ALBERT

Description: No abstract available

Description: Seasonal forecasts made by coupled atmosphere-ocean general circulation models (GCMs) are increasingly able to provide skillful forecasts of climate anomalies. At some centers, the capabilities of these models are being expanded to represent carbon-climate feedbacks including ocean biogeochemistry (OB), terrestrial biosphere (TB) interactions, and fires. These advances raise the question of whether such models can support skillful forecasts of carbon fluxes.Here, we examine whether land and ocean carbon flux anomalies associated with the 2015-16 El Nino could have been predicted months in advance. This El Nino was noteworthy for the magnitude of the ocean temperature perturbation, the skill with which this perturbation was predicted, and the extensive satellite observations that can be used to track its impact. We explore this topic using NASA's Goddard Earth Observing System (GEOS) model, which routinely produces an ensemble of seasonal climate forecasts, and a suite of offline dynamical and statistical models that estimate carbon flux processes. Using GEOS forecast fields from 2015-16 to force flux model hindcasts shows that these models are able to reproduce significant features observed by satellites. Specifically, OB hindcasts are able to predict anomalies in chlorophyll distributions with lead times of 3-4 months. The ability of TB hindcasts to reproduce NDVI anomalies is driven by the skill of the climate forecast, which is greatest at short lead times over tropical landmasses. Statistical fire forecasts driven by ocean climate indices are able to predict burned area in the tropics with lead times of 3-12 months. We also integrate the ocean and land hindcast fluxes into the GEOS GCM to examine the magnitude of the atmospheric carbon dioxide anomaly and compare with satellite and ground-based observations.While seasonal forecasting remains an active area of research, these results demonstrate that forecasts of carbon flux processes can support a variety of applications, potentially allowing scientists to understand carbon-climate feedbacks as they happen and to capitalize on more flexible satellite technologies that allow areas of interest to be targeted with lead times of weeks to months. We also provide a first glimpse at the spring 2019 carbon forecast using the GEOS-based forecasting system.

Description: This presentation includes the UAS-Enabled Market Categories used in Study, as well as the reason for the UAS-NAS NO Chase COA flight. It discusses the transitioning of a UA from different airspaces. UAS Integration is a community wide effort, and the FAA Symposium provides attendees with the opportunity to engage face-to-face with a cross-section of government and industry leaders and innovators about the latest industry developments, regulations, research, and other initiatives to safely integrate UAS into the National Airspace System (NAS).

Description: On-orbit Robotic External Leak Locator (RELL) (i.e., mass spectrometer and ion gauge) measurements on the International Space Station (ISS) are presented to show the detection of recurring Environmental Control and Life Support System (ECLSS) vents at multiple ISS locations and RELL pointing directions. The path of ECLSS effluents to the RELL detectors is not entirely obvious at some locations, but the data indicates that diffuse gas-surface reflection or scattering resulting from plume interaction with vehicle surfaces is responsible. RELL was also able to confirm the ISS ECLSS constituents and distinguish them from the ammonia leak based on the ion mass spectra and known venting times during its operation to locate a leak in the ISS port-side External Active Thermal Control System (EATCS) coolant loop.

Description: This paper presents the physical basis of the EPIC cloud product algorithms and an initial evaluation of their performance. Since June 2015, EPIC has been providing observations of the sunlit side of the Earth with its 10 spectral channels ranging from the UV to the near-IR. A suite of algorithms has been developed to generate the standard EPIC Level 2 Cloud Products that include cloud mask, cloud effective pressure/height, cloud optical thickness, etc. The EPIC cloud mask adopts the threshold method and utilizes multichannel observations and ratios as tests. Cloud effective pressure/height is derived with observations from the O2 A-band (780 nm and 764 nm), and B-band (680 nm and 688 nm) pairs. The EPIC cloud optical thickness retrieval adopts a single channel approach where the 780 nm and 680 nm channels are used for retrievals over ocean and over land, respectively. Comparison with co-located cloud retrievals from geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellites shows that the EPIC cloud product algorithms are performing well and are consistent with theoretical expectations. These products are publicly available at the Atmospheric Science Data Center at the NASA Langley Research Center for climate studies and for generating other geophysical products that require cloud properties as input.

Description: For many years, the concept of routinely flying unmanned aircraft systems (UAS) within the national airspace system (NAS) has been a long-term goal with numerous known and unknown technology and policy obstacles. Just within the last few years, the efforts and advancements from government, industry, and academia-sponsored research and development have greatly shortened the distance to the goal. The National Aeronautics and Space Administration (NASA) Aeronautics Research Mission Directorate (ARMD) has recognized that it is uniquely positioned to play a lead role in addressing the remaining UAS airspace integration (AI) challenges. To fully understand the magnitude and scope of these challenges, NASA ARMD initiated a study in 2015 to identify what would be needed to enable full integration of UAS for civil/commercial operations within the NAS by 2025. The desired outcome was a comprehensive analysis framework that ARMD could use to develop a research portfolio focused on retiring the remaining gaps and challenges standing in the way of full UAS integration. This document is a comprehensive assessment of UAS integration research to date.

Description: The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration less than 2%, relative calibration of 0.2%, polarization sensitivity less than 1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.