Climate models and projections: a brief explanation
Weather models are used to create forecasts for just a few days at a time. Climate is more complicated because it’s about average conditions over long periods of time.
Therefore, climate models use just the most necessary parts of the system—such as ocean and atmosphere variability, land surface conditions, carbon or water cycles, or “forcings” such as solar activity or greenhouse gasses—to provide projections for long-term planning.
The usefulness of climate models is evident when we compare observed historical climate and simulated data—the models capture the most important climate patterns.
This 13-minute video—featuring SNAP's Nancy Fresco and Katie Spellman, a postdoctoral fellow at the UAF International Arctic Research Center—explains the importance and relevance of computer modeling in making sense of climate change.
SNAP uses a subset of model data
SNAP offers a five-model average comprised of output from the models—CCSM4, GFDL-CM3, GISS-E2-R, IPSL-CM5A-LR, and MRI-CGCM3—that best replicate historical surface air temperature, precipitation, and sea level pressure over Alaska and western Canada. For more detail, see the paper (Walsh et al. 2018) that describes the models, model selection process, and downscaling of model output.
Best practices for making climate projections
Use multiple decades and historical comparisons.
Averages across 20–30 years resist model variability and natural variations. Compare a future (like 2070–2099) to a historical reference (like 1981–2010)—the later the reference, the more climate change is already a part of it!
Choose a large area.
Larger areas are usually more resistant to local variation in elevation, vegetation, etc. than very small, hyper-local areas. Watersheds and planning units are good examples of large areas.
Use multiple emissions scenarios.
Human behavior is unpredictable, so pick at least two scenarios that bracket the likely range, unless you only want the “best” or “worst” case. RCP 4.5 and RCP 8.5 are good choices.
Use multiple models and/or an average.
All models are plausible, if not equally likely. Use several models if the full range of possibilities is important to your work.
SNAP's five-model average is comprised of the average output from the top five models that best replicate historical climate in Alaska and the Arctic. Best for: looking at climate trends over time, as it smooths annual and decadal variability. Not recommended for: exploring climatic extremes or annual variability, due to smoothing.
Include medium–term and longer–term futures.
A comprehensive assessment would consider a historical, a mid-21st century future, and a late-21st century future. The two futures should have a high, low, and middle range each, possibly with multiple models and multiple emission scenarios in each future window.
PRO TIP! Projections are always improving, but don’t wait for a better one—you’ll always be waiting, and the costs of waiting will increase. Instead, plan for the range of historical variability plus the range of climates described by a less warm (none show cooling!) climate model under a lower emissions scenario.