CMIP5 UWPD: Probabilistic Downscaled Climate Data for North America

UWPD provides a probabilistic downscaling of CMIP5 climate models, predicting a daily Probability Density Function for precipitation and temperature rather than a single deterministic value. The dataset includes three variables at 0.1° resolution for the United States and southern Canada east of the Rocky Mountains. It contains multiple statistical realizations and derived statistics like means and annual maximum CDFs.

Use Cases

• Modeling regional climate change impacts based on probabilistic precipitation and temperature projections.
• Analyzing extreme weather event likelihood based on annual maximum precipitation CDFs.
• Comparing climate model scenarios using the ensemble member and realization structure.
• Assessing unexplained climate variability using the spatially and temporally varying PDFs.

Strengths

• Provides probabilistic outputs via PDFs for three key climate variables, capturing variability and extremes.
• Offers high spatial resolution (0.1°x0.1°) for a defined geographic region.
• Includes multiple realizations (3 for temperature, 14 for precipitation) and derived statistics like means and CDFs.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

NOAA, based on University of Wisconsin-Madison methodology and CMIP5 models.

Collection Method

Statistical downscaling of CMIP5 climate model outputs to create probabilistic PDFs for local-scale variables.

Time Range

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Freshness

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Geography

United States and southern Canada east of the Rocky Mountains.