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The Climate Scenario Aggregator (CSA) seeks to reduce the technical barriers to access fundamental climate date through a web-based facility that facilitates downloading and aggregating global grids (0.5 degree) of bias-corrected, monthly mean historical and future temperature and precipitation from the five General Circulation Models (GCMs) used by the Inter-Sectoral Impacts Model Intercomparison Project (ISI-MIP; Hempel et al. 2013, Warszawski et al. 2014. ( HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, GFDL-ESM2M, and NorESM1-M.) The tool targets mainly, but not exclusively, researchers interested on the effects of climate change on agriculture. At the most general level, the CSA tool can be used as a downloading platform of the raw GCM data in the ISI-MIP archive. The target user of this functionality is skilled with NetCDF formats, has a relatively powerful computer, reasonable bandwidth, and is comfortable with the scripting and/or programming languages needed for manipulating and processing spatially-explicit data. A second target user may need some assistance with basic preprocessing of the data, such as temporal and spatial aggregation. This user will benefit from the aggregation programs as well as preprocessed datasets for temporal aggregation (crop calendars) and spatial aggregation (e.g., from gridcells to countries.) Finally, a third target user may be interested in the download and aggregation capabilities of the tool,
but wishes to employ alternative spatial aggregation schemes (e.g., gridded population.)
The Climate Scenario Aggregator (CSA) tool is fully documented in Villoria et al. (2016) and the accompanying user manual (both in the documents section of the tool). Users are encouraged to read the main article and the citations therein before using the data delivered by this tool.
We are grateful to the ISI-MIP coordination team at the Postdam Institute for Climate Impact Research (Postdam, Germany) for making the climate data discussed in this paper available as part of the ISI-MIP Fast Track project. The output of these models is in turn available to the public thanks to the efforts and coordination of the different climate modeling groups through the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project.
Hempel, S., K. Frieler, L. Warszawski, J. Schewe, and F. Piontek. 2013. “A Trend-Preserving Bias Correction – the ISI-MIP Approach.” Earth Syst. Dynam. 4 (2): 219–36. doi:10.5194/esd-4-219-2013.
Warszawski, Lila, Katja Frieler, Veronika Huber, Franziska Piontek, Olivia Serdeczny, and Jacob Schewe. 2014. “The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project Framework.” Proceedings of the National Academy of Sciences 111 (9): 3228–32. doi:10.1073/pnas.1312330110.
Villoria, Nelson B., Joshua Elliott, Christoph Müller, Jaewoo Shin, Lan Zhao, and Carol Song. 2016. “Web-Based Access, Aggregation, and Visualization of Future Climate Projections with Emphasis on Agricultural Assessments.,” https://mygeohub.org/tools/climatetool/
Villoria, Nelson B., Joshua Elliott, Christoph Müller, Jaewoo Shin, Lan Zhao, and Carol Song. 2016. “Web-Based Access, Aggregation, and Visualization of Future Climate Projections with Emphasis on Agricultural Assessments.” https://mygeohub.org/tools/climatetool/
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