CHAPTER 13 LINKING SPATIAL AND TEMPORAL ASPECTS OF CLIMATE THROUGH
QUANTITATIVE METHODS
Computerized Climate Models
 Types of GCMs
o Generally involve the prediction of the global atmospheric circulation based on dynamical
conditions rather than by analog comparisons, and are characterized by their spatial
resolution, temporal resolution, and time step
o Atmospheric GCMs (AGCMs) may provide adequate simulation of atmospheric motion
at short time scales but may not be applicable at climatological time scales because they
only consider processes occurring in the atmosphere rather than in exchanges between the
atmosphere and the lithosphere, hydrosphere, cryosphere, and biosphere
o Like AGCMs, oceanic GCMs (OGCMs) simulate circulation, but in this case the
circulation remains in the hydrosphere
o “Coupled” atmosphere-ocean GCMs (AOGCMs) include an ability to simulate not only
the circulations of both the atmosphere and ocean, but also the feedbacks and energy
transfer between those two fluids
o In some cases, output from a global-scale GCM may be used as input to a regional climate
model (RCM), which zoom in on the particular region of interest and contain much
greater spatial resolution
 Representing the Earth-Ocean-Atmosphere System in GCMs
o Grid point models represent atmospheric phenomena by dividing the earth into
equidistant points with imaginary three-dimensional “boxes” centered on those points
representing the smallest area in the atmosphere for which motion can be calculated by the
model
o Spectral models adopt the strategy of expressing atmospheric motion as wavelike motion,
using a series of waves
 Data for GCMs
o Because meteorological data are not collected at equally-spaced locations around the earth
(except in the case of satellite data), the data at the network of grid points are most likely to
be interpolated computationally using spatial interpolation methods from the available,
collected data
The Seven Basic Equations
 All GCMs and all weather forecasting models use the seven basic equations (in some form) to analyze
and forecast atmospheric flow and behavior
 Navier-Stokes Equations of Motion
o Three equations – one governs velocity in the west-to-east direction (the positive “u”
direction), another is for south-to-north velocity (positive v), and the third is for down-toup velocity (positive w)
o East-to-west, north-to-south, and up-to-down velocities are simply represented as the
negative u, v, and w directions, respectively
o Thus, all motion (advection and convection) can be described by some combination of the
u, v, and w equations
o The equations themselves describe the rate of change of u, v, and w over time at each grid
point, and the rate of change of a velocity over time is actually acceleration
o The Primitive Equations of Motion are simplified forms of the first two equations, which
along with the hydrostatic equation, can be used to model atmospheric motion
simplistically
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The Thermodynamic Energy Equation
o Expresses the sum of the internal energy of the individual molecules comprising the
atmosphere and the kinetic energy that drives the synoptic- and planetary-scale motion of
the atmosphere (i.e., the wind)
The Moisture Conservation Equation
o States that the change in moisture content at a grid point is equal to the sum of the
contribution of moisture via advection and the contribution via phase changes
The Continuity Equation
o Total mass must be conserved (i.e., constant) in any model, so the amount of mass entering
any imaginary three-dimensional “box” centered on a grid point must be balanced by the
amount of mass leaving another adjacent “box”, and the amount of mass leaving the
imaginary “box” of interest must be balanced by mass entering an adjacent “box”
The Equation of State
o Expresses the relationship between pressure, density, and temperature so that they can be
used in the other equations
Similarities and Differences Between GCMs and Weather Forecasting Models
o Both types of models use the same general equations to simulate atmospheric motion and
energy, moisture, and momentum exchanges, as the same physical processes affect the
circulation of the atmosphere whether it is at “weather” or “climate” time scales
o The most fundamental differences between GCMs and weather forecasting models involve
the difference in temporal scale
o The importance of accuracy in the initial conditions (initialization) is also somewhat
relaxed in GCMs
o GCMs place greater importance on representing interactions and feedbacks between the
atmosphere and the lithosphere, hydrosphere, and biosphere
Statistical Techniques
o Several statistical techniques of importance in climatology are simple methods that are
used across the spectrum of natural and social sciences
o Eigenvector analysis provides a useful suite of information because these techniques are
the only ones that allow for simultaneous examination of variability and changes in climate
across space and time
o Uses matrix algebraic procedures to transform that matrix of data (where, for example, the
weather stations constitute the spatial variable and months in the time series are a temporal
variable) into two other matrices, the first of which has the first entity’s variables (in this
example, the set of all of the weather stations in the study area) along the rows and the
loading for each eigenvector along the columns, and the second of which contains the
second entity’s variables (in this example, all of the monthly weather observations) along
the rows and the score for each eigenvector along the columns
o If the variable in the loadings matrix is a spatial variable (as in this example), then the
loadings for each component can be mapped using isoline maps
o The score for a given eigenvalue tells the magnitude of the influence on the explained
variability on that eigenvector (mapped by the loadings matrix) during each time unit of
the time series
o Two main variants of eigenvector analysis have been used in climatological studies:
principal components analysis (PCA) and common factor analysis (CFA)
o Eigenvector analysis, and particularly PCA, has been used in synoptic climatology to
delineate the major modes of variability in the atmospheric flow
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Atmospheric Teleconnections
o Teleconnections describe correlations or “see-saws” in geopotential height or sea level
pressure patterns across a large area
o Can be a source of important regional- to planetary-scale climate impacts
 Extratropical Teleconnections in the Pacific: The Pacific Decadal Oscillation
o Like the El Niño phase of the Southern Oscillation (SO), the “warm phase” of the PDO is
characterized by a periodic warming of the tropical central and eastern Pacific Ocean
o Unlike the SO, the primary “signature” of the PDO is apparent not only in the tropical
Pacific, but also in the extratropical north Pacific Ocean
o The PDO fluctuates much more slowly than the SO – a PDO regime may last 20 – 30
years, during which one phase of the oscillation tends to dominate, while the SO fluctuates
back and forth over periods of 2 – 7 years
 Extratropical Teleconnections in the Atlantic Ocean
o The Atlantic Multidecadal Oscillation (AMO) refers to a cycling of warm and cold
surface waters over time scales ranging from about 15 to 30 years
o The North Atlantic Oscillation (NAO) is a see-saw in pressure patterns between the
Bermuda-Azores high and the Icelandic low
o The Arctic Oscillation is a NAO-like oscillation in which the “see-saw” in pressure exists
throughout most of the troposphere between the north polar region and the mid-latitudes
 Teleconnections over North America
o The Pacific-North America (PNA) pattern represents the oscillation between
geopotential height in the mid-troposphere of northwestern North America, with opposing
heights upwind in the northern Pacific and downwind in the southeastern United States
o Tropical-Northern Hemisphere (TNH) teleconnection has nodes in the Aleutian low
area and the subtropical Mexico/southeastern U.S. region, with a center of opposite sign
over northeastern Canada
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