PROcess-Guided Deep Learning and DAta-Driven Modeling (PRODA)

Feng Tao; Yiqi Luo

doi:10.1201/9781032711126-48

PROcess-Guided Deep Learning and DAta-Driven Modeling (PRODA)

Feng Tao, Yiqi Luo

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

This chapter describes a PROcess-guided deep learning and DAta-driven modeling (PRODA) approach to optimize parameterization of Earth system models (ESMs) using spatio-temporal datasets. PRODA involves both data assimilation to estimate parameter values and deep learning to predict spatial and temporal distributions of parameter values so as to optimize ESM prediction. An application to the Community Land Model version 5 (CLM5) using soil organic carbon (SOC) distributions in the conterminous United States illustrates the potential and utility of the PRODA approach.

Original language	English (US)
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	244-252
Number of pages	9
ISBN (Electronic)	9781040026298
ISBN (Print)	9781032698496
DOIs	https://doi.org/10.1201/9781032711126-48
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

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10.1201/9781032711126-48

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AB - This chapter describes a PROcess-guided deep learning and DAta-driven modeling (PRODA) approach to optimize parameterization of Earth system models (ESMs) using spatio-temporal datasets. PRODA involves both data assimilation to estimate parameter values and deep learning to predict spatial and temporal distributions of parameter values so as to optimize ESM prediction. An application to the Community Land Model version 5 (CLM5) using soil organic carbon (SOC) distributions in the conterminous United States illustrates the potential and utility of the PRODA approach.

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PROcess-Guided Deep Learning and DAta-Driven Modeling (PRODA)

Abstract

ASJC Scopus subject areas

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