The data presented in this tool are projections of future climate. They are not weather predictions and should not be treated as such. Weather is the behavior of the atmosphere over short periods, such as days and weeks. Climate is the long-term behavior of the atmosphere, and it is almost always expressed in averages—for example, average annual temperature, average monthly rainfall, or average water equivalent of mountain snowpack at a given time of year. In other words, climate is the statistics of weather.
Climate projections cannot tell us what will happen on a given date in the future. But they can tell us what to expect from our future climate in general: how much warmer the average July is likely to be, or how much less snow will accumulate in the mountains in the average winter. Climate projections can also tell us how much more often (or less often) extreme events such as heat waves and heavy rainfall are likely to occur in the future. However, they cannot predict when those events will actually occur.
Climate scientists create projections of future climate using powerful tools called global climate models. Global climate models are complex pieces of computer software that crunch through thousands of mathematical equations representing the scientific theory of how the climate system works. They can be used to simulate climate over past periods or to run experiments, in which scientists impose certain conditions on the model to see how the climate system responds. A future climate projection is the product of global climate model experiments in which scientists impose upon the model some scenario of the future atmospheric concentration of greenhouse gases.
When climate scientists run a climate model, they divide the area of study into a grid, and the model performs calculations for each individual cell within the grid. The output from those calculations can then be visualized on a map, similar to the visualizations in Cal-Adapt. In climate model projections, for any given snapshot in time, each grid cell is represented by a single value for temperature, precipitation, or other climate variable of interest.
The grid cells in most global climate models are very large—from 100 to 600 kilometers squared. This coarse resolution is OK when scientists are studying climate on the global scale, but it is not very useful when we are trying to understand climate change on smaller scales. We know that present-day climate varies greatly from region to region in California, and so we expect future climate to vary accordingly. But that detail is lost in the global climate models, in which all of California may be represented by just a few grid cells. To be able to plan for the future, we need to produce higher-resolution projections of future climate. Climate scientists do just that by using various techniques to "downscale" global climate model output to finer spatial scales. The data in Cal-Adapt is taken from a selection of global climate models, and downscaled to about 12-kilometer resolution.
The main driver of human-caused climate change is our emissions of carbon dioxide and other greenhouse gases into the atmosphere. Greenhouse gases are so called because they trap heat in the atmosphere, causing it to warm over time. Atmospheric warming in turn leads to other changes throughout the earth system. How much the climate changes in the future depends in large part on the amount of greenhouse gases we emit now and going forward. However, since our emissions of greenhouse gases depend on a variety of different social, political, and economic factors, we cannot be certain how they will change. But we can formulate educated guesses about how greenhouse gas emissions might change, and use those scenarios to create future climate projections.
Each tool in Cal-Adapt shows outcomes for two different greenhouse gas scenarios: a high-emissions scenario in which greenhouse gas emissions continue to rise over the 21st century, and a low-emissions scenario in which greenhouse gas emissions level off around the middle of the 21st century and by the end of the century are lower than 1990 levels.
Climate projections are our best approximations of future climate, but as with any statement about the future, there is no way to be certain they are accurate. One source of uncertainty in future climate projections is human greenhouse gas emissions. Projected climate data may not prove to be accurate if the actual emissions pathway we follow differs from the scenarios used to make the projections.
Another source of uncertainty in climate projections is the fact that different climate models—the tools used to simulate the climate system and produce future climate data—may produce different outcomes. There are more than 30 global climate models developed by climate modeling centers around the world, and they have different ways of representing aspects of the climate system. In addition, some aspects of the climate system are less well understood than others. Climate scientists are constantly working to improve our theories of the climate system and its representation in climate models. In the meantime, one way to account for model differences is to look at projections from as many different models as possible to get a range of possible outcomes. You can then take the average of the values across the different models, and this average value is a more likely outcome than the value from any single model. The default visualizations in this Cal-Adapt are based on the average values from a variety of models.
It is important to note that here the term "uncertainty" is being used in the scientific sense, to acknowledge that there is a range in possible future outcomes. When we discuss sources of uncertainty in the global climate models, we do not mean we are unsure whether climate change will affect California. That climate change is occurring and is caused by human activity is the consensus of the overwhelming majority of scientists engaged with the issue. Learn more the indicators of climate change in California. What is less certain is the extent to which the climate will change in the future, and precisely how the changes will affect natural and human systems.
f you have lived in California for any length of time, you know that our current climate experiences a great deal of natural variability. Some summers are much hotter than others, some winters produce more snow than others, and some fire seasons produce more burning than others. This natural variability will continue in the future, and it is expressed in future climate projections. Projections show that climate change will cause increases in average summer temperatures, reductions in average snowfall, and increases in average area burned by wildfire — but not every year looks like the average year. For example, in the future as in the current climate, some years will be hotter and some cooler. But overall, future years will be warmer compared with our current climate.
Climate projections tell us how conditions are likely to change on average; they cannot tell us what will happen on a given date in the future. Learn more about what climate projections can and cannot tell us.
The average values across different model projections is the default view on Cal-Adapt, and this outcome is considered more likely than any individual model value. But if you are trying to plan for the future, it is also important to look at individual model values and consider the full range of model outcomes. Learn more about uncertainty in model projections.
Since you know that averaging the results from different climate models is deemed more likely than any individual model, you might think this principle also applies the different greenhouse gas scenarios. However, it is not the case that averaging together the greenhouse gas scenarios gives you a more likely greenhouse gas emissions pathway, and you should avoid doing this. Instead, think of each greenhouse gas scenario as a separate possible future. Learn more about the greenhouse gas scenarios.
Because future climate projections express natural climate variability, analyzing a longer time period gives you a better sense of overall future conditions. In other words, if you analyze just a few years of a future climate projection, you might happen to select years that are anomalous. You will get a more accurate picture of future conditions if you look at a period of at least a few decades. Learn more about natural variability.