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Satellite Remote Sensing of Cyanobacteria: Success Stories of Management Taking Action and the CyAN Data Sharing App
Get PDFSupport the environmental management and public use of U.S. lakes by detecting and quantifying algal blooms and related water quality indicators using satellite data records
The Health Risks of Extraterrestrial Environments (THREE) 2019 Annual Report
Get PDFTHREE is an encyclopedic website (http://three.jsc.nasa.gov) about the space radiation environment and its health risks to humans. The goal for the site is threefold: 1. to serve as a starting point for researchers new to either space, radiation, or both; 2. to serve as a source of useful information for established investigators; 3. to serve as a teaching tool for students; and, 4. to serve as a NASA reference source on all scientific aspects of space radiation and health. THREE is funded by the Space Radiation (SR) Element within NASAs Human Research Program (HRP). The THREE Editorial Board is responsible for oversight of the content and policies for the website. The website is hosted by the NASA Johnson Space Center
Smoking and Mortality Among US Astronauts
Get PDFAstronauts have lower age-specific mortality risk than the U.S. general population from all natural causes of death, particularly cardiovascular disease and cancer. Yet, understanding if they are as healthy as their backgrounds predict they should be, requires that epidemiologists understand (and measure) all potentially confounding exposures in this cohort. Tobacco smoking prevalence has been measured in the U.S. astronaut cohort, but its impact on mortality has not been previously assessed. If smoking history has a negative impact on mortality, this could confound attempts to measure the relative health of astronauts
Exploration Medical Capability Medical System Requirements Overview and Update
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Improving Quantitative Laboratory Analysis of Phycobiliproteins to Provide High Quality Validation Data for Ocean Color Remote Sensing Algorithm
Get PDFIdentification and characterization of phytoplankton communities and their physiology is a primary aim of NASA's PACE satellite mission. The concentration and composition of phytoplankton pigments modulate the spectral distribution of light emanating from the ocean, which is measured by ocean color satellites, and thus provide critical information on phytoplankton community composition and physiological parameters. One diagnostic class of pigments not routinely well-characterized is the phycobiliproteins (PBPs), and NASA has a requirement to collect and distribute high quality in situ data in support of data product validation activities for ocean color missions. Phycobiliproteins are light-harvesting proteins that are the predominant photosynthetic pigments in some classes of phytoplankton including cyanobacteria, such as Synechococcus, Trichodesmium, and Microcystis. With the advance of hyperspectral ocean color sensors such as on PACE (expected to launch in late 2022), it is essential that we implement routine analysis of PBPs that satisfies several considerations: reproducible, high extraction efficiency for a variety of environments, and Suitable for large scale analysis. Published techniques for PBP analysis vary in recommendations for: collection, extraction, disruption mode, and analysis; evidence suggests the variation in results may depend at least in part on the species and even strain(s) of interest. Experiments that tested variations in these parameters have drawn very different conclusions regarding extraction efficiency and reproducibility. Cyanobacteria are more difficult to extract than other PBP-containing algae such as cryptophytes, but can be important primary producers. We used a cryptophyte (Rhodomonas salina) and cyanobacterium (Synechococcus sp.) to compare extraction efficiencies of water samples concentrated via centrifugation to filtered samples using two different extraction buffers (phosphate and asolectin-CHAPS). Samples were analyzed on a fluorometer configured for PC and PE detection. The results have important implications for collection and storage of samples for routine analysis; some previous studies (although not all) have suggested that filtered samples have a much lower extraction efficiency than whole water samples
Comparison of Surface Fluxes Derived from CYGNSS and Simulated by WRF Model: An MJO Case Study
Get PDFThis study focuses on ocean surface fluxes, mainly the latent heat flux, and their impact on MJO propagation and associated precipitation structures over the Indian Ocean and Maritime Continent. The Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model is used to simulate two MJO events during the 2017-2018 season: the December 10 - January 20, 2017 case, which maintained its strong precipitation signal over the Maritime Continent, and the March 1 - 20, 2018 case, which was weaker and did not propagate through the Maritime Continent. Both simulated MJO events show positive biases in surface rainfall compared with GPM IMERG data. During the MJO suppressed phase, the simulations rain more often than the observations. During the active phase, the westward propagating precipitation structures are more organized and much stronger compared with the observations, sometimes forming westward propagating cyclones that weakened the eastward precipitation signals. Two aspects of the surface flux interactions are investigated: the impact of the domain mean surface fluxes, and the impact of storm scale circulations and their interactions with local surface fluxes. Both aspects affect water vapor budget, atmosphere instability and mean flow, through which convection initiation, organization, and propagation are influenced. Model sensitivity tests with different radiation, microphysics, PBL schemes and nudging schemes indicate that in the control simulations, higher SST and surface fluxes, especially during the suppressed period, are the main reason of rainfall overestimation compared with IMERG data. The strong westward propagating signals are caused by both increased atmosphere instability and reduced mean wind shear. Unfortunately, the small differences in mean SST and surface fluxes between different model sensitivity tests are all within the satellite observation error margin, and cannot be directly corroborated by observations. One of the advantages of CYGNSS satellites is that they observe ocean surface wind and heat fluxes underneath strong rainfall events such as the convective systems associated with MJO active phases. Currently we are comparing CYGNSS level 2 surface fluxes retrievals and the model simulations in order to better understand the second aspect of the MJO and surface fluxes interactions, and how this affects MJO strengths and propagations. The interactive atmosphere-ocean-wave model also provides cases that directly comparing satellite observables (the bistatic radar cross section) and the model simulations (through CYGNSS satellite simulator). These discrepancies are more prominent in coupled ocean simulations, mainly due to higher SST and enhanced surface fluxes
Impact of Convectively Detrained Ice Crystals on the Tropical Upper Troposphere and Lower Stratosphere
Get PDFThe role of convectively detrained ice crystals on the humidity of the tropical upper troposphere and lower stratosphere (UTLS) is investigated in simulations of cirrus clouds along trajectories launched from the 378K potential temperature level in the tropics. The one-dimensional (vertical) cloud model tracks individual ice crystals through their lifecycle beginning with detrainment from convection, followed by deposition growth, sedimentation and sublimation. Convective influence of the parcels is diagnosed by tracing the trajectories through time-dependent fields of convective cloud-top height adjusted to match the CloudSAT and CALIPSO statistics. Model simulations of UTLS water vapor and cloud fields are evaluated and constrained by comparison with Aura MLS and CALIPSO measurements. Preliminary results indicate sensitivity of the detrained ice crystal lifecycle to atmospheric conditions downstream of convection. Specifically, cooling (high relative humidity and supersaturation) downstream of convection leads to deposition growth and sedimentation of detrained ice crystals, resulting in net dehydration of the UTLS. In contrast, warming (low relative humidity and subsaturation) downstream of convection leads to sublimation of detrained ice crystals and subsequent hydration. As such, the impact of detrained ice crystals on the humidity of the UTLS exhibits distinct spatial variability. Detrained ice crystals predominantly dehydrate the UTLS in the tropical mean. Sensitivities to the convectively detrained ice crystal size and concentration are also examined using measurements from the StatoClim aircraft campaign. The importance of convectively detrained ice crystals will be discussed within the context of the overall contribution of convection to the lower stratospheric humidity
Cold-Flow Model Tests to Determine Static Performance of a NASA One-Sided Ejector Nozzle System
Get PDFThis report presents the results of cold-flow model tests to determine the static
performance of multiple configurations of a NASA one-sided ejector nozzle system. The
existing ejector nozzle system hardware was provided by NASA and was previously used for
acoustic tests. A new facility adapter duct and ejector box support brackets were designed and
fabricated by the FluiDyne Aerotest Laboratory of Aero Systems Engineering, Inc. The tests
were performed in the Channel 8 static thrust stand at ASEs FluiDyne Aerotest Laboratory
in Plymouth, Minnesota.
Facility checkout tests were made using a standard American Society of Mechanical
Engineers (ASME) long-radius metering nozzle. These tests demonstrated facility data
accuracy at flow conditions similar to the model tests.
Channel 8 static tests included 40 ASME nozzle facility checkout tests and 24 model
tests (plus an additional 1 at no charge). The model nozzle pressure ratio varied from 1.4 to
3.0.
Test results include: thrust coefficients, thrust vector angles and location, nozzle
discharge coefficients, charging station total and static pressures, and model static pressure
distributions (in the Data Appendix)