Techology Maturation Program: List of 2018 Projects

 

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Project Name: 3D Winds with track and European Space Agency (ESA) Aeolus

Project ID: TMP 18-01

Project Partners: NOAA/AOML - Atlantic Oceanographic & Meteorological Laboratory

Description: Knowing the wind speed and direction is critical for weather forecasting. The challenge is not just at the ground level, but throughout the whole atmosphere, at all altitudes worldwide. NOAA has a lot of wind measurements on the ground. Upper air wind speed can be inferred from satellites watching cloud motion. Now we have a new capability, the ADM/Aeolus satellite, capable of measuring clear air wind speed worldwide. This effort will help NOAA learn how to get the maximum possible value from this data.

2018 Accomplishments: The team was able to complete development of a basic assimilation algorithm in a collaborative effort with STAR. In this effort, the team was able to incorporate AEOLUS Level-2B HLOS wind product in the Finite Volume Cubed-Sphere, Global Forecast System (FV3GFS) with a focus on Hurricane prediction. This effort has also fostered continued coordination between NOAA, ESA, and NASA with planned NOAA/NASA activities, and the Aeolus Calibration/Validation and Science Workshop in March of 2019.

Project Name: Project Management

Project ID: TMP 18-02

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: This is a special task focused on tracking all other TMP activities and ensuring timely and accurate submission of required reports, etc.

Project Name: Accelerate Data Assimilation

Project ID: TMP 18-03

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Most of NOAA’s big new satellites need over ten years to develop. This gives scientists a lot of time to plan for the new data and a lot of time for the National Weather Service to get ready. Since new satellites would be in service for well over ten years, this model worked for NOAA. Today, as technology enables smaller, faster and lower cost satellites, the satellites are designed to be frequently upgraded. A single satellite won’t replace a large one, but a group of satellites may be a superior solution. With many small and rapidly improving satellites, there is less time to get ready for new data. Also, commercial, international and NASA satellites are being launched frequently, some of which are useful to NOAA. If NOAA is to use these data, a much faster adoption process is required. This effort will streamline the NOAA process of adopting new satellite data.

2018 Accomplishments: The team developed quick and agile methodologies to entrain small-satellites that have limited lifetimes into the NOAA processing stream; the team developed workflows and a framework that will allow NOAA to work with partners to ingest, calibrate, validate, and exploit multi-sensor (MW, IR, and RO) data from multiple small satellites in a minimum amount of time. The team further developed approaches to incorporate the enterprise system of tools and algorithms into an Integrated Calibration Validation System (ICVS) for small satellites which further allows NOAA to better exploit upcoming constellations of small satellites, as well as help NOAA assess the full utility of smallsat constellations being considered by the NOAA Satellite Observing System Architecture (NSOSA) study team.

Project Name: Radio Occultation (RO) Data Optimization

Project ID: TMP 18-04

Project Partners: NOAA/AOML - Atlantic Oceanographic & Meteorological Laboratory

Description: One of the newest types of observation obtained by satellites is called Radio Occultation (RO), a technique of observing how radio waves from GPS satellites behave as they go through Earth’s atmosphere. NOAA has found RO data to be very useful, but our understanding of the potential is still limited. This effort will explore novel approaches to use this very important data, to derive even greater value from the data. Specifically, the question of how to get useful RO data in the very lowest layers in the atmosphere, an area previously found to be too difficult to process. If successful, NOAA and our partners will be able to derive significantly more value from these existing and planned systems.

2018 Accomplishments: The team developed and implemented codes that enabled the assimilation of lower-level Radio Occultation (RO) observations. The code reproduces results using operational configuration under similar quality control by discarding observations affected by atmospheric conditions where radar beams bend more than they would in Standard Atmospheric conditions [super-refraction].

Project Name: Enable Short-wavelength infrared (SW-IR) and Medium-Wavelength infrared (MW-IR) data use

Project ID: TMP 18-05

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Satellite-based Infrared (IR) data is very important for weather forecasting. It is one of the most valuable observations. IR data is split into three regions, shortwave (SW), midwave (MW) and longwave (LW). The LW is used for most weather forecasting, as it is the easiest to process. But, it is the most expensive and difficult to obtain. Now, scientists think they can adequately process the SW and MW data to provide forecast benefits like the LW data. The data processing will be somewhat harder, but the cost and complexity of the satellite for SW and MW will be much simpler and less expensive. If this works, cubesat-based SW and MW IR data can replace existing very large, expensive and complicated satellite instruments.

2018 Accomplishments: The NOAA Finite Volume Cubed-Sphere, Global Forecast System (FV3GFS) was modified to allow for assimilation of CrIS Short-Wave Infrared (SWIR) data. This modification improved forward operation, quality control, and implemented scene dependent errors. Via Observing System Experiments, the team was able to demonstrate that SWIR data attains similar impact on FV3GFS forecast skill.

Project Name: Low Latency Impact Assessment Observing System Simulation Experiment (OSSE)

Project ID: TMP 18-06

Project Partners: NOAA/AOML Atlantic Oceanographic & Meteorological Laboratory
NOAA/STAR - Center for Satellite Applications and Research
Cooperative Institute for Mesoscale Meteorological Studies (CIMSS)

Description: Today, we can share data around the world in seconds, viewing web pages, watching videos, and enjoying phone chats from very remote areas of the world. Yet for satellites, most data delivery is really slow, like maybe an hour or more. When we have to wait for the satellite to reach a ground station, vital weather data is getting older and older. Now that companies are planning to put the internet into satellites, it opens the enticing possibility of using their internet service to deliver data quickly and inexpensively. This study will consider the importance of fast data delivery on NOAA’s services. The more important fast data is, the quicker NOAA might want to prioritize fast delivery of satellite data. This study looks at the importance, while other studies can determine the best options.

2018 Accomplishments: The team studied the impact of weather satellite data latency on the forecast of high resolution Local Severe Storms (LSS) in regional National Weather Prediction (NWP) models. The team also quantified the impact of satellite data latency on global weather forecasting, including hurricane prediction.

Project Name: Assessing Time-Resolved Observations of Precipitation (TROPICS) value to Numerical Weather Prediction (NWP)

Project ID: TMP 18-07

Project Partners: NOAA/AOML Atlantic Oceanographic & Meteorological Laboratory
NOAA/STAR - Center for Satellite Applications and Research

Description: NASA’s new research satellite mission, the Time-Resolved Observations of Precipitation structure and Intensity with a Constellation of Smallsats (TROPICS), has a research goal of improving our understanding of hurricane formation. TROPICS is a constellation of twelve cubesats, each collecting some data very similar to NOAA’s big JPSS satellite. With twelve satellites, this offers NOAA the ability to study whether twelve additional satellites can improve the weather forecast. We may learn Yes, No, or that the weather model does not know how to effectively use this much data. Whatever the answer, this work will help NOAA intelligently plan for the future.

2018 Accomplishments: The team calibrated the global Observing System Simulation Experiment (OSSE) system with FV3GFS and GEOS-5 Nature Run (G5NR). From there, the team added the capability to simulate perfect clear-sky-radiance observations for Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS). Afterwards, the team completed the initial validation of the simulated radiances against two similar operational sensors, Advanced Technology Microwave Sounder (ATMS) and Microwave Humidity Sounder (MHS).

Project Name: Evaluation of CubeSat Solutions to Nocturnal Low-Light Visible Observations

Project ID: TMP 18-08

Project Partners: CSU/CIRA - Colorado State University/Cooperative Institute for Research in the Atmosphere
Aerospace Corporation, Inc.

Description: You may have seen the cool satellite photos of nighttime lights, showing cities around the world lit up at night. NOAA has learned that these photos are more than interesting, they are very important, especially for Alaska’s long nights. NOAA can monitor cloud motion from these at-night pictures and learn a lot about coming weather. But, that discovery was a surprise. We are only beginning to understand how to use this data. Plus, today, the data is limited. NOAA wants to learn more ways to use this data and learn whether additional observations can be taken from cubesats. This will help NOAA do optimal planning for our future satellites.

2018 Accomplishments: The team was able to take inventory of Low-light Visible Use in the Research and Operational Communities. The team completed comparisons of Day/Night Band (DNB) versus the CubeSat Multispectral observing System (CUMULOS) and Near-Infrared Airglow Camera (NIRAC)/Interaction with Aerospace. Additionally, an orbital analysis was completed.

Project Name: Exploit Tropospheric Monitoring Instrument (TROPOMI) sensor

Project ID: TMP 18-09

Project Partners: NOAA/STAR - Center for Satellite Applications and Research
Cooperative Institute for Mesoscale Meteorological Studies (CIMSS)

Description: NOAA is very lucky to have great European partners. For many years, we have shared our satellite data, recognizing that it is not feasible for anyone to do everything. So, the Europeans launched a new satellite in 2017, the TROPOspheric Monitoring Instrument (TROPOMI), that collects a lot of information about Earth’s atmosphere. TROPOMI monitors a lot of the trace gases in the atmosphere, like Ozone and Methane. NOAA needs this data too. Thanks to the Europeans, the data is free. This effort will work to determine how to best access and use this free data to benefit the United States.

2018 Accomplishments: The team was able to implement an assimilation system that integrated TROPOSpheric Monitoring Instrument (TropOMI) Nitrogen Dioxide (NO2) with Carbon Monoxide (CO). The team also completed TropOMI NOx emission adjustment impact studies.

Project Name: Exploit Near Space Data [Explore Near-Space Observations (Project Loon data - balloon-based internet provider)]

Project ID: TMP 18-10

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Several companies are exploring the potential for stratospheric balloons, to provide internet service. They may also provide a good platform to observe the Earth. These balloons stay up for months at an altitude of about 60,000 feet (above regular airline routes). An advantage of the balloons is their ability to land, so that instruments can be recovered, repaired and relaunched. This study will seek good opportunities for NOAA to partner with these companies for instrument hosting or other services (maybe data relay). An alternative is the satellite internet constellations, flying about 250 miles high. But, these systems burn up on reentry, so there is no recovery.

2018 Accomplishments: The team was able to acquire 2 years of data from a network of balloons travelling on the edge of space. This acquisition allowed the team to evaluate passive Infrared data, wind observations, and temperature observations. After converting the data to a binary format called BUFR (Binary Universal Form for the Representation of meteorological data), the team was able to optimize their respective data assimilation system, and complete experiments and impact studies.

Project Name: Hosted Payloads Study

Project ID: TMP 18-11

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Some of NOAA’s satellite instruments are big and heavy. These instruments are placed into geostationary orbit, over 22,000 miles high. For these instruments to see any detail on the Earth, they require large and heavy telescopes. So far, there is no way to make these systems small and light. One alternative to NOAA building satellites, is to rent space on somebody else's satellite. There are lots of big communications satellites in geostationary orbit with plenty of power. But, NOAA needs a prime spot to observe the Earth and the satellite cannot interfere with NOAA’s instrument. What seems to be easy has proven to be very hard. This study will take another look.

2018 Accomplishments: The team was able to complete near-space assessment, near-space observations simulations, space based surveys, and near-space Observing System Experiments.

Project Name: Artificial Intelligence (AI) and Machine Learning

Project ID: TMP 18-12

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Artificial intelligence (AI) is doing amazing feats today, including challenging doctors to make the right diagnosis. If AI can do medicine, maybe it can help with the weather. NOAA has wonderful highly skilled forecasters and some of the best weather prediction models in the world. But, it seems to be the right time to leverage the power of today’s machines to spot patterns quickly and draw connections that might elude human experts. If machines can issues alerts, a human expert can review the facts, potentially saving lives from faster and better watches and warnings.

2018 Accomplishments: The team was able to develop, validate, and implement Artificial Intelligence (AI) -based algorithms and approaches for Infrared (IR) and Mid-wave (MW) sensor exploitation, bias correction, and product generation. It is important to note that the performance of the combined IR/MW algorithm matched or exceeded the performance of traditional algorithms when compared to the European Center for Medium-Range Weather Forecasts (ECMWF) and NOAA Unique Combined Atmospheric Processing System (NUCAPS). The team was also able to modify and implement changes to software and script required for the AI-based operation. More specifically, an AI developed for the Multi-Instrument Inversion and Data Assimilation Pre-Processing System is ready for operation, and the team plans to work with the University of Washington to implement it into the Community Satellite Processing Package (CSPP).

Project Name: Technology Survey

Project ID: TMP 18-13

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: The innovation enterprise in the USA and around the world produces incredible innovations. While NOAA technologists work hard to keep touch on the latest innovations from NASA, there is always a risk of missing something important. Occasionally, we learn of exciting work years after the work has started. This survey is intended to be more methodical, and look in places that NOAA technologists may have missed. If one discovery can keep us from repeating some work that is already underway, the costs of this survey will be quickly recovered.

2018 Accomplishments: The team conducted a survey to identify emerging sensor system technologies that might have been overlooked or not sufficiently emphasized. The team’s analyses revealed a small number of emerging technologies (or a ‘handful of nuggets’) which were recommended to receive immediate or near-term NESDIS investment consideration in order to not find itself behind on the power curve if these technologies emerge rapidly.The team further recommended NESDIS consider involvement and investment ‘now’ in these handful of ‘nugget’ technologies, and to continue monitoring for evolving, emerging developments in the Research Technology Maturation for the Exploitation of Emerging Technology (RTMEE) Watchlist and Nugget Technologies.

Project Name: Weather Forecasting in Virtual Reality

Project ID: TMP 18-14

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Weather happens in four dimensions, up-down, right-left, front-back and time. Old (current) tools mostly show two dimensions, like a photograph compared to a one camera movie. If only, we could allow the forecaster to “live” in the weather, using a computer to “fly around” above, below and through weather as it evolves, it might provide unprecedented insights. Like a movie that keeps switching to where the action is best. Tremendous advanced have been made with in practical applications for immersive visualization. Now is the time to see if it can benefit weather forecasters. The primary benefits are likely to be in short term forecasting for severe weather, like tornadoes. This research will find out if virtual reality is useful to forecasters.

2018 Accomplishments: The team developed a versatile Virtual Reality (VR) program to ingest and display various Earth science/satellite datasets. The new VR system allows users to view data in its native 3D format. The team also implemented tools that provide both qualitative and quantitative analysis. The team will continue working to understand the spatial and temporal resolution needed from satellites to meet future forecaster needs and fully exploit future analysis capabilities.

Project Name: Maturing Reflectometry Usefulness to the NOAA Observing System Portfolio (Case of Cyclone Global Navigation Satellite System - CYGNSS) for Ocean Winds

Project ID: TMP 18-15

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Scientists are amazing how they discover creative ways to learn new things. The Global Positioning System (GPS) has been a real benefit in so many ways. Now, scientists have learned that reflections of GPS signals off of the Earth’s oceans and surface can provide an amazing array of new information. This information is extremely costly and difficult to get using more brute force methods. So, this study will see if this reflected data can meet NOAA’s operational needs. Initial work will focus on ocean winds and contours. Later work will explore options over the land. This work leverages the NASA science mission Cyclone Global Navigation Satellite System (CYGNSS).

2018 Accomplishments: The team completed analysis for the Cyclone Global Navigation Satellite System (CYGNSS) winds available on the Physical Oceanography Distributed Active Archive Center (PODAAC). Through this analysis, the team was able to develop and release the NOAA CYGNSS wind/wave product.

Project Name: Maturity of Reflectometry Phase Delay Altimetry

Project ID: TMP 18-16

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Scientists are amazing how they discover creative ways to learn new things. The Global Positioning System (GPS) has been a real benefit in so many ways. Now, scientists have learned that reflections of GPS signals off of the Earth’s oceans and surface can provide an amazing array of new information. This information is extremely costly and difficult to get using more brute force methods. So, this study will see if this reflected data can meet NOAA’s operational needs. Initial work will focus on ocean winds and contours. Later work will explore options over the land. This differs from project #15 by using a different space instrument.

2018 Accomplishments: The Spire team was able to implement the desired phase-delay altimetry concept on orbit using existing Radio Occultation Satellites. The results showed that nearly all sea ice reflections were coherent, and likely contained information on sea ice thickness that compliments ICESat-2 and Cryosat measurements. The team plans to continue collecting these observations and tasking more satellites to increase the number of observations and the overall coverage of the data.

Project Name: Dual-band radar satellite altimeter instrument studies for sea ice and sea state

Project ID: TMP 18-17

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: In the past, satellite-based radars have been used to observe the oceans. These systems use the Ka and Ku radio bands. These are microwave frequecies ranging from 27 to 40 gigahertz and 12 to 18 gigahertz respectively. To put that into perspective, a microwave oven uses S (short) radio bands ranging between 2 and 4 gigahertz, and, because the frequency of S bands is so small, they can only transfer energy to the things they are directed towards without passing through those objects. Both Ka and Ku bands, however, collect somewhat different information. Scientists think that using both bands together can yield a much greater amount of information about the ocean state, ice, and snow depth. This study will test this idea by using data from the two types of satellites and testing those moments where the same spot is viewed at the same time. If successful, NOAA (and our partners) can consider a satellite with these combined capabilities.

2018 Accomplishments: The team completed a literature review in which introduced the overall project and determined the scope. The team was able to develop and document a sea ice retracker algorithm by simulating and analyzing performance. The team was also able to compute crossover differences between infrared frequency band altimeters (specifically Ka & Ku) at various sea states in various regions/seasons.

Project Name: Exploiting Cubesat Ocean Color Data

Project ID: TMP 18-18

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Scientists can learn a lot about the health of the oceans by observing the water color. Very specific colors can show areas with high plankton levels, often associated with healthy fisheries. Other colors offer other insights. These sensors can take second priority to vital weather forecasting instruments. With tight budgets, weather takes priority. Now the University of North Carolina-Wilmington is launching a small cubesat designed to collect ocean color data. This system is called SeaHawk and will provide sustained ocean color observations with nanosatellites (cubesats). In this study, NOAA will examine SeaHawk data to see if it meets NOAA’s data quality needs.

2018 Accomplishments: The SeaHawk successfully launched in December 2018. The overall team was able to acquire the necessary SeaHawk sensor characteristics data to move forward with the project at large. Subsequently, the University of Georgia Team completed a presentation for the Cubesat Spectral Ocean Color (SPOC) project using the data collected. The team also built the SeaHawk ocean color data processing capability in the ship/platform named the Mikhail Lomonosov. Lastly, the team worked on in-situ data analysis for validation of the satellite ocean color product. It is important to note that the NOAA Visible Infrared Imaging Radiometer Suite (VIIRS) Calibration/Validation team successfully carried out the fifth dedicated cruise in September 2019.

Project Name: Maturing the exploitation of satellite data from Tundra–like platforms

Project ID: TMP 18-19

Project Partners: NOAA/STAR - Center for Satellite Applications and Research

Description: Most NOAA satellites are either Low Earth Orbit (LEO) or Geostationary orbits (GEO). LEO satellites are constantly moving around the Earth and cannot watch evolving weather events. GEO satellites can watch evolving weather events, but cannot look at the far North and South areas. So, Alaska and the polar regions get spotty coverage. A Tundra orbit is an egg shaped orbit, where the satellite hovers most of the day looking at the polar regions. For a brief period each day, these satellite swoop down close to Earth before zooming back up. This intriguing orbit produces data that is not stable (like GEO), making data understanding hard. This study will see how hard Tundra data will be for NOAA to use.

2018 Accomplishments: The team was able to complete development of a Tundra Orbit simulator, a navigation simulator, and radiance simulator. The team also completed development of a footprint size demonstration methodology as well as one for different regions.

Project Name: Advance Mid-wavelength Infrared (MWIR) maturity

Project ID: TMP-20

Project Partners: NASA/JPL - Jet Propulsion Laboratory

Description: In 2017, NASA JPL performed a study for an Earth Observing NanoSatellite-Infrared (EON-IR) that addressed key issues related to the design and development of a Hyperspectral IR sounder in a CubeSat (6U) configuration. The TMP 18-20 project will advance the technology readiness of the MWIR EON-IR by performing three key tasks leading to the ambient testing of an engineering model.

Described below are the three tasks required completing the opto-mechanical assembly and enabling a photons-to-bits demonstration of a fully functional MWIR EON-IR Engineering Model non-flight payload. This effort will validate the packaging approach by assembling all subsystems required in a 4U payload volume and enable tests to be performed in ambient for spectral, spatial, and radiometric response to verify atmospheric sounding performance. The tasks include: 1) build of the optics assembly, 2) build of the mechanical mounts, and 3) functional testing of the completed system in ambient. The effort builds on prior work performed at NASA and NOAA that completed the design of the optics and mounts and uses existing completed subsystems including the FPA, dewar, filters, cryocoolers, scanner, and electronics (3 boards).

2018 Accomplishments:

  1. Radiometric Model Update: An update to the radiometric model for MWIR was made to remove the background flux associated with the dewar window.
  2. Geolocation Algorithm Development: MWIR employs a very wide field of view along track, at 15.4°. This is unlike prior instruments like AIRS (1.1°) or CrIS (3.3°). The wide field of view in MWIR enables a slow scan resulting in a long dwell time. The long dwell time enables a smaller aperture for a given NEdT, and allows MWIR to fit in a 6U CubeSat. A model was developed to simulate the MWIR scan pattern. The model uses direction cosines in a raytrace that projects the slit off the mirror into the object space of the instrument. The scan and track angles are converted to locations on the Earth using projection software available in MATLAB. The model also takes into consideration the scan motion of the MWIR mirror and the orientation and motion of the satellite.
  3. Thermal Development: The thermal performance of the two coolers was measured in TVAC as a function of drive voltage to confirm power requirements to meet the needed thermal performance. Measurements were also made on the exported vibration of each operating cooler as a function of drive voltage to mitigate concerns of vibration causing an issue with the focal plane readout.
  4. Optics Demonstration: Key accomplishments in the spectrometer optics assembly for this year include completion of most spectrometer components as well as assembly and alignment tooling design and fabrication. Parts production efforts included completion of fabrication of all spectrometer hardware, including slit and grating flexure rings, spectrometer light baffles, and some housings. Additionally, diamond turning of input fold mirrors, generation of the spectrometer slit, and final polish and coating of all lenses were all completed.
  5. Mechanical Packaging Demonstration: Key accomplishments in the mechanical area largely involved accommodating removal of the Integrated Dewar Cryo-cooler Assembly. This addition improved the design by creating a more traditional flight-like mounting configuration of the detector, which allows more room to accommodate the instrument in the 4U configuration and providing more margin to stay within the 6U CubeSat constraints. Parallel work continued on the scan motor, cryo-cooler, electronics accommodation, blackbody design, and refining the spectrometer mounts by changing their location and orientation to be more kinematic.

Project Name: Advance Long-wavelength Infrared (LWIR) maturity

Project ID: TMP-21

Project Partners: NASA/JPL - Jet Propulsion Laboratory

Description: Of the three types of InfraRed (IR) satellite data, the longwave data is the most difficult to collect. The sensors need to be supercooled. So, these systems are hard. Even so, if we can get this capability into a cubesat (less than 100 lbs.), it can lead to a better solution for NOAA at lower cost. Being small, these satellites can be manufactured more quickly and launched much easier than the traditional billion dollar systems. This work is to determine if longwave IR can work in cubesats.

2018 Accomplishments: The team completed a system overview and development of a system design model. The team also developed a Long-Wavelength Infrared detector along with corresponding electronics, and optical configuration. Lastly, the team optimized the thermal design and mechanical packaging.

Project Name: Advance small microwave imager

Project ID: TMP-22

Project Partners: NASA/JPL - Jet Propulsion Laboratory

Description: Most of NOAA’s essential satellite instruments are very large, about the size of a small car. Amazing progress is being made to allow most of these instruments to be redesigned for cubesats, smaller than a microwave oven. However, one instrument does special microwave imaging and needs an antenna that is about six feet across. To make it harder, the antenna has to constantly spin around looking at different spots on the Earth. Various options will be explored to deal with the large spinning antenna. This effort is studying how to design this instrument and antenna to be about the size of a washing machine. If successful, NOAA will be able to dramatically cut the cost and weight.

2018 Accomplishments: The team was able to pin-point the baseline design for the radiometer sub-system to ensure optimal noise performance, and to simplify the receiver’s hardware. The team was able to complete prototyping of the radiometer radio frequency front-end, and a fully polarimetric digital sub-system design on a Field-Programmable Gate Array (FPGA). The team was also able to do a design study on the antenna sub-system for both low frequencies and high frequencies. Lastly, the team completed the mechanical packaging concept for the system to fit in the Evolved Expendable Launch Vehicle Secondary Payload Adapter (ESPA) volume.

Project Name: Light Detection & Ranging (LIDAR) Working Group

Project ID: TMP-23

Project Partners: NOAA/AOML - Atlantic Oceanographic & Meteorological Laboratory

Description: Wind speed and direction, at all levels in the atmosphere and all around the world are a vital piece of information needed to forecast the weather. Scientists and engineers have been working for years trying to figure out how to get this information. A technique called LIght Detection And Ranging (LIDAR) holds promise. This effort ensures that NOAA stays well connected with the international LIDAR community. This is particularly important as Europe recently launched the first wind LIDAR satellite.

2018 Accomplishments: The Light Detection and Ranging (LIDAR) Working Group provided NOAA and NASA leadership with the wind observations, weather forecasting and science communities to advance development, demonstrations and implementation of space-based wind measurements. The team also planned and carried out one working group meeting per year. Ahead of those meetings, the team identified topics, developed an agenda, invited speakers, arranged logistics, and coordinated with the NASA Co-chair. It is important to note that the team consulted with the NASA co-chair on the second, NASA-organized working group meeting. Lastly, the team traveled to, and co-chaired, two LIDAR Working Group meetings per year while maintaining a Working Group website at the University of Colorado.

Project Name: Hosted Payload Tech. Demo [NASA GOLD]

Project ID: TMP-24

Project Partners: NOAA Space Weather Prediction Center (SWPC)
Colorado State University/Cooperative Institute for Research in the Atmosphere (CSU CIRA)

Description: For years, NOAA has wanted the option of partnering with the commercial sector to “host” a NOAA instrument. Recently, NASA used a hosted payload for their Global Observations of the Limb and Disk (GOLD) mission. This mission is potentially important for NOAA’s space weather mission area. So, this effort is aimed at learning more about hosted payloads and at the same time exploring whether data from this new satellite can adequately meet needs of NOAA forecasters.

2018 Accomplishments: The NASA Global-scale Observations of the Limb and Disk (GOLD) mission was launched into orbit on January 25, 2018 as a commercially hosted payload on the SES-14 communications satellite. Working with the University of Colorado Laboratory for Atmospheric and Space Physics (LASP) and the National Weather Service’s (NWS) Space Weather Prediction Center (SWPC) in Boulder, the National Centers for Environmental Information (NCEI) Team managed the receipt of Level-2 (L2) science products. The team further analyzed the L2 science products from LASP real-time pipeline. The team worked with SWPC to assess the operational viability of these data and further reported on these findings concerning operational utility of data.

Project Name: Design Study for Day-Night Band (DNB) smallsat

Project ID: TMP-25

Project Partners: Aerospace Corporation, Inc.

Description: NOAA has a nighttime lights (Day-Night Band) capability on our large Joint Polar Satellite System, as part of the large and expensive “VIIRS” instrument. Nighttime imaging is extremely important over Alaska and other Arctic areas. NOAA’s European partners have a VIIRS-like instrument, but it lacks the nighttime lights capability. So, this is an effort to prove that NOAA can get the needed nighttime light imaging from a low-cost cubesat. Cubesats have already done amazing nighttime imaging, so this effort is only to improve performance to meet NOAA needs.

2018 Accomplishments: The team defined a set of requirements for the SmallSat instrument, performed technical trades, and completed a preliminary sensor design alongside a space segment concept design.

Project Name: Solar Sail

Project ID: TMP-26

Project Partners: Dynamic Concepts, Inc (DCI), Huntsville, AL

Description: NOAA has an operational Space Weather Prediction Center (SWPC) responsible for advising airlines, power companies and others of anticipated solar events with a likelihood of impacting operations on the Earth. For this service, solar observations are taken from a location about 1 million miles from Earth. Stationkeeping (maintaining the right spot) can take a lot of fuel, but a solar sail can “sail” in the solar wind and dramatically cut fuel use. This study is assessing how that might work for NOAA’s future sun-watching spacecraft.

2018 Accomplishments: The team completed an initial roadmap illustrating the results of recent solar sail flight demos; the team further assessed NOAA’s Solar Sail Requirements Against Near-Term Solar Sail Technology Readiness Levels (TRLs). The Initial Roadmap indicated that recent solar sail flight demonstrations showed sufficient characteristic acceleration to maintain an orbit of 4 degrees solar exclusion zone for communication to GOES from Lagrange-1* (L1). The team then updated the roadmap to include planned (2024) solar sail demonstration mission results would illustrate that increased acceleration would also allow stationkeeping at (.986 AU**) vice (.99 AU) which analysis results indicate a 40% increase in geomagnetic warning time.

*Note: Lagrange Points are positions in space where the gravitational forces of a two body system like the Sun and the Earth produce enhanced regions of attraction and repulsion. These can be used by spacecraft to reduce fuel consumption needed to remain in position. (Cornish, 2019).

**Note: AU stands for ‘Astronomical Units’. 1 AU = the physical distance between the Earth and the Sun (about 9.296*10^7 miles or 1.496*10^8 kilometers). (“Cool Cosmos”)



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