Intercomparison Data for 1-D Lake Thermal Regime Algorithms

The Inter-sectoral Impact Model Intercomparison Project (ISIMIP) 2a lake sector provided a highly diverse lake dataset for evaluating four key lake thermal processes. Algorithm codes for turbulent heat fluxes, wind-driven mixing, light extinction, and snow density were configured and run separately within the same parent model. The study by Mingyang Guo of Purdue University West Lafayette provides practical guides for improving 1-D lake models and feasible parameterization strategies.

Use Cases

• Evaluating turbulent heat flux algorithms based on their performance in predicting lake epilimnion temperatures.
• Assessing wind-driven mixing strategies based on lake shape and seasonal considerations.
• Comparing light extinction algorithms based on their simulated thermocline depths.
• Parameterizing snow density for lake ice phenology models based on regional differences, such as for Arctic lakes.

Strengths

• Algorithm codes were run separately within the same parent model to rule out interference from other factors.
• Evaluations are based on both simulation accuracy and recalibration complexity for application to global lakes.
• The study provides specific parameterization findings, such as a constant snow density of around 110 kg m⁻³ for most northern lakes.

Limitations

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

Provenance

Source

Inter-sectoral Impact Model Intercomparison Project (ISIMIP) 2a lake sector

Collection Method

Algorithm codes configured and run separately within a parent model for evaluation.

Geography

Global lakes, with specific findings for northern and Arctic lakes.