Space Weather Database Of Notifications, Knowledge, Information (DONKI)

The Flight Awareness Collaboration Tool (FACT) user interface is a quad design with four areas. The Primary Map View shows the US with several traffic and weather overlays. The Surface Map View displays the selected airport with information on runway conditions and other factors. The Information View has specific data from various sources about the area of interest. This view also has a built-in algorithm that predicts the impact of the forecast winter weather on airport capacity. The Communication View supports messaging within the geographically-dispersed team that is using FACT. When an airport is selected in the Primary Map View, the information presented in the Surface Map and Information Views is focused on that choice. FACT is a web-based application using Node.js and MongoDB. It receives Java messages from the Federal Aviation Administration System Wide Information Management (SWIM) data repository. Data acquired from web pages and SWIM are tailored for FACTs Information View area. FACT is designed to reside on an existing workstation monitor to be put into use as needed.

Radiosondes are launched twice a day from different locations of the world and meteorological data is collected to plot the STUV diagram and determining CAPE (Cumulative Average Potential Energy) values. Radiosondes are not re-usable and used only at pre-determined locations around the globe. Moreover, a radiosonde can drift up to 125 miles from its release point. About 75,000 radiosondes are used every year. Given this unmet need, an inventor at NASA has developed an advanced airborne meteorological system which can provide meteorological parameters at any location at any desired time. In additional to routinely used meteorological sensors, an infrasonic sensor is also included to determine wind shear at local and regional levels. The airborne system may also be used in towns and cities to track drones and UAVs in the area. The airborne vehicle (UAV or drone) should be able to track seismic waves, magnetic storms, magneto-hydrodynamic waves, tornadoes, meteor, and lightning, etc. This technology can be use to measure environmental turbulence including wind shear, vortices as well as large and small eddies is an important factor in forecasting local and regional weather. It can also detect infrasound at ranges of many miles from the source and the shape of the acoustic power spectrum can be used to identify type of turbulence in the atmosphere.

NASA Goddard Space Flight Center now offers a new capability for meeting this Big Data challenge: MERRA Analytic Services (MERRA/AS). MERRA/AS combines the power of high-performance computing, storage-side analytics, and web APIs to dramatically improve customer access to MERRA data. It represents NASAs first effort to provide Climate Analytics-as-a-Service. Retrospective analyses (or reanalyses) such as MERRA have long been important to scientists doing climate change research. MERRA is produced by NASAs Global Modeling and Assimilation Office (GMAO), which is a component of the Earth Sciences Division in Goddards Sciences and Exploration Directorate. GMAOs research and development activities aim to maximize the impact of satellite observations in climate, weather, atmospheric, and land prediction using global models and data assimilation. These products are becoming increasingly important to application areas beyond traditional climate science. MERRA/AS provides a new cloud-based approach to storing and accessing the MERRA dataset. By combining high-performance computing, MapReduce analytics, and NASAs Climate Data Services API (CDS API), MERRA/AS moves much of the work traditionally done on the client side to the server side, close to the data and close to large compute power. This reduces the need for large data transfers and provides a platform to support complex server-side data analysesit enables Climate Analytics-as-a-Service. MERRA/AS currently implements a set of commonly used operations (such as avg, min, and max) over all the MERRA variables. Of particular interest to many applications is a core collection of about two dozen MERRA land variables (such as humidity, precipitation, evaporation, and temperature). Using the RESTful services of the Climate Data Services API, it is now easy to extract basic historical climatology information about places and time spans of interest anywhere in the world. Since the CDS API is extensible, the community can participate in MERRA/ASs development by contributing new and more complex analytics to the MERRA/AS service. MERRA/AS demonstrates the power of CAaaS and advances NASAs ability to connect data, science, computational resources, and expertise to the many customers and applications it serves.

The CFIDS is a modular system, which consists of multiple types of detectors that work either together or separately to monitor different types of radiation from multiple directions at once. CFIDS measures high-energy charged particles using solid-state charged particle telescopes based on Silicon Carbide Micro-electromechanical Systems (MEMS) technology. Silicon carbide devices are more resistant to damage from the radiation in space than other candidate detector materials and exhibit steady operation over a very wide range of temperatures, and they have the same operating characteristics in bright sunlight as in shaded areas, unlike other electrical devices in space. The CFIDS also has a central scintillation detector for high energy cosmic rays, and scintillation detectors for lower energy particles that can also be used as start/stop indicators for data collection. These characteristics allow the CFIDS to provide accurate information in a wide variety of circumstances for longer periods of time. The CFIDS detector system, or one or more of its components can be positioned on satellites, landers, rovers, or planetary base structures to monitor the local space weather environment and report conditions to a network that can prepare systems and people for changes in space weather. The CFIDS is an integrated package comprised of a central spherical Cherenkov detector surrounded by compact detector stacks. The Spherical Geometry: LEW-18362-1 of the integrated system resembles the shape of a soccer ball. These stacks utilize arrays of Compact Large Area Charged Particle Telescopes: LEW-20486-1 made from silicon carbide (SiC) and engineered to be extremely compact, with prototypes measuring less than four centimeters wide. A key innovation is the replacement of conventional, fragile glass photomultiplier tubes (PMTs) with a patented solid-state, Low-power Charged Particle Detector: LEW-19171-1 allowing for operating in harsh and low-power environments. This is achieved using a Fast, Large-area, Wide-Bandgap (WBG) UV photodetector: LEW-19040-1. This photodetector is fabricated on a commercially available, single-crystal zinc oxide (ZnO) substrate and can detect the full range of UV light in two nanoseconds or less. By carefully matching the light emitted from the scintillator with the sensitivity of the UV-sensitive photodiode, the system eliminates the need for both high-voltage PMTs and efficiency-reducing wave shifters. This solid-state design makes the entire system smaller, lighter, and more power-efficient, allowing it to be integrated into platforms with significant size and power constraints, such as CubeSats.

Langley has developed various technologies to enable the portable detection system, including: - 3-inch electret condenser microphone - unprecedented sensitivity of -45 dB/Hz - compact nonporous windscreen - suitable for replacing spatially demanding soaker hoses in current use - infrasonic calibrator for field use - piston phone with a test signal of 110 dB at 14Hz. - laboratory calibration apparatus - to very low frequencies - vacuum isolation vessel - sufficiently anechoic to permit measurement of background noise in microphones at frequencies down to a few Hz - mobile source for reference - a Helmholtz resonator that provides pure tone at 19 Hz The NASA system uses a three-element array in the field to locate sources of infrasound and their direction. This information has been correlated with PIREPs available in real time via the Internet, with 10 examples of good correlation.