A climate index is real-valued time-series which has been designated of interest in the climate literature. For example, the El Niño–Southern Oscillation (ENSO) index has widespread uses for predictions of regional and seasonal conditions, as it tends to have strong (positive or negative) correlation with a variety of weather conditions and extreme events throughout the globe. The ENSO index is just one of the many climate indices studied. However there is currently significant room for improvement in predicting even this extremely well studied index with such high global impact. For example, most statistical and climatological models erred significantly in their predictions of the 2015 El Niño event; their predictions were off by several months. Better tools to predict such indices are critical for seasonal and regional climate prediction, and would thus address grand challenges in the study of climate change (World Climate Research Programme: Grand Challenges, 2013).
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News
- Introduction to Data Science in Python, November 2019 edition 2019/12/11
- Workshop “Introduction to Data Science in Python” 2019/03/26
- Data Scientist Position 2019/02/01
- Data Engineering Position 2019/02/01
- RAMP on detecting Solar storms, October 10 2018/10/01
- 3rd CDS pitching day November 28, call for contributions 2018/09/10
- CDS at the Scipy Conference 2018 2018/07/18
- RAMP: IMaging-PsychiAtry Challenge (IMPAC) 2018/07/01