Predicting Earth Orientation Parameters (EOP) is crucial for precise positioning and navigation both on the Earth’s surface and in space. In recent years, many approaches have been developed to forecast EOP, incorporating observed EOP as well as information on the effective angular momentum (EAM) derived from numerical models of the atmosphere, oceans, and land-surface dynamics. The Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) aimed to comprehensively evaluate EOP forecasts from many international participants and identify the most promising prediction methodologies. This paper presents the validation results of predictions for universal time and length-of-day variations submitted during the 2nd EOP PCC, providing an assessment of their accuracy and reliability. We conduct a detailed evaluation of all valid forecasts using the IERS 14 C04 solution provided by the International Earth Rotation and Reference Systems Service (IERS) as a reference and mean absolute error as the quality measure. Our analysis demonstrates that approaches based on machine learning or the combination of least squares and autoregression, with the use of EAM information as an additional input, provide the highest prediction accuracy for both investigated parameters. Utilizing precise EAM data and forecasts emerges as a pivotal factor in enhancing forecasting accuracy. Although several methods show some potential to outperform the IERS forecasts, the current standard predictions disseminated by IERS are highly reliable and can be fully recommended for operational purposes.

预测地球定向参数（EOP）对于地球表面和太空的精确定位和导航至关重要。近年来，人们开发了许多方法来预测 EOP，其中结合了观测到的 EOP 以及从大气、海洋和陆地表面动力学数值模型得出的有效角动量 (EAM) 信息。第二次地球定向参数预测比较活动（2nd EOP PCC）旨在全面评估许多国际参与者的EOP预测，并确定最有前途的预测方法。本文介绍了第二次 EOP PCC 期间提交的世界时和日长变化预测的验证结果，并对其准确性和可靠性进行了评估。我们使用国际地球自转和参考系统服务（IERS）提供的 IERS 14 C04 解决方案作为参考，并以平均绝对误差作为质量衡量标准，对所有有效预报进行了详细评估。我们的分析表明，基于机器学习或最小二乘法和自回归相结合的方法，并使用 EAM 信息作为附加输入，可为两个研究参数提供最高的预测精度。利用精确的 EAM 数据和预测成为提高预测准确性的关键因素。尽管多种方法显示出优于 IERS 预测的潜力，但 IERS 传播的当前标准预测高度可靠，可以完全推荐用于操作目的。