CAPE plot from Millersville PECAN data.

In the summer of 2015, from June 1st to July 15th, a fleet of scientists set out each evening in the Midwest. Their goal? To gain insight on the nocturnal mesoscale convective storms (MCS's) that plague America's heartland. While MCS's are necessary for irrigation and the replenishing of aquifers, often these storms can become vicious; especially at night when they are least detected.

With the implementation of the field experiment PECAN (Plains Elevated Convection at Night) scientists from eight research laboratories and fourteen Universities including Millersville University of Pennsylvania hope to gain insight to better predict these nocturnal storms. After the data were collected, the Unidata Program Center (UPC) worked closely with Millersville students and academic staff to help standardize their PECAN study data.

Unidata is searching for a second round of geoscience researchers or research groups to participate in an NSF-funded pilot project aimed at implementing publicly-available, robust data management workflows. The initial round of this project assisted three atmospheric science projects that collected data including model output, airplane-based lidar data, and observations from a large field campaign. The second round seeks to identify additional community partners with different data management requirements.

In addition to helping researchers satisfy current funding proposal requirements, we hope to test effective methods of collecting, transforming, storing, and sharing atmospheric or related geoscience data. The methods used will be documented and published for broad community application as examples in Unidata's Data Management Resource Center (DMRC), serving to guide similar projects.

Providing data services and tools to the geoscience community is at the core of Unidata's efforts. In addition to providing direct access to data (through the Internet Data Distribution network, LDM software, and THREDDS Data Servers), Unidata also strives to make community members aware of other services that provide support for our community's research.

In February of 2013, Unidata's long time collaborative partner, the University of Wisconsin's Space Science and Engineering Center (SSEC), began a program at the SSEC Data Center to provide a limited amount of archived geostationary satellite data to Unidata's academic community members at no cost. This post is a friendly reminder that members of Unidata's academic community can register with SSEC and receive up to 5 Gigabytes of archived data each month free of charge. We encourage you to investigate this valuable data resource.

The Big Data Project (BDP) is an initiative undertaken by the National Oceanic and Atmospheric Administration (NOAA) to increase public availability of large volumes of environmental data collected and generated by the agency. As part of the Big Data Project, Unidata is working in collaboration with Amazon Web Services (AWS) on a demonstration project to provide access to a more than twenty years of archived NEXRAD Level II radar data — augmented continuously with new, real-time data — stored in Amazon's Simple Storage Service (S3) environment. In addition to assisting AWS with ingesting new data flowing from the NEXRAD sites, Unidata Program Center staff have set up a THREDDS Data Server in the AWS environment to provide services allowing community access to the stored data.

The Unidata Program Center (UPC) is searching for atmospheric science researchers or research groups to participate in a pilot project aimed at designing and implementing robust data management workflows. The project aims to assist at least three community partners representing modest research projects of different scales in the implementation of data management processes that satisfy National Science Foundation and other federal funding agency requirements.

Beyond simply satisfying current funding proposal requirements, the project hopes to test effective methods of collecting, transforming, storing, and sharing atmospheric science data. The methods used will be documented and polished for broad community use as examples serving to guide similar projects. If successful, the project will give researchers tools to satisfy funding agency requirements while making their data more widely discoverable, available, open, and usable by others in the community.