太阳10.7cm射电流量（F_10.7）是反映太阳整体活动的重要指标，其主要源头是日面活动区.F_10.7指数与日面活动区具有显著的相关性，且不同面积的活动区与F_10.7并不遵循相同的线性关系.为进一步提高F_10.7预报的准确性，利用日面活动区面积与F_10.7的相关性，依据面积大小分类，提出F_10.7的预报公式并进行验证.采用2008-2018年SWPC （Space Weather Prediction Center）公布的活动区面积数据和CSWFC （Canadan Space Weather Forecast Center）公布的F_10.7实测数据计算预报公式系数，利用高年（2003年）和低年（1997年）的F_10.7预报验证其结果.研究结果表明，预报结果与实测值的相关系数分别为0.9318和0.9295，二者皆优于SWPC同时期的预报结果（相关系数分别为0.9186和0.8771）.本研究首次基于活动区的变化预测了F_10.7，提高了F_10.7预测的准确性.

Nonrecurrent geomagnetic storms caused by Coronal Mass Ejection (CME) can induce serious impacts on space‐ and ground‐based equipment. However, these nonrecurrent geomagnetic storms are hard to predict since CMEs are not periodic. Previous studies have shown that the variations of Cosmic Ray Intensity (CRI) before nonrecurrent storms may forebode the coming geomagnetic storm. But it is difficult to extract the variations since the cosmic ray flux is a complex signal. In order to identify the precursory signal in CRI variations triggered by CME, an ensemble self‐adaptive time‐frequency analysis method was proposed and applied to 65 nonrecurrent geomagnetic storms occurred between 1998 and 2019. The results indicate that the precursory signals are successfully identified in 43 of 45 storms, after excluding 20 storms accompanied by ground level enhancement. In addition, it is also found that the spectral density of the precursory signal could reflect the active level of geomagnetic condition, which is lower during geomagnetic quiet period.

Predicting non‐recurrent geomagnetic storms caused by Coronal Mass Ejection (CME) is important and necessary for space weather forecasting. Previous studies have shown that it is feasible to predict non‐recurrent geomagnetic storms by reconstructing precursors from cosmic ray intensity (CRI) in the frequency domain. However, the difficulty lies in predicting the minor storms, the moderate storms, and the storms accompanying ground level enhancement (GLE). This study proposes a new method that includes the spectral whitening method and CEEMDAN‐CWT for predicting non‐recurrent geomagnetic storms. The method was applied to 229 CME‐driven events, including 166 events with Kp ≥ 5 and 63 events with Kp < 5, during the solar cycles 23 and 24. This study analyzed 166 geomagnetic storm events and found that 129 of them were accurately predicted, resulting in a recall rate of 77.7%. Additionally, the study found that as the Kp index increased, the amplitude of the precursor detected by this method also increased, while the time interval between the onset of CME and the maximum amplitude of the precursor decreased.