Tribal Climate Tool

This visualization tool enables users to explore and download climate change projections and climate change summaries for priority geographies at the scale of tribal decision-making.

Exploring Uncertainty

There are three primary sources of uncertainty in climate change projections: (1) global climate models, (2) greenhouse gas scenarios, and (3) downscaling climate datasets.

Note: This text is largely excerpted  from the Climate Impacts Group’s State of Knowledge Report: Climate Change in Puget Sound and from the Climate Impacts Group Time of Emergence site.

Global Climate Models (GCMs)

Global climate models (GCMs) are designed to represent the processes controlling Earth’s climate. These models incorporate the state-of-the-art in climate science. As a result, they are periodically updated as the science progresses.

It is important to consider a range of projections among multiple different climate models. Each model simulates the earth’s climate using a different set of approaches. As a result, each model provides a unique estimate of the response of the climate to greenhouse gasses in the atmosphere. In addition, the timing and sequence of natural climatic variability is unpredictable, and is therefore unique for each climate model simulation. For example, all models represent the El Nino Southern Oscillation, but El Nino and La Nina events occur in different years and sequences in the different models. For a given amount of greenhouse gas emissions, the range among climate model projections encompasses both the variability due to different climate models, as well as natural variability. There is no single “best” global climate model, so a recommended approach is to use multiple models to assess potential changes in the climate.

The range among climate model projections may not encompass the full range of potential future climate changes. The range of climate projections among models provides an estimate of the uncertainty in projections. However, we cannot rule out the possibility that future changes in climate will be outside of the range projected by climate models.

Greenhouse Gas Scenarios

How much and how fast the climate changes depends on both the amount of future greenhouse gas emissions and how the climate system responds to those emissions. Irreducible uncertainty in both future greenhouse gas emissions and the climate system’s response means that projections of future climate will always be represented by a range of plausible outcomes.

  • Since it is impossible to predict the exact amount of greenhouse gas emissions that result from future human activities, scientists use scenarios to represent a range of conditions for future greenhouse gasses in the atmosphere.
  • It is also impossible to know the likelihood of different scenarios. Since greenhouse gas scenarios depend on uncertain predictions of economic development, policy, and human behavior, it is not possible to assign likelihoods to different scenarios or know which greenhouse gas scenario is most likely to occur.
  • It is important to consider a range of potential outcomes. There is no “best” scenario, and the appropriate range of scenarios depends on the specific climate impact under consideration. Deciding which scenario(s) to use involves clarifying how climate affects a particular decision and what level of risk is acceptable.
  • Projections will continue to be updated over time. As the science of climate change progresses, new greenhouse gas scenarios and updated climate models will inevitably replace the current climate projections.

Downscaled Climate Datasets

Global climate models simulate future climate for the globe at a resolution or scale that is too large to be useful for regional- or local-scale applications.

A process known as “downscaling” increases the detail, or precision, of global-scale climate projections to provide information that is more relevant to regional and local management or operations. There are different approaches to downscaling, each with their own strengths and weaknesses. No single downscaling approach is superior. A statistical downscaling approach is used for the climate data available in the Tribal Climate Tool.

Note: Increasing resolution or scale (i.e. level of detail) does not necessarily imply increasing accuracy (i.e. capturing the true value). More detail in climate model projections does not necessarily mean there is greater confidence or certainty in projections.

How to Use and Interpret Results from the Tool

The projections in this tool should be used to interpret trends across geographic regions, not specific locations (e.g., specific buildings or roads). While downscaling global climate models enables us to better understand the projected changes in climate across smaller spatial scales (e.g., across states or watersheds), constraints on the use of downscaled climate data do exist.  There are limitations and spatial gaps in the historical climate observations used to downscale the data.  For example, limited measurements of historical temperatures at high elevations makes the data less reliable at high elevations. As a result, the projections provided in this tool are best used to interpret trends in climate across relatively large geographic areas, such as watersheds, or for areas that are relatively similar in terms of geography and historical climate.  Projected changes in climate trends for a specific location within your tribe’s preferred geography should be interpreted with caution given the known limitations of downscaling global climate projections.

When using this climate tool it is important to consider a range global climate models because each model uses a different set of approaches to simulate the earth’s climate. However, rather than focusing on small differences among global climate model projections, we recommend emphasizing the overall trend or direction of the projected changes in the climate. For example, we recommend asking questions such as “are all models projecting warming air temperatures by mid-century?”, rather than “how many global climate models project 4.1°F of warming by mid-century?”

The climate variables you examine with the Tribal Climate Tool should be driven by the focus of the tribe’s vulnerability assessment. For example, an assessment evaluating future flood risk will likely want to focus on projected changes in winter precipitation and projected changes in peak streamflow, as these variables are drivers of winter flooding. Conversely, a vulnerability assessment evaluating the projected change in suitability of salmon habitat may want to focus on projected changes in stream temperatures and summer streamflow. It is critical to identify the appropriate drivers of climate-related impacts the vulnerability assessment is focused on.

The climate variables in the Tribal Tool are presented for three time periods in the 21st century:

  • 2010-2039
  • 2040-2019
  • 2070-2099

Climate projections take a longer-term view to and are often centered around thirty-year averages. This longer time window enables climate models to capture interannual and decadal patterns of natural variability in the climate system (e.g., ENSO and the Pacific Decadal Oscillation).

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