Predictions of the physical parameters of the solar wind at Earth are at the core of operational space weather forecasts. Such predictions typically use line‐of‐sight observations of the photospheric magnetic field to drive a heliospheric model. The models Wang‐Sheeley‐Arge (WSA) and ENLIL for the transport in the heliosphere are commonly used for these respective tasks. Here we analyze the impact of replacing the potential field coronal boundary conditions from WSA with two alternative approaches. The first approach uses a more realistic nonpotential rather than potential approach, based on the Durham Magneto Frictional Code (DUMFRIC) model. In the second approach the ENLIL inner boundary conditions are based on Inter Planetary Scintillation observations (IPS). We compare predicted solar wind speed, plasma density, and magnetic field magnitude with observations from the WIND spacecraft for two 6‐month intervals in 2014 and 2016. Results show that all models tested produce fairly similar output when compared to the observed time series. This is not only reflected in fairly low correlation coefficients (<0.3) but also large biases. For example, for solar wind speed some models have average biases of more than 150 km/s. On a positive note, the choice of coronal magnetic field model has a clear influence on the model results when compared to the other models in this study. Simulations driven by IPS data have a high success rate with regard to detection of the high speed solar wind. Our results also indicate that model forecasts do not degrade for longer forecast times.

中文翻译：

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内太阳圈边界条件对地球太阳风预报的影响

对地球太阳风物理参数的预测是运行空间天气预报的核心。这样的预测通常使用光球磁场的视线观察来驱动日球模型。这些天体中通常使用模型Wang-Sheeley-Arge（WSA）和ENLIL进行日光层中的运输。在这里，我们分析了用两种替代方法替代WSA的潜在场冠边界条件的影响。第一种方法基于达勒姆磁摩擦系数（DUMFRIC）模型，使用了更现实的非势而非势方法。在第二种方法中，ENLIL内部边界条件基于行星际闪烁观测（IPS）。我们比较了预测的太阳风速，等离子体密度，以及在2014年和2016年从WIND航天器进行的两个六个月间隔的观测得到的磁场强度。结果表明，与所观测的时间序列相比，所有测试的模型均产生相当相似的输出。这不仅反映在相当低的相关系数中（< 0.3），但偏差也很大。例如，对于太阳风速，某些模型的平均偏差超过150 km / s。积极的一点是，与本研究中的其他模型相比，日冕磁场模型的选择对模型结果有明显的影响。IPS数据驱动的模拟在检测高速太阳风方面具有很高的成功率。我们的结果还表明，模型预测不会在更长的预测时间内降级。