jdp's blog

TELECONNECTIVITY

 

Last month the climatologist Justin Maxwell from Indiana University gave an interesting talk at our department about drought-busting tropical cyclones. In his talk, and in conversations before and after with our physical geography crew, he had some interesting things to say about climate teleconnections involving mainly sea surface temperature and pressure patterns such as ENSO, NAO, etc. If teleconnections and the various acronyms are unfamiliar, check out the National Climatic Data Center’s teleconnections page: http://www.ncdc.noaa.gov/teleconnections/

SOUTH PARK & GEOMORPHOLOGY

 

I got a few e-mails last week about fluvial geomorphology—not because of anything I have done, or any current issues or unresolved questions in that field. No, it was because a character in the irreverent Comedy Central show South Park was identified on the show as a fluvial geomorphologist. Apparently that gives us a measure of popular culture street cred.

South Park character Randy Marsh, in his pop singer Lorde disguise.

An actual geomorphologist named Randy (R. Schaetzl, Department of Geography, Michigan State University).

 

Early in October, an episode of the show was based on the premise that the New Zealand pop singer Lorde is actually a 45 year old man, Randy Marsh, a regular character on the show. As explained during the episode, “Lorde isn’t just a singer, she’s also a very talented scientist who specialises in fluvial geomorphology.” If this is all a bit confusing, see http://musicfeeds.com.au/news/lordes-true-identity-revealed-on-south-park/

PLACE SIMILARITY

I've thought, written, and talked a lot about the need to incorporate geographical and historical contingency--that is, idiosyncratic characteristics of place and history--in geosciences, in addition to (not instead of!) general or universal laws. I've also emphasized the fact that places and environmental systems have elements of uniqueness. This leads to the issue of how to measure or assess place similarity (or the similarity of different, e.g., landscapes, ecosystems, plant communities, soils, etc.). This is a way of thinking about this problem, dressed up with some formal mathematical symbolism. Though I'm personally pretty informal, I'm a big believer in formal statements in science, as it makes arguments at least partly independent of linguistic skills (or lack thereof). 

 

 

 

SCALE RATIOS

 

In fluid dynamics the Reynolds Number is the ratio of inertial to viscous forces, and is used to distinguish laminar from turbulent flow. Peter Haff (2007) applied this logic to develop a landscape Reynolds number, and also suggested how other generalized “Reynolds numbers” can be constructed as ratios of large-scale to small-scale diffusivities to measure the efficiencies of complex processes that affect the surface. As far as I know, there has been little follow-up of this suggestion, but the premise seems to me quite promising at an even more general level, to produce dimensionless indices reflecting the ratio of larger to smaller scale sets of processes or relationships. The attached file gives a couple of examples. 

 

CLIMATE CHANGE & ENVIRONMENTAL MANAGEMENT

 

Climate change is here, it’s real, and it won’t be easy for humans to deal with. But few things are all good or all bad, and so it may be for climate change, at least with respect to environmental science and management.

A vast literature has accumulated in the past two or three decades in geosciences, environmental sciences, and ecology acknowledging the pervasive—and to some extent irreducible—roles of uncertainty and contingency. This does not make prediction impossible or unfeasible, but does change the context of prediction. We are obliged to not only acknowledge uncertainty, but also to frame prediction in terms of ranges or envelopes of probabilities and possibilities rather than single predicted outcomes. Think of hurricane track forecasts, which acknowledge a range of possible pathways, and that the uncertainty increases into the future.

Forecast track for Hurricane Lili, September 30, 2002. The range of possible tracks and the increasing uncertainty over time are clear. Source: National Hurricane Center.

"TAKEN" DYNAMICS TO THE SPATIAL DOMAIN

 

The foundation for time series analysis methods to detect chaos is the notion that phase spaces and dynamics of a nonlinear dynamical system (NDS) can be reconstructed from a single variable, based on Takens embedding theorem (Takens, 1981). Many years ago (Phillips, 1993) I showed that temporal-domain chaos in the presence of anything other than perfect spatial isotropy (and when does that ever happen in the real world?) leads to spatial-domain chaos. This implies an analogous principle in the spatial domain.

Assume an Earth surface system (ESS) characterized by n variables or components xi, i = 1, 2, . . , n, which vary as functions of each other:

ESS = f(x1, x2, , , , xn)

If spatial variation is directional along a gradient y (of e.g., elevation, moisture, insolation) then

dxi/dy = f(x1, x2, , , , xn)

dx2/dy = f(x1, x2, , , , xn)

.                 .                   .

.                 .                   .

.                 .                   .

THE SEMANTICS OF RESILIENCE

 

Resistance of environmental systems is their capacity to withstand or absorb force or disturbance with minimal change. In many cases we can measure it based on, e.g., strength or absorptive capacity. Resilience is the ability of a system to recover after a disturbance or applied force to (or toward) its pre-disturbance condition—in many cases a function of dynamical stability. In my classes I illustrate the difference by comparing a steel bar and a rubber band. The steel bar has high resistance and low resilience—you have to apply a great deal of force to bend it, but once bent it stays bent. A rubber band has low resistance and high resilience—it is easily broken, but after any application of force short of the breaking point, it snaps back to its original state.

THE RABBIT HOLE

 

I get frustrated sometimes with the way university administrators are fixated on marketing and branding, and on “student success” implicitly defined as processing as many passing grades as possible (not just at UK; the phenomenon is a pandemic).  Sometimes to relieve my frustrations I make things such as the flier below to amuse myself.

 

We’re supposed to advertise our courses to make them attractive to students, and to keep them entertained once they are in the class. If they don’t show up, it is the professor’s fault for not being entertaining enough.

I sent the flier to some colleagues in the department, none of whom recommend actually using it (I think I can safely assume that few, if any, potential GEO 130 students will read this blog). However, it has stimulated some interesting discussions.

RETURN OF THE JEDI

A couple of people (that is, about 50% of the blog’s readership) have asked about the “Jedi” reference in the Jedi Geoscience label. It comes from a PhD student about 10 years ago. After I answered his methodological question about his fieldwork, he good-naturedly suggested that my advice was about as helpful as if I had told him, like the Jedi Knights in the Star Wars movies, to “use the force.” After this story made the rounds, some of the grad students at Kentucky at the time referred to me as the “Jedi Geomorphologist.”

And now you know.

 

 

Jedi Geomorphologist using the force.

CHANGING LANES

Some form of the diagram below is often used as a pedagogical tool, and to represent a theoretical framework, in fluvial geomorphology, hydrology, and river science. It is called a Lane Diagram, and originated in a publication by E.W. Lane in 1955:

The diagram shows that stream degradation (net erosion and incision) and aggradation (net deposition) responds to changes in the relationship between sediment supply (amount of sediment, Qs, and typical sediment size, D50) and sediment transport capacity (a function of discharge or flow, Qw, and slope, S). The diagram is a very helpful metaphor in understanding the sediment supply vs. transport capacity relationship, and its effects on channel aggradation or degradation.

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