7th Training Course (Hybrid Virtual + in Person) on

New Advances in Land Carbon Cycle Modeling

June 3-14, 2024 (with weekend on June 8 and 9 off)

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

Ye Chen, Northern Arizona U, USA

Julia Green, U of Arizona, USA

Toby Hocking, Northern Arizona U, USA

Forrest Hoffman, ORNL, USA

Enqing Hou, South China Bot. Garden, China

Xin Huang, NCAR, USA

Yuanyuan Huang, IGSNRR, CAS, China

Jiang Jiang, Nanjing Forestry U, China

Lifen Jiang, Cornell U, USA

Junyi Liang, China Agricultural U, China

Xingjie Lu, Sun Yat-sen U, China

Yiqi Luo, Cornell U, USA

Shuang Ma, UCLA/JPL, USA

Daniel Ricciuto, ORNL, USA

Zheng Shi, U of Oklahoma, USA

Carlos Sierra, MPI-BGC, Germany

Ben Smith, Western Sydney U, Australia

Feng Tao, Cornell U, USA

Ying Wang, U of Oklahoma, USA

Matthew Williams, Edinburg U, UK

Jianyang Xia, East China Normal U, China

Yao Zhang, Peking U, China

Jian Zhou, Cornell U, USA

Yu Zhou, Cornell U, USA

Invited speakers

William Anderegg, U of Utah

Ana Bastos, Max Planck Institute for BGC, Germany

Katerina Georgiou, Livermore National Lab

Vipin Kumar, U of Minnesota

Shuli Niu, IGSNRR, Chinese Academy of Sciences

Jennifer Rudgers, U of New Mexico

Marko Scholze, Lund U, Sweden

Feng Tao, Cornell U

Xiangtao Xu, Cornell U

When and what is your commitment?

June 3-14, 2024 of Eastern Daylight Time (EDT) (with the weekend on June 8 and 9 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 $500 for online and $1200 for in-person attendees (in-person location: Cornell University, Ithaca, New York, USA) to compensate for the time of instructors.

Financial support available for applications from underrepresented groups in STEM in USA.

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 February 2, 2024 online


We will inform you of our decision about your application by February 16, 2024.

Please contact Dr. Lifen Jiang ( for any questions.

Download training course software, book, and videos in 2024

Download e-book Land Carbon Cycle Modeling: Matrix Approach, Data Assimilation, Ecological Forecasting, and Machine Learning

Download CarboTrain software

Download Appendices

Download Unit 1

Download Unit 2

Download Unit 3

Download Unit 4

Download Unit 5

Download Unit 6

Download Unit 7

Download Unit 8

Download Unit 9

Download Unit 10


Past Training Courses in 2018-2023

1st Training Course 2018

2nd Training Course 2019

3rd Training Course 2020

4th Training Course 2021

5th Training Course 2022

6th Training Course 2023