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Global Climate Models (GCMs) use our understanding of atmospheric physics and other earth processes to simulate potential future changes in climate on a global scale. However, these large scale models are not fit for predicting smaller scale, local changes. Downscaling methods can be applied to the outputs of GCMs to give guidance appropriate for a more regional level. No standard approach to downscaling currently exists, however, and the process often results in climate projections that suggest a wide array of possible futures. It is critical that decision-makers looking to incorporate climate information understand the uncertainties associated with different downscaling approaches and can evaluate downscaled data...
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Abstract (from International Journal of Climatology): The weather research and forecasting (WRF) model and a combination of the regional spectral model (RSM) and the Japanese Meteorological Agency Non‐Hydrostatic Model (NHM) were used to dynamically downscale selected CMIP5 global climate models to provide 2‐km projections with hourly model output for Puerto Rico and the U.S. Virgin Islands. Two 20‐year time slices were downscaled for historical (1986–2005) and future (2041–2060) periods following RCP8.5. Projected changes to mean and extreme temperature and precipitation were quantified for Holdridge life zones within Puerto Rico and for the U.S. Virgin Islands. The evaluation reveals a persistent cold bias for...
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