Interpreting the Community Charts
SNAP community charts can be examined for certain key changes and threshold values. Higher mean monthly temperatures in the spring and fall may be of particular interest. This could signify a longer growing season, a loss of ice and/or frozen ground needed for travel or food storage, or a shift in precipitation from snow to rain, which impacts water storage capacity and surface water availability. Warmer, drier spring weather may also be an indicator for increased fire risk. In many locations, winter temperatures are projected to increase dramatically. Warmer winters may allow for the growth of species that are less cold-hardy (including both desirable crops and invasive species), or it may decrease snowpack and increase the frequency of rain-on-snow events that impact wildlife. Higher temperatures across all seasons will likely impact permafrost and land-fast ice.
How the Community Charts Were Derived
Information for each community is based on the closest 2 km by 2 km pixel from SNAP's datasets. The charts show historical PRISM climatology data and downscaled outputs averaged from five Global Climate Models (GCMs). Results are also averaged across decades. This averaging lessens the influence of normal year-to-year climate variability on projected values, and tends to make overall projection trends clearer. It is important to note that uncertainty is associated with each of these graphed values. Uncertainty stems from the modeling of atmospheric and oceanic movements used to create GCMs, from the PRISM downscaling process, and from the assumptions made regarding greenhouse gas levels for each emissions scenario.
Standard deviation of precipitation between the five models, averaged over space, time, and the three scenarios, ranges from about 5.8 mm to 13.8 mm with a mean of 9.8 mm. For temperature, this measure ranges from 0.5 degrees C to 2.1 degrees C with a mean of 1.1 degrees C. This assessment of variability on a scale that encompasses space, time, and scenarios is relatively small, particularly due to the averaging across space. By comparison, it is important to note that standard deviation across the five models for a particular spatial pixel may be as large as 500+ mm or 5+ degrees C.
In general, a higher percentage of uncertainty is associated with precipitation values than with temperature values. It should also be noted that although our models project increases in precipitation, water availability may decrease in some areas due to longer growing seasons and warmer weather.
For further information on SNAP projections, please explore our Methods section.