The Course library provides video, slides, and other materials from Consulting Services Group (CSG) training events, workshops, and presentations.
Additional learning resources can be found in Archived CISL courses.
Keep an eye out for news about upcoming CSG training opportunities in our CISL Daily Bulletin.
Statistical emulators for climate model output, among which pattern scaling has been perhaps the most popular thus far, are techniques for generating (low- dimensional or fully spatial) projections of future climate using a statistical model designed to reproduce results that would be expected from a projection with a full global climate model.
Climate change and its consequences are increasingly being recognized as among the most significant challenges of our time, yet there is considerable uncertainty regarding the social and environmental impacts because the predictive potential of numerical models of the Earth system is limited.
The development of new approaches to the creation of bias-corrected land surface air temperature datasets has the potential to improve the interpretation of historical surface temperature observations. This is a problem of high scientific and societal relevance as the temperature record forms a backbone for the scientific characterization of climate variability over the past century.
Uncertainty is present in all phases of climate change research from the physical science (e.g., projections of future climate) to the impacts through to the effort to make decisions regarding mitigation and adaptation across different spatial scales. This theme will embrace all aspects of uncertainty in climate change research, providing a pedagogic whole for stu-dents, post-docs, and early career scientists interested in any and all aspects of climate change.
This workshop series is designed to help prepare the next generation of researchers and practitioners to work within, and contribute to, the data-rich era. The workshop will consist of computing and modeling tutorials, presentations from graduate student participants, and several invited talks from established leaders in environmental data modeling. Tutorials and invited talks will address useful ideas and tools directly applicable to student participants' current and future research.
XSEDE training resources
As part of NCAR's participation in the Extreme Science and Engineering Discovery Environment (XSEDE) collaboration, CISL is pleased to augment our training offerings with relevant courses provided by our XSEDE partners.
Numerous online learning opportunities are available, as are live training courses and webcasts.
For information, please see the overview of XSEDE’s training opportunities, and visit these sites: