\u201cThis year, we developed a software system for teaching that made it much easier for people to learn,\u201d Luo said. \u201cThis software means that attendees don\u2019t have to have as much modeling and programming background as they needed in previous years.\u201d<\/p>\n
He said the Earth system modeling community is vexed by a central issue: uncertainty. Uncertainty measures the imperfections of model outputs. In each of the agenda-setting Intergovernmental Panel on Climate Change (IPCC) reports, Luo said, \u201cuncertainty has always been an issue.\u201d<\/p>\n
\u201cWe really need to understand the causes of that uncertainty to make a diagnosis,\u201d he said. The matrix approach, one of the approaches he developed that is taught in 4T, functions as a \u201cdoctor\u201d of land carbon cycle models. \u201cUsing the matrix approach, we can diagnose exactly what causes that problem.\u201d<\/p>\n
To apply the knowledge and techniques learned from 4T, nearly 30 volunteers from the training course formed a working group to doctor the sixth phase of the Coupled Model Intercomparison Project, or CMIP6, a global modeling effort to predict the future states of climate and ecosystems. Results from CMIP6 will inform IPCC\u2019s sixth assessment report. Lifen Jiang<\/strong>, Luo\u2019s colleague and coordinator of the course, said that one of the major draws to join the working group was the use of CMIP6. Beyond the course, the working group continues to collaborate on CMIP6 through a \u201clearning by doing\u201d practice to address some of the big questions the modeling community is tackling.<\/p>\n According to Luo, Jiang is at the heart of the training course and a major key to its success. Jiang corresponded with all participants as they registered, answered questions, delivered a lecture, and monitored the course\u2019s Slack channel. \u201cWithout Lifen, we cannot organize this course,\u201d Luo said. \u201cShe is so essential.\u201d<\/p>\n Course attendees who were relatively new to modeling said Jiang and Luo created a welcoming and rigorous learning environment.<\/p>\n \u201cI learned the fundamentals of land carbon cycle modeling and a deeper understanding of how carbon cycle models work,\u201d said Lisa Haber, a Ph.D. student at Virginia Commonwealth University. Haber, who studies forest system ecology, hopes to use models to accurately simulate what happens to carbon during an ecological disturbance at her study site in northern Michigan. \u201cConnecting with other graduate students, postdocs, early career scientists and even senior researchers who taught and guest-lectured in this course was an incredibly rich experience for me\u2014one I would never have been able to access at my home institution.\u201d<\/p>\n \u201cThis course really was my entry point into the whole modeling community,\u201d said Bastian Buman, a Ph.D. candidate in the Remote Sensing Laboratories at the University of Zurich in Switzerland. Buman wants to combine remote sensing, modeling and in situ<\/em> measurements to learn more about carbon cycles at the interface of land and aquatic ecosystems. \u201cBoth Lifen and Yiqi created a very welcoming and happy community. It’s always great to meet peers and people interested in similar topics, but during these stressful pandemic times, it is even more encouraging and motivating to connect with others.\u201dLearn more about the Fourth Training Course on New Advances in Land Carbon Cycle Modeling at the Ecolab page<\/a>.<\/p>\n
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