1 / 27

An introduction to McIDAS – the M an- c omputer I nteractive D ata A ccess S ystem

This session provides an overview of McIDAS, a powerful data analysis and 3-D visualization tool. Learn about McIDAS-V, the fifth generation of McIDAS, and its features such as data integration, reprojection, and remote and local data access. Explore its extensible framework, Java programming language, and user-defined computation capabilities.

rpang
Download Presentation

An introduction to McIDAS – the M an- c omputer I nteractive D ata A ccess S ystem

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. An introduction to McIDAS– the Man-computer Interactive Data Access System (as part of the 20th Annual CIMSS Summer Workshop on Atmospheric and Earth Sciences – 25 June 2012) 10:45 AM – 12:45 PM - McIDAS overview (Gary); McIDAS-V training (Jay) <lunch, weather briefing> 02:00 PM – 04:15 PM - McIDAS hands-on development of mini-projects, concluding with student presentations of such. (with mentors: Rick, Joleen, Kaba, and Will)

  2. Who We Are SSEC (Space Science and Engineering Center) is part of the Graduate School of the University of Wisconsin-Madison (UW). SSEC hosts CIMSS (Cooperative Institute for Meteorological Satellite Studies), including a NOAA/NESDIS (National Oceanic and Atmospheric Administration /National Environmental Satellite, Data, and Information Service) research branch – ASPB (Advanced Satellite Products Branch).

  3. Who We Are – SSEC • Scientists - examining the Earth from satellites to gain insight into weather and climate • Modelers - developing diagnostic and forecast models to explain the weather and climate • Engineers - developing new observing tools for spacecraft, aircraft, and ground-based platforms • Data Center – real-time satellite imagery from 16 satellites and managing online archive of 1 Petabyte (back to 1978) • Software developers - creating tools to visualize and manipulate data for use by researchers and operational meteorologists

  4. What Is McIDAS-V? McIDAS – Man computer Interactive Data Access System • Powerful data analysis and 3-D visualization tool • McIDAS-V is the fifth generation of McIDAS • “V” stands for 5 (the Roman Numeral V) • The first generation of McIDAS began in 1972 Storm cloud temperatures, showing overshooting tops in 2-D from above Satellite composite image overlaid with GFS relative humidity contour cross-section Same overshooting tops, rotated to view from the side

  5. What Is McIDAS-V? McIDAS-X  VisAD + IDV + HYDRA =McIDAS-V • Viewing data, developing algorithms, validating results • Integration of geophysical data • Ease of reprojection • Remote and local data access • Includes a “bridge” to McIDAS-X, allowing –X users to continue using legacy code, but to visualize in McIDAS-V

  6. What Is McIDAS-V? • Uses an extensible framework - Built a framework on top for adapting new sources of data (format and type; local or remote), for updating user interface components, and for creating novel displays and analysis techniques • Developed in the Java programming language – object oriented; write once - run anywhere (very portable) • Persistence mechanism (bundles) for saving and sharing interesting displays/analysis with other McIDAS-V users • Python based user defined computation for scripting • Java-based, open-source, and freely available

  7. McIDAS Users Group (MUG) members June 2012 • 3TIER Group – Seattle, WA • Agencia Estatal de Meteorologia (AEMET) – Madrid, Spain • Antarctic Meteorological Research Center – Madison, WI • Australian Bureau of Meteorology – Melbourne, Australia • Aviation Weather Center - Kansas City, MO [NOAA] • The Boeing Company – Seattle, WA • Comision Nacional de Actividades Espaciales (CONAE) – Buenos Aires, Argentina • Comprehensive Large Array-Data Stewardship System (CLASS) – Asheville, NC [NOAA] • Energia Logistics Ltd. – Long Beach, CA • Environment Canada – Downsview, Ontario • Environmental Satellite Processing Center – Suitland, MD [NOAA] • European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) – Darmstadt, Germany • Harris Corporation – Melbourne , FL • Honeywell Aerospace Electronic Systems – Redmond, WA • Hong Kong Observatory – Kowloon, Hong Kong • ImpactWeather, Inc. – Houston, TX • ITOCHU Techno-Solutions Corporation – Tokyo, Japan • Johnson Space Center Spaceflight Meteorology Group – Houston, TX • Kwajalein Atoll - Atmospheric Technology Services Company – Kwajalein Atoll • Masdar Institute of Science and Technology – Abu Dhabi, UAE • Mexico National Water Commission – Mexico D.F., Mexico • NASA Langley Research Center – Hampton, VA • NASA Marshall Space Flight Center – Huntsville, AL • National Hurricane Center – Miami, FL [NOAA] • National Transportation Safety Board – Washington, DC • National Weather Service Pacific Region Headquarters – Honolulu, HI [NOAA] • National Weather Service Western Region Headquarters – Salt Lake City, UT [NOAA] • Northrop Grumman Information Systems – McLean, VA • Range Weather Operations, Cape Canaveral Air Station – Patrick Air Force Base, FL • Regional and Mesoscale Meteorology, Cooperative Institute for Research in the Atmosphere – Fort Collins, CO [NOAA] • Storm Prediction Center – Norman, OK [NOAA] • Telvent DTN – Burnsville, MN • Unidata Program Center – Boulder, CO • University of Wisconsin - Madison, Space Science & Engineering Center – Madison, WI • VisionTech, Inc. – Ibaraki, Japan • Weather Central, LP – Madison, WI • Weather Decision Technologies, Inc. – Norman, OK • Weathernews America, Inc. – Norman, OK • WTVT Fox 13 Weather – Tampa, FL

  8. On 6 December 1966, the Applications Technology Satellite (ATS-1) was launched. We have had the benefit of the geostationary perspective for over 45 years! ATS-1's spin scan camera (UW’s Suomi and Parent 1968) provided full disk visible images of the earth and its cloud cover every 20 minutes. The spin scan camera on ATS-1 occurred because of extraordinary efforts by Verner Suomi and Homer Newell, when the satellite was already well into its fabrication.

  9. Verner E. Suomi and Robert J. Parent

  10. ATS-3 1967-Nov-18 15:03Z

  11. Professor Suomi and McIDAS (Man computer Interactive Data Access System) an 1972 – “McIDAS” 2012 – “McIDAS-V” Including VIS-AD and HYDRA

  12. Water vapor tracked “winds” from Meteosat during FGGE (the First Global Atmospheric Research Program (GARP) Global Experiment) (15 Nov 1979)

  13. 1968 WINDCO generates wind vectors from ATS images History of McIDAS 1972 First Generation of McIDAS Runs on Harris /5 with 96 KB of programmable memory and 2-5 MB hard drives 1991 McIDAS runs on UNIX workstations 1997 McIDAS Users’ Group sunsets support for mainframe McIDAS 1983 People’s Republic of China funds port of McIDAS software to IBM mainframe 1970 1980 1990 2000 1976 GOES ingest system added to McIDAS 1994 Satellite and conventional data is served from UNIX workstations, beginning the use of ADDE (Abstract Data Distribution Environment) 1985 McIDAS runs on PCs under DOS operating system 1979 Wichita Falls, TX tornado disaster: Congress directs operational McIDAS system to be installed at the NOAA National Severe Storms Forecast Center 1987 McIDAS runs on PCs under OS/2 operating system and McIDAS Users’ Group is formed

  14. IBM Mainframe History of McIDASMainframe Communication

  15. NOAAPORT Signal Servers Clients History of McIDASADDE Client-Server Communication(Abstract Data Distribution Environment)

  16. History of McIDAS-V • 2006 - Investigations of a “new approach” to data analysis and visualization • 2007 – Collaboration with Unidata to advance VisAD and IDV as the basis of McIDAS-V • 2008 – McIDAS-V becomes an “alpha” • 2009 – January – beta 1 • 2010 – January – beta 5 • 2010 – September – V1.0 • 2012 – May – V1.2 (scripting capability demonstrated and promoted)

  17. MODIS data - define a transect to display radiance measurements Convection case study:19 June 2007

  18. NOAA-18 - AVHRR/3 - HIRS/4 - AMSU - MHS 14:00 DMSP F-18 - SSM/IS 08:00 DMSP F-17 - SSM/IS 05:30 NOAA-19 - AVHRR/3 - HIRS/4 - AMSU - MHS 14:00 NOAA-17 - AVHRR/3 - HIRS/3 - AMSU 09:30 • METOP-A • - AVHRR/3 • HIRS/4 • IASI • - AMSU • - MHS • 09:30 Meteorological Satellites and Instruments (2012) GOES-15 - Imager - Sounder 135 W GOES-13 - Imager - Sounder 75 W Meteosat-8 MSG-2 - SEVIRI 10 E GOES-12 - Imager - Sounder 60 W Meteosat-7 MSG-1 - MVIRI 57 E MTSAT-2 Imager 145 E ~ 36,000 km • SuomiNPP • - VIIRS • CrIS • ATMS • 13:30 ~ 850 km • Aqua • - MODIS • AIRS • 13:30 Terra - MODIS 10:30 AM PM [sats-o-day-gsw-20120621.ppt]

  19. CIMSS Cloud Top Pressure

  20. Thunderstorm features: over-shooting top and enhanced-V (thermal couplet) Setvak:http://www.convection-wg.org/sandwich.php Brunner et al.:http://cimss.ssec.wisc.edu/snaap/enhanced-v

  21. Advanced Display Capability AIRS Level 1B window channel image (grey-scale) and moveable 2-D slice of ECMWF-AIRS Single FOV water-vapor retrieval (color-scale). Slice values are re-sampled on the fly from the 3-D difference field and auto-updated as the slice is dragged in space - demonstrating interactive direct manipulation, data integration, and python driven data computation.

  22. Bringing observations of clouds together:MODIS (passive) and CALIPSO (active)

  23. Under development: interrogation of vertical structure of surrounding reference winds model analysis and/or in-situ obs at location of flagged AMV derived wind. AMV derived wind color scaled by wind speed ; GFS gridded wind field in magenta

  24. Fundamental CIMSS research: striving to make quality real-time GOES Sounder radiance observations into practical useful information for weather forecasting Atmospheric continuity and evolution are clearly evident in multi-spectral animation. Where will clouds be? Comparison between observed imagery (bottom) and forecast imagery (top) builds confidence in how well the CRAS model is assimilating retrieved GOES Sounder cloud and moisture information. Where will forecast (GFS) moisture need to be modified, monitoring trends, to provide a better forecast for convection (as across Texas)? Differences between retrieved GOES Sounder TPW and the GFS forecast values are plotted over the GOES TPW Derived Product Imagery (DPI). [1800 UT 2 Apr 2004]

  25. Atmospheric soundings from geostationary orbit Below is total precipitable water (TPW) derived from the Sounder on GOES-13 at 12 UTC on 21 Jun 2012. As a cold front moves across GrtLks and Cen Plns, dry air fills in across N Plns as moist air (previously advected from the Gulf of Mexico region) remains over most of rest of E US. Smooth GOES retrievals (profiles) are similar to near-by radiosonde profiles. [ http://cimss.ssec.wisc.edu/goes/realtime/eus/begin-eus.html]

  26. “Sift and Winnow” – a Wisconsin idea

More Related