Meteorology: Understanding the Atmosphere Ackerman and Knox
Temporal Scale of Climate
The most information about the temporal variations of a parameter over a given time period is provided by a plot of the frequency of occurrence, or the number of observations in a given time interval. The figure below is a plot of the frequency of occurrence, or histogram, of the annual average temperature of Madison WI, in intervals of 5F. The average, standard deviation, and the maximum and minimum values are also given. This type of plot is very useful, but it is difficult to plot over a large region, which makes the mean of a variable very useful. Plotting the mean over time allows us to quickly identify fluctuations in time.
Studying climate requires caution in comparing observations from different regions of the world. Observations must be over the same time periods. Recent climate norms are determined by averaging weather elements over a 30-year time period. The average temperature in January is the average temperature of 30 consecutive years of the temperature during January at a location. The most recent averaging period is the period 1971 through 2000. An exceptionally warm winter may be termed abnormal because it falls outside the typically observed temperatures during this period.
Climatology is concerned with averages and variations about the average value. The annual total precipitation of Portland, Oregon (USA) and Montreal, Canada is similar; Portland has 39.8 inches and Montreal has 40.8 inches. The average precipitation for a month is nearly the same for the two cities. Portland's average monthly precipitation is 3.32 inches, while that of Montreal is 3.4 inches. The following figure demonstrates that the distribution of this precipitation throughout the year is very different for these two cities. Portland has distinct rainy (winter) and dry (summer) seasons while precipitation is evenly distributed throughout the year over Montreal. Variation about the mean is often expressed in terms of the standard deviation. Small standard deviations indicate little variations while large values suggest broad variations. The following statement provides more information about the annual precipitation of these two cities. The monthly mean precipitation for Portland is 3.3 with a standard deviation of 2.2; Montreal has a monthly mean precipitation of 3.4 inches with a standard deviation 0.3.
Extreme values (e.g., record maximum and minimum temperatures) are observations that occur only rarely. They are of particular interest in engineering. For example, in designing a building it is important to know the highest winds a building will have to withstand. When burying water pipes the maximum penetration of frost must be known to avoid any possibility of bursting pipes. Record temperatures for a particular day that are reported in weather reports are additional examples of extreme values of temperature.
There are several factors
affecting our climate. These factors combine to cause fluctuations on many
different time scales (Table 15.1). Factors that cause long-term fluctuations
in climate include the Earth's orbit about the sun and changes in ocean
circulation. Fluctuations on a shorter time scale can be caused by
changes in clouds and water vapor, and increased concentration of greenhouse
gases due to human activities. To address the issue of global warming, this
chapter provides examples of climate fluctuations caused by natural phenomena
as well as those due to human activities. The chapter also provides a
foundation to answer future questions that will arise about climate change.