The solar wind prediction is based on the Wang and Sheeley (Astrophys. J. 365, 372, 1990) empirical relationship between the solar wind speed observed at 1 AU and the rate of magnetic flux tube expansion (FTE) between the photosphere and the inner corona, where the FTE is computed using coronal models (e.g. the current sheet source surface (CSSS) and the potential field source surface models). These models take the photospheric flux density synoptic maps as their inner boundary conditions to extrapolate the photospheric magnetic fields and to deduce the coronal and the heliospheric magnetic field configuration. These synoptic maps are among the most widely-used of all solar magnetic data products and therefore, the uncertainties in the model predictions that are caused by the uncertainties in the synoptic maps are worthy of study. However, an estimate of the uncertainties in the construction of these synoptic maps was not available until recently when Bertello et al. (Solar Phys. 289, 2419, 2014) obtained the spatial standard deviation synoptic maps. For each photospheric synoptic map, they obtained 98 Monte Carlo realizations of the spatial standard deviation maps. In this article, we present an estimate of uncertainties in the solar wind speed predicted at 1 AU by the CSSS model due to the uncertainties in the photospheric flux density synoptic maps. We also present a comparison of the coronal hole locations predicted by the models with the EUV synoptic maps obtained by the Sun Earth Connection Coronal and Heliospheric Investigation instruments on board the Solar Terrestrial Relations Observatory. For the present study, we used the Heliospheric and Magnetic Imager vector and longitudinal photospheric synoptic maps and the corresponding spatial standard deviation maps. In order to quantify the extent of the uncertainties involved, we compared the predicted speeds with the OMNI solar wind data during the same period (taking the solar wind transit time into account) and obtained the root mean square error between them. To illustrate the significance of the uncertainty estimate in the solar wind prediction, we carried out the analysis for three Carrington rotations at three different phases of the Solar Cycle 24, CR 2102 (3 – 30 October 2010), CR 2137 (14 May – 11 June 2013) and CR 2160 (1 – 28 February 2015), which fall within the extended minimum, the late-ascending, and the early-descending phases, respectively, of Solar Cycle 24.

中文翻译：

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使用 HMI 光球矢量和空间标准偏差天气图对太阳风预测的不确定性估计

太阳风预测基于 Wang 和 Sheeley (Astrophys. J. 365, 372, 1990) 在 1 AU 观测到的太阳风速与光球层和内部磁通管膨胀率 (FTE) 之间的经验关系。电晕，其中 FTE 是使用日冕模型（例如电流片源表面 (CSSS) 和势场源表面模型）计算的。这些模型以光球通量密度天气图作为其内部边界条件来外推光球磁场并推导出日冕和日球磁场的配置。这些天气图是所有太阳磁数据产品中应用最广泛的，因此，天气图的不确定性导致模型预测的不确定性值得研究。然而，直到最近 Bertello 等人才对构建这些天气图的不确定性进行了估计。(Solar Phys. 289, 2419, 2014) 得到空间标准差天气图。对于每张光球天气图，他们获得了空间标准偏差图的 98 个蒙特卡罗实现。在本文中，由于光球通量密度天气图中的不确定性，我们对 CSSS 模型在 1 AU 预测的太阳风速的不确定性进行了估计。我们还将模型预测的日冕洞位置与日地关系天文台上的太阳地球连接日冕和日光层调查仪器获得的 EUV 天气图进行了比较。对于目前的研究，我们使用了日球层和磁成像仪矢量和纵向光球层天气图以及相应的空间标准偏差图。为了量化所涉及的不确定性程度，我们将预测速度与同期（考虑到太阳风传播时间）的 OMNI 太阳风数据进行了比较，并获得了它们之间的均方根误差。为了说明太阳风预测中不确定性估计的重要性，我们对太阳周期 24、CR 2102（2010 年 10 月 3 日至 30 日）、CR 2137（5 月 14 日至 11 日）三个不同阶段的三个卡林顿旋转进行了分析2013 年 6 月）和 CR 2160（2015 年 2 月 1 日至 28 日），它们分别属于太阳活动周期 24 的扩展最小值、晚升和早降阶段。