Posts Tagged ‘foody’

Uncertainty and confidence: walking a fine line

Friday, March 9th, 2012

Foody states important end-users tend to underestimate uncertainty. Their perceptions of uncertainty, in turn, could prompt greater problems. Yet, according to the article, “uncertainty is ubiquitous and is inherent in geographical data” (115). Thus, the blame game is hard to play when uncertainty can be argued as ‘inherent’. The topic becomes more convoluted when geographic information (GI) systems are assessed. “…the ease of use of many GI systems enables users with little knowledge or appreciation of uncertainty to derive polished, but flawed, outputs” (116). Thus, it is even more important to think twice about generated outputs. Foody mentions data mining’s methods that do not consider the “uncertainty that is inherent in spatial data” (111). We have a tendency to find patterns in data. Therefore, we could create the wrong patterns, but utilize the outcomes as accurate or next to flawless because of an overconfidence that is produced by the systems and databases we create. In addition, these systems have slippery slopes with potentially irreversible outcomes. It reminds me of the infamous case of the northern cod fishery collapse. Here, the problems in the science of the northern cod assessment entailed overestimation of biomass and underestimation of fishing mortality (by 50 percent!). I believe the overestimation and/or underestimation of variables are important to the way uncertainty is perceived. The awareness of uncertainty matters, as noted in the article. The higher the level of awareness is the better.

ClimateNYC mentions social errors in the ‘visualizing uncertainty’ post, which made me think of representation and scale issues. In particular, the decisions Google Maps makes with regards to representing marginalized communities. The Ambedkar Nagar slum in Mumbai, India is labelled in Google Maps as ‘Settlement’. However, ‘Settlement’ disappears at 200m altitude but is visible at 500m. Adding to the ambiguity, at 50m altitude, the Organization for Social Change is mapped but this point is not visible at any other scale. Who makes these decisions when labelling these areas? Is it political? Or do they simply not care?

-henry miller

Climate Models, Uncertainty and Unmade Policy Decisions

Thursday, March 8th, 2012

I think we’d be remiss to cover the topic of uncertainty without thinking about the role that it plays when scientific research or other forms of data are transmitted from the academic or research realms into the public world of policy debates. As Giles M. Foody notes, problems with uncertainty “can lead to a resistance against calls for changes because of the uncertainties involved” (114). I think he’s right but this is a vast understatement.

In the climate change debate now swirling through most of the globe, uncertainty could be described as one of the main factors propelling so-called climate skeptics, naysayers and those generally unwilling to acknowledge that human energy consumption might be influencing the global climate. Just take a look at this skeptic’s blog post. He names uncertainty in climate science as the number one reason not to move too fast on this global, vexing issue. In fact, much of the opportunity for debate on the issue stems from varying points of view on just how certain the hundreds and thousands of climate models out there might be in predicting a warming world. In fact, just try Googling “climate” and “uncertainty” and you’ll find an avalanche of information – some more scientific than others.

Foody does a nice job of summarizing this paradigm when he writes about how “end-users and decision-makers often fail to appreciate uncertainty fully” (115). I couldn’t agree more. What most climate scientists will tell you is that while their models contain a great deal of uncertainty – which varies depending on what type of model your discussing or how it’s been parameterized – the overall trends are pretty clear. Most of the work done in this field concludes that a relationship does, in fact, exist between CO2 emissions and a warming global climate. Yet the importance of uncertainty, here, lies not within the scientific community but with publicly debated policy decisions where uncertainty/error can conveniently become a political football. I mean just look at some of the variation in predictions from climate models in the IPCC’s 2001 report:

Figure 1. A selection of climate models and their prediction of globally averaged surface air temperature change in response to emissions scenario A2 of IPCC Special Report on Emission Scenarios. CO2 is ~doubled present concentrations by year 2100. Figure reproduced from Cubasch et al. (2001).

Yes, there’s some definite variation between models, a degree of uncertainty. But how does this compare with the idea we discussed in class about scale. Can we ever expect to have complete accordance and certainty amongst climate models when the issue operates on such a vast, global scale? Should we expect it on smaller, regional scales with something as complex as the atmosphere’s inputs and ouputs and the sun’s radiation?