Abstract
All model intercomparison projects (MIPs) have shown large uncertainties in prediction of carbon sequestration among models and poor model-data matches. Although great efforts have been made, it is still difficult to identify causes of model uncertainty. This chapter offers a unified diagnostic system, which is also called a 1-3-5 scheme of diagnostics, for uncertainty analysis in carbon cycle modeling. The number 1 stands for one formula to unify the land carbon models, the number 3 is for one three-dimensional (3D) space to evaluate all model outputs, and the number 5 is for five traceable components to pinpoint uncertainty sources via traceability analysis. Once the uncertainty sources are pinpointed, the model uncertainty can be shrunk to zero by standardizing the traceable components.
Original language | English (US) |
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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 | 57-62 |
Number of pages | 6 |
ISBN (Electronic) | 9781040026298 |
ISBN (Print) | 9781032698496 |
DOIs | |
State | Published - Jan 1 2024 |
Externally published | Yes |
ASJC Scopus subject areas
- General Business, Management and Accounting
- General Agricultural and Biological Sciences
- General Earth and Planetary Sciences
- General Environmental Science
- General Engineering