Data Analysis Services Group - June 2014

News and Accomplishments

VAPOR Project

Project information is available at: http://www.vapor.ucar.edu

KISTI Award:

• Scott's CAM data importing code was reviewed, and all reviewer comments were addressed. Scott is now working on a memory leak, and then hopefully checking in a final version of the code.

• Alan has made numerous changes to the isoline renderer code so that we can trace each isoline from start to finish. This will be useful for annotation.

2.4 Development:

All five of Scott's FTGL action items from May 2014 were completed, listed as follows:

1) The need for an object oriented implementation of the draw functions.

2) A way to draw the text glyphs onto a solid black background.

3) A way to color the text and background according to user-input.

4) The ability to rotate and transpose the text within the scene.

5) The need to use a public domain .ttf font file.

Miles completed all development tasks for the GLFlow tube renderer:

• Assorted debugging in glflow

• Restructured glflow API

• Full support for stride, arrowstride in glflow

• Completed color support

• Investigation of post-execution memory errors in glflow (still ongoing)

John put together a project plan for the 2.4 release

Miles also completed development of a new vaporgui splash screen.

3.0 Development:

• Alan has been restructuring our doxygen support in vapor 3.0 to emphasize the aspects of the API that are important for developers.

Administrative:

John was on interview committees for a new Admin 1, and administrative assistant position.

Education and Outreach:

We presented a vapor/wrf mini-tutorial at the WRF 2014 Workshop.  This went very well, with help from Scott, Miles, and Sunni.  The attendees were quite enthusiastic

Mel Shapiro and Tom Galerneau are interested in a 1918 storm, “Bjerkes”, that was the subject of early weather modeling research.  The question is whether the theoretical understanding agrees with modern simulation results.  Tom ran a simulation, Alan has converted the data and performed some initial visualizations.

Scott presented Vapor’s capabilities in a science team meeting at the EOL to about 20 scientists from NCAR, NOAA, NASA, and other institutions.  The pitch was to apply Vapor to their WRF-CHEM forecasts to better plan their flight trajectories.  However it was expressed that Vapor would be a better candidate for post analysis given their already crowded daily routines.

Software Research Projects

Feature Tracking:

Climate data compression:

Production Visualization Services & Consulting

• Scott combined Vapor’s Fortran code for writing raw data with Peter Sullivan’s model output reader.  Two modifications were made.  One was to write an entire 3D volume to a file (as opposed to the default of horizontal slices); and the other was modifying the code on our website to re-define the record length variable used to allocate output file size.

ASD Support

• xxx

Publications, Papers & Presentations

• xxx

Proposals

John and Shawn collaborated with Larry Frank (UCSD) on an NIH proposal, led by UCSC, and entitled:

 John reviewed proposals for the NSF Big Data review panel.

SCIparCS Student Internship

• We met with Pfister and Barth (from ACD) on June 2 to see how Sunni will collaborate with the FRAPPE project (which will be collecting pollution data based on C130 flight paths in Colorado) Sunni wrote Python code to map the flight path data to visualize in VAPOR. Sunni has also use the Google Earth capabilities that Mohammad developed last summer, which proved to be useful for this community.
• We met again with Pfister and Barth on June 11, showing them the visualizations we have created in vapor.  They both were interested and had numerous suggestions of how to make this useful in the dry run on July1. 
• We prepared for the dry run of Frappe on July 1, and streamlined the process of converting this data, inserting flight paths, and making animation sequences from it.  We anticipate working with the Frappe team on post-flight analysis after their test flight on July 8.
  

Data Services

• xxx

Accounting & Statistics

• xxx

Security & Administration

• xxx

System Monitoring

• xxx

System Support

ML - Data Analysis & Visualization Clusters

• xxx

GLADE Storage Cluster

• xxx

Data Transfer Cluster

• xxx

Experimental Clusters

• xxx

Test Clusters

Storage Usage Statistics

NWSC+GLADE+Usage+Report

Other

• xxx