1. An introduction to McIDAS – the Man-computer Interactive Data Access System (as part of the 19 th Annual CIMSS High School Workshop on Atmospheric and Earth Sciences – 27 Jun 2011) 10:45 AM - McIDAS overview (Gary); McIDAS-V training (Jay) 01:30 PM - McIDAS hands-on development of mini-project (with mentors: Bob, Dave, Joleen, Kaba, and Will) 03:20 PM - student presentations of our mini-projects (all)

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.  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 McIDAS-X  VisAD + IDV + HYDRA = McIDAS-V What Is McIDAS-V?

6. Uses an Extensible Framework - Built on top an extensible framework for adapting new sources of data (format and type, local or remote), 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 Java-based, open-source, and freely available

7. On 6 December 1966, the Applications Technology Satellite (ATS-1) was launched. We have had the benefit of the geostationary perspective for over 40 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.

8. Verner E. Suomi and Robert J. Parent

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

10. Professor Suomi and McIDAS (Man computer Interactive Data Access System) 1972 – “McIDAS”2011 – “McIDAS-V” Including VIS-AD and HYDRA an

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

12. 1968 WINDCO generates wind vectors from ATS images 1972 First Generation of McIDAS Runs on Harris /5 with 96 KB of programmable memory and 2-5 MB hard drives 1976 GOES ingest system added to McIDAS 1979 Wichita Falls, TX tornado disaster: Congress directs operational McIDAS system to be installed at the NOAA National Severe Storms Forecast Center 1983 People ’ s Republic of China funds port of McIDAS software to IBM mainframe 1985 McIDAS runs on PCs under DOS operating system 1987 McIDAS runs on PCs under OS/2 operating system and McIDAS Users ’ Group is formed 1991 McIDAS runs on UNIX workstations 1994 Satellite and conventional data is served from UNIX workstations, beginning the use of ADDE (Abstract Data Distribution Environment) 1997 McIDAS Users ’ Group sunsets support for mainframe McIDAS History of McIDAS 1970198019902000

13. 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

14. IBM Mainframe History of McIDAS Mainframe Communication

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

16. CIMSS Cloud Top Pressure

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

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

19. 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. Advanced Display Capability

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

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

23. 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]

24. “Sift and Winnow” – a Wisconsin idea