New Sensing Strategies for Estimation of Global, Exospheric Density

Abstract

Reliable quantification of the global and time-dependent structure of the Earth's outermost atmosphere, a vast region known as the exosphere, has long been elusive, owing mainly to the sparse spatial and temporal sampling afforded by exospheric sensing platforms deployed to date. In this paper, we introduce new observing schemes that overcome these historical limitations and enable high-fidelity, high-cadence reconstruction of the exospheric density distribution on a global scale. Our approach leverages several state-of-the-art remote sensing capabilities, including (1) wide-field photometric imaging of exospheric emission, which is created through resonant photon scattering by the exosphere's constituent hydrogen atoms; (2) constellation sensor deployment near lunar orbit, which provides common-volume sensing; and (3) tomographic inversion of a discretized exospheric emission model that explicitly accounts for the Poisson-distributed shot noise inherent in the photometric data constraints. Using ensembles of synthetic emission data acquired at various realistic temporal cadences, we evaluate the fidelity of both static density reconstructions, in which the solution is formulated in the context of maximum a posteriori (MAP) estimation, as well as dynamic density reconstructions, which incorporate temporal evolution via Kalman filtering. The numerical results demonstrate that the new sensing strategies are capable of retrieving reliable estimates of exospheric density distribution at unprecedented spatial scales and temporal cadence, in support of numerous high-priority investigations of Earth's near-space environment.

The Earth’s Outer Exospheric Density Distributions Derived From PROCYON/LAICA UV Observations

“…Construction of a robust covariance matrix of the prior knowledge, Σ pr , requires a thorough analysis of the spatial distribution of the geocoronal H density only possible through extensive observations either by remote sensing of the scattered UV emission or direct sensing of H densities via mass spectrometry. However, the lack of designated exospheric missions has restricted the uniform spatial, and temporal sampling of the middle and outer exosphere (Cucho‐Padin & Waldrop, 2020). In this work, we estimate an appropriate Σ pr assuming that X pr is a Gaussian Markov Random Field (GMRF).…”

“…The broad coverage of this two‐dimensional (2‐D) data set and its adequate spatial resolution enable the estimation of H density distributions of the outer exosphere through inverse methods. Our approach is built on a previously developed technique to reconstruct exospheric H density via tomographic inversion of an ensemble of optically thin Ly‐ α measurements (Cucho‐Padin & Waldrop, 2018, 2019, 2020). In contrast to tomography where observations of the exosphere are carried out from various vantage points around it thus enabling inference of its 3‐D structure, reconstruction from a single image is only based on a 2‐D data set owing to the restricted line‐of‐sight (LOS) of a wide‐field sensor, making additional information of the structure necessary to perform accurate estimations.…”

Solar Cycle, Seasonal, and Dawn‐To‐Dusk Variations of the Hydrogen in the Upper Thermosphere

“…Since the 1980s, ground‐based observations of the Balmer‐α (656.3 nm) emission has been used to monitor the long‐term variations of the exospheric hydrogen (e.g., Nossal et al., 1993, 2004, 2008, 2019). In the last two decades, the geocoronal Lyman‐α (121.6 nm) emission has also been routinely observed by the Global Ultraviolet Imager (GUVI) onboard NASA's Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite (e.g., Joshi et al., 2019; Paxton et al., 2017; Qin et al., 2017; Qin & Waldrop, 2016) and by the Two Wide‐Angle Imaging Neutral‐Atom Spectrometers (TWINS) missions (e.g., Cucho‐Padin & Waldrop, 2018, 2019, 2020; Zoennchen et al., 2010, 2013, 2015). Despite decades of observations, the atomic hydrogen remains one of the least‐understood atmospheric constituents, in that discrepancies between models and observations have long been reported in the literature (e.g., Bishop et al., 2001; Gallant et al., 2019; Nossal et al., 2012; Qin & Waldrop, 2016; Waldrop & Paxton, 2013).…”

“…Ultraviolet Imager (GUVI) onboard NASA's Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite (e.g., Joshi et al, 2019;Paxton et al, 2017;Qin et al, 2017;Qin & Waldrop, 2016) and by the Two Wide-Angle Imaging Neutral-Atom Spectrometers (TWINS) missions (e.g., Cucho-Padin & Waldrop, 2018, 2020Zoennchen et al, 2010Zoennchen et al, , 2013Zoennchen et al, , 2015. Despite decades of observations, the atomic hydrogen remains one of the least-understood atmospheric constituents, in that discrepancies between models and observations have long been reported in the literature (e.g., Bishop et al, 2001;Gallant et al, 2019;Nossal et al, 2012;Qin & Waldrop, 2016;Waldrop & Paxton, 2013).…”

Neutral Densities in the Outer Exosphere Near the Subsolar Magnetopause

“…However, combinations of in‐situ plasma measurements with remote observations of energetic neutral atoms (ENAs) and soft X‐rays yield densities from 4 cm −3 (Fuselier et al., 2010) to 57.6 cm −3 (Connor & Carter, 2019). Until the launch of dedicated missions with new sensing strategies (e.g., Cucho‐Padin & Waldrop, 2020), researchers must employ existing observations to determine exospheric neutral densities near the subsolar magnetopause.…”