## 1 Introduction  
Tropical cyclones are accompanied by heavy rainfall, unusually high waves and strong winds, all of which have a great impact on the coastal environment. The intensity of tropical cyclones or the frequency of the most intense cyclones has increased as an effect of climate change [1, 2]. The intensity of tropical cyclones is increasing locally as a result of the changes in the cyclones' trajectories and the location of the maximum intensity [3, 4, 5]. The extreme significant wave height (SWH) is increasing globally as well as regionally, especially in coastal regions [6, 7, 8, 9, 10]. Increases in extreme wave height caused by tropical cyclones and hazardous events, combined with predicted sea-level rises (e.g., [11, 12, 13]), have the potential to increase the magnitude of disasters along with coastal erosion. Therefore, it is very important to estimate the extreme wave height, such as the 100-year return period SWH, as well as to understand the wave variability over decades. The long-term return period values of wave height, 100-year return period SWHs, are intuitively determinable if the SWHs have been measured for a sufficiently long period over 100 years. However, the temporal duration of most SWH measurements is shorter than the expected return period. Therefore, several methods for estimating extreme values by applying extreme value analysis (EVA) such as the Initial Distribution Method (IDM), Annual Maximum (AM) method, and Peaks over Threshold (PoT) method have been developed over the past few decades (e.g., [14, 15, 16, 17]). Studies have estimated the extreme wave height in the global ocean and regional seas by applying these statistical methods to buoy measurements and shipborne wave recorder data [7; 18; 19; 20; 21; 22; 23], satellite observation data [24; 25; 26; 27; 28; 29; 30], or model simulation data [31; 32; 33; 34; 35]. It is important to develop sophisticated statistical techniques for estimating extreme wave heights and to understand their spatio-temporal distribution in the global ocean and regional sea. In addition, it is also important to study the applicability and limitations of various estimation techniques that have been developed and utilized in previous studies. In particular, it is valuable to verify that long-term return period SWHs is adequately estimated in seas where extreme events such as typhoons frequently affect the estimation of extreme wave height. The Northwest Pacific has a variety of ocean and atmospheric phenomena that cause the spatial and temporal variability of SWH, as shown in the long-term mean of satellite SWH data from 1992 to 2016 (Figure 1a,b). Previous studies have reported an increasing trend for SHW as well as extreme SWH values corresponding to the upper 1% in the Northwest Pacific (e.g., [36]). In addition, as shown in Figure 1c,d, the Northwest Pacific is a region with one of the highest frequencies of high-intensity tropical cyclones [37]. On average, more than 28 tropical cyclones occur per year [38], and the frequency of tropical cyclones accounts for 30% of the total global tropical cyclones [39]. Therefore, the Northwest Pacific is very suitable for the estimation of the 100-year return period SWH because of the relative abundance of extreme events such as tropical cyclones. Thus, it is important to understand the characteristics of extreme wave height in regions affected by tropical cyclones. Although the spatial distribution of the 100-year return period of SWH in the Northwest Pacific region has been presented [40; 41], few studies have been conducted on the effect of tropical cyclones on extreme SWH. The objective of this study is to investigate and verify the extreme wave heights using satellite altimeter-observed data in the Northwest Pacific, where typhoons and extratropical storms occur frequently.