Snow Algae Model Data: Global Surface Concentration and Simulation Output

A dataset for numerical simulation using the snow algae model (Onuma et al., 2018; 2020). It contains algal cell concentration observed on surface snow worldwide, along with model input, output, and visualization scripts. The data and code were created by Yukihiko Onuma of The University of Tokyo.

Use Cases

• Calibrating and validating the snow algae model based on observed global surface concentration data.
• Analyzing spatial patterns of snow algae blooms using the provided geospatial concentration data.
• Visualizing model simulation results with the included Python scripts for creating figures.
• Comparing simulated snow algae dynamics from Bio-MATSIRO against field observations.

Strengths

• Includes both observed field data (algal cell concentration) and corresponding model simulation outputs.
• Provides associated Python scripts for data visualization, facilitating reproducibility.
• Data is linked to a specific, peer-reviewed model (Onuma et al., 2018; 2020) from a research institution.

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

Yukihiko Onuma, The University of Tokyo.

Collection Method

Likely combines field observations with outputs from the Bio-MATSIRO model.

Geography

Global surface snow coverage.