ClimRR Data

ADDA data layers visible in ClimRR represent a weather variable for an associated emissions scenario (e.g., mid-century RCP4.5). For each scenario, three GCMs are downscaled, producing three decades of weather data for each decadal scenario. By using the outputs from three different GCMs, rather than a single model, Argonne’s projections better account for the internal uncertainty associated with any single model.

Each model produces weather outputs for every 3 hours, or 8 modeled outputs per day. While this allows for a high degree of granularity in assessing future weather trends, there are many ways to analyze this data; however, there are several important common methodologies shared across all variables presented in ClimRR. Most variables are presented as annual or seasonal averages of daily observations, yet each annual/seasonal average draws upon all three downscaled GCM runs for that scenario and the ten years of data produced by each model. Therefore, each variable (e.g., total annual precipitation) for a given scenario (e.g., mid-century RCP4.5) is produced by calculating an individual estimate for each of the 30 years of weather data associated with that scenario, and then taking the average of the 30 estimates. This result is what we term the ensemble mean.