Table 1 Advantages and limitations of statistical and dynamical downscaling procedures. Adapted from ref. 196
From: Systematic review of the uncertainty of coral reef futures under climate change
Advantages | Limitations | |
|---|---|---|
Statistical downscaling | • Computationally inexpensive and requires minimal expertise | • Assumes constant relationship between local and large-scale climate through time |
• May correct for biases in GCMs | • May not capture climate mechanisms | |
• Can be applied in data-scarce regions | • Limited ability to capture variability and extremes | |
• More flexibility in models and scenarios | ||
Dynamical downscaling | • Simulates climate mechanisms and more likely to capture key processes involved | • Computationally demanding, requires specialized expertise, and longer run-time |
• No assumptions of the relationship between current and future climate conditions | • Biases present in GCMs can extend and propagate to regional scales | |
• Technology advances constantly improving availability of regional climate models | • Results can be sensitive to uncertain parameterizations | |
• Limited flexibility, often tied to specific models and scenarios |
