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At least 1,027 records · Page 57

Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content(LWC)

This paper presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetically active radiation (PAR) absorbed by chlorophyll of a canopy (fAPARchl) and leaf water content (LWC), for future HyspIRI implementation at 60-m spatial resolution. For this, we used existing 30-m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRIlike images were atmospherically corrected to obtain surface reflectance and spectrally resampled to produce 60-m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest. With this paper, we provide additional evidence that the fAPARchl product is more realistic in describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPARcanopy), and thus, it should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle and ecosystem studies.

Earth Observing One↗

Quantifying the Amount of Ice in Cold Tropical Cirrus Clouds

How much ice is there in the Tropical Tropopause layer, globally? How does one begin to answer that question? Clouds are currently the largest source of uncertainty in climate models, and the ice water content (IWC) of cold cirrus clouds is needed to understand the total water and radiation budgets of the upper troposphere and lower stratosphere (UT/LS). The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, originally a "pathfinder" mission only expected to last for three years, has now been operational for more than eight years. Lidar data from CALIPSO can provide information about how IWC is vertically distributed in the UT/LS, and about inter-annual variability and seasonal changes in cloud ice. However, cloud IWC is difficult to measure accurately with either remote or in situ instruments because IWC from cold cirrus clouds is derived from the particle cross-sectional area or visible extinction coefficient. Assumptions must be made about the relationship between the area, volume and density of ice particles with various crystal habits. Recently there have been numerous aircraft field campaigns providing detailed information about cirrus ice water content from cloud probes. This presentation evaluates the assumptions made when creating the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) global IWC data set, using recently reanalyzed aircraft particle probe measurements of very cold, thin TTL cirrus from the 2006 CR-AVE.

Avery, Melody A.↗

Sonic Boom Pressure Signature Uncertainty Calculation and Propagation to Ground Noise

The objective of this study was to outline an approach for the quantification of uncertainty in sonic boom measurements and to investigate the effect of various near-field uncertainty representation approaches on ground noise predictions. These approaches included a symmetric versus asymmetric uncertainty band representation and a dispersion technique based on a partial sum Fourier series that allows for the inclusion of random error sources in the uncertainty. The near-field uncertainty was propagated to the ground level, along with additional uncertainty in the propagation modeling. Estimates of perceived loudness were obtained for the various types of uncertainty representation in the near-field. Analyses were performed on three configurations of interest to the sonic boom community: the SEEB-ALR, the 69o DeltaWing, and the LM 1021-01. Results showed that representation of the near-field uncertainty plays a key role in ground noise predictions. Using a Fourier series based dispersion approach can double the amount of uncertainty in the ground noise compared to a pure bias representation. Compared to previous computational fluid dynamics results, uncertainty in ground noise predictions were greater when considering the near-field experimental uncertainty.

West, Thomas K., IV↗

National Climate Assessment - Land Data Assimilation System (NCA-LDAS) Data at NASA GES DISC

As part of NASA's active participation in the Interagency National Climate Assessment (NCA) program, the Goddard Space Flight Center's Hydrological Sciences Laboratory (HSL) is supporting an Integrated Terrestrial Water Analysis, by using NASA's Land Information System (LIS) and Land Data Assimilation System (LDAS) capabilities. To maximize the benefit of the NCA-LDAS, on completion of planned model runs and uncertainty analysis, NASA will provide open access to all NCA-LDAS components, including input data, output fields, and indicator data, to other NCA-teams and the general public. The NCA-LDAS data will be archived at the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) and can be accessed via direct ftp, THREDDS, Mirador search and download, and Giovanni visualization and analysis system.

land surface↗

Cis-Lunar Reusable In-Space Transportation Architecture for the Evolvable Mars Campaign

Human exploration missions to Mars or other destinations in the solar system require large quantities of propellant to enable the transportation of required elements from Earth's sphere of influence to Mars. Current and proposed launch vehicles are incapable of launching all of the requisite mass on a single vehicle; hence, multiple launches and in-space aggregation are required to perform a Mars mission. This study examines the potential of reusable chemical propulsion stages based in cis-lunar space to meet the transportation objectives of the Evolvable Mars Campaign and identifies cis-lunar propellant supply requirements. These stages could be supplied with fuel and oxidizer delivered to cis-lunar space, either launched from Earth or other inner solar system sources such as the Moon or near Earth asteroids. The effects of uncertainty in the model parameters are evaluated through sensitivity analysis of key parameters including the liquid propellant combination, inert mass fraction of the vehicle, change in velocity margin, and change in payload masses. The outcomes of this research include a description of the transportation elements, the architecture that they enable, and an option for a campaign that meets the objectives of the Evolvable Mars Campaign. This provides a more complete understanding of the propellant requirements, as a function of time, that must be delivered to cis-lunar space. Over the selected sensitivity ranges for the current payload and schedule requirements of the 2016 point of departure of the Evolvable Mars Campaign destination systems, the resulting propellant delivery quantities are between 34 and 61 tonnes per year of hydrogen and oxygen propellant, or between 53 and 76 tonnes per year of methane and oxygen propellant, or between 74 and 92 tonnes per year of hypergolic propellant. These estimates can guide future propellant manufacture and/or delivery architectural analysis.

McVay, Eric S.↗

The Global Drivers of Photosynthesis and Light Use Efficiency Seasonality: A Granger Frequency Causality Analysis

Photosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe.

photosynthesis↗

Overview of Recent EAST Testing, Modeling & Analysis

Shock Layer Radiation at NASA Ames - Background: Complex aerothermal and thermochemical phenomena of planetary entry define convective and radiative heating. A spacecraft's TPS (Thermal Protective System) mitigates heat transfer to substructure. Successful TPS design relies on verifiable characterization of these phenomena in the anticipated flight environment. - Approach: EAST (Electric Arc Shock Tube) [facility at Ames] simulates high-enthalpy, real-gas phenomena encountered by hypersonic vehicles entering planetary atmospheres by spectrally imaging the flow behind a moving shock wave. - Goal: Validate aerothermal models (DPLR (Data Parallel Line Relaxation Code) and NEQAIR (Nonequilibrium Radiative Transport and Spectra Program)), inform model improvements, reduce uncertainty and quantify design uncertainties. - Recent Relevant Projects: MSL (Mars Science Laboratory) & Mars 2020, InSight, OSIRIS-REx (Origins Spectral Interpretation Resource Identification Security Regolith Explorer), Orion EFT-1 (Exploration Flight-1) and EM-1 (Exploration Mission-1) and New Frontiers.

Brandis, Aaron↗

Parameter Estimation for Compact Binary Coalescence Signals with the First Generation Gravitational-Wave Detector Network

Compact binary systems with neutron stars or black holes are one of the most promising sources for ground-based gravitational-wave detectors. Gravitational radiation encodes rich information about source physics; thus parameter estimation and model selection are crucial analysis steps for any detection candidate events. Detailed models of the anticipated waveforms enable inference on several parameters, such as component masses, spins, sky location and distance, that are essential for new astrophysical studies of these sources. However, accurate measurements of these parameters and discrimination of models describing the underlying physics are complicated by artifacts in the data, uncertainties in the waveform models and in the calibration of the detectors. Here we report such measurements on a selection of simulated signals added either in hardware or software to the data collected by the two LIGO instruments and the Virgo detector during their most recent joint science run, including a blind injection where the signal was not initially revealed to the collaboration. We exemplify the ability to extract information about the source physics on signals that cover the neutron-star and black-hole binary parameter space over the component mass range 1M25M and the full range of spin parameters. The cases reported in this study provide a snapshot of the status of parameter estimation in preparation for the operation of advanced detectors.

Aasi, J.↗

Charactarization of Thermal Protection Systems

In 2012, NASA's mission of landing the Mars Science Laboratory (MSL) on Mars was successful. MSL was protected by an ablative heatshield of tiled low density material known as PICA (phenolic impregnated carbon ablator). The heatshield was instrumented with MEDLI (MSL Entry Descent Landing Instrument) a suite of sensors & thermocouples at discrete locations in order to monitor the in-depth ablator temperature response and surface pressure. MEDLI was designed and developed by NASA Langley, in partnership with NASA Ames Research Center for the purposes of probing Mars and evaluating the performance of the spacecraft upon entry into the Martian atmosphere. The flight data reduces the uncertainty in engineer models for predicting the response of a spacecraft towards the extreme heating environment of an entry into the Martian atmosphere. MEDLI2 is a part of the Mars 2020 mission and is the next-generation sensor suite for entry, descent, and landing. This data will again help engineers validate their flight models. Additionally, the atmospheric data, can help us understand atmospheric density and winds. This is a critical study for reducing risks to both robotic and future human missions to Mars. Engineered models for Mars 2020 are dependent upon parameters related to the materials response to heating and radiation. In this work, the thermal properties and other measurements of various ablative materials are analyzed to achieve greater utility of the 2012 MEDLI flight data and more accurately determine the parameters being used in Mars 2020. The purpose of this study was to measure specific heat, thermal conductivity, char yield, reflectance as a function of wavelength, and other thermal parameters and optical properties of various ablative materials. CO2(g) at extreme temperatures emits radiation impacting MEDLI2 flight predictions. Emissivity & absorptivity as a function of temperature were calculated from FTIR and UV-Vis data as a means of investigating whether these materials might absorb CO2 radiation upon entry into the Mars atmosphere.

HEEET↗

SWIRP (Submm-Wave and Long Wave InfraRed Polarimeter); Development and Characterization of a Sub-Mm Polarimeter for Ice Cloud Investigations

A major source of uncertainty in climate models is the presence, shape and distribution of ice particles in the uppermost layers of the clouds. The effects of this component are poorly constrained, turning ice particles into an almost-free variable in many climate models.NASA-GSFC is developing a new instrument aimed at measuring the size and shape of ice particles. The instrument consists of two sub-mm polarimeters (at 220 and 670 GHz) coupled with a long-wave infrared polarimeter at 10 micron. Each polarimeter has identical V-pol and H-pol channels; the axes of polarization are defined geometrically by the orientation of the waveguide elements, and the purity has been measured in the lab. The instrument is configured as a conical scanner, suitable for deployment as a payload on a small satellite or on a high-altitude sub-orbital platform. From a 400 km orbit, the instrument has a 3dB spatial resolution of 20 (10) km at 220 (670) GHz and a swath of 600 km over 180 degrees of view.The BAPTA (Bearing And Power Transfer Assembly) carries heritage from the SSMIS design, now in its 22nd year of on-orbit operation, but with a much reduced SWaP (Size Weight and Power) footprint, suitable for a small satellite.The main components of the instrument have been fabricated and are undergoing final testing prior to their integration as a single unit. The sub-mm channels have dedicated secondary reflectors which illuminate a shared primary reflector. The receiving units are placed behind the focal point of the optical arrangement, so that all beams equally illuminate the primary reflector and are almost co-located on the ground (within a single 220 GHz footprint). Primary and secondary beam patterns have been measured and verified to match the as-designed expectations. A Zytex (TM) window is deployed to protect the secondary reflectors and the feed horns from debris and other contaminants, and to reduce the heat load from the active (hot) IR calibration unit. The insertion loss of Zytex has been measured and is accounted in the calibration equation of the sub-mm channels.The radiometric performance of the sub-mm receivers has been characterized in the lab and under operational conditions of temperature and pressure.This paper discusses the design constraints on the sub-mm components, details of the scientific goals and their flowdown, and describes the characterization of the polarimeters. Options to optimize the layout and distribution of the masses within the assembly, with the goal of making the instrument even more compact and fully-compatible with cubesat-class satellites will be presented.

De Amici, G.↗

TPSAS-NF1676L-33231-DND

It is well established that clouds have a profound influence on Earth's energy budget and that cloud feedbacks are responsible for much of the uncertainty in climate model projections of global warming in response to radiative forcing by greenhouse gases. While most model evaluation efforts focus on model representation of the observed mean state. For example, the regional mean climatology of key climate variables there is also tremendous value in testing how a model represents observed internal variations of the climate system. Here we use CERES observations during and after the so-called global warming hiatus to evaluate a subset of CMIP6 climate models. The CERES data show a marked 0.83 Wm-2 reduction in global mean reflected SW TOA flux during the three years following the hiatus that results in an increase in net energy into the climate system. The primary driver of the decrease in SW TOA flux is a reduction in low cloud cover over the eastern Pacific Ocean that occurs in response to an unprecedented increase in SSTs in that region following the hiatus. The CMIP6 simulations consist of AMIP-style experiments in which SSTs and sea-ice boundary conditions are constrained by observations. For each model, the AMIP runs were extended through the end of 2017 from the official CMIP6 AMIP end period in 2014. Results show that the models do a good job at capturing the pattern of observed changes in TOA flux observed by CERES, but tend to underestimate the magnitude.

Norman G Loeb↗

Submm polarimetric radiometers for investigations of distribution and size of ice in clouds' top layers

The sources of uncertainty in climate models are many and varied. Over the years, experiment and theory have reduced their importance and extent, but the effect of clouds, and ice clouds in particular, remains poorly understood. The effects of ice clouds are often used as tuning parameters, to balance the budget of incoming and outgoing radiation at the top of the atmosphere and achieve energy equilibrium. NASA's Aerosol, Cloud and Ecosystems (ACE), an Earth Science Decadal Survey (DS) mission, recommends that a science payload with submillimeter wave (sub-mm) and longwave infrared(LWIR) radiometers be developed for such cloud ice measurement. This paper reports on the calibration and characterization of the sub-millimeter channels of one such instrument.

G De Amici↗

Recent Amplified Global Gross Primary Productivity Due to Temperature Increase is Offset by Reduced Productivity Due to Water Constraints

Satellite remote sensing observationsshow an increased greenness trend over land in recent decades. Whilegreennessobservationscanindicateincreased productivity, estimation of total annual productivity is highly dependent on vegetation response to climate and environmental conditions. Models have been struggling to determinehow much carbon is taken up by plants as a result of increased atmospheric CO2fertilization. Current remote sensing light use efficiency (LUE) models contain considerable uncertainty due to the lack of spatial and temporal variability in maximum LUE parameter and climate sensitivity defined for global plantfunctional types (PFTs). We usedthe optimum LUE (LUEopt) previously derived fromtheglobal FLUXNET network to improve estimation of global gross primary productivity (GPP)for the period 1982–2016. Our results indicateincreasing GPP in northern latitudesowing to reduced cold temperature constraintson plant growth, thereby suggesting increasing negative carbon-climate feedbackin high latitudes. In the tropics, by contrast, our results indicate an emerging positive climate feedback,mainly due to increasing atmospheric vapor pressure deficit(VPD).Further pervasive VPD increase is likely to continue to reduce global GPPand amplify carbon emissions.

Climate change↗

Laboratory Measurements of X-ray Emission from Highly Charged Argon Ions

Uncertainties in atomic models will introduce noticeable additional systematics in calculating the flux of weak dielectronic recombination (DR) satellite lines, affecting the detection and flux measurements of other weak spectral lines. One important example is the Ar xvii Heβ DR, which is expected to be present in emission from the hot intracluster medium of galaxy clusters and could impact measurements of the flux of the 3.5 keV line that has been suggested as a secondary emission from a dark matter interaction. We perform a set of experiments using the Lawrence Livermore National Laboratory's electron beam ion trap (EBIT-I) and the X-ray Spectrometer quantum calorimeter (XRS/EBIT) to test the Ar xvii Heβ DR origin of the 3.5 keV line. We measured the X-ray emission following resonant DR onto helium-like and lithium-like Argon using EBIT-I's Maxwellian simulator mode at a simulated electron temperature of T(e) = 1.74 keV. The measured flux of the Ar xvii Heβ DR lined is too weak to account for the flux in the 3.5 keV line, assuming reasonable plasma parameters. We, therefore, rule out Ar xvii Heβ DR as a significant contributor to the 3.5 keV line. A comprehensive comparison between the atomic theory and the EBIT experiment results is also provided.

Esra Bulbul↗

Preconditioning of overcast-to-broken cloud transitions by riming in marine cold air outbreaks

Marine cold air outbreaks (CAOs) commonly form overcast cloud decks that transition into broken cloud fields downwind, dramatically altering the local radiation budget. In this study, we investigate the impact of frozen hydrometeors on these transitions. We focus on a CAO case in the NW Atlantic, the location of the multi-year flight campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment). We use MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2) reanalysis fields to drive large eddy simulations with mixed-phase two-moment microphysics in a Lagrangian framework. We find that transitions are triggered by substantial rain (rainwater paths >25 g m−2), and only simulations that allow for aerosol depletion result in sustained breakups, as observed. Using a range of diagnostic ice nucleating particle concentrations, Ninp, we find that increasing ice progressively accelerates transitions, thus abbreviating the overcast state. Ice particles affect the cloud-topped boundary layer evolution, primarily through riming-related processes prior to substantial rain, leading to (1) a reduction in cloud liquid water, (2) early consumption of cloud condensation nuclei, and (3) early and light precipitation cooling and moistening below cloud. We refer to these three effects collectively as “preconditioning by riming”. Greater boundary layer aerosol concentrations available as cloud condensation nuclei (CCN) delay the onset of substantial rain. However, cloud breakup and low CCN concentration final stages are found to be inevitable in this case, due, primarily, to liquid water path buildup. An ice-modulated cloud transition speed suggests the possibility of a negative cloud–climate feedback. To address prevailing uncertainties in the model representation of mixed-phase processes, the magnitude of ice formation and riming impacts and, thereby, the strength of an associated negative cloud–climate feedback process, requires further observational evaluation by targeting riming hot spots with in situ imaging probes that allow for both the characterization of ice particles and abundance of supercooled droplets.

Marine cold air outbreaks↗

ArcjetCV: a new machine learning application for extracting time-resolved recession measurements from arc jet test videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗

Analyzing the Efficacy of Flexible Execution, Replanning, and Plan Optimization for a Planetary Lander

Plan execution in unknown environments poses a number of challenges: uncertainty in domain modeling, stochasticity at execution time, and the presence of exogenous events. These challenges motivate an integrated approach to planning and execution that is able to respond intelligently to variation. We examine this problem in the context of the Europa Lander mission concept, and propose a planning and execution framework that responds to feedback and task failure using two techniques: flexible execution and replanning with plan optimization. We develop a theoretical framework to predict the value of each of these techniques, and we compare these predictions to empirical results generated in simulation. We demonstrate that an integrated approach to planning and execution that is grounded in flexible execution, replanning, and utility maximization will be an enabling technology for future tightly-constrained planetary surface missions.

Chien, Steve↗