The Drag-based Model (DBM) is a 2D analytical model for heliospheric propagation of Coronal Mass Ejections (CMEs) in ecliptic plane predicting the CME arrival time and speed at Earth or any other given target in the solar system. It is based on the equation of motion and depends on initial CME parameters, background solar wind speed, \(w\) and the drag parameter \(\gamma \). A very short computational time of DBM (< 0.01 s) allowed us to develop the Drag-Based Ensemble Model (DBEM) that takes into account the variability of model input parameters by making an ensemble of n different input parameters to calculate the distribution and significance of the DBM results. Thus the DBEM is able to calculate the most likely CME arrival times and speeds, quantify the prediction uncertainties and determine the confidence intervals. A new DBEMv3 version is described in detail and evaluated for the first time determining the DBEMv3 performance and errors by using various CME–ICME lists and it is compared with previous DBEM versions, ICME being a short-hand for interplanetary CME. The analysis to find the optimal drag parameter \(\gamma \) and ambient solar wind speed \(w\) showed that somewhat higher values (\(\gamma \approx 0.3 \times 10^{-7}\) km⁻¹, \(w \approx \) 425 km s⁻¹) for both of these DBEM input parameters should be used for the evaluation than the previously employed ones. Based on the evaluation performed for 146 CME–ICME pairs, the DBEMv3 performance with mean error (ME) of −11.3 h, mean absolute error (MAE) of 17.3 h was obtained. There is a clear bias towards the negative prediction errors where the fast CMEs are predicted to arrive too early, probably due to the model physical limitations and input errors (e.g. CME launch speed). This can be partially reduced by using larger values for \(\gamma \) resulting in smaller prediction errors (\(\mathrm{ME} =-3.9\) h, MAE = 14.5 h) but at the cost of larger prediction errors for single fast CMEs as well as larger CME arrival speed prediction errors. DBEMv3 showed also slight improvement in the performance for all calculated output parameters compared to the previous DBEM versions.

基于阻力的模型 (DBM) 是用于日冕物质抛射 (CME) 在黄道平面中的日光层传播的二维分析模型，可预测 CME 到达地球或太阳系中任何其他给定目标的时间和速度。它基于运动方程，取决于初始 CME 参数、背景太阳风速、\(w\)和阻力参数\(\gamma \). DBM 非常短的计算时间（< 0.01 s）使我们能够开发基于阻力的集成模型（DBEM），该模型通过制作 n 个不同输入参数的集成来计算分布和显着性，从而将模型输入参数的可变性考虑在内DBM 结果。因此，DBEM 能够计算最可能的 CME 到达时间和速度，量化预测不确定性并确定置信区间。一个新的 DBEMv3 版本被详细描述和评估，首次通过使用各种 CME-ICME 列表确定 DBEMv3 性能和错误，并将其与以前的 DBEM 版本进行比较，ICME 是行星际 CME 的简写。寻找最优阻力参数\(\gamma\)和环境太阳风速\(w\)的分析表明应该对这两个 DBEM 输入参数使用更高的值（\(\gamma \approx 0.3 \times 10^{-7}\) km ^-1 , \(w \approx \) 425 km s ^-1）用于评估比以前使用的。基于对 146 个 CME-ICME 对进行的评估，获得了平均误差 (ME) 为 -11.3 小时、平均绝对误差 (MAE) 为 17.3 小时的 DBEMv3 性能。由于模型物理限制和输入错误（例如CME 启动速度），在预测快速 CME 过早到达的情况下，明显偏向于负预测误差。这可以通过对\(\gamma \)使用更大的值来部分减少导致更小的预测误差（\(\mathrm{ME} =-3.9\)  h, MAE = 14.5 h），但代价是单个快速 CME 的预测误差更大，以及更大的 CME 到达速度预测误差。与以前的 DBEM 版本相比，DBEMv3 还显示所有计算输出参数的性能略有提高。