4.6 Chapter Summary

This chapter has introduced you to state-of-the art methods of bias correction (4.2) and downscaling (4.3) for calibrating climate model projections. Then, using pre-produced downscaled climate model data from the Pacific Climate Impacts Consortium (PCIC), we compared downscaled data to the raw model output and demonstrated how to assess the quality of downscaled data for the historical period (4.4). Finally, you learned standard methods of assessing the statistical significance of climate change signals in both raw and downscaled model output.

The examples in Sections 4.4 and 4.5 of this chapter all used data from a single model and ensemble member. As has been repeatedly emphasized, this is sufficient only for pedagogical purposes. Complete characterization of the uncertainty in climate projections (as covered in Chapter 2.3) requires an ensemble of simulations, ideally with multiple models and multiple ensemble members from each. More on model and ensemble selection will be covered in Chapter 5.

This chapter marks the end of the background material necessary for working on a climate downscaling project. The remainder of the UTCDW Guidebook will provide guidance on the decisions you’ll need to make when designing a climate impact study, and give further examples of the practical steps to implement the knowledge you’ve gained by working through the first 4 chapters.