1. Climate information for community decision making May 2016 North Saanich Residents Association North Saanich, BC
Photo: F. Zwiers
Trevor Murdock
Climate Scientist
Pacific Climate Impacts Consortium

2. Nutrition Facts Serving Size 1 presentation Amount Per Serving
Slides Minutes 45
% Daily Value*
Maps 25
90%
Diagrams 3
50%
Plots 3
Photos 2 5%
Cartoons 0 0%
Humour
* Percent Daily Values are based on a diet of one annual meeting.

3. Refresher Weather is at a given location on a given day
02 Dec 2005
19oC sunny in Montreal
-5oC snowing in Victoria
Climate is the long term statistics of weather
average December
4°C, 14 cm snow Victoria
-6°C, 48 cm snow Montreal
Weather is at a given location on a given day
02 Dec 2005
19oC sunny in Montreal
-5oC snowing in Victoria
Climate is the long term statistics of weather
average December
4°C, 14 cm snow ________
-6°C, 48 cm snow ________
Weather is at a given location on a given day
02 Dec 2005
19oC sunny in _____
-5oC snowing in ______
3: Climate baseline (2 min)
Before we examine BC’s climate baseline, let us elaborate on what we mean by climate baseline using a real example.
My voice: On December 2nd, 2005, I was at an international climate conference in Montreal. When I phoned my family back home in Victoria we compared notes on the weather we were each experiencing. In one place it was 19 degrees Celsius and sunny, in the other it was minus 5 degrees Celsius and snowing.
Back to narrator Which place was 19 degrees Celsius and sunny? What is your guess? Select A for Victoria and B for Montreal.
After their choice: It was 19 degrees Celsius and sunny in Montreal. This is counter-intuitive because we know that during winter in Victoria it is usually warmer and snows much less than in Montreal. However, we also know that the weather on a given day can differ greatly from our expectation. For this reason, when this question is asked of a large number of people, there are usually roughly equal numbers of people making choice A as choice B.
Now the bottom part of the screen comes in but with the blanks for the locations: What if we ask a different question about the difference between winters in Victoria and Montreal, on average? The average December conditions during the 30 year period from 1971 to 2000 are 4 degrees Celsius and 14 cm of snow in one location and minus 6 degrees Celsius with 48 cm of snow in the other location. Now what is your guess? Which one do you think was minus 6 degrees Celsius with 48 cm of snow. Select A for Victoria and B for Montreal.
After their choice: The correct answer is B. Even though on December 2nd of 2005, it was much warmer in Montreal and it was snowing in Victoria, normally it snows more and is colder in Montreal. When asked this way, virtually everyone who is familiar with these locations selects the correct choice. This demonstrates that we intuitively know what a climate baseline is and how it differs from weather.

4. Climate variability with location*
Warming has spatial variability – examples of extreme events European heat wave. The 2003 European heat wave was the hottest summer on record in Europe since at least 1540.[1] France was hit especially hard. The heat wave led to health crises in several countries and combined with drought to create a crop shortfall in parts of Southern Europe. Peer reviewed analysis places the European death toll at 76,000.[2]
Temperature Anomaly 0C

5. Climate variability with location
750,000 hectares *
The summer of 2010 brought intensely hot weather to large portions of the northeastern U.S., central Europe, and Russia. Russia was especially hard hit as a heat wave — with daily high temperatures hitting 100°F — contributing to the deaths of as many as 15,000 people in Moscow while wildfires tore across more than 2,900 square miles in the central and western part of the country. Drought accompanied the record high temperatures decimating more than a quarter of Russia’s grain harvest. Economists estimated the grain losses cost the Russian economy upwards of $15 billion dollars.
Temperature Anomaly 0C

6. Climate variability with location* *
Temperature Anomaly 0C

7. Climate varies in space*
Temperature Anomaly 0C

8. Outline Historical climate & variability Planning for future climate
long term statistics of weather
varies with location
Planning for future climate
Projected climate change

9. Climate variability is ongoing - need to plan for variability
Climate Normals
Climate Variability
Short term : (years to decadal) rises and falls about the trend line (ENSO)
Climate Oscillations
Multi-decadal oscillations in regional climate: (e.g. PDO)
Climate Change
Long Term Trends or major shifts in climate: (centuries)
Long term averages (e.g., )
“Normals” change
Climate variability is ongoing - need to plan for variability
Note that short-term negative trends in climate warming will occur

10. Trends Can historical trends be extended to predict the future? a) Yes
b) No

11. Trends Can historical trends inform future projections?
Yes – they give context
Yes – they reflect what actually happened
Yes – more certain than climate models (maybe)
Can historical trends alone predict the future?
No – the climate system is not linear
No – trends change through time
No – even the direction of change can depend on the historical period considered

12. Outline Historical climate & variability Planning for future climate
long term statistics of weather
varies with location & time
historical trends insufficient to plan for future
Planning for future climate
Projected climate change

13. Regional temperature / precipitation differences  different water supply vulnerabilities

14. The future Estimated future conditions are needed for planning OR
We can we become more resilient to change instead

15. The future
Estimated future conditions are needed for planning AND We can we become more resilient to change instead Estimated future conditions  prioritize how to become resilient to change

16. Assess vulnerability & increase resilience: iterative process

17. Brainstorming: Climate change impacts in North Saanich

18. Outline Historical climate & variability Planning for future climate
long term statistics of weather
varies with location & time
historical trends insufficient to plan for future
Planning for future climate
detailed estimates of future conditions are useful but planning can begin without them
Projected climate change

19. Global Climate Model temperature
Courtesy CCCma
CGCM3

20. Projected BC warming

21. Outline Historical climate & variability Planning for future climate
long term statistics of weather
varies with location & time
historical trends insufficient to plan for future
Planning for future climate
detailed estimates of future conditions are useful but planning can begin without them
Projected climate change
Projected warming is considerable compared with historical variability
Amount of warming depends on emissions/policy

22. Warming

23. Shorter frost free period

24. Double the pineapples by 2050s

25. Precipitation: Wetter extremes
Precipitation 1-in-20 wet day event
baseline: 100 mm 2050s projected change: 45% increase

26. Precipitation: Drier Summers
Summer Precipitation
baseline: 90 mm
2050s projected change: 20% decrease

27. Ecosystem Impacts: Species Changes
Growing Degree Days (GDD)
baseline: 1500 degree-days
2050s projected change: 45%

28. Sea Level Rise http://www.env.gov.bc.ca/cas/adaptation/sea_level.html
Guidelines based on 1 m / 2100

29. Brainstorming: North Saanich Impacts
warm & hot days in summer
growing, cooling & frost-free days precipitation in winter
wet days winter, spring, and esp. autumn
sea level rise
summer precipitation/wet days
snowpack

31. Take away messages Climate varies in space and on multiple time scales
Climate models: tools for projecting future climate
Projected impacts include
warming
reduced snowpack
changes to species suitability
changes to precipitation (wet wetter and dry drier)
extremes
storminess
sea level rise
hydrological impacts
ocean acidification
Climate information can help plan for increased resilience

32. Questions?
Thank you For more information and