Uncertainty in projections of future lake thermal dynamics is
differentially driven by lake and global climate models
Abstract
Freshwater ecosystems provide vital services, yet are facing increasing
risks from global change. In particular, lake thermal dynamics have been
altered around the world as a result of climate change, necessitating a
predictive understanding of how climate will continue to alter lakes in
the future as well as the associated uncertainty in these predictions.
Numerous sources of uncertainty affect projections of future lake
conditions but few are quantified, limiting the use of lake modeling
projections as management tools. To quantify and evaluate the effects of
two potentially important sources of uncertainty, lake model selection
uncertainty and climate model selection uncertainty, we developed
ensemble projections of lake thermal dynamics for a dimictic lake in New
Hampshire, USA (Lake Sunapee). Our ensemble projections used four
different climate models as inputs to five vertical one-dimensional
(1-D) hydrodynamic lake models under three different climate change
scenarios to simulate thermal metrics from 2006 to 2099. We found that
almost all the lake thermal metrics modeled (surface water temperature,
bottom water temperature, Schmidt stability, stratification duration,
and ice cover, but not thermocline depth) are projected to change over
the next century. Importantly, we found that the dominant source of
uncertainty varied among the thermal metrics, as thermal metrics
associated with the surface waters (surface water temperature, total ice
duration) were driven primarily by climate model selection uncertainty,
while metrics associated with deeper depths (bottom water temperature,
stratification duration) were dominated by lake model selection
uncertainty. Consequently, our results indicate that researchers
generating projections of lake bottom water metrics should prioritize
including multiple lake models for best capturing projection
uncertainty, while those focusing on lake surface metrics should
prioritize including multiple climate models. Overall, our ensemble
modeling study reveals important information on how climate change will
affect lake thermal properties, and also provides some of the first
analyses on how climate model selection uncertainty and lake model
selection uncertainty interact to affect projections of future lake
dynamics.