Scenario: ASCII Data from a Variety of Instruments (VLITE)

CASE STUDY UNDER CONSTRUCTION

Tools at a Glance

This case study describes an experiment that gathered data from a range of atmospheric sensors, collected mostly in ASCII format. Data files are converted to netCDF format using Unidata's Rosetta data transformation tool, and data are made available using Geode Systems' RAMADDA data server.

Project Background

John Kaiser and Dr. Jay Shafer from Lyndon State University are working on a project titled “Improving the Forecasting of Weather Driven Outages and Long Term Renewable Energy Production” which is funded by the nonprofit organization Vermont Low Income Trust for Electricity (VLITE). The project is part of the The Vermont Weather Analytics Center, which is managed by the Velco Vermont Electric Power Company. Lyndon State is directly involved with is seeking to better understand how anticipated climate change will affect production from Vermont's renewable energy sources.

Data Collected

Data used by the project are collected from four weather stations, a variety of weather observing programs, and resulting output data from WRF model simulations. The Lyndon State team collects data from Citizen Weather Observing Program (CWOP), Meteorological Assimilation Data Ingest System (MADIS), MESOWEST, as well as the Vermont Weather Analytics Center (VTWAC). Data from VTWAC's four weather stations is uploaded into CWOP's cloud database every fifteen minutes, and is then run through MADIS. The WRF model that Lyndon State is using pulls its initial conditions from MADIS, after being run through a North American Mesoscale Forecasting System (NAM) Analyses. The data from the four weather stations is therefore used indirectly to set the initial conditions in the WRF model after NAM has integrated the data, and is downloaded into the WRF models when the data is available, at 0 and 12 Z. The initial conditions are uploaded into a WRF model in GRIB format.

Tools Used for Data Processing and Analysis

Data from past weather events are also analyzed using a WRF model. Volume of data being produced by Lyndon States project is in the order of 1 to 5 TB with the WRF model simulations making up the majority of the data produced. To analyze past events Python RGIS is used.

Data Storage Strategy and Tools Used

The WRF output data is natively output in netCDF format and stored on the Vortex00 internal data server. Data is then pulled from Vortex00 and ran through the Unified Post Processor (UPP) is used to convert from netCDF format to a GRIB format. Lyndon state then runs GRaDS on these GRIB files to produce images.

Data Access Strategy and Tools Used

Sample output from the WRF model
(Click to enlarge)

Images that have been produced from the GRIB files are stored on a web server for public access. The link to that webpage can be found here. Currently the data is not archived but is stored internally on Lyndon State's network.