Parametric spectrum models describing a frequency spectrum of ocean surface waves (e.g., Pierson-Moskowitz and JONSWAP (Joint North Sea Wave Project) spectrum) as a function of the significant wave height and peak period $\left(T_p\right)$ have been used to estimate the energy period $\left(T_e\right)$ using a relation, $T_e=C{T}_p$, when the frequency wave spectrum is not available. This approach, however, introduces uncertainties in $T_e$ estimation for irregular waves. In the present study, a regression model for defining the coefficient $\left(C\right)$ is developed to minimize the uncertainty in $T_e$ estimation using buoy wave measurements and WaveWatch III® hindcast for coastal waters of the United States. The result shows that the coefficients $\left(C\right)$ of wind sea, swell, and total sea vary geographically and range from 0.84 to 0.90, 0.92 to 0.98, and 0.79 to 0.85. This approach derives consistent coefficients with different periods of record and results in better agreements in $T_e$ estimation compared to those of the approach relying on parametric spectrum models. Frequency distributions of dominant wave systems reaching different coastal regions, e.g., Pacific northwest swell in the Pacific Ocean, nor'easter swell and trade wind swell in the Atlantic Ocean, explain the observed spatial trends in the coefficient.

参数化频谱模型描述了海洋表面波的频谱（例如，Pierson-Moskowitz和JONSWAP（联合北海波项目）频谱）与有效波高和峰值周期的关系 $（{Ť}_p）$ 已经被用来估计能量周期 $（{Ť}_{Ë}）$ 使用关系 ${Ť}_{Ë}=C{Ť}_p$，当频谱不可用时。但是，这种方法带来了不确定性${Ť}_{Ë}$不规则波的估计。在本研究中，用于定义系数的回归模型$（C）$ 被开发来使不确定性最小化 ${Ť}_{Ë}$使用浮标波测量和WaveWatchIII®后播对美国沿海水域进行估算。结果表明，系数$（C）$风海，海浪和总海的地理分布在地理位置上有所不同，范围从0.84到0.90、0.92到0.98和0.79到0.85。这种方法得出了不同记录期间的一致系数，并导致了更好的协议一致性。${Ť}_{Ë}$与依赖参数频谱模型的方法相比，该方法的估计效率更高。到达不同沿海地区的主导波系统的频率分布，例如太平洋的西北太平洋海浪，大西洋的诺斯特海浪和信风海浪，解释了该系数的空间趋势。