If you are a regular user of the Climate Atlas, then you’ve probably noticed that the climate data presented on the map and throughout the site has changed.
This is because the Atlas now uses a new and more robust climate projection dataset provided by the Pacific Climate Impacts Consortium (PCIC). The new data contains 24 climate models (double the number used in the previous version of the Atlas) and was created using a statistical method called BCCAQv2 that offers important improvements over the old BCSD method. (Our “Data and Methods” page goes into more technical detail if you’re interested.) This switchover brings the Climate Atlas into alignment with other national climate data websites, such as climatedata.ca.
As a result of this update, many of the average and extreme values presented across the Atlas and in our various reports have changed somewhat. Importantly, this doesn’t mean that the previous values were wrong or aren’t still valuable for understanding climate change. Both the new BCCAQv2 data and the old BCSD data reflect consistent warming trends and regional patterns. There are some differences in detail between the two sets of model data, but their outcomes are vastly more similar than they are different.
There are several reasons for the change in values.
More climate models
In climatology, it is standard practise to use many climate models when analyzing future climate changes. This is because no single climate model can ever be considered “best”. Each model has its own strengths and weaknesses. (See our “Climate models” page for more details.)
By comparing the results from many models, climatologists can see where the models agree and disagree. For variables like temperature, the models almost always agree on the direction of change (warming) but more often disagree with each other on the magnitude of the change (how much warming).
By doubling the number of models used to create the Climate Atlas maps we hope to become more confident in the direction of the climate changes indicated by the data. However, we can also expect to find a larger range between the hottest and coldest (or wettest and driest) models than we did before, using only half as many models. These changes in extremes will be reflected in changed mean values, too.
Sensitivity of extremes
A seemingly small change in a location’s climate (for example, its mean temperature) can result in shockingly large changes in the number of extreme events (such as the number of +30 °C days). Why is this?
Extremes are, by definition, rare. Most of the time, the climate hovers close to the average. But as the climate warms, the ‘new average’ moves closer to the old threshold for what was considered an “extreme” event—meaning many more days now risk being counted as extreme.
As an example, consider the following table which highlights just two of the 24 climate models used in the Atlas:
Scenario: RCP8.5 (“High Carbon”)
Location: Winnipeg, Manitoba
Future Period: 2051-2080
| Model | Increase in average annual temperature | Increase in average number of +30 °C days per year |
|---|---|---|
| GFDL-ESM2M | +2.6 °C | +13 |
| bcc-csm1-1 | +4.4 °C | +33 |
Both of these models agree that the average annual temperature in Winnipeg will increase under this scenario; however, they disagree on the magnitude of the change. The seemingly small difference in the projected mean temperature--a difference of only 1.8 °C--results in a very large difference in the number of very hot days for this location. The bcc-csm1-1 model projects that Winnipeg will experience an additional month of these very hot days, more than double the number projected by the other model. This dramatic rise in extremes is a direct result of a relatively small shift in the mean value.
This example also illustrates why it is helpful to take the average value of many climate models, to capture their overall agreement about the magnitude of projected change.
Adding more climate models to the Climate Atlas very often increases the total range of model projections one can expect to find when one clicks on the map. And, as we’ve just demonstrated here, even very small differences in the average can generate very large changes in extremes.
New downscaling method
The data we use in the Climate Atlas has the somewhat strange sounding name of BCCAQv2.
BCCAQv2 is actually the short-hand name (acronym) of an advanced statistical “downscaling” method (you can learn all about it from our “Data and Methods” page). PCIC uses this method to take raw global climate model projections and make them usable at a local scale, hence the name downscaling. There are many downscaling methods to choose from. PCIC has evaluated many of them and determined that BCCAQv2 is one of the best for Canadians.
This downscaling method differs greatly from the method used in the previous version of the Climate Atlas. The older method, called BCSD, is much simpler. Although it did a fine job—meaning it was able to downscale average values to a local scale when suitably long periods of time were used—it has been shown to do a poorer job of translating climate extremes over shorter time periods. The new BCCAQv2 method was specifically introduced to reduce, as much as possible, the effect of this known deficiency.
The BCCAQv2 method allows us to calculate climate values that weren’t possible before, and also gives us more confidence in many of the precipitation-related values in the Atlas. But using a new downscaling method also contributes inherent variability to differences between the two sets of model data.
What should I do if the numbers I was using in my community have changed?
The projected values from the BCSD data in version 1 of the Atlas are still relevant, and can be used with confidence to understand and plan for change. The new BCCAQv2 data represent a significant improvement in method, however, and may be preferred, especially when working with precipitation.
It’s important to note that each set of data is internally consistent, but can’t easily be compared to one another. Thus, it’s best to not mix and match numbers from the two versions.
Just as no single climate model can ever be considered ‘best’, no single methodology can ever fully resolve future climate changes into a single ‘best’ number for your community. As climate science evolves, utilizing more powerful and detailed climate models, so too will our resolution of future climate change impacts.
We hope that this update will help you and your community by:
- increasing the confidence in the direction of future climate changes by using more climate models,
- better resolving future changes in climatic extremes by using a more advanced downscaling methodology; and
- improving our confidence in projected precipitation changes by capturing more detailed temporal patterns in precipitation.
At the Prairie Climate Centre, our continuing goal is to stay on top of the latest research and to provide Canadians with the most up-to-date information possible. Together, we hope to continue to generate a clearer picture of what the future has in store, so we can all move collectively from risk to resilience.
Recommended Article Citation
Climate Atlas of Canada. (n.d.) Climate Atlas v2: Why have the Numbers Changed? Prairie Climate Centre. https://climateatlas.ca/climate-atlas-v2-why-have-numbers-changed
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