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NASA Global Daily Downscaled Projections, CMIP6
Bridget Thrasher1, Weile Wang2, Andrew Michaelis2
1Climate Analytics Group, Boulder, CO, 80305, USA. bridget@climateanalyticsgroup.org.
Scientific Data
|June 2, 2022
Summary
NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) offers updated climate data. This archive provides downscaled historical and future climate projections from 1950-2100 for climate change research.
Area of Science:
- Climate Science
- Earth System Science
- Environmental Modeling
Background:
- The Climate Model Intercomparison Project Phase 6 (CMIP6) provides crucial climate projection data.
- Downscaled climate data is essential for regional impact assessments and adaptation planning.
- Previous versions of NEX-GDDP have been widely used by the research community.
Purpose of the Study:
- To introduce and describe the latest version of the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset.
- To provide researchers with access to high-resolution, downscaled climate projections for a range of future scenarios.
- To support climate change impact studies by offering reliable historical and future climate data.
Main Methods:
- Utilized a daily variant of the monthly bias correction/spatial disaggregation (BCSD) method for downscaling.
- Processed output from thirty-five global climate models participating in CMIP6.
- Achieved a 1/4-degree horizontal resolution for all downscaled products.
Main Results:
- The NEX-GDDP-CMIP6 archive now includes downscaled projections spanning 1950-2100.
- Data is available for five CMIP6 experiments: historical, SSP126, SSP245, SSP370, and SSP585.
- Eight key climate variables are provided, offering a comprehensive dataset for analysis.
Conclusions:
- The NEX-GDDP-CMIP6 dataset represents a significant advancement in the availability of high-resolution climate projection data.
- This updated archive will facilitate more accurate and detailed climate change impact assessments.
- The accessibility of this data from numerous global climate models enhances its utility for diverse research applications.
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