With a Nod to Hildegard Kneff

The snow came down to the tree line during the night
It rained all morning in the village

The tourists have returned to the city
The village is quiet
The work is finished
Walking in the rain?
Church tomorrow?

The shops will be closed tomorrow
My dollars are flowing – the life is simple

An expat wonders where his home is…
Where does one belong?

Knowing Beans (nod to John Thorne)

I have the great fortune to be spending a good chunk of time at the end of one of those Maine peninsulas that sticks out straight south from the mainland.  In the little bit of poking around I have done so far, I acquired a bean pot of the kind roughly recommended by John Thorne in Serious Pig.  Turns out that the proper vessel does indeed improve the outcomes of the beans.

In reading and re-reading the “Knowing Beans” chapter, it has slowly dawned on me the extent to which I take a richly varied diet for granted.  Baked beans and brown bread were dinner; they did not accompany dinner, they were the main and only attraction.  It is a good show, but much simpler than the dinner I usually sit down to.  It also calls attention to the detail that one can devote to Knowing Beans.

Living here in the spectacular natural beauty of Maine in the Fall is a wonderful think.

Now I just need to find some good salt pork…

Things we need to decide…

I am getting ready to return to my half-finished, densely-prosed book entitled (at least when I stopped working on it a decade or so ago) Humans and the Future of Earth.  That is actually still a pretty good title, but, thankfully, my thinking has evolved a bit since I put it down last; and as I begin to prep my brain for returning to that topic, I am going to write a few things down.

One of the things that has emerged ever more strongly from the shadows of the earlier work is that Humans are in Control.  It follows then, and I repeat ad nauseamsustainability is the process by which we create the future we desire.

If we assume (which I will do the early part of the book) that human intentionality is a thing that makes sense, then there are some things we need to decide about the future of our planet.  This post is a short list to get the juices flowing…

How much inequality are we willing to tolerate?  

There is so much to unpack in my sustainability definition that it would take an entire book to shake it all out, but one of its key implications is that differences among humans and our differing qualities of life are central to sustainability.  Furthermore to say that we are moving toward sustainability will require that we give strong attention to differences among aspirations across cultures and the distance between current conditions and those aspirations.

How important is a democracy?

Sustainability is definitely one of the great challenges that democracies face.  If we are willing to accept less democracy, sustainability will be easier because the number of aspirations for the future that count will be less.  The scale of decision-making and compromise that is implied by the aspiration to create a desirable future for humans on Earth is nearly unfathomable.  The distribution of capital as we currently understand it is related to this; if we really value distributed decision making as is commonly attributed to constitutional democracies, then I think it is likely that the relationships among capital accumulation and political power will need to be addressed.

What value do we place on transparency and privacy?

This is a new one to me, but I think that it is important.  Privately held organizations such as Google and Amazon, and some we probably haven’t heard of, have amassed staggering stores of data about us as individuals and as groups.  A related case is data that is held by governments.  Do we care about this?  I am starting to; especially as I come to understand better the power of current computational methods.  Different people and cultures will have different ideas about what is appropriate, but in the future that I desire, there is a lot more clarity about the costs and benefits of privacy and transparency.

What level of engineering are we willing to inflict on our grandchildren?

And lo and behold, we finally get to the relationship between Human activity and the functioning of the Earth System.  We cannot go back to The Garden for the apple has been genetically modified, turned into juice and packed in a box that will survive into eternity.  The path forward will call for tradeoffs and interplays among human and nature engineered systems.  Human activity will play an outsized role in that balance and a great deal of human engineering is likely to take place in a reaction, rather than proactive mode.  The time scales of these engineering projects will be such that it will be at least the second generation out that will feel the full brunt.  The rhetoric of my framing hints toward my opinion here.



Equation 0

The following is an excerpt from The Boxes Paper (see the bottom-most entry in the Library).  It lays out a very simple idea regarding how we interpret the world around us.  As simple as it is, I have found that keeping the basic idea in mind has helped me be clear about what I think I know and what I am uncertain about.

The job of the scientist is to make sense of the world. A common way to further this effort is to make analogies between things which are understood and those which are not. The analogy is often in the form of a physical model and we can always write:

data = model + residual      (0

The terms in Eqn. 0 can be interpreted on a number of levels. At the most general level, data are observations, model is an analog to the processes being studied, and residual is that which the model cannot explain.

In this interpretation, the form of Eqn. 0 is slightly odd; one might expect something more like:

data – model = residual      (0a

The form of Eqn. 0 was chosen to illustrate an often overlooked aspect of the observation process. When we collect data, we have in mind, consciously or unconsciously, a model of what we expect to find. It is that model which guides the experiment design process; we design experiments/measurements with expected results in mind. We do not design equipment to measure things which are not expected, but this does not mean that the unexpected would not be measured if it was looked for. In this way, what we actually do find is determined in large part by our expectations (Kuhn 1970). In this abstraction of the data gathering process, residual is a nagging sense that something is not entirely right.

An individual model is identified by a set of equations whose free variables, the model parameters, take on specific values. A class of models is a set of models which are defined by the same equations, but whose model parameters are unspecified. A class of models (e.g., y = ax + b) is a subset of all the possible models, and an individual model (e.g., a = 1; b = 0) is a member of that subset.

As with boxes, models divide the world into two bits; the bit which the model explains (that which is understood) and the bit which the model fails to explain (that which is still a mystery). The objective in a modeling effort is to maximize the portion of the data which is understood and to minimize that which is not. To do this we look for model parameters which minimize the residual in Eqn. 0a. This is equivalent to choosing the member of a class of models which most resembles the data on hand. An unavoidable part of the modeling process is the selection of {selecting} the class of models from which the best representative will be chosen. If an inappropriate class of models is chosen, the best representative will still be an inadequate analog for the process being studied. Following this, another approach to minimizing residual is to choose another class of models; thus the modeling process has two levels: 1) selecting the class of models to be considered; and 2) choosing the best model from within the selected class. The multiple working hypothesis idea of Chamberlain (1897) implies that we should always use at least two classes of models in our attempts to understand our data. There is no guarantee that the “best” (meaning True) model is a member of any class of models.

Models which are interesting and add significantly to our understanding have far fewer adjustable parameters than there are data which need explaining. In such a situation the residual will always be finite and the possibility of finding a better model will always exist.

And then there was Blogger…

I suppose that I should connect with the past… Many years ago and far away, I found myself with time on my hands and Blogger at my disposal.  I had been thinking hard about Earth Systems and about the foibles of science, technology, and policy.  So I started a blog and worked at it pretty diligently for a while and then not so much. Eventually Google bought Blogger, changed its name to blogspot, and sent me a sweatshirt that I still wear and that every now and again garners a knowing comment from someone roughly within my demographic.  Earth Systems Management still spins around on a disk somewhere and I still find that some of the posts have stood the test of time…