

New Advances in Land Carbon Cycle Modeling
Modelers who want to gain simplicity in coding, diagnostic capability, computational efficiency, and data constraints for your models
Empiricists who want to use your data to constrain models toward ecological forecasting
What are you going to learn?
Matrix approach to land carbon, nitrogen, and phosphorus modeling
Data assimilation system with both flux- and pool-based observations
Deep learning and machine learning to enhance process-based research
Ecological forecasting
Who is going to teach?
Ye Chen, Northern Arizona University, USA
Toby Hocking, Northern Arizona University, USA
Enqing Hou, Northern Arizona University, USA
Xin Huang, Northern Arizona University, USA
Yuanyuan Huang, CSIRO, Australia
Jiang Jiang, Nanjing Forestry University, China
Lifen Jiang, Northern Arizona University, USA
Cuijuan Liao, Tsinghua University, China
Chris Lu, Sun Yat-sen University, China
Yiqi Luo, Northern Arizona University, USA
Shuang Ma, JPL/Cal Tech, USA
Daniel Ricciuto, Oak Ridge National Laboratory, USA
Zheng Shi, UC Irvine, USA
Carlos Sierra, MPI-BGC, Germany
Feng Tao, Tsinghua University, China
Jianyang Xia, East China Normal University, China
When and what is your commitment?
You will go through 10 units of training at your home, one unit per day. For each unit, you will read one paper/syllabus, listen to pre-recorded lectures, take quizzes for each lecture, do exercises according to pre-recorded instruction, and attend one synchronized virtual meeting. You will get feedback from instructors on your answers to quizzes and exercises.
What is the cost?
Graduate students enrolled for the summer course pay tuition fee of $1198 for 2 credits through Northern Arizona University, USA
Financial support available for applications from underrepresented groups in STEM in USA
How to apply?
We will select up to 40 applicants by May 29, 2020 to attend the training course.