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Author(s):  
Christian Siemes ◽  
Stephen Maddox ◽  
Olivier Carraz ◽  
Trevor Cross ◽  
Steven George ◽  
...  

AbstractCold Atom technology has undergone rapid development in recent years and has been demonstrated in space in the form of cold atom scientific experiments and technology demonstrators, but has so far not been used as the fundamental sensor technology in a science mission. The European Space Agency therefore funded a 7-month project to define the CASPA-ADM mission concept, which serves to demonstrate cold-atom interferometer (CAI) accelerometer technology in space. To make the mission concept useful beyond the technology demonstration, it aims at providing observations of thermosphere mass density in the altitude region of 300–400 km, which is presently not well covered with observations by other missions. The goal for the accuracy of the thermosphere density observations is 1% of the signal, which will enable the study of gas–surface interactions as well as the observation of atmospheric waves. To reach this accuracy, the CAI accelerometer is complemented with a neutral mass spectrometer, ram wind sensor, and a star sensor. The neutral mass spectrometer data is considered valuable on its own since the last measurements of atmospheric composition and temperature in the targeted altitude range date back to 1980s. A multi-frequency GNSS receiver provides not only precise positions, but also thermosphere density observations with a lower resolution along the orbit, which can be used to validate the CAI accelerometer measurements. In this paper, we provide an overview of the mission concept and its objectives, the orbit selection, and derive first requirements for the scientific payload.


2022 ◽  
Author(s):  
Patrick Sullivan ◽  
Kelly O'Neill ◽  
Andrew Thorpe ◽  
Riley Duren ◽  
Philip Dennison

2021 ◽  
Vol 163 (1) ◽  
pp. 2
Author(s):  
Ashley Gerard Davies

Abstract Between 1996 and 2001, the Galileo Near-Infrared Mapping Spectrometer (NIMS) obtained 190 observations of the volcanic Jovian moon Io. Rathbun et al. (2018) [Astron. J., 156, 207] published a list of 287 measurements of 3.5 μm spectral radiance from some of Io’s active volcanoes, derived from a subset of the NIMS data. However, the spectral radiances reported by Rathbun et al. are lower, in some cases by multiple orders of magnitude, than other analyses of the same observations and spectral radiances derived from contemporaneous ground-based data. In many cases, the Rathbun et al. hot-spot radiances are underreported by a factor of π, likely due to a mistake in unit conversion. For a small number of powerful hot spots, additional discrepancies appear to be the result of poor fits to data limited in wavelength range by NIMS detector saturation and a methodology that discards short-wavelength NIMS data that otherwise would have provided more robust temperature model fits.


2021 ◽  
Vol 8 ◽  
Author(s):  
Steven R. Schill ◽  
Gregory P. Asner ◽  
Valerie Pietsch McNulty ◽  
F. Joseph Pollock ◽  
Aldo Croquer ◽  
...  

Over the past decade, coral restoration efforts have increased as reefs continue to decline at unprecedented rates. Identifying suitable coral outplanting locations to maximize coral survival continues to be one of the biggest challenges for restoration practitioners. Here, we demonstrate methods of using derivatives from imaging spectroscopy from the Global Airborne Observatory (GAO) to identify suitable coral outplant sites and report on the survival rates of restored coral at those sites. Outplant sites for a community-based, citizen science outplant event in Bávaro, Dominican Republic, were identified using expert-defined criteria applied to a suitability model from data layers derived from airborne imagery. Photo quadrat analysis of the benthic community confirmed the accuracy of airborne remote sensing maps with live coral cover averaging 3.5–4% and mean algal cover (macro algae and turf) ranging from 28 to 32%. Coral outplant sites were selected at 3–7 m depth with maximized levels of habitat complexity (i.e., rugosity) and live coral cover and minimized levels of macroalgal cover, as predicted by the imaging spectrometer data. In November 2019, 1,722 Acropora cervicornis fragments (80–180 mm in length) were outplanted to these sites. Surveys conducted in January 2020 in four of these sites confirmed that 92% of outplants survived after 3 months. By October 2020 (11 months after outplanting), survivorship remained above 76%. These results demonstrate higher than average success rates for coral outplant survival for this species. An online tool was developed to enable replication and facilitate future selection of coral restoration sites. Our objective is to present a case study that uses GAO-derived map products within a suitability model framework to provide a quantitative and replicable method for selecting coral restoration sites with the goal of increasing outplant survival over time.


2021 ◽  
Author(s):  
Patrícia Gonçalves ◽  
Luisa Arruda ◽  
Marco Pinto

<p>The characterisation of the Martian radiation environment is essential to understand if the planet can sustain life and ultimately if its human exploration is feasible. The major components of the radiation environment in the Mars orbit, are Galactic Cosmic Rays (GCRs) and Solar Energetic Particle (SEP) events. Since Mars has a negligible magnetic field and a much thinner atmosphere compared to the Earth’s, its surface is exposed to GCR and eventual SEP events, as well as to secondary particles produced in the atmosphere and in the shallow layers of the planet. The Curiosity rover that has been exploring the surface of Mars since August 2012, carries in its Mars Science Laboratory (MSL), the Radiation Assessment Detector (RAD) which measures high-energy radiation, such as protons, energetic ions of various elements, neutrons, and gamma rays. That includes not only direct radiation from space, but also secondary radiation produced by the interaction of space radiation with the atmosphere and surface rocks and soil.</p> <p><br />The detailed Martian Energetic Radiation Environment Model (dMEREM) is a GEometry ANd Tracking (GEANT4) based model developed for ESA which enables to predict the radiation environment expected at different locations on the Martian orbit, atmosphere and surface, as a function of epoch, latitude and longitude, taking into account the specific atmospheric and soil composition. dMEREM can be interfaced to different Primary Particle Models, such as the ISO-15390 and the Badhwar - O'Neill (BON) 2014 or 2020 Galactic Cosmic Ray Flux Models, or the National Aeronautics and Space Administration (NASA) Emission of Solar Protons (ESP) model for solar energetic proton fluences. dMEREM is interfaced with the European Mars Climate Database from where it retrieves information on the atmosphere composition and density at specific locations and solar longitudes and Gamma Ray Spectrometer data aboard Mars Odyssey, for the description of Mars soil composition, although soil compositions for specific locations, including those locally sampled by Martian rovers can also be defined by the user. dMEREM provides the kinetic energy and directional spectra of all particle types produced in the interactions of energetic particles with the Martian Atmosphere and Soil.</p> <p>The dMEREM validation results using differential proton fluxes stopping in the RAD sensor head as measured by MSL/RAD in Gale crater from November 15, 2015 to January 15, 2016 and in the begin of September 2017 is presented. Although the RAD only measures a limited field-of-view in zenith angle of the Martian Particle Radiation Field, the good agreement between the RAD data and the dMEREM predictions for protons within the RAD field of-view, are used as the basis for the use of dMEREM in the assessment of the expected ionizing radiation field on the surface of Mars for particles coming from all directions, including albedo particles. This assessment is also used to make predictions of dosimetric quantities, such as Ambient Dose Equivalent and Effective Dose, relevant for Human Space Flight, for the considered data periods.  </p>


2021 ◽  
Author(s):  
Vladimir Mikhailov ◽  
S.Yu. Aleksandrin ◽  
A.M. Galper ◽  
T.R. Zharaspayev

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