CGD Scientific Visitor Program
CGD has a robust and long-standing program that brings scientific visitors to NCAR's Mesa Lab each year for collaborative research. Graduate students and postdocs sponsored by their universities are eligible to participate. Enhanced interaction with the university community allows us to play an important role in the education and training of the next generation of scientists.
More information is available at https://www.cgd.ucar.edu/visitors/
Every August, CGD hosts a week-long Community Earth System Model Tutorial for graduate students and early-career scientists. The selection process is carefully orchestrated to ensure the maximum impact: only one student per advisor; and a student body with expertise over a wide range of scientific disciplines. Lectures and exercises are made available via the web.
More information is available at https://www.cesm.ucar.edu/events/tutorials/
Every June CGD hosts a week-long Community Earth System Model Workshop for the scientific community. The workshop is a combination of plenary presentations, special interest presentations by the CESM working groups, and a poster session for participants to highlight their work. Working groups meet to discuss current and future priorities, model development, and model simulations. This is also a time to collaborate and communicate CESM science to users and researchers. Presentations are made available to the community via the web.
More information is available at https://www.cesm.ucar.edu/events/workshops/
CGD partners with NCAR's Computational and Information Systems Lab to run tutorials training scientists in the use of the interpreted NCAR Command Language. Multiple tutorial workshops are given throughout the year in Boulder, at UCAR member universities, and at other research organizations around the world. NCL is one of the fastest growing interpreted languages in the geosciences. CGD’s support of the NCL project helps prepare young scientists with the programming tools they need to easily and effectively analyze data sets based on modeling and observations in a variety of formats.
More information is available at http://www.ncl.ucar.edu