PQG Numerical Tests: Stochastic Model Data for Three Evaporation Rates

Three data sets of PQG (likely a stochastic model) numerical test results with evaporation rates of E=0.02, E=0.2, and E=0.35. The data was created by Changhong Mou from the University of Wisconsin–Madison for the paper "Combining Stochastic Parameterized Reduced-Order Models with Machine Learning for Data Assimilation and Uncertainty Quantification with Partial Observations". The data is stored in MATLAB (.mat) file format.

Use Cases

• Testing data assimilation algorithms based on the described stochastic parameterized reduced-order models.
• Benchmarking uncertainty quantification methods using the provided data sets with different evaporation rates.
• Developing or validating machine learning models for dynamical systems based on the partial observations scenario described in the source paper.

Strengths

• Data is directly associated with a published research paper, providing academic context.
• Includes three distinct data sets defined by specific evaporation rate parameters (E=0.02, E=0.2, E=0.35).

Limitations

• Row count, file size, and specific column definitions are unknown, limiting suitability assessment.
• Description metadata is limited; actual data quality and structure require manual inspection after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Changhong Mou, University of Wisconsin–Madison

Collection Method

Likely generated from numerical simulations of a stochastic parameterized reduced-order model, as described in the associated paper.