Dr. Alejandro Flores - Cloud-Resolving Climate Modeling in the Cloud: Challenges and Opportunities

Dr. Alejandro Flores
Associate Professor
Boise State University

lejoflores@boisestate.edu

Zoom Link

Cloud-Resolving Climate Modeling in the Cloud: Challenges and Opportunities

Biography

Dr. Flores has been faculty at Boise State University since 2009. In that time, he has secured more than $5M in sponsored projects as Principal Investigator from the National Science Foundation, Department of Energy Office of Science, NASA, US Department of Agriculture, Army Research Office, and a variety of federal and state mission agencies to support work in regional and watershed hydrologic modeling, remote sensing, and data assimilation. He has published 41 peer-reviewed publications. He serves the hydrologic sciences community in a number of capacities, some of which are highlighted in the next section.

Abstract

This talk provides an overview of a new NSF project that will produce knowledge of how precipitation, snow, and runoff in the Snake River Basin will be impacted by climate variability and change, while also expanding the use of cloud computing in water science research. Although cloud computing is increasingly important in research, the water science community lacks training materials and case studies to onboard researchers to effective practices. This project addresses this tension by: (1) developing cloud computing solutions to three common computing uses in water science, (2) using those approaches to create datasets that characterize the effects of climate variability and change on hydrology in the Snake River Basin, and (3) designing and disseminating educational materials to train water scientists in the use of cloud computing. This project will produce scientific insights and datasets to help water managers prepare for climate change in the western US and prepare the next generation of water scientists in modern computing paradigms. Specific focus is paid here to how open and reproducible computing platforms are essential to this project and, importantly, can help advance co-production of knowledge and decision support for stakeholders in the realm of water management.