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90 records · Page 5

Understanding the Role of 𝛼 Particles in Oblique Heliospheric Shock Oscillations

Recent observations by DSCOVR provide high temporal resolution (50 samples per second) magnetic vector field data that allows investigating the details of oblique heliospheric shock oscillations. It was found that some of these shocks exhibit magnetic oscillations, both downstream and upstream of the shock front. The DSCOVR/MAG magnetic field data are supplemented by an extensive database of low Mach number (M < 3) low‐β (<1) shock data observed by Wind albeit with lower temporal resolution. Motivated by the observations, we use the 2.5D hybrid model of the oblique shocks with α particles in addition to kinetic protons and electron fluid. We model the properties of the oblique shocks for a number of typical parameters found in observations and study the effects of the shock parameters and the relative α particle abundances on the properties of the shock magnetic field, density, and velocity oscillations. We find the α particles “surf” on the shock front and produce a wake of density oscillations. We examine the details of the phase space of the ions as well as the ion velocity distribution functions in various parts of the shock and study their nonthermal properties. We determine the effects of the α particle kinetic properties and abundances on the structure and dynamics of the shock downstream oscillations for a range of parameters relevant to low Mach number low‐β heliospheric shocks.

Ofman, L.↗

Cloud Remote Sensing with EPIC/DSCOVR Observations: A Sensitivity Study with Radiative Transfer Simulations

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) views nearly the whole sunlit face of the Earth with 10 spectral bands ranging from the UV to the near-infrared, including two oxygen absorbing bands centered at 764 nm (A-band) and 687.75 nm (B-band). Clouds are among the primary remote sensing targets using EPIC images because of their important impacts on the Earth’s radiation budget. In order to facilitate the EPIC cloud data product development, we have built a radiative transfer simulator featuring flexible cloud microphysical parameters, gas absorptions, and the instrument line shape functions for each EPIC band. The radiative transfer simulator is used to explore the sensitivity of EPIC observations on liquid-phase cloud microphysical parameters, including optical depth, geometric thickness, and cloud top height. We found that the ratios of the reflectances in the oxygen A and B bands to their respective continuum measurements can be used to increase the confidence level of cloud masking over scenes with sun-glint. In addition, the 388 nm band can be used to differentiate low and high clouds with the uncertainty of roughly 2–3 km. Combining this information with the oxygen absorption bands, the cloud geometric thickness can be obtained with the rough uncertainty of 3–4 km.

atmospheric and ocean optics↗

Deep Space Observations of Sun Glints from Marine Ice Clouds

The Earth Polychromatic Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft takes images of the sunlit face of Earth from a million miles away. Earlier work showed that EPIC detected the specular reflection of sunlight (that is, sun glint) from ice crystals floating in cold clouds over land; here we show that this phenomenon can also be detected over oceans. Furthermore, the results show that - using its observations at Oxygen A-band absorption bands - EPIC can distinguish glints off marine ice clouds from those off the ocean surface. The analysis of more than two years of EPIC data reveals that the two kinds of glints are detected with comparable frequency. Glints off clouds are shown to be generally brighter but smaller in spatial extent. It is also demonstrated that glints off ice clouds have a discernible effect on the regional mean reflectance and that EPIC observations can help constrain the radiative contribution of oriented ice crystals.

Atmosphere↗

A New Discrete Wavelength BUV Algorithm for Consistent Volcanic SO2 Retrievals from Multiple Satellite Missions

This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, and Lambertian effective reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) onboard NASA's Nimbus-7 satellite (N7/TOMS: 1978-1993) and from the current Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory (DSCOVR: 2015-) from the Earth-Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were assessed using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as the Ozone Monitoring Instrument (OMI) onboard NASA's Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) onboard NASA-NOAA Suomi National Polar Partnership (SNPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus-7/TOMS instrument, described in Sect. S1 of the Supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as the 1991 Pinatubo eruption. To estimate SO2 retrieval systematic uncertainties, we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.

Bradford L Fisher↗

Deep Space Observations of Cloud Glints: Spectral and Seasonal Dependence

From a distance of about one and a half million kilometers, the Earth Polychromatic Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft takes about 13 or 22 images a day of the sunlit side of Earth. Several earlier studies showed that these images often feature sun glint from water surfaces and from ice crystals that float inside clouds in a horizontal orientation. This presentation expands on the earlier analyses of observed glints caused by clouds, focusing on the way the appearance of these glints varies with wavelength and season. The statistical analysis of all EPIC images taken in 2017 reveals that the wavelength dependence of glints is shaped predominantly by the Rayleigh scattering and gaseous absorption caused by the atmosphere above the cloud top. The analysis also reveals that the radiative impact of cloud glints displays seasonal variations that are consistent with seasonal changes in the amount and temperature of ice clouds that were observed independently by the Moderate resolution imaging spectroradiometer (MODIS).

ice cloud↗

Oblique High Mach Number Heliospheric Shocks: The Role of α Particles

Spacecraft observations of heliospheric shocks often find oscillations in the magnetic field and density both, upstream and downstream. The downstream magnetic oscillations of oblique collisionless shocks were detected by Wind with 10.9 samples/s and DSCOVR spacecraft with high temporal resolution of 50 samples/s. The density oscillations associated with the shocks are also evident in proton and α particle density by Wind (with much lower temporal resolution). Recently, we have investigated low Mach number low-β oblique shock oscillations using satellite data and 2.5D hybrid modeling with electrons modeled as fluid and ions modeled as particles and found that α particles—an important component of heliospheric plasma—may affect considerably the downstream oscillations and the shock structure. The objective of the present study is to investigate the effects of α particles on high Mach number heliospheric shocks dynamics, oscillations, nonstationarity, and shock-front rippling. We extend the study to high Mach number shocks (M > 3), investigate several α particle typical densities, and compare the results for the various shock parameters. We model the effects of α particles on the shock ramp, wake, and downstream oscillation structure and the kinetic properties of proton and α particle velocity distributions at various locations downstream of the shocks. Using the 2.5D hybrid model we found that the modeled high Mach number quasi-perpendicular shock magnetic and density structures are significantly affected by α particles with typical solar wind relative abundances, suggesting that the observed high Mach number shocks are similarly affected by α particles.

Leon Ofman↗

Detecting Layer Height of Smoke Aerosols over Vegetated Land and Water Surfaces via Oxygen Absorption Bands: Hourly Results from EPIC/DSCOVR in Deep Space

We present an algorithm for retrieving aerosol layer height (ALH) and aerosol optical depth (AOD) for smoke over vegetated land and water surfaces from measurements of the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR). The algorithm uses Earth-reflected radiances in six EPIC bands in the visible and near-infrared and incorporates flexible spectral fitting that accounts for specifics of land and water surface reflectivity. The fitting procedure first determines AOD using EPIC atmospheric window bands (443 nm, 551 nm, 680nm, and 780 nm), then uses oxygen (O2) A and B bands (688 nm and 764 nm) to derive ALH, which represents an optical centroid altitude. ALH retrieval over vegetated surface primarily takes advantage of measurements in the O2B band. We applied the algorithm to EPIC observations of several biomass burning events over the United States and Canada in August 2017. We found that the algorithm can be used to obtain AOD and ALH multiple times daily over water and vegetated land surface. Validation is performed against aerosol extinction profiles detected by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and against AOD observed at nine Aerosol Robotic Network (AERONET) sites, showing, on average, an error of 0.58 km and a bias of -0.13 km in retrieved ALH and an error of 0.05 and a bias of 0.03 in retrieved AOD. Additionally, we show that the aerosol height information retrieved by the present algorithm can potentially benefit the retrieval of aerosol properties from EPIC’s ultraviolet (UV) bands.

Cloud–Aerosol Lidar with Orthogonal Polarization (↗

Detecting Layer Height of Smoke and Dust Aerosols Over Vegetated Land and Water Surfaces Via Oxygen Absorption Bands

We present an algorithm for retrieving aerosol layer height (ALH) and aerosol optical depth (AOD) for smoke and dust over vegetated land and water surfaces from measurements of the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR). Our algorithm uses EPIC atmospheric window bands to determine AOD and then takes advantage of oxygen A and B bands to derive ALH. We applied this algorithm on several dust and smoke events. Validation shows our results are of high accuracy.

Jing Zeng↗

Astrodynamics Convention and Modeling Reference for Lunar, Cislunar, and Libration Point Orbits

The purpose and direction of this document is to provide U.S. government agencies, specifically National Aeronautics and Space Administration (NASA) and Department of Defense (DoD) space related centers, with a foundational summary of astrodynamics concepts for trajectory design, navigation, and operations in the cislunar, lunar, and libration point regions. This document is provided in response to an Interagency Agreement (IAA) between NASA and the National Geospatial-Intelligence Agency (NGA). With applications to these regions of the Earth-Moon system, this document summarizes: the definitions of standard and unique coordinate systems for Positioning, Navigation, Timing and targeting (PNT), transformations between those coordinate frames, definitions of common time systems, a description of numerical integration, description of a widely-used and approximate dynamical model of a three-body system for preliminary analysis and nomenclature definition, description of higher-fidelity models of cislunar space, and the application of these concepts to sample scenarios with a focus on common steps in trajectory and maneuver design for a spacecraft in cislunar space. This information is critical to mission design and navigation far above the geosynchronous orbit region, where lunar perturbations are required to be modeled accurately and consistently but render trajectory design and analysis a complex procedure. Software tools such as the Goddard Space Flight Center (GSFC) open source General Mission Analysis Tool (GMAT) is used as a reference, along with a wide variety of resources constructed by NASA and other government agencies, academia, and industry, for mathematical specifications and practical considerations. This document has been prepared by and under the auspices of NASA. The GSFC Mission Engineering and Systems Analysis (MESA) Division (Code 590) and the Navigation and Mission Design Branch (Code 595) are part of NASA. Their engineers and scientists have expertise in lunar, cislunar, and libration point region trajectory guidance and navigation and timing. NASA GSFC has supported many successful lunar and cislunar missions over the past several decades. These missions include the Lunar Reconnaissance Orbiter (LRO), the two Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon’s Interaction with the Sun (ARTEMIS) spacecraft, Transiting Exoplanet Survey Satellite (TESS), Lunar Prospector, Lunar Crater Observation and Sensing Satellite (LCROSS), Clementine, and several Sun-Earth libration point missions such as WIND and Deep Space Climate Observatory (DSCOVR), dating back four decades. NASA GSFC also supports the upcoming Gateway lunar mission, the Artemis Lunar Program and Human Landing Systems, and leads both the Lunar IceCube low thrust mission and concept design for the Lunar Communication Relay and Navigation System (LCRNS).

Lunar, CisLunar, Libration, trajectory dynamics, p↗

Out of the blue: volcanic SO e2 emissions during the 2021–2022 eruptions of Hunga Tonga – Hunga Ha'apai (Tonga)

Most volcanism on Earth is submarine, but volcanic gas emissions by submarine eruptions are rarely observed and hence largely unquantified. On January 15, 2022 a submarine eruption of Hunga Tonga-Hunga Ha'apai (HTHH) volcano (Tonga) generated an explosion of historic magnitude, and was preceded by ≈1 month of Surtseyan eruptive activity and two precursory explosive eruptions. We present an analysis of ultraviolet (UV) satellite measurements of volcanic sulfur dioxide (SO 2 ) between December 2021 and the climactic January 15, 2022 eruption, comprising an unprecedented record of Surtseyan eruptive emissions. UV measurements from the Ozone Monitoring Instrument (OMI) on NASA’s Aura satellite, the Ozone Mapping and Profiler Suite (OMPS) on Suomi-NPP, the Tropospheric Monitoring Instrument (TROPOMI) on ESA’s Sentinel-5P, and the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) are combined to yield a consistent multi-sensor record of eruptive degassing. We estimate SO 2 emissions during the eruption’s key phases: the initial December 19, 2021 eruption (≈0.01 Tg SO 2 ); continuous SO 2 emissions from December 20, 2021 – early January 2022 (≈0.12 Tg SO 2 ); the January 13, 2022 stratospheric eruption (0.06 Tg SO 2 ); and the paroxysmal January 15, 2022 eruption (≈0.4-0.5 Tg SO 2 ); yielding a total SO 2 emission of ≈0.60.7 Tg SO 2 for the eruptive episode. We interpret the vigorous SO 2 emissions observed prior to the January 2022 eruptions, which were significantly higher than measured in the 2009 and 2014 HTHH eruptions, as strong evidence for a rejuvenated magmatic system. High cadence DSCOVR/EPIC SO 2 imagery permits the first UV-based analysis of umbrella cloud spreading and volume flux in the January 13, 2022 eruption, and also tracks early dispersion of the stratospheric SO 2 cloud injected on January 15. The ≈0.4-0.5 Tg SO 2 discharged by the paroxysmal January 15, 2022 HTHH eruption is low relative to other eruptions of similar magnitude, and a review of other submarine eruptions in the satellite era indicates that modest SO 2 yields may be characteristic of submarine volcanism, with the emissions and atmospheric impacts likely dominated by water vapor. The origin of the low SO 2 loading awaits further investigation but scrubbing of SO 2 in the water-rich eruption plumes and rapid conversion to sulfate aerosol are plausible, given the exceptional water emission by the January 15, 2022 HTHH eruption.

Volcanoes↗

Multi-Spacecraft Observations of Shocklets at an Interplanetary Shock

Interplanetary (IP) shocks are fundamental building blocks of the heliosphere, and the possibility to observe them in situ is crucial to address important aspects of energy conversion for a variety of astrophysical systems. Steepened waves known as shocklets are known to be important structures of planetary bow shocks, but they are very rarely observed related to IP shocks. We present here the first multi-spacecraft observations of shocklets observed by upstream of an unusually strong IP shock observed on 3 No v ember 2021 by several spacecraft at L1 and near-Earth solar wind. The same shock was detected also by radially aligned Solar Orbiter at 0.8 AU from the Sun, but no shocklets were identified from its data, introducing the possibility to study the environment in which shocklets developed. The Wind spacecraft has been used to characterize the shocklets, associated with pre-conditioning of the shock upstream by decelerating incoming plasma in the shock normal direction. Finally, using the Wind observations together with ACE and DSCOVR spacecraft at L1, as well as THEMIS B and THEMIS C in the near-Earth solar wind, the portion of interplanetary space filled with shocklets is addressed, and a lower limit for its extent is estimated to be of about 110 R E in the shock normal direction and 25 R E in the directions transverse to the shock normal. Using multiple spacecraft also reveals that for this strong IP shock, shocklets are observed for a large range of local obliquity estimates (9° –64°).

plasmas↗

Evaluation of EPIC Oxygen Bands Stability With Radiative Transfer Simulations Over the South Pole

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite orbiting the Sun at the Lagrange-1 point was launched without onboard calibration systems. Vicarious calibration is conducted for 8 of the 10 UV/VIS/NIR channels using other low earth orbiting satellite instruments, while its two O 2 bands (688 nm and 764nm) rely on indirect moon-view calibrations because the same narrow-band O 2 bands are not readily available from other in-flight instruments. This study compares EPIC measurements from the four O 2 bands aiming at examining sensor stability over a uniquely suited location, i.e., the permanently snow-covered South Pole. The study utilizes radiative transfer model simulations with in-situ atmospheric soundings taken at South Pole during months of December and January from 2015 to 2022. The absolute discrepancy between the model simulations and observations is less than 1.0% for the two reference bands, but 5.75% and 15.63% for the 688nm, and 764 nm absorption bands, respectively. The simulated A-band and B-band ratios are 16.09% and 4.74% higher than that from the observations. Various sensitivities are conducted to estimate possible contributions to the discrepancies from input atmospheric profiles, spectral surface albedos and surface BRDF. While none of the input uncertainties is likely to account for the large discrepancies in the oxygen absorption bands, a small shift in the instrument response function could be the main reason for these biases. On the other hand, the model simulations are able to capture systematic variations with observed angular measurements and explain the multi-year trends found in observed O 2 band ratios due to satellite orbit shifting. When model simulated contributions from the angle variations are deducted from the observed O 2 band ratios, the residual O 2 band ratios are found to be stable since 2015.

EPIC↗

June 2023 Canadian Wildfire Effects on Hampton Roads VA using ASDC Data

In June of 2023 thousands of acres of wildfires spread across northwestern Canada. This event emitted huge amounts of smoke, and pollutants that travelled east across the North America, the Atlantic ocean and eventually all the way to Continental Europe. This smoke created a dangerous air quality event throughout the Atlantic Coast. As climate change increases the prevalence of wildfires more cities and states will be affected by the dangerous smoke and pollutants produced by these events. In this poster we documented and investigated the June 06th Air Quality Event over Hampton Roads, VA. To perform a comparative analysis, we utilized two data sources: NASA’s Atmospheric Science Data Center we used the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), the Deep Space Climate ObserVatoRy (DSCOVR) Enhanced Polychromatic Imaging Camera (EPIC), data product, and the EPA’s ground-based Air Quality System (AQS).

Air Quality↗

A Relationship Between Blue and Near‐IR Global Spectral Reflectance and the Response of Global Average Reflectance to Change in Cloud Cover Observed From EPIC

We performed a detailed analysis of Earth Polychromatic Imaging Camera (EPIC) spectral data. We found that the vector composed of blue and near-infrared (NIR) reflectance follows a counterclockwise closed-loop trajectory from 0 to 24 UTC as Earth rotates. This non-linear relationship was not observed by any other satellites due to limited spatial or temporal coverage of either low earth orbit (LEO) or geostationary (GEO) satellites. We found that clouds play an important role in determining the non-linear relationship in addition to the well-known cloud free land-ocean reflectance contrast in the two bands. The non-linear relationship is the result of three factors: (1) a much larger cloud free land-ocean contrast in the NIR band compared to the blue band; (2) significantly larger difference between cloudy-land and cloudy-ocean reflectance in theNIR band compared to the blue band; (3) the periodic variation of fractions of clear land, clear ocean, cloudy land, and cloudy ocean in the sunlit hemisphere as Earth rotates. We found that the green vegetation contributes significantly to the NIR global average reflectance when the South and North Americas appear and disappear in the EPIC's field-of-view. The blue and NIR relationship can be useful for exoplanet research. Clouds impose a strong impact on global spectral reflectance and the reflectance response to a change in cloud cover depends on whether the change is over land or over the ocean. On average, an increase of 0.1 in cloud coverage will lead to a 7%increase in spectrally integrated global average reflectance.

EPIC↗

Global Daily Variability of Cloud Amount from EPIC Observations

EPIC’s vantage point provide a unique opportunity to study the global daytime variability of clouds using a single sensor for the first time. We demonstrate that liquid clouds have opposite daytime evolution between land and ocean, reaching a maximum and minimum around noon, respectively. On the contrary, daytime evolution of ice clouds is independent of the type of underlying surface, with higher values in the morning and afternoon and minimum around noon. Our results are presented with an unprecedent spatial and temporal view of these changes for the whole planet.

clouds↗

EPIC L2 Cloud Products Update

In this presentation, we will update the status of the EPIC L2 cloud products. During this research period, we have conducted investigation on cloud detection over snow and ice using the Oxygen A- and B-band (paper published), as well as cloud detection over ocean sunglint regions. The cloud system algorithm has been upgraded. The new version of cloud product will be tested and released soon.

DSCOVR↗

EPIC Cloud Observations with Oxygen Bands Over Snow, Ice and Sunglint Regions

Cloud detections over snow/ice surfaces and sunglint regions are challenging with passive remote sensing instrument due to lack of contract between cold/bright surfaces in the former and glint reflectance that could exceed that of cloudy sky in the latter. We developed novel cloud detection algorithms for these regions utilizing EPIC’s unique oxygen-bands. Over the snow and ice surfaces, a dynamic threshold scheme based on the ratios of two pairs of EPIC’s oxygen bands are developed to significantly improve the existing algorithm in these regions. Over the ocean, we improved the EPIC’s ocean cloud mask algorithm by implementing a dynamic reflectance threshold and supplemental A-band ratio test for cloud detection in the sun glint regions. The new ocean cloud mask algorithm improves the diurnal cycles of cloud fraction over ocean by reducing the artificial peak at local noon time in the glint center latitudes and reducing early morning and afternoon cloud fraction in most oceanic regions.

EPIC↗