Abstract
Global future land use (LU) is an important input for Earth system models for projecting Earth system dynamics and is critical for many modeling studies on future global change. Here we generated a new global gridded LU dataset using the Global Change Analysis Model (GCAM) and a land use spatial downscaling model, named Demeter, under the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios. Compared to existing similar datasets, the presented dataset has a higher spatial resolution (0.05° × 0.05°) and spreads under a more comprehensive set of SSP-RCP scenarios (in total 15 scenarios), and considers uncertainties from the forcing climates. We compared our dataset with the Land Use Harmonization version 2 (LUH2) dataset and found our results are in general spatially consistent with LUH2. The presented dataset will be useful for global Earth system modeling studies, especially for the analysis of the impacts of land use and land cover change and socioeconomics, as well as the characterizing the uncertainties associated with these impacts.
Highlights
Background & SummaryLand use (LU) change represents one of the most important human effects on the Earth system[1,2], with profound physical and biogeochemical impacts at both regional and global scales
Global Change Analysis Model (GCAM) projects the evolution of the land use (LU) mix with up to 39 land cover types
Note that the GCAM Land Types (GLTs) are primarily classified according to ag-economic sectors and from the land use perspective, have to be reconciled to user-defined final land types (FLTs) which are directly applicable to Earth system models (ESMs) with user-defined rules[34]
Summary
Land use (LU) change represents one of the most important human effects on the Earth system[1,2], with profound physical and biogeochemical impacts at both regional and global scales. LUH2 classifies the land into five land use states (cropland, pasture, primary, secondary and urban) and 12 sub-states, in a classification system by emphasizing human activities (e.g., primary vs secondary) This classification system cannot be directly used in many of the land models of ESMs, which typically use plant functional types (PFTs)[19,20,21], with detailed classification according to the physical, phylogenetic and phenological characteristics of the land covers. We started from GCAM v4.3, but incorporated water basin level modeling of water supply and demands[28], distinctions between renewable and nonrenewable water sources[29], and socioeconomic scenario specific water demand responses[30], and used it to provide LU projections at the intersection of geopolitical regions and water basins at 5-year time step[31] (Fig. 1). We anticipate that the dataset will be widely used by researchers in ecological modeling, Earth system modeling, land-atmosphere interactions, agriculture, energy market, water resources management, and socioeconomic analysis, to investigate the complex feedbacks between each of these Earth system components, and better understand the role of human activities in these processes
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