Variations in the atmospheric conditions because of climate change could have impacts on the ocean wave climate. Variations in ocean wave climate, including mean and extreme wave conditions, could have considerable impact on various applications, e.g., coastal planning (flood disaster prevention, coastal environment), design of coastal and offshore structures, ship design, harbor activities, and the evaluation of wave energy resources. Projections of future wave climate are indispensable for the assessment of the impact of variations in wave climate and for the development of appropriate adaptation strategies. However, Global Climate Models (GCMs) for climate research do not simulate ocean waves, and some postprocessing or analysis method is necessary to investigate the effects of climate change on ocean waves. Projections with high spatial resolution are desirable especially for detail assessment of the impact on wave climate for specific coastal areas.
There are two approaches to generate projections of wave climate. One is dynamical downscaling based on numerical models, and another one is statistical downscaling technique. In both approaches, atmospheric conditions (near-surface wind and/or sea level pressure) projected by GCMs are used to generate ocean wave conditions.
Seasonal mean and extreme global ocean wave heights were projected with sea level pressure projected by multiple GCMs and emission scenarios as forcing [1
]. A statistical downscaling method was applied using a regression model, and the projected ocean wave height was estimated on a 96–48 Gaussian grid in [1
]. Future variations of global ocean wave climate were examined with ocean wave heights projections by another statistical method by the authors of [2
]. The sea level pressure from 20 GCMs in the Coupled Model Intercomparison Project Phase 5 (CMIP5 [3
]) were used to generate the ocean wave projections with spatial resolution of 2.0° × 2.0° [2
]. A statistical method for different weather types was developed and future variations of the wave climate in Europe were investigated in [4
]. The three-day average sea level pressure and sea level pressure gradient were used as predictors and the mean wave heights were projected in their method. Using dynamical methods, global wave climate was projected by a wave model with the resolutions of 1.25° and the variations in the mean and the extreme wave climate were examined in [5
]. Different tendencies of future variations of wave climate were found in different regions (including the seas around Japan) [5
]. The spatial resolutions in above studies were too coarse to examine the details in relation to the Japan Sea.
The variations in ocean waves in the Bay of Biscay were examined by wave simulations with the spatial resolution of 0.1° in [6
]. Both downscaling by the wave model and error correction were applied in [6
]. Decreasing winter wave height was found according to a decrease of wind speed in the central North Atlantic Ocean and the Bay of Biscay. Future projections of the wave climate were generated by a third-generation wave model (WAM) with resolution of 0.05° × 0.075 ° with two initial conditions and two emission scenarios [7
]. Variations of the wave direction were larger than variations of the wave height in the North Sea. Ten future projections showed an increasing mean and extreme wave heights in eastern parts of the North Sea but decrease in western parts [8
]. A spectral wave model was used with forcing data from GCM projections with 1.0° × 1.0° spatial resolution in [9
]. Increases of the wave generation and the mean significant wave height in the Southern Ocean and decrease of the wave generation with comparable wave height in the North Atlantic Ocean were reported in [9
]. Variations in the global wave climate were examined using simulation results from a wave model with forcing from a GCM projection [10
]. The changes of wave climate in different regions and seasons were discussed in [10
]. Global swell and wind–sea characteristics at the end of the 21st century were investigated by using the results of a coupled atmosphere-ocean wave simulation system with the resolution of 0.5° × 0.5° [11
]. Wave climate in the Pacific Ocean was examined with wave simulations based on the multiple emission scenarios of two different GCMs with 0.25° × 0.25° resolution [12
]. Mean and extreme wave heights decreased along the west coast of North America in [12
]. For the western North Pacific Ocean, 0.5° × 0.5° resolution wave simulations were generated and the effects of sea surface temperature conditions were investigated to understand the mechanism behind changes in wave climate [13
Finer resolution wave climates by statistical and dynamical downscaling methods were compared by the authors of [14
]. The results from the dynamical method were slightly closer to the observations, and the difference between the dynamical and the statistical methods was larger under more severe global warming conditions [14
]. In addition, statistical methods showed disadvantages in the estimation of extreme wave events [14
]. Another comparison of statistical and dynamical downscaling method showed that statistical projection using climate indices (sea level pressure and/or pressure gradient) did not reproduce long-term trend in the North Atlantic wave climate [15
]. Another disadvantage of the statistical downscaling methods is that it does not consider swell effects [16
]. Thus, dynamical methods could be more appropriate for evaluation of global warming impact in more energetic conditions.
The direct use of GCM output as wave model forcing could cause overestimation of swell in broad regions of the Southern Pacific Ocean [9
]. Large negative biases were also recognized in wave simulation with direct use of CMIP5 GCM output as forcing [17
]. To prevent such defects of using GCMs output directly in downscaling, a pseudo global warming (PGW) method [18
] was applied in this study. The PGW conditions are generated by adding future anomalies from the GCM output to reanalysis data. Then, simulations forced by PGW conditions are made and compared with simulations forced by reanalysis data (more accurate forcing than the direct use of GCMs).
Strong seasonal northwesterly winds prevail during winter over the Japan Sea, which can make sea conditions difficult. Sometimes, a large swell can be generated by the passage of an intense low-pressure system. For example, in 2008, a very large swell exceeding 9.9 m affected Toyama Bay (northern Honshu, Japan). In this study, a dynamical method was applied for the Japan Sea. The wind output of a numerical model was used as the forcing data in a wave simulation. For the present climate, winds simulated with reanalysis data were used. For the future climate, the results of PGW simulations implemented using multiple GCM products were used as the forcing for the wave simulations.
The remainder of this paper is organized as follows. In Section 2
, the data and wave model used in this study are described. In Section 3
, the results and a discussion of wave simulations are presented. Finally, in Section 4
, a summary of the study is provided.
Using a third-generation wave model, the winter wave climate of the Japan Sea was projected based on five different GCM products. Sea surface wind speed, which was used for forcing the wave simulation, showed significant enhancement in the Japan Sea under the condition of global warming in four out of five future projections. Corresponding to the enhanced wind, the mean significant wave height over the Japan Sea is projected to become greater in the future climate. In one future projection (PGW-2), clear variations were not recognized in sea surface wind and mean significant wave height along the coast of the Japan Sea. The mean wave period did not show any common tendency in the five future projections. The maxima of significant wave height and of mean wave period also did not show clear future variations in the Japan Sea. The top 1% of significant wave heights and mean wave periods indicated higher and longer wavelength ocean waves in more than half of the future projections. In two future projections (PGW-2 and PGW-3), top 1% significant wave height and mean wave period are comparable to or smaller than in the present climate. The frequency distributions of significant wave height, mean wave period, mean wave length, and wave direction showed a range of different variations among the five future projections. Significant wave height showed a certain shift in several future projections. These results indicate that, although not extreme, the daily significant wave height will become greater along the coast of the Japan Sea. The frequency distributions of the mean wave period and wavelength also indicated that daily ocean waves would become longer. The results of wave directions showed an increasing frequency of waves from the west in four projections at Kanazawa. Daily ocean waves cannot cause severe disasters or change the topography and environment of the coast over short periods. However, the repetitive effect of ocean waves could have certain impact on coastal areas over the long term. Therefore, changes in daily ocean climate cannot be neglected, and long-term simulations of coastal morphology or the coastal environment are recognized as indispensable in assessing future variations and for preparing adaptation strategies.
Some future variations are common among more than half the multiple projections using different GCMs, but there are uncertainties that remain in the results of the wave simulations. For example, in the northern part of the Japan Sea showed an opposite tendency of variation (Figure 6
), i.e., both increasing and decreasing tendencies were statistically significant in that area. In [16
], a statistical downscaling method was applied using multiple GCM projections to estimate global wave height and sea level rise, and opposite (i.e., increasing and decreasing) trends of Hs
were found in different regions. At the same time, large uncertainties in the projected values of Hs
for different GCMs were also reported. Ocean waves are controlled by local/remote sea surface winds, but the projections of GCMs and the outputs of weather forecasting models are not perfect. In this moment, it is difficult to elicit definitive conclusions of future variations of wave climate along the coast of the Japan Sea. But, in order to exploit available future projections, a probabilistic evaluation method should be established using multiple model outputs. Furthermore, bias correction of the forcing data could be a useful method to prevent some of the uncertainties. To utilize future projections based on multiple global experiments, the development of postprocessing techniques or methods for interpretation will be indispensable.
Numerical wave simulations can provide wave spectra. In this study, changes in Hs and Tm were examined, but from a scientific point of view, the reasons behind the changes in wave climate are of greater interest. Using wave spectra, the causes of the changes in wave characteristics (e.g., effects of local wind waves or remotely developed swell) could be investigated. This would enable an assessment of their impact and further the understanding of the mechanism of variations in wave climate, which is an important challenge in this field.