Practice 5: Traceability Analysis for Evaluating Terrestrial Carbon Cycle Models

Jianyang Xia; Jian Zhou

doi:10.1201/9781032711126-25

Practice 5: Traceability Analysis for Evaluating Terrestrial Carbon Cycle Models

Jianyang Xia, Jian Zhou

School of Ecology and Environmental Sciences

East China Normal University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

The practice is designed to help you learn traceability analysis to identify sources of model uncertainty in predicting terrestrial carbon (C) storage. All practices are performed in the training software CarboTrain. With this tool, you will apply traceability analysis to simulation results from a matrix form model (called authentic traceability analysis) and to model intercomparison projects (MIP) without matrix models (i.e., post-MIP traceability analysis). The authentic traceability analysis will show you how simulation results from a matrix model are explained by traceable components over space and among biomes. The post-MIP traceability analysis can help you understand the sources of uncertainty among different models.

Original language	English
Title of host publication	Land Carbon Cycle Modeling
Subtitle of host publication	Matrix Approach, Data Assimilation, Ecological Forecasting, and Machine Learning, Second Edition
Publisher	CRC Press
Pages	126-130
Number of pages	5
ISBN (Electronic)	9781040026298
ISBN (Print)	9781032698496
DOIs	https://doi.org/10.1201/9781032711126-25
State	Published - 1 Jan 2024

Access to Document

10.1201/9781032711126-25

Cite this

@inbook{3309afa90377409789a5a14334baf5c5,

title = "Practice 5: Traceability Analysis for Evaluating Terrestrial Carbon Cycle Models",

abstract = "The practice is designed to help you learn traceability analysis to identify sources of model uncertainty in predicting terrestrial carbon (C) storage. All practices are performed in the training software CarboTrain. With this tool, you will apply traceability analysis to simulation results from a matrix form model (called authentic traceability analysis) and to model intercomparison projects (MIP) without matrix models (i.e., post-MIP traceability analysis). The authentic traceability analysis will show you how simulation results from a matrix model are explained by traceable components over space and among biomes. The post-MIP traceability analysis can help you understand the sources of uncertainty among different models.",

author = "Jianyang Xia and Jian Zhou",

note = "Publisher Copyright: {\textcopyright} 2024 selection and editorial matter, Yiqi Luo and Benjamin Smith.",

year = "2024",

month = jan,

day = "1",

doi = "10.1201/9781032711126-25",

language = "英语",

isbn = "9781032698496",

pages = "126--130",

booktitle = "Land Carbon Cycle Modeling",

publisher = "CRC Press",

address = "荷兰",

}

TY - CHAP

T1 - Practice 5

T2 - Traceability Analysis for Evaluating Terrestrial Carbon Cycle Models

AU - Xia, Jianyang

AU - Zhou, Jian

PY - 2024/1/1

Y1 - 2024/1/1

N2 - The practice is designed to help you learn traceability analysis to identify sources of model uncertainty in predicting terrestrial carbon (C) storage. All practices are performed in the training software CarboTrain. With this tool, you will apply traceability analysis to simulation results from a matrix form model (called authentic traceability analysis) and to model intercomparison projects (MIP) without matrix models (i.e., post-MIP traceability analysis). The authentic traceability analysis will show you how simulation results from a matrix model are explained by traceable components over space and among biomes. The post-MIP traceability analysis can help you understand the sources of uncertainty among different models.

AB - The practice is designed to help you learn traceability analysis to identify sources of model uncertainty in predicting terrestrial carbon (C) storage. All practices are performed in the training software CarboTrain. With this tool, you will apply traceability analysis to simulation results from a matrix form model (called authentic traceability analysis) and to model intercomparison projects (MIP) without matrix models (i.e., post-MIP traceability analysis). The authentic traceability analysis will show you how simulation results from a matrix model are explained by traceable components over space and among biomes. The post-MIP traceability analysis can help you understand the sources of uncertainty among different models.

UR - https://www.scopus.com/pages/publications/85195905319

U2 - 10.1201/9781032711126-25

DO - 10.1201/9781032711126-25

M3 - 章节

AN - SCOPUS:85195905319

SN - 9781032698496

SP - 126

EP - 130

BT - Land Carbon Cycle Modeling

PB - CRC Press

ER -

Practice 5: Traceability Analysis for Evaluating Terrestrial Carbon Cycle Models

Abstract

Access to Document

Other files and links

Fingerprint

Cite this