Global land use for 2015–2100 at 0.05° resolution under diverse socioeconomic and climate scenarios
Autor: | Maoyi Huang, Katherine Calvin, Mohamad Hejazi, Yanyan Cheng, Chris R. Vernon, Min Chen, N. T. Graham |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Statistics and Probability
Data Descriptor 010504 meteorology & atmospheric sciences Land use Global change Representative Concentration Pathways Forcing (mathematics) Land cover 010501 environmental sciences Library and Information Sciences 01 natural sciences Projection and prediction Computer Science Applications Education Earth system science Metadata Climatology Environmental science lcsh:Q Statistics Probability and Uncertainty lcsh:Science Climate and Earth system modelling 0105 earth and related environmental sciences Information Systems Downscaling |
Zdroj: | Scientific Data, Vol 7, Iss 1, Pp 1-11 (2020) Scientific Data |
ISSN: | 2052-4463 |
Popis: | 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. Measurement(s) land use process • global land use and land cover Technology Type(s) computational modeling technique Factor Type(s) year of data collection • Shared Socioeconomic Pathways scenarios • Representative Concentration Pathways scenarios Sample Characteristic - Environment land Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12967760 |
Databáze: | OpenAIRE |
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