A photo of the view from Aquatic Informatics office 2013.

IPCC, AR5 & AI – An Unintended Consequence of Climate Change?

Photo: View from the new Aquatic Informatics office at 2400 – 1111 Georgia Street, Vancouver, B.C

Is the growth of Aquatic Informatics an unintended consequence of climate change?

The rapid rate of growth of Aquatic Informatics has resulted in a move from our old Granville Street address to a new, much larger space, on Georgia Street in downtown Vancouver. This move happened at almost the same time as the International Panel for Climate Change (IPCC) released their 5th Assessment Report (AR5) for Working Group 1.

Is this coincidence or is there, in fact, a link between the demand for hydrometric monitoring software and the risks highlighted by the IPCC?

A conventional explanation for the growth in demand for AQUARIUS is that it is a quality product, designed and supported by quality people, led by quality management. There is evidence that this explanation may, in fact, be true. A visit to the new office reveals a commitment to quality at every turn.

The new office is open, airy and spacious creating an environment conducive to creativity and innovation.

I particularly like the easy accessibility of relevant expertise to whatever problem is at hand.  The resulting social dynamic that is collegial, spontaneous and responsive leads to speedy and effective resolution of questions that would otherwise require scheduled meetings. Form follows function and it can be argued that this space has been created to match the very qualities of the people that created AQUARIUS in the first place.

An alternate explanation for the growth of AQUARIUS is that global experts are advocating for a massive upgrade of environmental monitoring infrastructure to provide an evidence base for the multi-trillion dollars in decisions that will be required for an increasingly uncertain climate future. If this were the case then AI is simply riding the wave.

One of the findings of AR5 that has caused considerable glee amongst climate skeptics is the discovery of an apparent hiatus in the rate of warming. This has resulted in much hand wringing about why model predictions clearly connecting growth in carbon emissions to global warming are not supported by recent evidence. There are several explanations for this discrepancy salted through the report. However, there need be only one.

All models are wrong.

The IPCC is very careful to characterize the uncertainty in their predictions in chapter 1. This is commendable but, for me at least, uncertainty is an attribute of data. I think a better metric for model predictions would be a humility scale.

Think about all of the interactions of energy and water between the atmosphere, hydrosphere, cryosphere, lithosphere and biosphere. Think about the algorithms to conserve mass energy and momentum over the arbitrary discretization of these domains into a model matrix. Think about all of the assumptions that are required to represent all of these physical interactions as mathematical computations to be solved by a computer. Then think about how difficult it would be to get it all exactly right.

Let me be clear, the science is strong with respect to the net effect of greenhouse gas emissions.

It is only the artifact of models that seek to represent the underlying science that I question. The model humility scale should be proportional to the number of unverified assumptions in the model. Unfortunately, the humility scale does not exist. Meteorologists have been found to be skeptical about climate change predictions. This is often attributed to meteorologists being humbled by how difficult it is to even predict the weather next weekend. Climate modelers never have to worry about feedback at the scale of their neighbors plan for a weekend barbecue and hence operate with much more hubris.

Just because all models are wrong does not mean that some models are not useful.

I would argue that most models are very useful if for no other reason than to help identify the limits of our understanding of complex systems. It is for this very reason that we need modeling and monitoring to develop in harmony. We need to aggressively acquire data to expand our knowledge and understanding of critical systems whenever we come up against evidence that our knowledge and understanding is incomplete.

AR5 is full of compelling evidence that we have reached a point of unprecedented risk in our ability to understand and predict the climate and hence threats to our water sources. This should have, in my opinion, resulted in a call to develop a robust monitoring infrastructure to mitigate for these risks. Unfortunately, the IPCC messaging remains silent on this topic. If individual water resource managers are coming to this decision on their own, they are doing so without the benefit of guidance from the IPCC.

Any reader of this blog is hereby invited to come and visit our new office to share their opinion about the factors contributing to the growth of Aquatic Informatics.

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