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NASA NTRS2019

No Clear, Direct Evidence for Multiple Protoplanets Orbiting LkCa 15: LkCa 15 bcd are Likely Inner Disk Signals

Two studies utilizing sparse aperture-masking (SAM) interferometry and Hα differential imaging have reported multiple Jovian companions around the young solar-mass star, LkCa 15 (LkCa 15 bcd): theﬁrst claimed direct detection of infant, newly formed planets (“protoplanets”). We present new near-infrared direct imaging/spectroscopy from the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system coupled with Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS) integral ﬁeld spectrograph and multi-epoch thermal infrared imaging from Keck/ NIRC2 of LkCa 15 at high Strehl ratios. These data provide the ﬁrst direct imaging look at the same wavelengths and in the same locations where previous studies identiﬁed the LkCa 15 protoplanets,and thus offer the ﬁrst decisive test of their existence.The data do not reveal these planets. Instead,we resolve extended emission tracing adust disk with a brightness and location comparable to that claimed for LkCa 15 bcd. Forward-models attributing this signal to orbiting planets are inconsistent with the combined SCExAO/CHARIS and Keck/NIRC2 data. An inner disk provides a more compelling explanation for the SAM detections and perhaps also the claimed Hα detection of LkCa 15 b. We conclude that there is currently no clear, direct evidence for multiple protoplanets orbiting LkCa 15, although the system likely contains at least one unseen Jovian companion. To identify Jovian companions around LkCa 15 from future observations, the inner disk should be detected and its effect modeled, removed, and shown to be distinguishable from planets. Protoplanet candidates identiﬁed from similar systems should likewise be clearly distinguished from disk emission through modeling.

Thayne Currie↗

NASA NTRSDate not supplied

Mapping Ocean-Reflected Radio Frequency Interference for the GPM Microwave Imager Using Normalized Retrieval Cost Function

By adapting an approach originally developed for WindSat, we identify regions where GMI is affected by radio frequency interference from ocean-reflected geostationary satellite emissions. Around North America, K-band emissions from geostationary satellites affect the GMI 18.7-GHz brightness temperatures, resulting in increases in the retrieval cost function. The method does not detect any 10.7-GHz RFI reflected of the ocean surrounding Europe. This study, which depends on the physically-based forward model for non-raining ocean retrievals, confirms results from a previous study that employed an empirical methodology.

Ian S. Adams↗

NASA NTRSDate not supplied

The View From Out Here: The Solar System Planets as Exoplanet Analogs

As we begin to characterize planets orbiting other stars, one of the most important tools available to us is the collection of disk-integrated solar system observations. To date, these have been limited in how they match up with expected exoplanet observations in terms of wavelength, time, viewing geometry, and separations. The Interstellar Probe mission could push the boundaries of planetary science by providing a much-needed and unique dataset for the solar system viewed as an extrasolar system in advance of the next generation of ground and space-based telescopes. Viewing the solar system at large separations over a long period serves several purposes. It acts as a practical test directly analogous to exoplanet observations under realistic conditions, including such effects as zodiacal dust (e.g., Roberge et al., 2012). Secondly, it allows for both the validation of forward models (that is, simulating a planet and generating spectra) and retrievals (where some of the planetary properties are not known) (e.g., Robinson et al., 2011; Agarwal and Wettlaufer, 2017). Third, the mission pro le would be able to collect data at both high- and low-phase angles, which are lacking for most of the solar system planets (e.g., Mallama and Hilton, 2018). Lastly, the long duration of the proposed mission would allow not only snapshots, but time resolved observations using the same instrument, highlighting the dynamic nature of the planets (e.g., seasonality, storms). The planets need not be resolved to make these observations, which eases instrumentation requirements. Here, we show simulations of what an Interstellar Probe imager would see, improving on work that was part of a white paper submitted to the Planetary Science and Astrobiology Decadal Survey. The opportunity for multiple full orbits for most of the solar system planets, including a full phase curve of Saturn, is unique and worth pursuing during the development of the Interstellar Probe mission.

Chester Harman↗

NASA NTRS2020

WISEA J041451.67-585456.7 and WISEA J181006.18-101000.5: The First Extreme T-type Subdwarfs?

We present the discoveries of WISEA J041451.67−585456.7 and WISEA J181006.18−101000.5, two low-temperature (1200–1400 K), high proper motion T-type subdwarfs. Both objects were discovered via their high proper motion (>0farcs5 yr(exp -1)); WISEA J181006.18−101000.5 as part of the NEOWISE proper motion survey and WISEA J041451.67−585456.7 as part of the citizen science project Backyard Worlds; Planet 9. We have confirmed both as brown dwarfs with follow-up near-infrared spectroscopy. Their spectra and near-infrared colors are unique among known brown dwarfs, with some colors consistent with L-type brown dwarfs and other colors resembling those of the latest-type T dwarfs. While no forward model consistently reproduces the features seen in their near-infrared spectra, the closest matches suggest very low metallicities ([Fe/H] ≼ −1), making these objects likely the first examples of extreme subdwarfs of the T spectral class (esdT). WISEA J041451.67−585456.7 and WISEA J181006.18−101000.5 are found to be part of a small population of objects that occupy the “substellar transition zone,” and have the lowest masses and effective temperatures of all objects in this group.

T subdwarfs↗

NASA NTRS2020

Predicting Soil Moisture Retrieval Performance for the NISAR Mission

The National Aeronautics and Space Administration (NASA) - Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) is being developed in order to provide highly spatial resolution L- and S-band backscatter observations of the Earth’s surface. Remotely sensed soil moisture is one of NISAR applications of interest. This paper reports an initial analysis of the possibility of using NISAR modes to retrieve soil moisture based on two different methods: a snapshot method and the time series technique. Preliminary results of the forward modeling of the backscattered signal over land and the soil moisture retrievals are presented for bare surfaces.

Alexandra Bringer↗

NASA NTRS2021

IQ Collaboratory. II. The Quiescent Fraction of Isolated, Low-mass Galaxies across Simulations and Observations

We compare three major large-scale hydrodynamical galaxy simulations (EAGLE, Illustris-TNG, and SIMBA) by forward modeling simulated galaxies into observational space and computing the fraction of isolated and quiescent low-mass galaxies as a function of stellar mass. Using SDSS as our observational template, we create mock surveys and synthetic spectroscopic and photometric observations of each simulation, adding realistic noise and observational limits. All three simulations show a decrease in the number of quiescent, isolated galaxies in the mass range M * = 10 9−10 M ꙩ , in broad agreement with observations. However, even after accounting for observational and selection biases, none of the simulations reproduce the observed absence of quiescent field galaxies below M * = 10 9 M ꙩ . We find that the low-mass quiescent populations selected via synthetic observations have consistent quenching timescales, despite an apparent variation in the late-time star formation histories. The effect of increased numerical resolution is not uniform across simulations and cannot fully mitigate the differences between the simulations and the observations. The framework presented here demonstrates a path toward more robust and accurate comparisons between theoretical simulations and galaxy survey observations, while the quenching threshold serves as a sensitive probe of feedback implementations.

Claire M. Dickey↗

NASA NTRSDate not supplied

Assimilation of microwave satellite observations over the rainbands of tropical cyclones

The potential of microwave observations in improving the weather forecasts is limited by the accuracy of all-sky radiative transfer calculations. We introduce a novel Bayesian MonteCarlo technique to improve the assimilation of microwave observations over the rainbands of tropical cyclones. The BMCI technique eliminates the need for a forward model in the data assimilation system. The technique includes three steps, (i) generating a comprehensive dataset using in-situ cloud measurements and atmospheric profiles, (ii) generating synthetic ATMS observations from the training dataset, and (iii) using real observations to estimate the geophysical variables over the rainbands of tropical cyclones. The retrieved profiles of temperature, relative humidity, and cloud water content as well assurface information such as SST were then assimilated into the model. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns.

Monte Carlo↗

NASA NTRS2021

Adaptive Data Screening for Multi-Angle Polarimetric Aerosol and Ocean Color Remote Sensing Accelerated by Automatic Differentiation

Remote sensing measurements from multi-angle polarimeters (MAPs) contain rich aerosol microphysical property information, and these sensors have been used to perform retrievals in optically complex atmosphere and ocean systems. Previous studies have concluded that, generally, five moderately separated viewing angles in each spectral band provide sufficient accuracy for aerosol property retrievals, with performance gradually saturating as angles are added above that threshold. The Hyper-Angular Rainbow Polarimeter (HARP) instruments provide high angular sampling with a total of 90-120 unique angles across four bands, a capability developed mainly for liquid cloud retrievals. In practice, not all view angles are optimal for aerosol retrievals due to impacts of clouds, sun glint, and other impediments. The many viewing angles of HARP can provide resilience to these effects, if the impacted views are screened from the dataset, as the remaining views may be sufficient for successful analysis. In this study, we discuss how the number of available viewing angles impacts aerosol and ocean color retrieval uncertainties, as applied to two versions of the HARP instrument. AirHARP is an airborne prototype that was deployed in the ACEPOL field campaign, while HARP2 is an instrument in development for the upcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Based on synthetic data, we find that a total of 20-30 angles across all bands (i.e. five to eight viewing angles per band) are sufficient to achieve good retrieval performance. Following from this result, we develop an adaptive multi-angle polarimetric data screening (MAPDS) approach to evaluate data quality by comparing measurements with their best-fitted forward model. The FastMAPOL retrieval algorithm is used to retrieve scene geophysical values, by matching an efficient, deep learning-based, radiative transfer emulator to observations. The data screening method effectively identifies and removes viewing angles affected by thin cirrus clouds and other anomalies, improving retrieval performance. This was tested with AirHARP data, and we found agreement with the High Spectral Resolution Lidar-2 (HSRL-2) aerosol data. The data screening approach can be applied to modern satellite remote sensing missions, such as PACE, where a large amount of multi-angle, hyperspectral, polarimetric measurements will be collected.

multi-angle polarimeter↗

NASA NTRSDate not supplied

Did an Ancient Habitable Venus Provide the Seeds for Life Today?

Recent possible detections of Phosphine in the Venusian atmosphere [1,2] have spurred interest in the potential for life in the clouds of Venus given the limited number of abiotic alternatives determined thus far [3]. A number of theories have been posited as to how life could have arisen in the cloud decks of Venus (e.g. [4] and references therein) and how it might thrive in a supposedly hostile environment [5]. Over the past few years we have used forward modeling to investigate the possibilities of a temperate Venusian climate in its deep past. This affords us the opportunity to discuss the possibility for an early habitable Venus and its implications for habitability in the cloud layers today.

habitability↗

NASA NTRS2022

Optimal Estimation Framework for Ocean Color Atmospheric Correction and Pixel-level Uncertainty Quantification

Ocean color remote sensing requires compensation for atmospheric scattering and absorption (aerosol, Rayleigh, and trace gases), referred to as atmospheric correction (AC). AC allows inference of parameters such as spectrally resolved remote sensing reflectance ( R rs )(λ) ; sr 1 ) at the ocean surface from the top-of-atmosphere reflectance. Often, the uncertainty of this process is not fully explored. Bayesian inference techniques provide a simultaneous AC and uncertainty assessment via a full posterior distribution of the relevant variables, given the prior distribution of those variables and the radiative transfer (RT) likelihood function. Given uncertainties in the algorithm inputs, the Bayesian framework enables better constraints on the AC process by using the complete spectral information compared to traditional approaches that use only a subset of bands for AC. This paper investigates a Bayesian inference research method (Optimal Estimation, OE) for ocean color AC by simultaneously retrieving atmospheric and ocean properties using all visible and near-infrared spectral bands. The OE algorithm analytically approximates the posterior distribution of parameters based on normality assumptions and provides a potentially viable operational algorithm with a reduced computational expense. We developed a Neural Network (NN) RT forward model look-up-table-based emulator to increase algorithm efficiency further and thus speed up the likelihood computations. We then applied the OE algorithm to synthetic data and observations from the MODerate resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua spacecraft. We compared the R rs )(λ) retrieval and its uncertainty estimates from the OE method with in-situ validation data from the SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and Aerosol Robotic Network Ocean Color (AERONET-OC) datasets. The OE algorithm improved R rs )(λ) estimates relative to the NASA standard operational algorithm by improving all statistical metrics at 443, 555, and 667 nm. Unphysical negative R rs )(λ) , which often appear in complex water conditions, was reduced by a factor of 3. The OE-derived pixel-level R rs )(λ) uncertainty estimates were also assessed relative to in-situ data and were shown to have skill.

Atmospheric correction↗

NASA NTRS2022

Determining the Spectral Content of MOSES Images

The Multi-Order Solar Extreme Ultraviolet Spectrograph (MOSES) sounding rocket was launched from White Sands Missile Range on 2006 February 8th, to capture images of the Sun in the He ii 303.8 Å emission line. MOSES is a slitless spectrograph that forms images in multiple spectral orders simultaneously using a concave diffraction grating in an effort to measure line profiles over a wide field of view from a single exposure. Early work on MOSES data showed evidence of solar features composed of neither He ii 303.8 Å nor the nearby Si xi 303.3 Å spectral lines. We have built a forward model that uses cotemporal EIT images and the Chianti atomic database to fit synthetic images with known spectra to the MOSES data in order to quantify this additional spectral content. Our fit reveals a host of dim lines that alone are insignificant but combined contribute a comparable intensity to MOSES images as Si xi 303.3 Å. In total, lines other than He ii 303.8 Å and Si xi 303.3 Å contribute approximately 10% of the total intensity in the MOSES zero order image. This additional content, if not properly accounted for, could significantly impact the analysis of MOSES and similar slitless spectrograph data, especially those using a zero-order (undispersed) image. More broadly, this serves as a reminder that multilayer EUV imagers are sensitive to a host of weak contaminant lines.

Solar transition region↗

NASA NTRS2022

Tentative Evidence for Water Vapor in the Atmosphere of the Neptune-sized Exoplanet HD106315c

We present a transmission spectrum for the Neptune-sized exoplanet HD 106315c from optical to infrared wavelengths based on transit observations from the Hubble Space Telescope/Wide Field Camera 3, K2, and Spitzer. The spectrum shows tentative evidence for a water absorption feature in the 1.1–1.7 μm wavelength range with a small amplitude of 30 ppm (corresponding to just 0.8 ± 0.04 atmospheric scale heights). Based on an atmospheric retrieval analysis, the presence of water vapor is tentatively favored with a Bayes factor of 1.7–2.6 (depending on prior assumptions). The spectrum is most consistent with either an enhanced metallicity or high-altitude condensates, or both. Cloud-free solar composition atmospheres are ruled out at >5σ confidence. We compare the spectrum to grids of cloudy and hazy forward models and find that the spectrum is fit well by models with moderate cloud lofting or haze formation efficiency over a wide range of metallicities (1–100× solar). We combine the constraints on the envelope composition with an interior structure model and estimate that the core mass fraction is ≳0.3. With a bulk composition reminiscent of that of Neptune and an orbital distance of 0.15 au, HD 106315c hints that planets may form out of broadly similar material and arrive at vastly different orbits later in their evolution.

Exoplanet atmospheres↗

NASA NTRSDate not supplied

Composite Bond Line Measurements Based on A Bayesian Analysis of Flash Thermography Data

For bonded composite materials, an accurate characterization of the adhesive bond line is needed to predict failure modes and fracture toughness. In this paper, bond line thickness was estimated from data obtained using through transmission flash thermography. The forward model that predicts back surface temperature is based on a three layer heat diffusion equation with varying diffusivity and flux boundary conditions. The corresponding inverse problem of estimating bond line thickness from measurement data was solved using a Bayesian approach that assumed Gaussian priors for the bond line thickness and thermal diffusivity of the adherends. Finally, the outputs of the thermography based method were compared to measurements that were collected using a micrometer and ultrasound testing.

Flash thermography↗

NASA NTRSDate not supplied

Composite Bond Line Measurements Based on a Bayesian Analysis of Flash Thermography Data

Flash thermography↗

NASA NTRS2023

The Impact and Estimation of Uncertainty Correlation for Multi-Angle Polarimetric Remote Sensing of Aerosols and Ocean Color

Multi-angle polarimetric (MAP) measurements contain rich information for characterization of aerosol microphysical and optical properties that can be used to improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere-ocean system, although uncertainty correlation among measurements is generally ignored due to lack of knowledge on its strength and characterization. In this work, we provide a practical framework to evaluate the impact of the angular uncertainty correlation from retrieval results and a method to estimate correlation strength from retrieval fitting residuals. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on neural network forward models, is used to conduct the retrievals and uncertainty quantification. In addition, we also discuss a flexible approach to include a correlated uncertainty model in the retrieval algorithm. The impact of angular correlation on retrieval uncertainties is discussed based on synthetic AirHARP and HARP2 measurements using a Monte Carlo uncertainty estimation method. Correlation properties are estimated using auto-correlation functions based on the fitting residuals from both synthetic AirHARP and HARP2 data and real AirHARP measurement, with the resulting angular correlation parameters found to be larger than 0.9 and 0.8 for reflectance and DoLP, respectively, which correspond to correlation angles of 10° and 5°. Although this study focuses on angular correlation from HARP instruments, the methodology to study and quantify uncertainty correlation is also applicable to other instruments with angular, spectral, or spatial correlations, and can help inform laboratory calibration and characterization of the instrument uncertainty structure.

PACE↗

NASA NTRS2023

The Apparent Absence of Forward Scattering in the HD 53143 Debris Disk

HD 53143 is a mature Sun-like star and host to a broad disk of dusty debris, including a cold outer ring of planetesimals near 90 au. Unlike most other inclined debris disks imaged at visible wavelengths, the cold disk around HD 53143 appears as disconnected "arcs" of material, with no forward-scattering side detected to date. We present new, deeper Hubble Space Telescope Imaging Spectrograph coronagraphic observations of the HD 53143 debris disk and show that the forward-scattering side of the disk remains undetected. By fitting our KLIP-reduced observations via forward modeling with an optically thin disk model, we show that fitting the visible wavelength images with an azimuthally symmetric disk with unconstrained orientation results in an unphysical edge-on orientation that is at odds with recent ALMA observations, while constraining the orientation to that observed by ALMA results in nearly isotropically scattering dust. We show that the HD 53143 host star exhibits significant stellar variations due to spot rotation and revisit age estimates for this system.

Christopher C Stark↗

NASA NTRS2021

3D Cloud Tomography and Droplet Size Retrieval from Multi-Angle Polarimetric Imaging of Scattered Sunlight from Above

Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging,it is extensively used for diagnostics via X-ray computed tomography (CT). We define and derive a tomographyof cloud droplet distributions via passive remote sensing. We use multi-view polarimetric images to fit a 3Dpolarized radiative transfer (RT) forward model. Our motivation is 3D volumetric probing of vertically-developedconvectively-driven clouds that are ill-served by current methods in operational passive remote sensing. Currenttechniques are indeed based on strictly 1D RT modeling and applied to a single cloudy pixel, where cloud geometrydefaults to that of a plane-parallel slab. Incident unpolarized sunlight, once scattered by cloud droplets, changesits polarization state according to droplet size. Therefore, polarimetric measurements in the rainbow and gloryangular regions can be used to infer the droplet size distribution. This work defines and derives a framework for afull 3D tomography of cloud droplets for both their mass concentration in space and their distribution across arange of sizes. This gridded 3D retrieval of key microphysical properties is made tractable by our novel approachthat involves a restructuring and partial linearization of an open-source polarized 3D RT code to accommodate aspecial two-step iterative optimization technique. Physically-realistic synthetic clouds are used to demonstrate themethodology with rigorous uncertainty quantification, while a real-world cloud imaged by AirMSPI is processedto illustrate the new remote sensing capability

Schechner, Yoav Y.↗

NASA NTRS2023

First VLTI/GRAVITY Observations of HIP 65426 b: Evidence for a Low or Moderate Orbital Eccentricity

Giant exoplanets have been directly imaged over orders of magnitude of orbital separations, prompting theoretical and observational investigations of their formation pathways. In this paper, we present new VLTI/GRAVITY astrometric data of HIP 65426 b, a cold, giant exoplanet which is a particular challenge for most formation theories at a projected separation of 92 au from its primary. Leveraging GRAVITY's astrometric precision, we present an updated eccentricity posterior that disfavors large eccentricities. The eccentricity posterior is still prior dependent, and we extensively interpret and discuss the limits of the posterior constraints presented here. We also perform updated spectral comparisons with self-consistent forward-modeled spectra, finding a best-fit ExoREM model with solar metallicity and C/O = 0.6. An important caveat is that it is difficult to estimate robust errors on these values, which are subject to interpolation errors as well as potentially missing model physics. Taken together, the orbital and atmospheric constraints paint a preliminary picture of formation inconsistent with scattering after disk dispersal. Further work is needed to validate this interpretation. Analysis code used to perform this work is available on GitHub: https://github.com/sblunt/hip65426.

Sarah Blunt↗