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GOES-R Data Distribution

GOES-R Data Distribution. Timothy J. Schmit NOAA/NESDIS – Office of Research and Applications (ORA) Advanced Satellite Products Team (ASPT), Madison, WI James Gurka and Roger Heymann (NOAA/NESDIS/OSD) and the whole GRB working group, etc. Introduction GOES Re-Broadcast (GRB)

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GOES-R Data Distribution

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  1. GOES-R Data Distribution Timothy J. Schmit NOAA/NESDIS – Office of Research and Applications (ORA) Advanced Satellite Products Team (ASPT), Madison, WI James Gurka and Roger Heymann (NOAA/NESDIS/OSD) and the whole GRB working group, etc Introduction GOES Re-Broadcast (GRB) Data compression Other options Summary May 2004 GOES User Conference

  2. What we know • Data distribution is very important • There are a large number of current GVAR reception sites, more sites are being added • These are a combination of fixed and mobile sites. • There is a wide range of current users needs • GOES-R instrument data rates increase by approximately two orders of magnitude over current instruments • Data compression can help to reduce data rates (and hence distribute more data) while preserving information

  3. What we think we know • Data (raw) downlink most likely will be in the X-band • Data re-broadcast will most likely be in the L-band • GOES Re-Broadcast (GRB) format will be different than todays GVAR • There will be some form of satellite re-broadcast • A tunable range of data compression options, depending on data, is ideal. • Data compression techniques will continue to improve

  4. What we do not know • Data formats • Data rate of re-broadcast data • Contents of re-broadcast data • Type or Amount of data compression • Relationship between amount of data “pushed” versus “pulled” • Etc.

  5. GOES Re-Broadcast (GRB) • Working Group (WG)assembled to examine the nature of GOES-R high rate data to be distributed • Led by James Gurka (OSD) & Tim Schmit (ORA) • Includes senior scientists, senior engineers, and policy officials

  6. While no final decisions have been made, several data distribution options are being investigated for the GOES-R era. • Various amounts of bandwidth rebroadcast via GOES • Various amounts of data rebroadcast via other than GOES (commercial) • Other methods (Internet, push/pull etc) • Combination, etc.

  7. Future GOES Rebroadcast • GRB system is extension of current GVAR system for GOES-R era • Serve users in Near RealTime throughout western hemisphere • Current GVAR mainly only rebroadcasts radiance data; GRB may/could rebroadcast both radiances and some products • GRB system is payload service, separate from any direct service (LRIT, DCPI/R, EMWIN, and SAR) • GRB is needed to make a large amount of data available to a wide range of users (both geographically and in terms of data use) in a cost efficient manner • Main difference between GVAR and GRB: • Due to new, largedata rates for the instruments currently planned for GOES-R, the GRB system will not realistically be able to transmit all level 1b data without data compression

  8. Satellite Satellite “Archive” 2:1 10+:1 Users • Data compression can have applications in a number of areas: • downlink –rebroadcast - distribution - archive Possible GOES ReBroadcast System “Downlink” 2:1? “Re-broadcast” 6:1? Wallops CDAS/ Backup Any GRB site “Data Pool” “Data pool” of full GOES (the compete level 1b data) would not be compressed, nor rebroadcast. Full GOES would be available for ground-based transfers and archive.

  9. General GRB Assumptions • User needs • All users and applications not known • Forecasting all future users and applications uncertain • If the data is available, user will work to gain access to it • Users (DoD, WMO nations, academia, etc) will expect a similar (or higher) level of service • Communications capabilities will continue to evolve – bringing improved capability, technologies, and lower cost • Future data compression techniques will continue to improve (both lossless and lossy) • Send out as much information (as opposed to just data) to as many users as possible while balancing cost of dissemination with the goal of maximizing the usefulness of the information

  10. How might we move from 100 to 24 Mbps for a rebroadcast? • Data compression is the key • Maintain a "data pool" concept for land access and archive of • uncompressed sensor data • Users could then "test what is not being sent“ for their own application(s) • One method going from ~100 Mbps to 24 Mbps: • 10X for the 0.5 km visible band • 6X for the "1km” bands • 2X for the IR bands of the ABI • 6X for the HES-IR • Means approximately half of the band width would be used by the imager and half by the sounder; each image could be sent out

  11. 0.5 km visible data dominates the data rate of ABI Total (uncompressed) 43.5 Mbps Assuming 13-bit data and a 5-minute full disk scan mode

  12. 10:1 6:1 2:1 IR dominates the data rate of ABI after compression Total (uncompressed) 43.5 Mbps Total (compressed) 10.4 Mbps

  13. MODIS 0.64 μm (0.5 km on ABI) Original Compression Ratio ~9:1

  14. MODIS 0.86 μm (1.0 km on ABI) Original Compression Ratio ~6:1

  15. Simulation study shows that reconstructed brightness temperature is nearly noise-free AIRS instrument noise Reconstructed minus noise-free Poster…Goldberg

  16. Lossless CompressionComparison of Methodologies Without pre-processing, JPEG-LS gives the best compression ratio Poster…B. Huang

  17. Poster…B. Huang Very Fast Lossy Compression JPEG-LS RMS error A compression ratio of 5 is less than the instrument noise. A pre-processing step (right side graph) improves the performance.

  18. NOAA NESDIS has investigated Alternative Dissemination Methods (ADM) for distribution of weather/environmental data by means of Internet, Commercial Space Communications, or Dedicated Landline. The ADM methods of communication are separate from communication methods utilized in Direct Readout (DR), which is a broadcast from government satellites. From Marlin Perkins

  19. A Broad Agency Announcement (BAA) for future geostationary satellite architecture study is currently under-way. Task Area 3: Production Generation and Distribution, Archive and Access, and User Interface Segments http://www.osd.noaa.gov/goesr_arch_study/index.htm

  20. Breakout Session Quesiton • Question for each group during the break-out session on Thursday: “Please discuss your needs for [realtime] data and product distribution, archiving and access. For example, timeliness, registration, etc. ”

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