are the first demonstrations of LII performed in a microgravity environment. Examples are shown for laminar and turbulent gas-jet diffusion flames in 0-g.

VanderWal, Randy L.↗

NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗

NASA NTRS2001

Models of Small-Scale Patchiness

Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.

McGillicuddy, D. J.↗

NASA NTRS1995

Clouds and the Earth's Radiant Energy System (CERES) algorithm theoretical basis document: Determination of surface and atmosphere fluxes and temporally and spatially averaged products (subsystems 5-12) - volume 4

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and the Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 4 details the advanced CERES techniques for computing surface and atmospheric radiative fluxes (using the coincident CERES cloud property and top-of-the-atmosphere (TOA) flux products) and for averaging the cloud properties and TOA, atmospheric, and surface radiative fluxes over various temporal and spatial scales. CERES attempts to match the observed TOA fluxes with radiative transfer calculations that use as input the CERES cloud products and NOAA National Meteorological Center analyses of temperature and humidity. Slight adjustments in the cloud products are made to obtain agreement of the calculated and observed TOA fluxes. The computed products include shortwave and longwave fluxes from the surface to the TOA. The CERES instantaneous products are averaged on a 1.25-deg latitude-longitude grid, then interpolated to produce global, synoptic maps to TOA fluxes and cloud properties by using 3-hourly, normalized radiances from geostationary meteorological satellites. Surface and atmospheric fluxes are computed by using these interpolated quantities. Clear-sky and total fluxes and cloud properties are then averaged over various scales.

Wielicki, Bruce A.↗

NASA NTRS2014

Diagnosis of Middle Atmosphere Climate Sensitivity by the Climate Feedback Response Analysis Method

We present a new method to diagnose the middle atmosphere climate sensitivity by extending the Climate Feedback-Response Analysis Method (CFRAM) for the coupled atmosphere-surface system to the middle atmosphere. The Middle atmosphere CFRAM (MCFRAM) is built on the atmospheric energy equation per unit mass with radiative heating and cooling rates as its major thermal energy sources. MCFRAM preserves the CFRAM unique feature of an additive property for which the sum of all partial temperature changes due to variations in external forcing and feedback processes equals the observed temperature change. In addition, MCFRAM establishes a physical relationship of radiative damping between the energy perturbations associated with various feedback processes and temperature perturbations associated with thermal responses. MCFRAM is applied to both measurements and model output fields to diagnose the middle atmosphere climate sensitivity. It is found that the largest component of the middle atmosphere temperature response to the 11-year solar cycle (solar maximum vs. solar minimum) is directly from the partial temperature change due to the variation of the input solar flux. Increasing CO2 always cools the middle atmosphere with time whereas partial temperature change due to O3 variation could be either positive or negative. The partial temperature changes due to different feedbacks show distinctly different spatial patterns. The thermally driven globally averaged partial temperature change due to all radiative processes is approximately equal to the observed temperature change, ranging from 0.5 K near 70 km from the near solar maximum to the solar minimum.

MCFRAM↗

NASA NTRS2010

Direct Measurement Sensor of the Boundary Shear Stress in Fluid Flow

The flow fields and boundary erosion that are associated with scour at bridge piers are very complex. Direct measurement of the boundary shear stress and boundary pressure fluctuations in experimental scour research has always been a challenge and high spatial resolution and fidelity have been almost impossible. Most researchers have applied an indirect process to determine shear stress using precise measured velocity profiles. Laser Doppler Anemometry and Particle Image Velocimetry are common techniques used to accurately measure velocity profiles. These methods are based on theoretical assumptions to estimate boundary shear stress. In addition, available turbulence models cannot very well account for the effect of bed roughness which is fundamentally important for any CFD simulation. The authors have taken on the challenge to advance the magnitude level to which direct measurements of the shear stress in water flow can be performed. This paper covered the challenges and the efforts to develop a higher accuracy and small spatial resolution sensor. Also, preliminary sensor designs and test results are presented.

Badescu, Mircea↗

NASA NTRS1993

Grand challenge scientific questions in coupled modeling

Most convective field experiments in the past (e.g., SESAME, CCOPE, CINDE) have attempted to resolve only the immediate scales of moist convection using network arrays that spanned two or three atmospheric scales at most. Furthermore, these scales have been defined more on practical considerations (cost, manpower, etc.) than on a clear understanding of their theoretical significance. Unfortunately, this has precluded a description of the entire life cycle of MCS's and their interaction with larger scale systems, the land surface, and trace species. Fortunately, the following factors now make it possible to attempt to simulate scale contraction processes from the synoptic scale down to the cloud scale, as well as interactions between complex meteorological, land surface, precipitation, chemical, and hydrologic processes with coupled, multiscale models: the availability of new technology to sample meteorological fields at high temporal and spatial resolution over a broad region made possible by the weather observing modernization program; increased computer power and improved numerical approaches to run limited area models with nonhydrostatic precipitation physics so as to explicitly resolve MCS (Mesoscale Convective System) processes; and four dimensional assimilation of non-conventional data to provide dynamically consistent datasets for diagnostic analysis of nonlinear scale-interactive dynamics. Several examples of scale-interactive processes which present grand challenges for coupled, multiscale modeling were presented.

Koch, Steven↗

NASA NTRS2001

A dissociation between attention and selection

It is widely assumed that the allocatian of spatial attention results in the "selection" of attended objects or regions of space. That is, once a stimulus is attended, all its feature dimensions are processed irrespective of their relevance to behavioral goals. This assumption is based in part on experiments showing significant interference for attended stimuli when the response to an irrelevant dimension conflicts with the response to the relevant dimension (e.g., the Stroop effect). Here we show that such interference is not due to attending per se. In two spatial cuing experiments, we found that it was possible to restrict processing of attended stimuli to task-relevant dimensions. This new evidence supports two novel conclusions: (a) Selection involves more than the focusing of attention per se: and (b) task expectations play a key role in detertnining the depth of processing of the elementary feature dimensions of attended stimuli.

Attention↗

NASA NTRS1992

Three-dimensional co-culture process

The present invention relates to a 3-dimensional co-culture process, more particularly to methods or co-culturing at least two types of cells in a culture environment, either in space or in unit gravity, with minimum shear stress, freedom for 3-dimensional spatial orientation of the suspended particles and localization of particles with differing or similar sedimentation properties in a similar spatial region to form 3-dimensional tissue-like structures. Several examples of multicellular 3-dimensional experiences are included. The protocol and procedure are also set forth. The process allows simultaneous culture of multiple cell types and supporting substrates in a manner which does not disrupt the 3-dimensional spatial orientation of these components. The co-cultured cells cause a mutual induction effect which mimics the natural hormonal signals and cell interactions found in the intact organism. This causes the tissues to differentiate and form higher 3-dimensional structures such as glands, junctional complexes polypoid geometries, and microvilli which represent the corresponding in-vitro structures to a greater degree than when the cell types are cultured individually or by conventional processes. This process was clearly demonstrated for the case of two epithelial derived colon cancer lines, each co-cultured with normal human fibroblasts and with microcarrier bead substrates. The results clearly demonstrate increased 3-dimensional tissue-like structure and biochemical evidence of an increased differentiation state. With the present invention a variety of cells may be co-cultured to produce tissue which has 3-dimensionality and has some of the characteristics of in-vitro tissue. The process provides enhanced 3-dimensional tissue which create a multicellular organoid differentiation model.

Wolf, David A.↗

NASA NTRS2010

Utilizing Earth Observations for Societal Issues

Over the last four decades a tremendous progress has been made in the Earth science space-based remote sensing observations, technologies and algorithms. Such advancements have improved the predictability by providing lead-time and accuracy of forecast in weather, climate, natural hazards, and natural resources. It has further reduced or bounded the overall uncertainties by partially improving our understanding of planet Earth as an integrated system that is governed by non-linear and chaotic behavior. Many countries such as the US, European Community, Japan, China, Russia, India has and others have invested billions of dollars in developing and launching space-based assets in the low earth (LEO) and geostationary (GEO) orbits. However, the wealth of this scientific knowledge that has potential of extracting monumental socio-economic benefits from such large investments have been slow in reaching the public and decision makers. For instance, there are a number of areas such as water resources and availability, energy forecasting, aviation safety, agricultural competitiveness, disaster management, air quality and public health, which can directly take advantage. Nevertheless, we all live in a global economy that depends on access to the best available Earth Science information for all inhabitants of this planet. This presentation discusses a process to transition Earth science data and products for societal needs including NASA's experience in achieving such objectives. It is important to mention that there are many challenges and issues that pertain to a number of areas such as: (1) difficulties in making a speedy transition of data and information from observations and models to relevant Decision Support Systems (DSS) or tools, (2) data and models inter-operability issues, (3) limitations of spatial, spectral and temporal resolution, (4) communication limitations as dictated by the availability of image processing and data compression techniques. Additionally, the most critical element amongst all is the organizational and management boundaries that must be resolved at local, state, national and international levels to implement and realize free flow of such vital information.

Habib, Shahid↗

NASA NTRS1973

On Digital Simulation of Multicorrelated Random Processes and Its Applications

Two methods are described to simulate, on a digital computer, a set of correlated, stationary, and Gaussian time series with zero mean from the given matrix of power spectral densities and cross spectral densities. The first method is based upon trigonometric series with random amplitudes and deterministic phase angles. The random amplitudes are generated by using a standard random number generator subroutine. An example is given which corresponds to three components of wind velocities at two different spatial locations for a total of six correlated time series. In the second method, the whole process is carried out using the Fast Fourier Transform approach. This method gives more accurate results and works about twenty times faster for a set of six correlated time series.

Sinha, A. K.↗