Geology Reference
In-Depth Information
Map Pattern of
Cooling Ages
Accelerating,
Narrowing Uplift
Steady-State,
Differential Uplift
1 Ma
1 Ma
5 My
A
B
C
3 My
3 Ma
3 Ma
1 My
cross section
5 Ma
5 Ma
Distance
Distance
Fig. 10.31
Contrasting interpretations of cooling-age distributions.
A. Concentric zones of cooling ages indicate that erosion is most rapid in the center. Horizontal line shows
cross-section location of parts B and C. B, C. Map pattern of ages could be produced by (B) an acceleration of
erosion rates into an increasingly narrow zone over the past 5 Myr or by (C) a spatially focused pattern of erosion
that persists for millions of years.
subtle effects. We almost always have to rely on
proxy data: cooling ages, rather than actual erosion
rates; isotopes, rather than elevation; sediments
from non-specific sources, rather than
in situ
bedrock; etc. Each type of proxy data separates us
farther from the actual process of interest and
requires a suite of assumptions to interpret.
Because mountain ranges erode, we simply cannot
go back to the bedrock to determine the
distribution of cooling ages at 5 or 10 Ma. Instead,
we have to examine the detrital record found in
sediments of those ages in nearby basins. But
then, we usually cannot be certain from where
those sediments were actually derived, and we are
still forced to reconstruct a scenario to explain
their characteristics.
Another challenge when we examine a “snap-
shot” of current data is to try to determine the
time frame for which it is relevant. Consider, for
example, a map pattern showing a bull's eye with
progressively younger cooling ages toward the
center (Fig. 10.31). One interpretation of these
data would be that a significant acceleration of
erosion has occurred in the central part of the
mapped area, whereas a rather different interpre-
tation would argue that a gradient of erosion
from rapid in the center to slower on the margins
has persisted for an unknown length of time, but
for at least a few million years. Although data to
distinguish between these alternatives may be
difficult to obtain, the implications of these dif-
ferent interpretations are profound: accelerating
versus steady erosion; and a spatial and temporal
evolution of erosion versus a spatial and tempo-
ral persistence of erosion (Fig. 10.31).
Orographic rainfall and topography
As previously described, when moisture-laden
winds hit mountains, air is forced to rise and,
therefore, to cool and ultimately to condense and
precipitate the moisture within it. Hence, loci of
high rainfall develop on the upwind side of a
range, whereas rain shadows commonly develop
on the downwind side. The patterns of such oro-
graphic rainfall can vary depending on the size of
the mountain range (Can air flow around it, rather
than over it?) and wind speed, as well as the
height and shape of the range. Such interactions
have been studied both from a theoretical van-
tage point (Galewsky, 2009; Roe, 2005; Smith and
Barstad, 2004), as well as from an observational
perspective, relying on data either from networks
of weather stations (e.g., Bookhagen and Strecker,
2008; Burbank
et al
., 2003), or from remote sens-
ing of rainfall and snowfall (Bookhagen and
Burbank, 2010). Whereas weather stations can
provide higher accuracy and precision at a point,
space-based measurements can provide both
spatially broader and more uniform records. With
improved remote sensing, measurement of both
snowfall and the snowmelt contribution to runoff
is becoming more tractable. Similarly, these new
high-quality data enable the relationship of pre-
cipitation to topography to be examined in more
detail (Bookhagen and Burbank, 2010).
Every summer, for example, we expect that
monsoon rains will soak the southern flank of the
Himalaya. But, is the distribution and relative
intensity of monsoon rainfall predictable? To
answer this question, we can now exploit a
