Remote Online Sessions for Emerging Seismologists

Remote Online Sessions for Emerging Seismologists (ROSES)

In 2020, the American Geophysical Union Seismology Section offered the ROSES Seismology Summer School for the first time. Targeted at graduate students, ROSES was a series of 11 virtual sessions offered over Zoom. Coupled with interactive Python notebooks and delivered by field experts, the course sessions presented an opportunity to gain experience with aspects of seismology spanning a range of applications and data-types, as well as an opportunity to interact and network with seismologists across the globe. This page provides key information about the current and previous offerings of ROSES.


Returning for 2021: ROSES (Remote Online Sessions for Emerging Seismologists)

Following the success of the first ROSES offering in the depths of global lockdown, we are pleased to announce the return of ROSES for mid-year 2021. ROSES will run from June 7 to August 16, 2021. We welcome applications from MS students, PhD students, early career researchers and lecturers, and incoming graduate students that have already taken the IRIS Seismology Skill Building Workshop workshop or have the applicable computing experience. We will continue to cultivate the successful, cohort-based learning environment while expanding accessibility globally – offering synchronous and asynchronous options for lectures, facilitating regional working groups, and providing a global forum for collaborative discussion.

This year, ROSES will consist of 11 sessions (an introduction + 10 topical sessions)
delivered via Zoom for live sessions and the ROSES YouTube channel for
asynchronous sessions and general access. Live sessions will occur Tuesdays at
12pm EDT. Admission to the ROSES 2021 cohort will provide access to live sessions,
the community Slack channel, and computational resource support. Applicants are
expected to meet the following criteria:
1. Be enrolled in / employed by an institution of higher education and/or research
2. Be prepared to engage with at least 9 sessions and preferably all 11 sessions
3. Be prepared to complete pre-session reading and coding-based pre-analysis
assignments
4. Meet the computational proficiency requirements:
- Familiarity with Unix commands (note: Windows users are welcome!)
- Familiarity with the Python programming language
- Familiarity with the ObsPy Python toolbox
- General familiarity with Jupyter notebooks
- Access to a Unix-based computing environment with a Conda3 Python
environment pre-installed (Note: ROSES will provide a cloud-based solution
for Windows users)
- Elementary knowledge of git and GitHub for accessing course materials

Preference will be given to applicants who did not already participate in ROSES 2020.
If you need a Python refresher, please check out the following “TRANSFORM 2020” course offered by Software Underground: https://www.youtube.com/watch?v=iIOMiN8Cacs (duration: 2.5 hours)
If you need an ObsPy refresher, please check out tutorials here:
https://docs.obspy.org/tutorial/index.html; https://www.youtube.com/watch?v=PRECSp2bb20
To apply for ROSES 2021, submit your information here by Friday, May 7, 2021.

Please direct any questions to the ROSES organization team at
roseseismo@gmail.com.

 

Course Structure: 2020

ROSES 2020: Resources

Topics Covered in 2020

The course was structured so that each session contained a live, hour-long lecture component, where a field expert presented information about an important aspect of seismology. This was followed by a live 'laboratory' session, where this instructor would demonstrate and execute code that built upon and applied the topics discussed in that day's lecture. This code was made available to all students, who would work through it simultaneously. After this, breakout rooms provided groups of students the opportunity to work through exercises that allowed them to practice and build upon the skills that were introduced during the day's lecture.

1) ObsPy
2) Data and Metadata
3) Time Series Analysis
4) Waveform Cross Correlation
5) Array Seismology/Network Analysis
6) Polarization Analysis
7) Machine Learning
8) PyGMT
9) Bayesian Inversion
10) Optimal Interpolation
11) Gridding and Inversion