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Publication Date
15 January 2020

Moirai Version 3: A Data Processing System to Generate Recent Historical Land Inputs for Global Modeling Applications at Various Scales

Subtitle
Land data integration for global modeling applications.
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Science

Global models of human and Earth systems require a tremendous amount of data for initialization and boundary conditions. Multi-sector models, in particular, need self-consistent data that spans a variety of sources and formats, and different models have different spatial configurations. Moirai is a data integration tool that provides a comprehensive set of land data spanning physical and economic dimensions that can be customized to various spatial configurations for different modeling applications. It also has the capacity to generate multiple versions of a data set to explore uncertainty in source data or spatial configuration. The resulting data sets are self-consistent in content and spatially, which contributes to confidence in model results.

Impact

Processing data for use by models is a complicated and time-consuming task that is often under-resourced. By providing an open-source data integration platform we enable others in the community to perform more efficient data integration for modeling applications. This also supports model comparison projects where goals may include standardizing data inputs across models. The code is licensed such that users may modify it to suit their needs, which provides a solid basis for valid data integration that can be expanded or updated as more or new data become available. As a result, this software may also increase the efficiency of future, related data integration tasks.

Summary

The Moirai land data system, written in C and R, is designed to produce recent historical land inputs for an integrated human-Earth systems model. The primary function of Moirai is to combine spatially explicit input data (e.g., raster images) with tabular input data (e.g., crop price table) to generate spatially-referenced tabular data of crop production, crop harvested area, land value, irrigated and rainfed crop area, water footprint, soil and vegetation carbon density of unmanaged land, and historical land use/cover. These data are aggregated to user-defined geographic boundaries within 231 countries and the default boundaries are defined globally by 235 watersheds. The production, harvested area, and land value outputs reconstruct those available from the Global Trade Analysis Project, while the other outputs provide additional information for various applications, such as initializing or evaluating a land-use change model or an economic general/partial equilibrium model. Furthermore, Moirai is a modular system that can be updated and customized through replacement and addition of source data.

Point of Contact
Alan Di Vittorio
Institution(s)
Lawrence Berkeley National Laboratory (LBNL)
Funding Program Area(s)
Publication