Projecting impacts of climate change on surface water temperatures of a large subalpine lake: Lake Tahoe, USA

Abstract

Predicted increases in atmospheric CO2 concentration are expected to cause increases in air temperatures in many regions around the world, and this will likely lead to increases in the surface water temperatures of aquatic ecosystems in these regions. Using daily air and littoral water temperature data collected from Lake Tahoe, a large sub-alpine lake located in the Sierra Nevada mountains (USA), we developed and tested an empirical approach for constructing models designed to estimate site-specific daily surface water temperatures from daily air temperature projections generated from a regional climate model. We used cluster analysis to identify thermally distinct groups among sampled sites within the lake and then developed and independently validated a set of linked regression models designed to estimate daily water temperatures for each spatially distinct thermal group using daily air temperature data. When daily air temperatures projections, generated for 2080-2099 by a regional climate model, were used as input to these group models, projected increases in summer surface water temperatures of as much as 3 °C were projected. This study demonstrates an empirical approach for generating models capable of using daily air temperature projections from established climate models to project site specific impacts on littoral surface waters within large limnetic ecosystems.