Meteorological research satellites on polar orbits observe occasionally the Moon, when it moves through their deep space view. Over the last few decades, a large data set built up, which allows to determine the lunar flux with unprecedented accuracy especially at wavelengths, for which the Earth’s atmosphere is opaque. We determined the disk-integrated brightness temperature of the Moon at 19 wavelengths between 4 and 15 µm and at five frequencies between 89 and 190 GHz for phase angles between -80° and +70° with HIRS, AMSU-B, MHS, and ATMS on NOAA and MetOp satellites
The transition from sand ripples to megaripples encodes information about the physics of how both sand-sized (moved via saltation) and coarsegrained (moved via impact creep) particles interact under Martian conditions. Previous studies have focused on the aeolian mobility of sand on Mars; here we examine how mobile sand interacts with larger particles moved by creep. HiRISE images of small dunes (lacking well developed slip faces) on Mars reveal a transition of aeolian bedform scale with increasing distance from the dune. Here we document the particles in a similar transition on Earth. High Resolution Imaging Science Experiment (HiRISE) images have documented that sand is moving at many locations around Mars under current conditions. Unlike the active sand deposits, enigmatic “Transverse Aeolian Ridges” (TARs; the non-genetic term for linear to curvilinear aeolian bedforms resulting from either dune- or ripple-forming processes) are found at locations widely distributed across Mars. Recently bright TARs were documented to have moved in HiRISE images taken many Earth years apart at three widely separated locations. Great Sand Dunes National Park and Preserve (GSDNPP) in Colorado has a bimodal particle size distribution along with a seasonal bimodal wind regime, providing the setting to examine the transition from sand ripples (<1 cm in height) to megaripples (typically ~25 cm in height). A Smithsonian Scholarly Studies Award for FY19 funded trips to GSDNPP during May and September of 2019 to collect thousands of digital photographs of ripple-megaripple transitions that were later processed using Multiview Stereo Photogrammetry software to produce detailed Digital Terrain Models (DTMs). The digital images were obtained using a Nikon camera that was motor-driven along a track above the study area. The track was then manually advanced following each photo traverse. Photos were obtained using both a 35 mm lens and a 85 mm Macro lens. The DTMs clearly resolve individual coarse (1-2-mm diameter) particles on the bedforms, providing a detailed record of the surface distribution of coarse grains across both sand ripple and megaripple bedforms, including cases where the crests were continuous between sand ripples and megaripples.
Introduction: Ocean Worlds are of high interest to the planetary community [1, 2] due to the potential habitability of their subsurface oceans [3–5]. Over the next few decades several missions will be sent to ocean worlds including the Europa Clipper , Dragonfly , and possibly a Europa lander . The Dragonfly and Europa lander missions will carry seismic payloads tasked with detecting and locating seismic sources. The Seismometer to Investigate Ice and Ocean Structure (SIIOS) is a NASA PSTAR funded project that investigates ocean world seismology using terrestrial analogs. One goal of the SIIOS experiment is characterizing the local seismic environment of our field sites. Here we present an analysis of detected local events at our field sites at Gulkana Glacier in Alaska and in Northwest Greenland approximately 80 km North of Qaanaaq, Greenland (Fig. 1a). Both field sites passively recorded data for about two weeks. We deployed our experiment on Gulkana Glacier in September 2017 (Fig. 1b) and in Greenland in June 2018 (Fig. 1c). At Gulkana there was a nearby USGS weather station  which recorded wind data. Temperature data was collected using the MERRA satellite . In Greenland we deployed our own weather station to collect temperature and wind data. Gulkana represents a noisier and more active environment: Temperatures fluctuated around 0C, allowing for surface runoff to occur during the day. The glacier had several moulins, and during deployment we heard several rockfalls from nearby mountains. In addition to the local environment, Gulkana is located close to an active plate boundary (relative to Greenland). This meant that there were more regional events recorded over two weeks, than in Greenland. Greenland’s local environment was also quieter, and less active: Temperatures remained below freezing. The Greenland ice was much thicker than Gulkana (~850 m  versus ~100 m [12, 13]) and our stations were above a subglacial lake. Both conditions can reduce event detections from basal motion. Lastly, we encased our Greenland array in an aluminum vault and buried it beneath the surface unlike our array in Gulkana where the instruments were at the surface and covered with plastic bins. The vault further insulated the array from thermal and atmospheric events. Event Detection and Clustering: To detect local events we filtered the data between 5-20 Hz. Using the Obspy module in python , we performed a short-term average/long-term average (STA/LTA) approach to determine where amplitudes spiked. For short term we used 1.5 seconds and 40 seconds and a ratio of 20 to detect events . Through this approach we detect-ed 104 events at our Greenland site and 2252 events at our Gulkana site. The Gulkana site showed a strong correlation with both temperature and changes in temperature, while Greenland did not show this relationship . Once we had a catalog of events, we performed a hierarchal cluster analysis to cluster events.
Does life currently exist, or did life once exist, on other worlds in our solar system? The proximity of the rocky planets of our solar system, Venus and Mars, make them obvious targets for the first attempts to answer these questions via direct exploration, with concomitant implications for, and input to, how we think of exoplanets. Given the limited resources we have to explore our neighbors in space, an ecological assessment (based on terrestrial ecosystem principles) might help us target our search and methodology. Studies of extreme life on Earth consistently reveal adaptability. Mars has been the target of many life-related investigations [1, many others]. Venus has not, yet there may be compelling reasons to think about extant life on the second planet , and lessons to learn there about searching for life elsewhere in the solar system and beyond. The Venus Life Equation: Venus may have been habitable for billions of years its history and may still be habitable today. Our current state of knowledge of the past climate of Venus suggests that the planet may have had an extended period – perhaps 1-2 billion years – where a water ocean and a land ocean interface could have existed on the surface, in conditions possibly resembling those of Archaean Earth . At present, Venus’ surface is not hospitable to life as we know it, but there is a zone of the Venus middle atmosphere, ~55 km altitude, just above the sulfuric acid cloud layer, where the combination of pressure, temperature, and gas-mix are more Earth-like than anywhere else in the solar system [2, 4]. The question of whether life could have – or could still – exist on the Earth’s closest neighbor is more open today than it’s ever been. Here we approach the question of present-day life on Venus in a manner analogous to the Drake Equation , treating the possibility of current Venus life as an exercise in informal probability – seeking qualitatively the likelihood or chance of the answer being nonzero.The working version of the Venus Life Equation is expressed as: L = O * R * A where L is the likelihood (zero to 1) of there being life on Venus in the present-day, O (origination) is the chance life ever began and “broke out” on Venus, R (robustness) is the potential current and historical size of diversity of the Venus biosphere, A (acceptability) is the chance that conditions amenable to live persisted spatially and temporally to the present. The Venus Life Equation is a work-in-progress as a pre-decadal White Paper  and its variables are currently being refined.  McKay 1997, Springer, Dordrecht, 1997. 263-289.  Limaye et al. 2018 Astrobiology, 18(9), 1181-1198.  Way et al. 2016 JGR 43(16) 8376-8383.  Schulz-Makuch et al. 2004 Astrobiology 4, 11-18.  Burchell 2006, Int. J. Astrobio, 5(3) 243-250.  Izenberg et al. 2020, https://is.gd/vd4JE7 (location of Latest version of Venus Life Equation White Paper).
We propose a thermal-fluid system model for hollow formation. A subsurface heat source (typically impact-related) produces volatiles from LRM and drives them to the surface. Volatiles generated through heating of LRM are likely S and S-bearing gases produced by thermal decomposition of sulfides heated by the impact process. C-bearing volatiles, such as CH4 and other simple organics, and potentially fullerenes within LRM, may also be involved in proposed thermal-fluid systems responsible for hollow formation.