Data and Code Supporting "A Scalable Spark-Based Model–Data Fusion Framework for Regional Carbon-Cycle Modeling: A Case Study in China's Forest Ecosystems"

This repository contains the code and input data associated with the study “A Scalable Spark-Based Model–Data Fusion Framework for Regional Carbon-Cycle Modeling: A Case Study in China’s Forest Ecosystems.” The repository includes: Spark-Based Model–Data Fusion Framework.py: implementation of the Spark-based distributed model–data fusion framework, including the DALEC carbon-cycle model, Bayesian parameter inversion using PyMC, and site-level parallel execution with Apache Spark. forcing.csv: contains the environmental forcing variables used by the regional MDF framework and is publicly available. constraint.csv: provides the structure of the observational constraint dataset and all variables that can be publicly shared. The original constraint dataset also contains vegetation and soil carbon observations derived from field surveys and inventory data. These observations are subject to institutional data-use and confidentiality restrictions and therefore cannot be publicly released. Restricted carbon observations have been removed from the public version of the dataset.