Projection of Climate-Induced Future Water Temperature for the Aquatic Environment

Abstract

To project the effects of climate-induced change on aquatic environments, it is necessary to know the thermal constraints affecting different fish species and to acquire time series of the current and projected water temperature (WT). A regression between the WT at individual stations and the ambient air temperature (AT) at nearby weather stations could represent the easiest practical method of estimating the WT for an entire region. Assuming that the grid-averaged observations of AT correspond to the AT output from a general circulation model (GCM) simulation, this study constructed a regression curve between the observations of the local WT and the concurrent GCM-simulated surface AT, minimizing the difference between the time series of the measured and modeled WT, which implicitly includes downscaling to local conditions. The regression model shows excellent performance in capturing the WT trend in response to the AT of the GCM. The projected WT under the global-warming scenario shows a 1.5–2.5°C increase for the period 2080–2100. The maximum/minimum WT shows an amount of change similar to that of the mean values. The results also predict that the WT will increase during most seasons by 2100 but that only minor changes will occur during the summers.