The Impact of Climate Change on the Wave Climate in the Gulf of St. Lawrence

We investigate the wave climate, including the extreme waves, over the Gulf of St Lawrence (GSL) by using CRCM (Canadian Regional Climate Model) simulations to provide relatively high resolution winds to drive a modern operational wave model WAVEWATCHIII^TM (WW3). By comparing WW3 results with the IOWAGA wave hindcast, we show that the constructed wave climate for the present period can capture spatial patterns of mean significant wave heights (Hs), mean 10% highest and the maximum Hs well, in summer and winter. We also show that CRCM can reproduce the extratropical cyclone climate well in the North Atlantic, and sea ice concentrations driven by NEMO (ocean model) are well simulated well. Thus, we have confidence in projections of wave climate changes under a warmer climate scenario.

Under the SRES A1B scenario from IPCC (2007), the WW3 simulations driven by winds from CRCM outputs suggest that projected changes in wave climate have seasonal differences. In summer, the mean Hs, mean 10% highest Hs, and the maximum Hs are expected to decrease for nearly the entire GSL whereas the associated values for winter are projected to increase over almost the entire GSL. These seasonal variations with respect to climate change can be related to particular climate change characteristics, such as storms and sea ice properties in the GSL.

In summer, projected decreases in mean Hs, mean 10% highest Hs and the maximum Hs are linked to decreases in GSL cyclone track density. In winter, the effects of changes in the cyclone climate on wave climate in GSL in the future change scenario are expected to be small. These effects are mitigated by competing climate factors, namely sea ice. The impacts of climate change reductions in ice are an important factor related to increases in the mean Hs, mean 10% highest and the maximum Hs values in the GSL in winter. Expected reductions in ice allow more open water for waves to be generated and to grow, whereas in former decades, the GSL was frozen in winter. Thus, changes in sea ice are consistent with increases in the wave climate.

In terms of the extreme wave analysis for the GSL, we show that the GPD distribution provides a better fit for the extreme Hs values than the GEV distribution, in both summer and winter. Comparing a statistical analysis based on different thresholds (95% and 97% percentile) and three methods (MPS, ML and PWM) for parameter estimation, the 95% percentile threshold and the ML method in GPD are treated as the best choice to fit the distribution of extreme Hs values and to estimate the return values. The spatial patterns of estimated 10-, 50- and 100-year extreme values for Hs are similar to each other, respectively.

In summer, the return values for Hs over the western coastal area of the GSL are around 0-6m for the 10-year return value for Hs and around 0-7 for the 50- and 100-year extreme values. Return values for the northern GSL area are higher than those for the western coastal area, with values between 5-7m. In the central GSL, the largest values are relatively high, estimated as 9m, 10m and 11m for return values in Hs. Under the A1B scenario, results obtained from WW3 simulations of waves suggest that the return values of Hs will decrease over the eastern part of GSL and increase over small areas of the St. Lawrence Estuary, Jacques Cartier Strait and southwestern part of GSL. The projected changes in the return values of extremes in Hs in these areas are consistent with the associated changes in the maximum Hs values over most of the GSL, although covering a relatively larger area for the increases in return values of Hs.

In winter, the return values over the St. Lawrence Estuary and southwestern portion of the GSL are around 0-5m and over the northern GSL, around 5-9m. In the central GSL, for 10-, 50- and 100-year extreme values in Hs, the largest values are up to 11m, 11m and 13m, respectively. In the future climate scenario, the projected increases in return values are mostly concentrated in the St. Lawrence Estuary, the northern part, and the southwestern GSL, which is consistent with changes in the maximum Hs in these regions.

In this paper, a qualitative analysis using a single model simulation is performed to estimate possible future climate change. The results are qualitative in that they are similar to what would be obtained using a larger ensemble of simulations. However, within a large ensemble of simulations, uncertainty varies from one member of the ensemble to another, and thus the entire ensemble needs to be calculated in order to accurately estimate the uncertainty for a particular given member of the ensemble. Presently, for any given IPCC climate change scenario, many climate projection studies are based on multi-model ensembles. A discussion of the application and development of multi-model ensembles for studies of climate change and the variance of results across different members of the ensemble may be found in IPCC (2007, 2013) and references therein. On average, the dominant source of uncertainty in the simulated climate response at middle and high latitudes is internal atmospheric variability, which is estimated to account for at least half of the inter-model spread in projected climate trends (Deser et al. 2012). In the Gulf of St. Lawrence, the uncertainties are generally larger for surface wind speeds than for surface air temperatures (SAT). For example, the variance of SAT changes is about 0.2^oC, which is about 10% of the SAT increase. However, the variance for projected changes in surface wind speed is about 0.2m/s, which has the same magnitude as the projected changes, suggesting significant uncertainty in the projected changes in the surface wind speeds (Wang et al., 2018; Perrie et al. 2015). The uncertainties associated with the inter-model spread in the projections of the possible future wave height climate will need to be addressed in future studies.