AWS talk and blog post, XrVis, Lab-relevant AGU sessions, and Climata!Highlights from your favorite Virtual Earth Science Lab. 




Highlights from your favorite Earth science virtual lab! 
July 10, 2019
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NOTE FROM THE LAB DIRECTOR: The ESIP Summer Meeting is next week! If you can't be there in person, remember all sessions are available for remote participation. Find your sessions of interest here – after you select a session the call-in details will be at the bottom.

Lastly, check out our ESIP Lab talk from the AWS Public Sector Summit here and the associated blog post!
Annie B. Burgess


1. AGU Sessions of Interest
2. XrViz: An Interactive visualization interface for Xarrays
3. Climata: A Pythonic interface for loading and processing time series data

AGU Sessions of Interest

It's that time of year again! As you consider where to submit your AGU Fall meeting abstracts, consider the following ESIP Lab-relevant sessions:

XrViz: An interactive visualization interface for Xarrays

XrViz is an interactive, in-browser visualization interface for Xarrays backed by the full power of the Python ecosystem. It allows controlled data points selection, massive rendering, data display, custom interaction and selection of fields for plotting in the browser using IntakeXarray, and PyViz(now HoloViz) collection of tools. It holds the promise of saving Earth Science and other researchers significant amounts of time since they can directly focus on visual data analysis and research rather than writing custom code to explore data.

XrViz is an ESIP Google Summer of Code project with the gifted student Harman Deep Singh. The project is being mentored by Rich Signell at USGS and Martin Durant from Anaconda, inc. 

Read more here

Climata: A Pythonic interface for loading and processing time series data. 

Lab Fellow Ben Roberts-Pierel highlights one of his favorite data exploration tools

Anybody who works with time series data will know there are myriad ways of acquiring, cleaning and analyzing those data. As the scientific community continues to work with these more temporally and spatially continuous datasets, streamlining workflows becomes likewise more important. There are numerous ways to do this but recently I have found the climata package ( for Python a useful tool for pulling down data from the SNOTEL network. The package is setup to acquire time series data from a variety of climatological and hydrological sensor networks maintained by several government agencies. The tool can be run from the command line or embedded in a larger workflow. Although there are many such packages out there, this one has been easy to use, it is already setup to acquire domain specific data and has been (mostly) free of unexpected glitches. Anybody who is interested can check the github at:

For those of you interested in the SNOTEL network and other applications of sensor network and remote sensing data, please consider attending the “Multi-sensor data integration for cryosphere and hydrosphere monitoring” session that I will be organizing at this year’s ESIP Summer Meeting. The session will feature presentations on applications of sensor network, remote sensing and modeled data by Dr. Jeff Deems of the National Snow and Ice Data Center (NSIDC), Dr. Eric Sproles of Montana State University and recipient of an ESIP Lab grant, Scott Oviatt from the Natural Resources Conservation Service (NRCS) and NOAA postdoc and ESIP Community Fellow, Dr. Yuhan Rao. The session will take place on Thursday, July 18th at 10:30 AM. Please contact me at with any questions!

ESIP is funded with support from NASA, NOAA, and the USGS. 
Keep up on all the action on Slack – here is your INVITATION!

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