There are many different climate models out there, some types of which will systematically tell you different things from others. But, are these systematic differences large enough to affect practitioners’ decisions on how to adapt to climate change? This study aims to answer this question for one prominent practitioner group in the NE CASC region as an example case study: maple syrup producers. Maple syrup is a major cultural resource in the Northeast and Midwest U.S. — one with a strong link to climate. In the traditional spout-and-bucket method of collecting sap, collection requires sapflow, which occurs only on days when the temperature drops below freezing at night and rises above freezing the next day. These conditions occur over a narrow window during the year. And, once producers “tap” a maple tree, they have 6-8 weeks before the bacteria development closes the tap and collection ceases. These factors make the timing of when producers tap their trees an important and very difficult decision as tapping too early or too late can reduce their seasonal yield. Further complicating matters, climatic warming is shifting the average “optimal” tap date (i.e. maximizing sapflow conditions) earlier in the year. Warming also means fewer days and nights below freezing, resulting in fewer days with sapflow, and thus, lower seasonal sap yields, especially for producers at the southern edge of the maple range (e.g., VA, KY). Going forward — as warming continues — producers will need to decide how to adapt their tapping practices, or whether conditions will render the practice unsustainable. To help with these decisions, producers can look to climate models for guidance on the timing and magnitude of projected changes in the freeze-thaw patterns that drive sapflow. However, different climate models can produce very different guidance, and maple syrup producers are not readily trained in how to interpret disparate guidance. Climate scientists, too, while perhaps aware of certain biases between different models with respect to climate metrics (e.g., temperature, precipitation, etc.), are not aware of their implications for decision-relevant metrics, such as the number of freeze-thaw crossings in an 8-week tapping season. This study identifies systematic discrepancies between different climate models with respect to several metrics relevant to maple syrup producers. Does one model predict a shift of 3 days in the optimal tapping date while another predicts 3 weeks or 3 months? Or, does one predict a 50% fewer sub-freezing nights over the next 10 years while another predicts no substantial change for at least another 50 years, if at all? If these systematic discrepancies exist, are they large enough that choosing one over the other will have consequences for producers? If so, is one result more reliable than the other? If not, what options do producers have, using these imperfect results, until more robust information becomes available?
Alex Bryan is a Postdoctoral Fellow with the Northeast Climate Science Center and the USGS. After earning a degree in meteorology at Valparaiso University in Indiana, Alex pursued his doctorate at the University of Michigan, where he explored atmospheric interactions with vegetation in climate and atmospheric chemistry models. With the NE CASC, Alex provides guidance on climate assessments and scenarios to help partners and stakeholders of the Center make informed decisions toward climate change adaptation. Such guidance ranges from climate model selection to translating output to environmental response. As part of this work, Alex is exploring the utility of downscaled regional climate models for climate change adaptation in the northeast region.