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At least 163 records · Page 9

Analysis of the Advantages and Limitations of Stationary Imaging Fourier Transform Spectrometer

New developments in infrared sensor technology have potentially made possible a new space-based system which can measure far-infrared radiation at lower costs (mass, power and expense). The Stationary Imaging Fourier Transform Spectrometer (SIFTS) proposed by NASA Langley Research Center, makes use of new detector array technology. A mathematical model which simulates resolution and spectral range relationships has been developed for analyzing the utility of such a radically new approach to spectroscopy. Calculations with this forward model emulate the effects of a detector array on the ability to retrieve accurate spectral features. Initial computations indicate significant attenuation at high wavenumbers.

Beecken, Brian P.↗

Global Soil Moisture Estimation from L-Band Satellite Data: The Impact of Radiative Transfer Modeling in Assimilation and Retrieval Systems

The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.

De Lannoy, Gabrielle↗

Stereoscopic Analysis of STEREO/SECCHI Data for CME Trajectory Determination

The Sun Earth Connection Coronal and Heliospheric Investigation (SECCHI) coronagraphs on the twin Solar TErrestrial RElations Observatory (STEREO) spacecraft provide simultaneous views of the corona and coronal mass ejections from two view points. Here, we analyze simultaneous image pairs using the technique of tie-pointing and triangulation (T&T) to determine the three-dimensional trajectory of seven coronal mass ejections (CMEs). The bright leading edge of a CME seen in coronagraph images results from line-of-sight integration through the CME front; the two STEREO coronagraphs see different apparent leading edges, leading to a systematic error in its three-dimensional reconstruction. We analyze this systematic error using a simple geometric model of a CME front. We validate the technique and analysis by comparing T&T trajectory determinations for seven CMEs with trajectories determined by Thernisien et al. (2009) using a forward modeling technique not susceptible to this systematic effect.

CORONAGRAPHS↗

Geodetic Strain Analysis Tool

A geodetic software analysis tool enables the user to analyze 2D crustal strain from geodetic ground motion, and create models of crustal deformation using a graphical interface. Users can use any geodetic measurements of ground motion and derive the 2D crustal strain interactively. This software also provides a forward-modeling tool that calculates a geodetic velocity and strain field for a given fault model, and lets the user compare the modeled strain field with the strain field obtained from the user s data. Users may change parameters on-the-fly and obtain a real-time recalculation of the resulting strain field. Four data products are computed: maximum shear, dilatation, shear angle, and principal components. The current view and data dependencies are processed first. The remaining data products and views are then computed in a round-robin fashion to anticipate view changes. When an analysis or display parameter is changed, the affected data products and views are invalidated and progressively re-displayed as available. This software is designed to facilitate the derivation of the strain fields from the GPS and strain meter data that sample it to facilitate the understanding of the strengths and weaknesses of the strain field derivation from continuous GPS (CGPS) and other geodetic data from a variety of tectonic settings, to converge on the "best practices" strain derivation strategy for the Solid Earth Science ESDR System (SESES) project given the CGPS station distribution in the western U.S., and to provide SESES users with a scientific and educational tool to explore the strain field on their own with user-defined parameters.

Kedar, Sharon↗

Viscoelastic responses of a hard transition zone - Effects on postglacial uplifts and rotational signatures

A five-layer viscoelastic spherical model is used to calculate the transient displacements of postglacial rebound, the induced polar motions, and the temporal variations of the geopotential up to degree 8 of the zonal coefficients. Two models - one with two viscoelastic layers separated at 670 km, and the other with three layers in which a hard garnet layer lies between the upper and lower mantle - are compared. Forward modeling shows that it may be possible to discern the presence of a hard garnet layer with a viscosity of at least ten times greater than the upper mantle, on the basis of uplift data near the center of the former Laurentide ice-sheet and from polar wander and j2 data. Temporal variations of higher gravity harmonics, such as j6 and j8, can potentially place even tighter constraints on the rheological properties of the hard transition zone. A lower mantle viscosity between 2 and 4 x 10 to the 22nd Pa is generally preferred in models with a garnet layer which may be as large as 50 times more viscous than the upper mantle.

Spada, Giorgio↗

Resolution of Lava Tubes with Ground Penetrating Radar: The TubeX project

Remote sensing surveys of the Moon and Mars show evidence of lava tubes, which are potential safe havens for human crews and their equipment. Ground penetrating radar (GPR) can be used to map tubes because the void/rock interface at tube ceilings and floors strongly reflects radar pulses. We have tested the capacity of GPR to sense lava tube geometry at Lava Beds National Monument (LBNM) in California, USA. GPR and detailed LiDAR data are presented for two tubes: Skull Cave, with a few meters of overburden, diameter ~10-20 m, and a rubbly floor; and Valentine Cave, with similarly thin overburden, diameter ~1-3 meters, and a flatter smoother floor. On both caves GPR clearly resolves the ceiling and permits good estimates of the cave width as validated with LiDAR data. Where GPR fails, the primary cause is inferred to be strong out-of-plane effects due to complex 3D geometries. Recovery of the floor position requires migrating the GPR data with a 2D velocity model, as signal velocity is faster in void space. We find that floor position is recoverable in caves whose voids are taller than the radar wavelength (~3 m in this study). Forward modeling assuming planetary parameters suggests GPR should be similarly successful on the Moon or Mars.

S. Esmaeili↗

Parametric Performance of a Spiral-Artery, Liquid-Trap-Diode Heat Pipe

A series of parametric investigations are described which determine the effect of various fluid charges on the performance of a 0.635-cm-diam spiral-artery, liquid-trap diode in both the forward and reverse modes. Specific parameters such as forward- and reverse-mode conductances, shutdown times and energies, and recovery to forward-model operation, are evaluated for ethane as a working fluid in the temperature range 170 K to 220 K. Results indicate that the heat pipe will not reliably start up in the forward mode. However, startup can be initiated when preceded by a diode reversal. Also included are data which show the susceptibility of the diode to fluid charge and tilt. The optimum fluid charge was found to be 2.67 g and transport capability at this charge was in excess of 1200 W-cm at 200 K. The diode in the reverse mode exhibited a rapid shutdown (within 9 min) with a shutdown energy of 1150 J (0.32 Wh).

Williams, R. J.↗

Tip Vortex and Wake Characteristics of a Counterrotating Open Rotor

One of the primary noise sources for Open Rotor systems is the interaction of the forward rotor tip vortex and blade wake with the aft rotor. NASA has collaborated with General Electric on the testing of a new generation of low noise, counterrotating Open Rotor systems. Three-dimensional particle image velocimetry measurements were acquired in the intra-rotor gap of the Historical Baseline blade set. The velocity measurements are of sufficient resolution to characterize the tip vortex size and trajectory as well as the rotor wake decay and turbulence character. The tip clearance vortex trajectory is compared to results from previously developed models. Forward rotor wake velocity profiles are shown. Results are presented in a form as to assist numerical modeling of Open Rotor system aerodynamics and acoustics.

VanZante, Dale E.↗

Tip Vortex and Wake Characteristics of a Counterrotating Open Rotor

One of the primary noise sources for Open Rotor systems is the interaction of the forward rotor tip vortex and blade wake with the aft rotor. NASA has collaborated with General Electric on the testing of a new generation of low noise, counterrotating Open Rotor systems. Three-dimensional particle image velocimetry measurements were acquired in the intra-rotor gap of the Historical Baseline blade set. The velocity measurements are of sufficient resolution to characterize the tip vortex size and trajectory as well as the rotor wake decay and turbulence character. The tip clearance vortex trajectory is compared to results from previously developed models. Forward rotor wake velocity profiles are shown. Results are presented in a form as to assist numerical modeling of Open Rotor system aerodynamics and acoustics.

Van Zante, Dale E.↗

Seasonal Dependence of SMAP Radiometer-Based Soil Moisture Performance as Observed over Core Validation Sites

The NASA SMAP (Soil Moisture Active Passive) mission provides a global coverage of soil moisture measurements based on its L-band microwave radiometer every 2-3 days at about 40 km resolution. The soil moisture retrieval algorithms model the brightness temperature as a function of soil moisture, surface conditions and vegetation. External data sources inform the algorithms about the surface conditions and vegetation, which enable the retrieval of soil moisture. The inversion process contains uncertainties related to radiometer measurements, forward model assumptions and ancillary data sources. This study focuses on the uncertainties that depend on the seasonal evolution of the surface conditions and vegetation. This study compares the SMAP and core validation site (CVS) soil moisture values over a period of three years to extract the evolution of performance metrics over time. The analysis showed that most CVS that include managed agriculture exhibit significant time-dependent seasonal bias. This bias was linked to seasonal temperature cycle, which is a proxy to several features that can cause seasonally dependent errors in the SMAP product.

core validation site↗

Patterns of Activity in A Global Model of A Solar Active Region

In this work we investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of frequencies. What differs is the average frequency of the distributions. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine hydrodynamic and forward modeling codes with a magnetic field extrapolation to create a model active region and apply the time lag method to synthetic observations. Our aim is not to reproduce a particular set of observations in detail, but to recover some typical properties and patterns observed in active regions. Our key findings are the following. (1) Cooling dominates the time lag signature and the time lags between the channel pairs are generally consistent with observed values. (2) Shorter coronal loops in the core cool more quickly than longer loops at the periphery. (3) All channel pairs show zero time lag when the line of sight passes through coronal loop footpoints. (4) There is strong evidence that plasma must be re-energized on a timescale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies are operating across active regions. (5) Due to their highly dynamic nature, we find nanoflare trains produce zero time lags along entire flux tubes in our model active region that are seen between the same channel pairs in observed active regions.

Bradshaw, S. J.↗

TPSAS-NF1676L-27604-DND

Satellite-based hyperspectral observations provide high information content for the Earth's atmospheric and surface properties; however, in order to analyze hyperspectral data efficiently, fast and accurate radiative transfer model is needed. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate radiative transfer in the cloudy atmosphere from far IR to visible and UV spectral regions quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. The computation speed is 3 to 4 orders of magnitude faster than the medium speed correlated-k option MODTRAN5 and LBLRTM. The PCRTM calculated radiance spectra agree with the Modtran and LBLRTM within 0.02%. We will demonstrate the application of the PCRTM forward model for atmospheric and surface property inversions and for climate observation studies.

X Liu↗

Interrogating Solar Flare Loop Models With IRIS Observations 1: Overview of the Models, and Mass Flows

Solar flares are transient yet dramatic events in the atmosphere of the Sun, during which a vast amount of magnetic energy is liberated. This energy is subsequently transported through the solar atmosphere or into the heliosphere, and together with coronal mass ejections flares comprise a fundamental component of space weather. Thus, understanding the physical processes at play in flares is vital. That understanding often requires the use of forward modelling in order to predict the hydrodynamic and radiative response of the solar atmosphere. Those predictions must then be critiqued by observations to show us where our models are missing ingredients. While flares are of course 3D phenomenon, simulating the flaring atmosphere including an accurate chromosphere with the required spatial scales in 3D is largely beyond current computational capabilities, and certainly performing parameter studies of energy transport mechanisms is not yet tractable in 3D. Therefore, field-aligned 1D loop models that can resolve the relevant scales have a crucial role to play in advancing our knowledge of flares. In recent years, driven in part by the spectacular observations from the Interface Region Imaging Spectrograph (IRIS), flare loop models have revealed many interesting features of flares. For this review I highlight some important results that illustrate the utility of attacking the problem of solar flares with a combination of high quality observations, and state-of-the-art flare loop models, demonstrating: 1) how models help to interpret flare observations from IRIS, 2) how those observations show us where we are missing physics from our models, and 3) how the ever increasing quality of solar observations drives model improvements. Here in Paper one of this two part review I provide an overview of modern flare loop models, and of electron-beam driven mass flows during solar flares.

solar flares↗

Pushing the Limits of Aquatic Remote Sensing: Synthetic Data and Deep Learning for Fast Inverse Emulation of A Coupled Ocean-Atmosphere Radiative Transfer Model

The inversion of electromagnetic information to physical and biological properties of the water column is a notoriously difficult problem, yet fundamental to our ability of understanding aquatic processes on large time and space scales. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will discuss research integrating advanced biological and radiative modeling, high-end computation, and machine learning to develop a portable global processor for simultaneous retrieval of atmosphere and water optics for diverse aquatic systems from the open and coastal ocean to optically extreme inland waters and harmful algal blooms. We will discuss some of the basic concepts behind the forward modeling approach including DEAP, the novel Distributed Equivalent Algal Populations model, for developing large spectral libraries of aquatic particle optics to aid in our ability to distinguish phytoplankton functional types (PFTs) and inorganic material, as well as other factors which enable comprehensive modeling from the benthos to top-of-atmosphere (TOA). This information is being used to understand how we can leverage next-generation deep learning methods for maximum information retrieval and rapid image processing, while also providing capabilities to identify minimum sensor spectral requirements necessary for certain aquatic applications. Further, I will touch on how we envision this research to enable the aquatic community for science discovery and how we are moving closer towards the capability for high-fidelity global analysis of aquatic ecosystems.

Jeremy Alan Kravitz↗

Earth as an Extrasolar Planet: Earth Model Validation Using EPOXI Earth Observations

The EPOXI Discovery Mission of Opportunity reused the Deep Impact flyby spacecraft to obtain spatially and temporally resolved visible photometric and moderate resolution near-infrared (NIR) spectroscopic observations of Earth. These remote observations provide a rigorous validation of whole disk Earth model simulations used to better under- stand remotely detectable extrasolar planet characteristics. We have used these data to upgrade, correct, and validate the NASA Astrobiology Institute s Virtual Planetary Laboratory three-dimensional line-by-line, multiple-scattering spectral Earth model (Tinetti et al., 2006a,b). This comprehensive model now includes specular reflectance from the ocean and explicitly includes atmospheric effects such as Rayleigh scattering, gas absorption, and temperature structure. We have used this model to generate spatially and temporally resolved synthetic spectra and images of Earth for the dates of EPOXI observation. Model parameters were varied to yield an optimum fit to the data. We found that a minimum spatial resolution of approx.100 pixels on the visible disk, and four categories of water clouds, which were defined using observed cloud positions and optical thicknesses, were needed to yield acceptable fits. The validated model provides a simultaneous fit to the Earth s lightcurve, absolute brightness, and spectral data, with a root-mean-square error of typically less than 3% for the multiwavelength lightcurves, and residuals of approx.10% for the absolute brightness throughout the visible and NIR spectral range. We extend our validation into the mid-infrared by comparing the model to high spectral resolution observations of Earth from the Atmospheric Infrared Sounder, obtaining a fit with residuals of approx.7%, and temperature errors of less than 1K in the atmospheric window. For the purpose of understanding the observable characteristics of the distant Earth at arbitrary viewing geometry and observing cadence, our validated forward model can be used to simulate Earth s time dependent brightness and spectral properties for wavelengths from the far ultraviolet to the far infrared.brightness

Robinson, Tyler D.↗

Polar Firn Properties in Greenland and Antarctica and Related Effects on Microwave Brightness Temperatures

In studying the mass balance of polar ice sheets, fluctuations of firn density near the surface is a major uncertainty. In this paper, we explore these variations at locations in the Greenland Ice Sheet and at the Dome C location in Antarctica. Borehole in situ measurements, Snow Radar echoes, microwave brightness temperatures, and modelling results from the Community firn model (CFM) are used. It is shown that firn density profiles can be represented using 3 processes: “long” and “short” length scale density variations and “refrozen layers”. Consistency with this description is observed in the dynamic range of airborne 0.5-2 GHz brightness temperatures and Snow Radar echo peaks in measurements performed in Greenland in 2017. Based on these insights, a new analytical partially coherent model is implemented to explain the microwave brightness temperatures using the three scale description of the firn. Short and long scale firn processes are modelled as a 3D continuous random medium with finite vertical and horizontal correlation lengths as opposed to past 1D random layered medium descriptions. Refrozen layers are described as deterministic sheets with planar interfaces, with the number of refrozen layer interfaces determined by radar observations. Firn density and correlation length parameters used in forward modelling to match measured 0.5-2 GHz brightness temperatures in Greenland show consistency with similar parameters in CFM predictions. Model predictions also are in good agreement with multi-angle 1.4 GHz vertically and horizontally polarized brightness temperature measured by the SMOS satellite at DOME C, Antarctica. This work shows that co-located active and passive microwave measurements can be used to infer polar firn properties that can be compared with predictions of the CFM. In particular, 0.5-2 GHz brightness temperature measurements are shown to be sensitive to long scale firn density fluctuations with density standard deviations in the range 0.01-0.06 g/cm^3 and vertical correlation lengths of 6-20 cm.

Haokui Xu↗

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

aerosols above clouds↗

Developing Fast and Accurate Radiative Transfer Models to Meet the Needs of Modern Satellite Remote Sensing Applications

Modern hyperspectral satellite remote sensors provide highly accurate measurements the Earth’s Top-of-Atmosphere (TOA) radiance, reflectance, or polarized spectra with hundreds to thousands of spectral channels and with millions of observations per day. The large data volume and high spectral dimensionality of the data pose challenges for retrieval algorithms. To process the satellite Level-1 data (e.g. calibrated TOA spectra) into Level-2 products (e.g. atmospheric and surface properties) using physical-based retrieval algorithms, accurate and fast Radiative Transfer Models (RTMs) are needed. RTMs are usually the limiting factor in determining the speed of a level-2 algorithm. For example, more than one million Line-by-Line (LBL) radiative transfer (RT) calculations are needed in order to properly capture the spectral contributions of important atmospheric molecules for an IR hyperspectral sensor with a spectral coverage from 3.5 m to 15 m or a solar hyperspectral sensor with spectral coverage from 0.25 m to 2.5 m. In this presentation, we will discuss advantages and disadvantages of different ways (e.g. correlated k and effective transmittance) to accelerate the speed of a fast RTM. We finally describe a Principal Component-based Radiative Transfer Model (PCRTM), which can calculate TOA radiance or reflectance spectra from 50 cm-1 to 40,000 cm-1 (200 m to 0.25 m). It has demonstrated very good accuracy relative to reference LBL RTMs and saves orders of magnitude in computational time. The PCRTM has been used in many satellite remote sensing applications. Examples include forward modeling in Level-2 and Level-3 retrieval algorithms, high fidelity satellite instrument simulators and instrument performance trade studies, spectral and radiometric accuracy characterizations of satellite Level-1 data, tools for inter-satellite calibrations, tools for satellite RTM lookup table generations, and tools for generating physically based training datasets for Artificial Intelligence (AI) algorithms.

climate data record↗