EPA Dynamically Downscaled Ensemble (EDDE): Datasets for Adaptation and Resilience Planning for Environmental...

Area of Science:

• Environmental science
• Climate modeling
• Atmospheric science

Background:

• The U.S. Environmental Protection Agency (EPA) developed the EPA Dynamically Downscaled Ensemble (EDDE) to address a need for comprehensive climate data.
• Existing climate datasets lacked the breadth and temporal resolution required for detailed impact assessments.

Purpose of the Study:

• To describe the history, evolution, applications, and future of the EDDE dataset.
• To highlight EDDE's utility in projecting climate change impacts across the United States.
• To support strategic development, adaptation, and resilience planning.

Main Methods:

• Utilizes the WRF Model for dynamical downscaling of global climate simulations over North America.
• Includes hourly, 3D data from continuous simulations for historical periods and future projections through 2100.
• Covers various forcing scenarios for the twentieth and twenty-first centuries.

Main Results:

• EDDE provides high-resolution regional climate projections essential for understanding climate variability and change.
• The dataset enables quantification of climate change impacts on air quality, human health, ecosystems, and agriculture.
• EDDE data have been integral to national climate assessments, including NCA4, and are planned for NCA6.

Conclusions:

• EDDE is a valuable resource for exploring regional climate impacts and informing decision-making.
• The availability of EDDE data, including via AWS Open Data, enhances accessibility for researchers and planners.
• The evolution of EDDE reflects the growing need for detailed regional climate datasets to support climate resilience efforts.