5th Training Course (Hybrid Virtual + in Person) on

New Advances in Land Carbon Cycle Modeling

May 16-27, 2022 (with weekend on May 21 and 22 off)

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Download Unit 5

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Download Unit 7

Download Unit 8

Download Unit 9

Download Unit 10

Map of Participant Locations for 2022

Map of Participant Locations for 2022

Who should attend?

Graduate students, post-docs and young scientists who want to learn modeling, data assimilation, machine learning, deep learning, and ecological forecasting

Modelers who want to gain simplicity in structure, computational efficiency for your models

Empiricists who want to use your data to constrain models toward ecological forecasting

What are you going to learn?

New theory on land carbon storage dynamics

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?

Lecturers and instructors

Keanan Allen, Northern Arizona University, USA

Aneesh Chandel, Northern Arizona University, USA

Ye Chen, Northern Arizona University, USA

Toby Hocking, Northern Arizona University, USA

Forrest Hoffman, Oak Ridge National Laboratory, USA

Enqing Hou, South China Botanical Garden, China

Xin Huang, Northern Arizona University, USA

Yuanyuan Huang, CSIRO, Australia

Jiang Jiang, Nanjing Forestry University, China

Lifen Jiang, Northern Arizona University, USA

Yu Jiang, Cornell University, USA

Junyi Liang, China Agricultural University, China

Cuijuan Liao, Tsinghua University, China

Xingjie (Chris) Lu, Sun Yat-sen University, China

Yiqi Luo, Northern Arizona University, USA

Shuang Ma, JPL/Cal Tech, USA

Umakant Mishra, Sandia National Laboratory, USA

Markus Mueller, Northern Arizona University, USA

Daniel Ricciuto, Oak Ridge National Laboratory, USA

Carlos Sierra, MPI-BGC, Germany

Ben Smith, Western Sydney University, Australia

Feng Tao, Tsinghua University, China

Kostiantyn Viatkin, Northern Arizona University, USA

Ying Wang, University of Oklahoma, USA

Jon Wells, Northern Arizona University, USA

Matthew Williams, Edinburg University, UK

Jianyang Xia, East China Normal University, China

Yao Zhang, Peking University, China

Yu Zhou, Northern Arizona University, USA

Invited speakers

Pep Canadell, CSIRO, Australia

Istem Fer, Finnish Meteorological Institute, Finland

Hyungsub Kim, Korea University, South Korea

Dave Lawrence, NCAR, USA

Natasha MacBean, Indiana University, USA

Peter Reich, University of Minnesota, USA

Yang Song, University of Arizona, USA

Emma Stell, University of Delaware, USA

Kostiantyn Viatkin, Northern Arizona University, USA

When and what is your commitment?

May 16-27, 2022 of Phoenix, Arizona, US time (with the weekend on May 21 and 22 off)

You will go through 10 units of online training, one unit per day. For each unit, you will read three chapters or other training materials, listen to corresponding pre-recorded lectures, take quizzes, do exercises according to one 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?

Tuition fee $400 for online and $1000 for in-person attendees to compensate for the time of instructors.

Financial support available for applications from underrepresented groups in STEM.

One textbook Land Carbon Cycle Modeling: Matrix Approach, Data Assimilation, and Ecological Forecasting is freely available.

How to apply?

Please submit your application form by March 4, 2022 online via the link


We will inform you of our decision about your application by March 18, 2022.

Please contact Dr. Lifen Jiang ( for any questions.

Past Training Courses

1st Training Course 2018

2nd Training Course 2019

3rd Training Course 2020

4th Training Course 2021