WEEK 1: Introduction to Climate Change
Weather and Climate
• Weather: actual/instantaneous state of atmosphere at particular time, easy to measure
o Important for making short-term decisions i.e. whether you bring umbrella
o Chaotic -> Even microscopic disturbances can lead to huge changes
o “Good” weather is relative -> Depends how you use land and your experiences
• Climate: statistical description of the weather over a period of time, usually a few
decades, much harder to measure (requires decades of data)
o More important for long-term i.e. choosing where to build vacation home
o Shaped by global forces that alter energy valves in atmosphere
o Average set of atmospheric conditions for given region
o We divide the world up into climate-types i.e. arctic, continental, tropical
• Commonly see extreme weather events linked to yields of some product or impact on
direct community
o Accurate in only some cases
• Weather hard to predict, climate very unpredictable
o Climate always changes in response to global forces
o Strongest force driving climate change right now is CO2, which traps heat of sun
• Temperature most often associated with climate, directly affects Earth’s inhabitants
o Most commonly discussed is average temperature, but extremes also matter i.e.
heat waves which can kill people
• Precipitation rivals temperature in importance because life without freshwater impossible
o Total annual precipitation of region, and distribution of rainfall throughout a year
o Form also important i.e. snow vs rain
• Two most important things we rely on to survive – food production and freshwater
availability – greatly affected by climate
Climate Normals and Anomalies
• Usually when analyzing climate, compare it to a “climate normal”
• Climate values typically presented as normal averaged over a 30-year period
• No quantitative reason necessarily to use 30 years, but having longer periods are better
for understanding variability, and captures information suitable for lifespan
• In earlier normal periods, air temperature tended to be cooler than later periods
• Just because there is a normal trend, doesn’t mean each year will map onto it exactly
o Should expect a bit of fluctuating variations in the data
o But if there is data extremely different from normal (i.e. warm spell indicated by
lots of data above normal) it is an anomaly
• Climate anomalies: deviations from a climate normal
o Anomaly = (observed valued) – (climate normal for same unit of time for a longer
or different time period)
o Useful because if you represent anomalies across space, you can see patterns
(deviations from normal) you wouldn’t see otherwise
• Temperature tends to be clumpy in representation while precipitation is noisier
• Important to remember we tend to get strong associations between climate anomalies
across long distances
o Especially temperature i.e. cold region in Kingston, expect cold period in Ottawa