Sponsor:

National Science Foundation, award number CCF-1029166

Project Team Members:

Northwestern University

North Carolina A&T State University

North Carolina State University

University of Minnesota






Northwestern University - EECS Dept.



Understanding Climate Change: A Data Driven Approach


Introduction

Data-driven approaches that have been highly successful in other scientific disciplines hold significant potential for application in environmental sciences. This Expeditions project aims to address key challenges in the science of climate change by developing methods that leverage the abundance of climate and ecological data available from satellite and ground-based sensors, the observational record for atmospheric, oceanic, and terrestrial processes, and physics-based climate model simulations. To realize this ambitious goal, novel methodologies appropriate to climate change science are being developed. These innovative approaches will help provide new understanding of the complex nature of the Earth system and the mechanisms contributing to the adverse consequences of climate change, such as increased frequency and intensity of hurricanes, precipitation regime shifts, and the propensity for extreme weather events that result in environmental and socioeconomic disasters. Methodologies developed as part of this project will be used to advance scientific knowledge, to gain actionable insights, and to inform policymakers.

The education and mentoring opportunities from this Expeditions project go significantly above and beyond what can be achieved with a single PI-driven or smaller-scale collaborative project.
The goals are as follows:

  1. Train students and postdoctoral researchers in the fields of data mining, climate data procurement and analysis, pattern recognition, image processing, and the design and implementation of algorithms including the use of distributed platforms.
  2. Create educational initiatives to engage students (including women and those from underrepresented minorities) to create interest and awareness of the work in this area. The Expeditions team is collaborating with the Interdisciplinary Scientific Environmental Technology (ISET) program, whose objective is to provide opportunities for underrepresented students to study climate or environmental sciences and the related technologies.
  3. Design and develop techniques for identifying the structure of climatological data on a decadal scale.
  4. Design and develop methodologies for Accurate Forecasting of Adverse Spatio-Temporal Events.
  5. Design and develop a set of data analysis kernels as part of an effort to provide a library of high performance implementations of standard data mining kernels.
  6. Present the developed techniques, methodologies and data analysis kernels in the form of technical papers or at related technical conferences.

Publications

Datasets

External Links

This work is supported by NSF (National Science Foundation) Division of Computer and Communication Foundations, under award number CCF-1029166.

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