为了准确地预报短期波浪波高周期的联合分布，基于条件概率方法提出了一种新模型. 在新模型中波高分布采用双参数威布尔分布描述，条件周期分布采用对数正态分布描述. 考虑波浪谱形状的影响，采用谱宽范围较大的Wallops谱，给出了新模型中参数的表达式. 以Wallops谱和实测波浪谱为靶谱，通过仿真得到波高周期的联合分布. 以仿真数据为基准，对提出的新模型以及现有文献中的5种联合分布模型进行了对比分析. 结果表明，在Wallops谱和实测波浪谱中，新模型与仿真数据最为接近，其它5种模型仅在部分情况下较为接近. 同时对各模型的波高分布、周期分布进行了对比分析，分析了各模型预报误差产生的原因. 此外，新模型具有显式闭合表达式，便于推广到非高斯波浪情况.

A new joint distribution model based on a conditional probability approach accurately predicts the joint distribution of wave heights and periods for short-term sea states. In this model, the wave height distribution follows a two-parameter Weibull distribution, and the conditional period distribution is modeled using a log-normal distribution. To account for the effects of wave spectral shape, the Wallops spectrum with a broad spectral width is used, and the model parameters are derived. Simulations using both the Wallops spectrum and measured wave spectra as target spectra are conducted to obtain the joint distribution of wave heights and periods. Simulated data serve as the benchmark, and the proposed model is compared with five commonly used joint distribution models. The results show that the new model closely matches the simulated data for both Wallops and measured spectra, while the other models only align well with simulated data in specific cases. Additionally, wave height and period distributions are analyzed, and the sources of prediction errors are discussed. The new model includes an explicit closed-form expression, making it suitable for non-Gaussian wave conditions.