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At least 487 records · Page 27

The Abandoned Ice Sheet Base at Camp Century, Greenland, in a Warming Climate

In 1959 the U.S. Army Corps of Engineers built Camp Century beneath the surface of the northwestern Greenland Ice Sheet. There they studied the feasibility of deploying ballistic missiles within the ice sheet. The base and its wastes were abandoned with minimal decommissioning in 1967, under the assumption they would be preserved for eternity by perpetually accumulating snowfall. Here we show that a transition in ice sheet surface mass balance at Camp Century from net accumulation to net ablation is plausible within the next 75years, under a business-as-usual anthropogenic emissions scenario (Representative Concentration Pathway 8.5). Net ablation would guarantee the eventual remobilization of physical, chemical, biological, and radiological wastes abandoned at the site. While Camp Century and four other contemporaneous ice sheet bases were legally established under a Danish-U.S. treaty, the potential remobilization of their abandoned wastes, previously regarded as sequestered, represents an entirely new pathway of political dispute resulting from climate change.

ice sheet↗

Light Microscopy Module: International Space Station Premier Automated Microscope

The Light Microscopy Module (LMM) was launched to the International Space Station (ISS) in 2009 and began hardware operations in 2010. It continues to support Physical and Biological scientific research on ISS. During 2016, if all goes as planned, three experiments will be completed: [1] Advanced Colloids Experiments with Heated base-2 (ACE-H2) and [2] Advanced Colloids Experiments with Temperature control (ACE-T1). Preliminary results, along with an overview of present and future LMM capabilities will be presented; this includes details on the planned data imaging processing and storage system, along with the confocal upgrade to the core microscope. [1] a consortium of universities from the State of Kentucky working through the Experimental Program to Stimulate Competitive Research (EPSCoR): Stuart Williams, Gerold Willing, Hemali Rathnayake, et al. and [2] from Chungnam National University, Daejeon, S. Korea: Chang-Soo Lee, et al.

Microgravity Biology Research↗

Using the Light Microscopy Module (LMM) on the International Space Station (ISS), The Advanced Colloids Experiment (ACE) and MacroMolecular Biophysics (MMB)

The Light Microscopy Module (LMM) was launched to the International Space Station (ISS) in 2009 and began science operations in 2010. It continues to support Physical and Biological scientific research on ISS. During 2016, if all goes as planned, three experiments will be completed: [1] Advanced Colloids Experiments with Heated base-2 (ACE-H2) and [2] Advanced Colloids Experiments with Temperature control (ACE-T1). Preliminary results, along with an overview of present and future LMM capabilities will be presented; this includes details on the planned data imaging processing and storage system, along with the confocal upgrade to the core microscope. [1] a consortium of universities from the State of Kentucky working through the Experimental Program to Stimulate Competitive Research (EPSCoR): Stuart Williams, Gerold Willing, Hemali Rathnayake, et al. and [2] from Chungnam National University, Daejeon, S. Korea: Chang-Soo Lee, et al.

Microgravity Biology Research↗

Biogeochemical Protocols and Diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP)

The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948-2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF [subscript] 6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.

Carbon↗

Southeast Atmosphere Studies: Learning from Model-Observation Syntheses

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

atmospheric chemistry↗

The Astrobiology Primer v2.0

Astrobiology is the science that seeks to understand the story of life in our universe. Astrobiology includes investigation of the conditions that are necessary for life to emerge and flourish, the origin of life, the ways that life has evolved and adapted to the wide range of environmental conditions here on Earth, the search for life beyond Earth, the habitability of extraterrestrial environments, and consideration of the future of life here on Earth and elsewhere. It therefore requires knowledge of physics, chemistry, biology, and many more specialized scientific areas including astronomy, geology, planetary science, microbiology, atmospheric science, and oceanography. However, astrobiology is more than just a collection of different disciplines. In seeking to understand the full story of life in the Universe in a holistic way, astrobiology asks questions that transcend all these individual scientific subjects. Astrobiological research potentially has much broader consequences than simply scientific discovery, as it includes questions that have been of great interest to human beings for millennia (e.g., are we alone?) and raises issues that could affect the way the human race views and conducts itself as a species (e.g., what are our ethical responsibilities to any life discovered beyond Earth?).

Domagal-Goldman, Shawn D.↗

Climate Change and Drought: From Past to Future

Drought is a complex and multivariate phenomenon influenced by diverse physical and biological processes. Such complexity precludes simplistic explanations of cause and effect, making investigations of climate change and drought a challenging task. Here, we review important recent advances in our understanding of drought dynamics, drawing from studies of paleoclimate, the historical record, and model simulations of the past and future. Paleoclimate studies of drought variability over the last two millennia have progressed considerably through the development of new reconstructions and analyses combining reconstructions with process-based models. This work has generated new evidence for tropical Pacific forcing of megadroughts in Southwest North America, provided additional constraints for interpreting climate change projections in poorly characterized regions like East Africa, and demonstrated the exceptional magnitude of many modern era droughts. Development of high resolution proxy networks has lagged in many regions (e.g., South America, Africa), however, and quantitative comparisons between the paleoclimate record, models, and observations remain challenging. Fingerprints of anthropogenic climate change consistent with long-term warming projections have been identified for droughts in California, the Pacific Northwest, Western North America, and the Mediterranean. In other regions (e.g., Southwest North America, Australia, Africa), however, the degree to which climate change has affected recent droughts is more uncertain. While climate change-forced declines in precipitation have been detected for the Mediterranean, in most regions, the climate change signal has manifested through warmer temperatures that have increased evaporative losses and reduced snowfall and snowpack levels, amplifying deficits in soil moisture and runoff despite uncertain precipitation changes. Over the next century, projections indicate that warming will increase drought risk and severity across much of the subtropics and mid-latitudes in both hemispheres, a consequence of regional precipitation declines and widespread warming. For many regions, however, the magnitude, robustness, and even direction of climate change-forced trends in drought depends on how drought is defined, with often large differences across indicators of precipitation, soil moisture, runoff, and vegetation health. Increasing confidence in climate change projections of drought and the associated impacts will likely depend on resolving uncertainties in processes that are currently poorly constrained (e.g., land-atmosphere interactions, terrestrial vegetation) and improved consideration of the role for human policies and management in ameliorating and adapting to changes in drought risk.

Detection and attribution↗

How Do UTLS Jet and Tropopause Dynamics Influence Ozone Variability? Investigations Supporting the SPARC OCTAV-UTLS Activity

Understanding changes in UTLS ozone is exceptionally challenging because of large spatial and temporal variability and because of the difficulty of satellite measurements in the UTLS. It is also exceptionally important: for example, to understand climate impacts of radiatively active substances and to understand physical and biological effects of pollution transport and stratosphere-troposphere exchange (STE). Multi-decadal global observations of UTLS ozone are now available from numerous satellite platforms, as well as local and regional observations from aircraft, balloons, and lidar. The upper tropospheric (UT) jets and tropopauses are important drivers of composition variability in the UTLS, acting as transport barriers and controlling STE and long-range transport. We report here on investigations of relationships between extratropical UTLS ozone variability and dynamical diagnostics of mixing / transport barriers, Rossby Wave breaking, and stratosphere-troposphere exchange. We will view these relationships in the context of ozone mapped into dynamical coordinates with respect to the UTLS jets and / or the tropopause. This work will help provide direction for analyses within the Stratosphere-troposphere Processes And their Role in Climate (SPARC) Observed Composition Trends and Variability in the UTLS (OCTAV-UTLS) activity, which aims to use dynamical coordinate mapping to help detect and attribute observed UTLS composition trends, and to project future data needs to better quantify those trends. The work we report on here will focus on satellite ozone observations (primarily from the Aura Microwave Limb Sounder, additionally from ACE-FTS and OSIRIS) and assimilated ozone and dynamical fields (from multiple reanalyses); we will also provide some examples of comparisons with aircraft and balloon observations.

Manney, Gloria L.↗

Understanding the Effects of Climate on Ocean Carbon Pools

The role of oceans as a carbon sink has long been accepted. The uncertainties related to the physical and biological pump and their role in the carbon cycle remain however high. In this talk, we dive into the various pathways of carbon in the oceans, the effects that climate has on the ocean carbon cycle and the methodologies used to assess these effects.

Rousseaux, Cecile S.↗

NeMO-Net – The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.

Chirayath, Ved↗

Literature Review of Disinfection Techniques For Water Treatment

Water treatment is a developing concern, both terrestrially and in spacecraft, as exploration missions extend in time and distance. Current biofilm control is limited for long-term applications. To optimize biocides for present and future space exploration vehicles, a thorough understanding of common and traditional disinfectant techniques is required. This review is focused on the three fundamental disinfection techniques: chemical, physical, and biological. Mechanisms, advantages, disadvantages, and specific properties of each major technique, as well as their studied effect on established biofilms, are also considered. This paper provides a general background on disinfectants and some information on effects on biofilms that can be useful to develop innovative ideas for state-of-the-art disinfection techniques for water treatment in specific environments, such as those currently posing mission risks as well as for future spacecraft water system development.

Nilab Azim↗

Legume Organoleptic and Nutritional Analysis

Long-duration missions beyond low Earth orbit will encounter challenges in maintaining adequate nutrition and acceptability in the food system. In situ production of fresh produce can supplement nutrients deficient in the stored diet. Currently there is a limited number of crops that can be reliably grown for space crop production. Recent challenges with Veggie plant growth technical demonstrations (i.e. Tokyo Bekana Chinese cabbage interveinal chlorosis and necrosis when grown under elevated CO2 (~3000ppm) and narrow-band LED lighting) have highlighted the necessity to conduct rigorous ISS-relevant crop screening on the ground. Additionally, crops must be selected to address specific nutritional deficits as identified by HRP, with an emphasis on having a large diversity of crops available to meet nutritional requirements and crew acceptability. A variety of crop types are necessary to address known nutritional deficits in the stored astronaut diet, to include leafy greens (vitamin C, vitamin K, potassium), tomatoes and peppers (vitamin C, potassium, lycopene), and legumes (vitamin B1).Legumes are being evaluated for biological performance and suitability under ISS-like environmental conditions as well as nutritional content and acceptability. Legumes are one of the few pick and eat crop types that is an excellent source of Vitamin B1.In FY21-22 Biological and Physical Sciences (BPS) is funding screening of 32 legume crop cultivars at KSC, 16 of which will be down-selected based on horticultural performance and informal taste testing for further horticultural assessment and analysis. HRP in FY21-22 is funding organoleptic and nutritional analysis of these 16 down-selected legume cultivars to determine the most promising candidates for future space applications. Nutritional analysis will include full elemental, proximate (fat, protein, calories, carbohydrates, ash), and vitamins B1, C, K. This new work is currently postponed due to Covid-19.

L E Spencer↗

Virtual Sensing with Unsupervised Image-to-Image Translation

Earth observing satellites carrying multi-spectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the earth and different spectral imaging bands resulting in inconsistent imagery from one to another. This presents challenges in building downstream applications. What if we could generate synthetic bands for existing satellites from the union of all domains? We tackle the problem of generating synthetic spectral imagery for multispectral sensors as an unsupervised image-to-image translation problem with partial labels and introduce a novel shared spectral reconstruction loss. Simulated experiments performed by dropping one or more spectral bands show that cross-domain reconstruction outperforms measurements obtained from a second vantage point. On a downstream cloud detection task, we show that generating synthetic bands with our model improves segmentation performance beyond our baseline. Our proposed approach enables synchronization of multispectral data and provides a basis for more homogeneous remote sensing datasets.

Geostationary satellites↗

SMD Technology Highlights

Six technology highlights from the Science Mission Directorate (SMD) Heliophysics, Astrophysics, Earth, and Biological and Physical Sciences divisions. Technologies featured include 1. the 1653 m2 Solar Cruiser Solar Sail Propulsion system to enable missions to reach novel and otherwise difficult or impossible destinations for observing the Sun. 2. Technology sponsored by NASA and developed by MIT Space Nanotechnology Lab is developing high-performance space instrumentation for more powerful future X-ray telescopes that will study the dynamics of the high-energy universe. 3. Active thermal control technology that will help enable large ultra-stable telescopes needed to detect and characterize Earth-like planets around other stars. 4. SMD sponsored high-performance infrared sensors with reduced requirements for cooling onboard satellites and these sensors could potentially be flown on small satellite platforms like CubeSats. 5. A new technology that will utilize electron beams/ultraviolet light to remove dust that could help protect future space assets and astronauts from dangerous effects that arise from Moon/Mars dust exposure. 6. Studies using model organisms on ISS to understand the impact of the spaceflight environment on organisms in preparation for long-duration missions.

solar sail↗

Delineation of vulnerable areas to water erosion in a mountain region using SDR-InVEST model: A case study of the Ourika watershed, Morocco

The Ourika watershed is characterized by higher than average flood flows, a rugged topography, a sparse vegetation cover and a friable substrate that makes it vulnerable to soil erosion. Soil is an important non-renewable asset capital, providing several ecosystem services that sustain life through physical and biological regulation processes. The loss, or otherwise, redistribution of biota by soil erosion in the Ourika watershed has received little attention and thus constitutes a key knowledge gap that needs to be addressed. This study quantifies the level of erosion and maps its spatial distribution in the watershed using the Sediment Delivery Ratio (SDR) of the Integrated Valuation of Ecosystem Services and Tradeoffs model (InVEST3.6.0). The SDR maps the overland sediment generation and delivery to the stream at the watershed level using rainfall, soil properties, topography, cover management and cropping practices as predefined set of input variables. Recommended internal model calibration was used and results were compared to similar studies carried out in different parts of Morocco for validation. The results reveal that 93% of the watershed is subject to a strong rainfall aggressiveness greater than 50 MJ mm ha–1 h–1 yr1 under an average rainfall intensity of 541 mm/year, rainfall capacity to initiate the detachment and transport of soil particles by runoff, and only 11.5% of the watershed area is protected with vegetative cover. We find that overall, the Ourika watershed is losing its soil to erosion at an alarming average rate of 258.48 ton.ha–1.yr–1, a rate well above the tolerable threshold of 7ton.ha–1.yr–1. The spatial distribution of this loss shows areas that need to be urgently remedied. The primary factors for soil erosion in the Ourika watershed appear to be related to the aggressive nature of local rainfall and the inherent susceptibility of soils, which can be costly to this cash-crop region. Because rainfall intensity, soil properties, and topography are intrinsic characteristics of the watershed, we suggest that seasonally adapted cropping rotations that maintains conservative practices with a high cover management may reduce soil erosion in the Ourika watershed.

Erosion↗

Cultivating Plants in a Controlled Environment

Presentation on the challenges and needs for space crop production in controlled environments. This will be part of a technical interchange meeting with the United Arab Emirates and NASA Biological and Physical Sciences.

Space Crop Production↗

SMD Technology Highlights

Seven technology highlights from the Science Mission Directorate (SMD) Astrophysics, Planetary Science, Heliophysics, and Biological and Physical Sciences, and Earth Science divisions are featured: 1. Technology using precisely controlled ultraviolet light source that to suppress electrostatic noise in gravitational wave observatories 2. New micro-shutter technology that will enable space telescopes to perform spectroscopy on a large number of objects simultaneously 3. An optical seismometer that is micro-fabricated, easy to manufacture, immune to radiation damage, and operates with low power consumption to characterize ice sheets and mantle on icy worlds 4. Rediscovering the lost art of fluxgate magnetometer cores 5. Innovative technology to measure muscle strength of worms in space to prepare astronauts for future missions 6. A new state-of-the-art sensor and satellite platform to enable continued monitoring of Earth’s radiant energy system 7. Novel Algorithms to merge ground- and space-based data to forecast air pollution events

ultraviolet↗

Spectral Synthesis for Geostationary Satellite-to-Satellite Translation

Earth-observing satellites carrying multispectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the Earth and different spectral imaging bands resulting in inconsistent imagery from one to another. This presents challenges in building downstream applications. What if we could generate synthetic bands for existing satellites from the union of all domains? We tackle the problem of generating synthetic spectral imagery for multispectral sensors as an unsupervised image-to-image translation problem modeled with a variational autoencoder (VAE) and generative adversarial network (GAN) architecture. Our approach introduces a novel shared spectral reconstruction loss to constrain the high-dimensional feature space of multispectral images. Simulated experiments performed by dropping one or more spectral bands show that cross-domain reconstruction outperforms measurements obtained from a second vantage point. Our proposed approach enables the synchronization of multispectral data and provides a basis for more homogeneous remote sensing datasets.

Geostationary satellites↗