…I’m just not sure we’re focused on the right sources of uncertainty. I spent the beginning of this week at the Southwest Climate Summit in Sacramento. The conversation among the scientists, natural resource managers, and bureaucrats inevitably turned towards uncertainty. I say inevitably because in my work with the Southwest Climate Science Center I often hear that climate models are “just too uncertain to be useful”. This seems reasonable. After all, there are at least 30 different models that describe our best estimate of how future climate will look (or feel)*. If one of these models was “right”, wouldn’t we simply get rid of the other models? Some of the models predict a warmer, wetter future – others predict a warmer, drier future. How do we know which model to believe? These are challenging questions to answer (especially for someone who is not a climate modeler), so I’m not going to try. I’m also not going to try because I don’t think these questions are the real roadblock to our collective ability to begin taking actions to plan for a warmer future**. I say this because making decisions under uncertainty is normal and because we are actually not that uncertain about how warm the future will be.
Decision-makers are asked to make choices without perfect information all the time. They often use models to help inform those decisions. Forest managers, for example, must often assess the potential impacts of timber harvest on sensitive wildlife species. Doing so often involves models of wildlife-habitat relationships. These models provide a forecast of whether a species will increase or decrease following forest management, but the precise effects may be largely uncertain. That is to say, we may be able to say with some confidence that removing large diameter trees will cause a decrease in Northern Spotted Owls, but just how big that decrease will be is difficult to predict because the relationship between owl populations and forest structure is complex and affected by myriad factors. The point is not that our models of ecosystem function are unreliable or unusable. Rather, it is that we accept uncertainty (or imprecision) when managing complex systems and that we expect land managers to use the tools available to them to make the best decision possible (i.e., the best available science).
Now let’s turn our attention to climate models. We’ve known (or at least Svante Arrhenius knew) about the role of greenhouse gases in warming the Earth’s climate since 1896. Not only that, Dr. Jim Hanson testified to Congress in 1988 that the Earth’s temperature would increase by 3 to 9 degrees Fahrenheit***. Despite continuing advances in our understanding of the global climate system and increasingly sophisticated computer models, our predictions have not changed much. Perhaps the reason we don’t use climate models more often lies in the fact that we’re not used to thinking about time horizons that are longer than (most) of our own lives. Or maybe it’s because we have a hard time understanding what it would mean for the temperature to be 4°F warmer (although I can imagine how much more my air-conditioning bill might be). Or maybe we simply don’t know enough about how temperatures affect the plants, trees, and wildlife that sustain life on the planet.
This last bit seems particularly important as we try to develop climate adaptation strategies (things we can do to help reduce the impact of climate change). After all, I can imagine what might happen to an owl that depends on trees if I decide to cut down those trees. I have no idea what would happen if I turned up the temperature on that owl or, for that matter, the species that spotted owls eat (and I certainly have no idea what happens if you do both at the same time). Perhaps our most important adaptation strategy isn’t to move species to where we think they’ll survive in the future or to thin forests to reduce the impact of drought stress. Perhaps we should be putting more energy and resources into monitoring the changes that are happening in our ecosystems now. After all, climate is already changing (and we are still trying different adaptation strategies). Why not take this opportunity to monitor those changes in a way that allows us to understand what actually drives the changes we see in plants, trees, wildlife, and even humans? Then we might actually be able to develop strategies that address the cause of the problem, not the symptoms.
Would knowing whether the future is going to be 2.7°C, 3.2°C, or 4.5°C warmer change the decisions you make now? Would it matter if that temperature change was 3.4oC on a ridge, but only 2.9oC down in the valley? Would knowing that a particularly important species has a 90%, 70%, or 50% chance of no longer occurring in the area you currently manage change your approach to that species? How different does your management look if you anticipate three ten-year droughts versus two? What would you need to know to answer these questions? Your answers (ideally provided in the comments) can help us design a monitoring system that translates climate change into things we understand and identifies opportunities for taking action!!
*Want to learn more about climate models? Check this out (it’s worth 2 minutes).
**Incidentally, I also don’t believe they are the reasons we’re not taking action to reduce how much warmer the future will be, but that’s another (much longer) discussion.
***Regardless of your feelings about Jim Hanson, the point is that he was able to use the Arrhenius equation to forecast that the earth would warm 3 to 8 degrees Fahrenheit with a doubling of carbon dioxide. The IPCC, 25 years and millions of dollars later, says the same thing, only now we have much more spatial and temporal resolution on how that warming may materialize.
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