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UID:pretalx-2024-3DVH7S@cfp.scipy.org
DTSTART;TZID=PST:20240708T080000
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DESCRIPTION:This tutorial walks participants — Earth scientists with some
  prior Python experience — through analyses of two particular climate ri
 sk scenarios: floods & wildfires. The goal is to obtain hands-on experienc
 e with common reproducible Jupyter/Python workflows based on data products
  from the [NASA Earthdata Cloud](https://www.earthdata.nasa.gov/). The cas
 e studies highlight the interplay of distributed data with scalable numeri
 cal strategies — "data-proximate computing" — implemented using scient
 ific Python libraries like NumPy\, Pandas\, & Xarray. This tutorial — co
 -developed by 2i2c and MetaDocencia — constitutes part of NASA's [Transf
 orm to Open Science (TOPS)](https://nasa.github.io/Transform-to-Open-Scien
 ce/) initiative to reinforce principles of Open Science & reproducibility.
DTSTAMP:20260614T133431Z
LOCATION:Room 316
SUMMARY:Determining Climate Risks with NASA Earthdata Cloud - Dhavide Aruli
 ah\, Karthik Venkataramani\, Patricia  A. Loto
URL:https://cfp.scipy.org/2024/talk/3DVH7S/
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