Publication Abstracts

Monteleoni et al. 2013

Monteleoni, C., G.A. Schmidt, and S. McQuade, 2013: Climate informatics: Accelerating discovering in climate science with machine learning. Comput. Sci. Eng., 15, 32-41, doi:10.1109/MCSE.2013.50.

The goal of climate informatics, an emerging discipline, is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the field's remaining challenges.

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BibTeX Citation

@article{mo05100o,
  author={Monteleoni, C. and Schmidt, G. A. and McQuade, S.},
  title={Climate informatics: Accelerating discovering in climate science with machine learning},
  year={2013},
  journal={Comput. Sci. Eng.},
  volume={15},
  pages={32--41},
  doi={10.1109/MCSE.2013.50},
}

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RIS Citation

TY  - JOUR
ID  - mo05100o
AU  - Monteleoni, C.
AU  - Schmidt, G. A.
AU  - McQuade, S.
PY  - 2013
TI  - Climate informatics: Accelerating discovering in climate science with machine learning
JA  - Comput. Sci. Eng.
VL  - 15
SP  - 32
EP  - 41
DO  - 10.1109/MCSE.2013.50
ER  -

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