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Introduction
We have reviewed the scientific consensus on how the chemistry of
the atmosphere is changing. We also have estimated future changes in
atmospheric composition. And most recently, we have reviewed calculations
of the change in radiative forcing that will result from various policy
scenarios on energy generation and regulation of other sources of
greenhouse gases. Now we take the next step and translate these changes in
radiative forcing into changes in climate of the earth. We first examine
what we mean by climate change.
Changing Climate
In our discussion of climate change we can consider change of three types
Important Climate Change Questions
The real questions, then, are not whether climate of the future will
change, because we know it will.
| The more important questions are: | Examples: |
|---|---|
| What elements of climate are changing? |
Is the surface temperature at Alexandria Egypt changing? Are the number of hurricanes per year in Florida on average different than during some previous time? Does the rainy season begin at a different time of year now compared to the previous century? |
| In what direction are they changing? | Is the temperature going up or down? Are there more or less hurricanes than previously? Does the rainy season in India start earlier or later than in the previous century? |
| How much are they changing? | Is the change in temperature Are there 1%, 10%, or 100% more hurricanes than the previous period? Does the rainy season start a day later, a week later, or a month later than in the previous century? |
| For what reasons are they changing? |
Has the city grown up around the historical measurement
site? Is the Gulf of Mexico water temperature higher than some previous time? Have humans somehow perturbed the mechanisms that cause rainfall? |
| What should we do about it? |
Nothing Take collective (political) action to limit emission of greenhouse gases Adopt a less-consuming personal lifestyle Let private industry determine when and how to mitigate climate change |
In the next several units we will define climate and examine the means by which we can calculate the influence of natural and anthropogenic factors in causing climate change.
Climate
We begin by defining what we mean by climate. I received an e-mail
from a colleague in France and at the bottom of his
signature line was the message: "Climate is what we expect and weather is
what we get." This says it in a nutshell. Weather is day-to-day values
of temperature, rainfall, pressure, winds, etc., and climate is the mean of
these variables over some suitably long period of time.
But climate encompasses more than just weather variables. A more general definition of climate is the average behavior of the land, ocean, atmosphere, cryosphere (ice masses), biosphere system over relatively long periods of time. There is not a rigidly defined period for the averaging process, but for many operational applications a 30-year period is used. This definition acknowledges the interactive role of land, water, and ice in determining atmospheric properties. The cryosphere includes the ice masses of Antarctica and Greenland as well as North Polar sea ice and mountain glaciers. Ice masses are very important because their physical dimensions can change, thereby changing the amount of radiation reflected from the surface of the earth. They also are repositories for enormous amounts of H2O, and so their change in volume influences the amount of liquid and gaseous water in the atmosphere and liquid water in the ocean.
Time Scales of Change
The difficulty of defining appropriate time scales for the climate
system can be better appreciated by considering the residence time of a
water molecule in various components of the climate system. If we put some
water vapor into the atmosphere and tracked the molecules through the
hydrological cycle, we can examine the different time scales. Water
molecules remain in the atmosphere for about two weeks, on average, before being
precipitated out. If they fall in the ocean, they may remain in the upper
layer (top 100 meters) for a couple of months, but if they are by some
process moved to the deep ocean they may reside there for thousands of
years.
Water molecules that fall as precipitation on land might evaporate within the day or might go into the soil and migrate through the groundwater to a stream or lake and then be re-evaporate after a period of maybe six months to two years. If the water molecule is taken up by a plant, it might stay in the biosphere for the growing season before being returned to the soil or atmosphere. If the atmospheric water molecules are deposited on the Antarctic Ice sheet, they might be locked away for 100,000 years. Clearly, different components of the climate system have different time scales. Those components of the climate system that have very long time scales, such as the Antarctic ice sheet, can be considered as unchanging when we are evaluating changes in atmospheric and oceanic circulation. Others, such as the amount of sea ice in the ocean over the North Pole which has a lifetime of half a year, must be considered as part of the changing component of climate.
In summary, the atmosphere responds quickly to climate changes, but the biosphere, surface ocean, deep ocean and ice masses respond successively slower.
Components of the Climate System
Figure 1 illustrates, in the broadest sense, the various
components of the climate system. The physical components of the earth or
climate system are given in capital letters: atmosphere, ocean, earth,
land, ice-sheets and snow, biomass, and sea-ice, and space. The atmosphere,
with its major gases, trace gases, clouds and aerosol, is influenced from
space by radiation and from the underlying solid and liquid surface of the
earth by a variety of processes.
External and Internal Influences
To better organize the factors that relate to climate, we can
define internal influences and external influences of the climate system.
External influences, which are illustrated in
Figure 1 by arrows
crossing the exterior boundary of the domain, are those that do not respond
to changes occurring within the climate system we have defined. For
instance, fluctuations in solar emission and variations in the earth's
orbital parameters are external influences since they do not change if the
earth's climate warms or cools. Anthropogenically produced greenhouse
gases and dust and changes of albedo of the earth's surface due to human
activity are generally considered external influences, although it could be
argued that humans are a part of the larger definition of climate.
Internal conditions include such factors as variations in ocean surface temperature, changes in reflectivity of the surface due to seasonal changes in vegetation or snow cover. Ocean water salinity (saltiness) also is internal to the climate system because it depends on the local amount of rainfall (which dilutes the salt content of surface water) or flow of rivers into the ocean. We will see later that, because salt water is more dense than fresh water, salinity is a very important factor in driving ocean circulation. Fresh water from precipitation or melting sea ice tends to float on top of salty water and suppress the mixing to deeper layers.
Chaos and Climate
One final comment on internal influences relates to the concept of
chaos. We will see in a later unit that the climate system can be
described by a set of time-dependent, coupled, nonlinear, first-order,
partial differential equations. Professor Ed Lorenz, meteorologist at MIT,
discovered some thirty years ago that systems described by such a set of
equations have the property of being "almost intransitive".
"There are extremely simple and also very complicated systems of equations possessing solutions which behave in one manner for an extended period of time, and then change more or less abruptly to another mode of behavior for an equally long time. Such systems have been described as almost intransitive." (Lorenz, 1970)
Solutions to these equations give a set of weather conditions that vary over a confined range of values for an extended period of time and then more or less abruptly change to some other confined range for another (but likely different) extended period. A simple example of this is the dripping water faucet which drips at a steady rate for a period of time, then suddenly, for no apparent reason, drips very rapidly for a short period and then reverts to a slower (but different from the original) rate. The theory describing these systems governed by time-dependent, nonlinear differential equations is called "chaos theory".
The climate system is thought to possibly have such multiple states; that is, the climate (or some components of the climate system) could be stable for a period of time and then abruptly, and for no overtly evident reason, change to another stable regime. There is evidence that certain components of the climate system have done this. The circulation in the north Atlantic Ocean is believed to have gone through an abrupt change in which the Gulf Stream, instead of tracking northeastward off the East Coast of the United States and heading toward Scandinavia, at one time switched very abruptly over about fifty years (that's abrupt on geological time scales) to an easterly direction toward the Mediterranean Sea. This caused an abrupt cooling of the climate in Scandinavia.
In summary, almost-intransitivity is an inherent characteristic of the dynamics of the climate system that may, for seemingly small or unknown reasons, launch some component of the climate system into a pattern not previously seen.
Predicting Future Climates
Leaving aside the almost-intransitivity property of climate, we now
consider what is meant by climate predictability. Recall that we had set
out to quantitatively determine the changes to the climate of the earth
that will result from changes in future emissions of greenhouse gases.
Simply put, we want to estimate the magnitude of future global warming.
An astute observer of weather and weather forecasts might raise the point that since 10-day weather forecasts are essentially useless for planning purposes, it is audacious and absurd for meteorologists to pretend they can predict anything 1 year, much less 50 years, into the future.
Pinball Machine Analogy
To understand the concept of a climate model and to clarify the
concept of climate predictions as compared to weather predictions, we
consider the
"pinball machine analogy".
The accompanying sketch shows the result of many outcomes of dropping balls through the pinball matrix. If the matrix is very large there will be many, many individual paths to the bottom. The exact positions of the pegs determine the distribution of balls at the bottom. A slight change in peg position will have some influence on the distribution of possible paths, with some pegs being more influential than others.
Pinball Climate
Simulation.
(Takle, G.S., 1995)
Climate Forecast vs Weather Forecast
A weather forecast for the next several days is analogous to an individual
path through the matrix. Each horizontal line of pegs might represent a successive day.
If we know from which position (A, B, C, D, or E) the ball started (i.e., if
we know the initial conditions for the differential equations describing the atmospheric motions),
we will know reasonably well the first part of the trajectory through the matrix
but less and less as the ball moves downward. After the ball passes several pegs,
our predictability of the actual path is completely lost (the equations are nonlinear and dissipative and
include some approximations).
A climate forecast is analogous to the distribution of balls at the bottom of the matrix. If we know the positions of the pegs, the equations that describe (with some uncertainty at each bounce) the trajectory through the matrix, and the number of times each initial condition is used, we can estimate the distribution at the bottom. In this case, an individual trajectory through the matrix does not represent a forecast of day-by-day actual weather, but rather a plausible sequence of daily weather consistent with the known positions of all the pegs.
Initial Conditions and Boundary Conditions
Another feature of the climate prediction problem is that if the
range of initial conditions (starting points A,...,E) remains limited
(limited horizontal distance in the pinball sketch) but the size of the
matrix in extended downward (length of the forecast period is increased),
then eventually the distribution of final outcomes at the bottom will be
essentially independent of how many times the ball started at A, B, C, D,
E, or F. We say that the ball forgets its initial conditions or that the
outcome is independent of initial conditions and depends only on the
positions of the pegs (e.g., the boundary conditions).
A change in greenhouse gas concentration is analogous to changing the positions of one or more pegs. The change this creates in individual trajectories (e.g., weather for a particular year) might not be noticeable, but over a larger number of events (many years) a slight change might become detectable.
A "Model" of Climate
Suppose the real climate system is given by a pinball matrix for which we do not
know the exact peg positions or the elasticity of the pegs (how far the ball rebounds after
hitting a peg). We will try to understand the real climate system by building a matrix
that looks as close to the real matrix as we can make it. We use pegs of material that
gives rebounds as close as possible to the real matrix.
The trajectory through a given matrix is described by a single set of equations, so by extension, we say that the set of equations and peg positions is the "model" that describes the behavior of the matrix. This "model" can be used to predict the distribution of balls at the bottom (i.e., the climate). We test how well the model works by comparing its predicted results with outcomes from the real matrix. We might find in making this comparison that we need to adjust some constants or compensate for subtle influences (this is called "tuning the model"). This is analogous to using the climate model to predict the characteristics of the present climate. Once we have it working well for a given set of matrix conditions, we should change the real matrix slightly by moving a few pegs slightly (analogous to finding a different real climate, such as an ice-age climate), make comparable changes in the mathematical conditions in the model, and compare model and real outcomes. This is typically done by studying the climate that existed 15,000 years ago during the last ice age (we will discuss later how we get the observed conditions for comparison with model results).
If these "reality checks" prove successful, we feel confident that we can use the model to predict the effects of changing pegs to some configuration for which there are no observed results. This is analogous to making predictions of the effect of changing the "peg" (e.g., equations or conditions) representing increases of greenhouse gases.
Abrupt Climate Change
One of the types of climate change that was listed at the beginning of this unit summary was climate
surprises ("abrupt" changes to climate conditions not seen before in our recorded climate
history). There is mounting evidence for the occurrence of such events in the past. Steven
M. Stanley in the 15 February 2000 issue of the Proceedings of the National Academy
of Science surveys 15 recent articles assessing the speed at which major climate change
can sweep across the planet, in what could be called "climate surprises."
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