F2层临界频率foF2是高频通信的重要参数,目前获取F2层临界频率(foF2)最有效的手段是电离层测高仪,但磁暴期间电离层自身剧烈变化会造成测高仪foF2数据严重缺失。经验模型如NeQuick虽能给出foF2估计值,但磁暴期精度却不及磁静日水平。本...F2层临界频率foF2是高频通信的重要参数,目前获取F2层临界频率(foF2)最有效的手段是电离层测高仪,但磁暴期间电离层自身剧烈变化会造成测高仪foF2数据严重缺失。经验模型如NeQuick虽能给出foF2估计值,但磁暴期精度却不及磁静日水平。本文选取2015年12月19日至2015年12月22日磁暴期中国地壳运动监测网GNSS双频数据进行区域建模并估算出电子总含量(total electron content,TEC),利用实测区域TEC对NeQuick模型有效电离参数Az进行估计,得出NeQuick模型优化后TEC总含量和F2层临界频率foF2,并反演出磁暴期初相,主相及恢复相阶段变化过程。以中国地区台站实测数据作为参考对比,结果表明:GNSS数据优化后的NeQuick模型TEC精度大概提升了20%~40%,foF2的实时精度提升了10%~25%。GNSS优化后NeQuick模型能准确反演出电离层的由正相暴转为负相暴演化过程,而原始模型由于仅依赖于输入的太阳活动水平,只能反映出与磁静日水平相当的日变化趋势值。利用该方法可以有效提高磁暴期TEC和foF2的经验模型的计算精度,特别是弥补磁暴期foF2数据缺失的不足,可以作为磁暴期电离层垂直探测仪的有益补充或者有效参考。展开更多
利用全球203个电离层测高仪台站的F_2层临界频率(f_oF_2)和E层临界频率(f_oE),以及美国喷气推进实验室(JPL)提供的电离层总电子含量(TEC)地图数据统计分析了电离层春秋分(March Equinox and September Equinox,ME and SE)不对称的特点....利用全球203个电离层测高仪台站的F_2层临界频率(f_oF_2)和E层临界频率(f_oE),以及美国喷气推进实验室(JPL)提供的电离层总电子含量(TEC)地图数据统计分析了电离层春秋分(March Equinox and September Equinox,ME and SE)不对称的特点.基于电离层参量随年积日(Day of Year,DoY)和太阳活动指数F_(10.7)变化的傅里叶级数模型,对f_oF_2、f_oE及TEC数据分别进行最小二乘法拟合,将电离层参量归算到低太阳活动(F_(10.7)=80)、中等太阳活动(F_(10.7)=150)和高太阳活动(F_(10.7)=200)水平.该方法定量分离了实际观测数据中包含的电离层参量随季节和太阳活动的变化,因而得到了更为定量、精确的电离层春秋分不对称性特征.分析了不同地方时(LT)的春秋分不对称性指数(Asymmetry Index,AI)和春秋分差值Δ(=ME-SE)的全球分布特征与太阳活动依赖性.结果表明,foE日出时全球主要表现为9月分点值高于3月分点值,午后春秋分不对称性几乎消失,而日落时则反转为3月分点值高于9月分点值;f_oF_2日出时除少数地区外也主要表现为9月分点值高于3月分点值,而其他时段则相反;TEC日出时低太阳活动时的全球及中高太阳活动时的低纬地区表现为9月分点值高于3月分点值,而其他时段则相反.fo_E春秋分不对称性受太阳活动影响较弱,而f_oF_2和TEC的春秋分不对称随太阳活动有明显的变化,其3月分点值相对于9月分点值增加.计算了F_2层峰高(h_mF_2)处对应的氧氮浓度比([O]/[N_2],由大气模型NRLMSISE-00计算得到)和h_mF_2的春秋分不对称性,提取了TEC年变化的幅度及相位信息.氧氮浓度比和h_mF_2的春秋分不对称性能够部分解释电离层的春秋分不对称性,而TEC春秋分不对称的全球分布特征可以用TEC年变化的相位的全球分布解释.展开更多
The hourly values of the ionospheric F2 layer critical frequency, foF2, recorded at Wakkanai ionosonde station (45.4°N, 141.7°E) have been collected to construct a middle-latitude single-station model for fo...The hourly values of the ionospheric F2 layer critical frequency, foF2, recorded at Wakkanai ionosonde station (45.4°N, 141.7°E) have been collected to construct a middle-latitude single-station model for forecasting foF2 under geomagnetic quiet and disturbed conditions. The module for the geomagnetic quiet conditions incorporates local time, seasonal, and solar variability of climatological foF2 and its upper and lower quartiles. It is the first attempt to predict the upper and lower quartiles of foF2 to account for the notable day-to-day variability in ionospheric foF2. The validation statistically verifies that the model captures the climatological variations of foF2 with higher accuracy than IRI does. The storm-time module is built to capture the geomagnetic storm induced relative deviations of foF2 from the quiet time references. In the geomagnetically disturbed module, the storm-induced deviations are described by diurnal and semidiurnal waves, which are modulated by a modified magnetic activity index, the Kf index, reflecting the delayed responses of foF2 to geomagnetic activity forcing. The coefficients of the model in each month are determined by fitting the model formula to the observation in a least-squares way. We provide two options for the geomagnetic disturbed module, including or not including Kalman filter algorithm. The Kalman filter algorithm is introduced to optimize these coefficients in real time. Our results demonstrate that the introduction of the Kalman filter algorithm in the storm time module is promising for improving the accuracy of predication. In addition, comparisons indicate that the IRI model prediction of the F2 layer can be improved to provide better performances over this region.展开更多
文摘F2层临界频率foF2是高频通信的重要参数,目前获取F2层临界频率(foF2)最有效的手段是电离层测高仪,但磁暴期间电离层自身剧烈变化会造成测高仪foF2数据严重缺失。经验模型如NeQuick虽能给出foF2估计值,但磁暴期精度却不及磁静日水平。本文选取2015年12月19日至2015年12月22日磁暴期中国地壳运动监测网GNSS双频数据进行区域建模并估算出电子总含量(total electron content,TEC),利用实测区域TEC对NeQuick模型有效电离参数Az进行估计,得出NeQuick模型优化后TEC总含量和F2层临界频率foF2,并反演出磁暴期初相,主相及恢复相阶段变化过程。以中国地区台站实测数据作为参考对比,结果表明:GNSS数据优化后的NeQuick模型TEC精度大概提升了20%~40%,foF2的实时精度提升了10%~25%。GNSS优化后NeQuick模型能准确反演出电离层的由正相暴转为负相暴演化过程,而原始模型由于仅依赖于输入的太阳活动水平,只能反映出与磁静日水平相当的日变化趋势值。利用该方法可以有效提高磁暴期TEC和foF2的经验模型的计算精度,特别是弥补磁暴期foF2数据缺失的不足,可以作为磁暴期电离层垂直探测仪的有益补充或者有效参考。
文摘利用全球203个电离层测高仪台站的F_2层临界频率(f_oF_2)和E层临界频率(f_oE),以及美国喷气推进实验室(JPL)提供的电离层总电子含量(TEC)地图数据统计分析了电离层春秋分(March Equinox and September Equinox,ME and SE)不对称的特点.基于电离层参量随年积日(Day of Year,DoY)和太阳活动指数F_(10.7)变化的傅里叶级数模型,对f_oF_2、f_oE及TEC数据分别进行最小二乘法拟合,将电离层参量归算到低太阳活动(F_(10.7)=80)、中等太阳活动(F_(10.7)=150)和高太阳活动(F_(10.7)=200)水平.该方法定量分离了实际观测数据中包含的电离层参量随季节和太阳活动的变化,因而得到了更为定量、精确的电离层春秋分不对称性特征.分析了不同地方时(LT)的春秋分不对称性指数(Asymmetry Index,AI)和春秋分差值Δ(=ME-SE)的全球分布特征与太阳活动依赖性.结果表明,foE日出时全球主要表现为9月分点值高于3月分点值,午后春秋分不对称性几乎消失,而日落时则反转为3月分点值高于9月分点值;f_oF_2日出时除少数地区外也主要表现为9月分点值高于3月分点值,而其他时段则相反;TEC日出时低太阳活动时的全球及中高太阳活动时的低纬地区表现为9月分点值高于3月分点值,而其他时段则相反.fo_E春秋分不对称性受太阳活动影响较弱,而f_oF_2和TEC的春秋分不对称随太阳活动有明显的变化,其3月分点值相对于9月分点值增加.计算了F_2层峰高(h_mF_2)处对应的氧氮浓度比([O]/[N_2],由大气模型NRLMSISE-00计算得到)和h_mF_2的春秋分不对称性,提取了TEC年变化的幅度及相位信息.氧氮浓度比和h_mF_2的春秋分不对称性能够部分解释电离层的春秋分不对称性,而TEC春秋分不对称的全球分布特征可以用TEC年变化的相位的全球分布解释.
基金supported by the CMA (Grant No. GYHY201106011)the National Basic Research Program of China ("973" Project) (Grant No. 2012CB- 825604)+1 种基金the National Natural Science Foundation of China (Grant Nos. 41074112, 41174137, 41174138)the Specialized Research Fund for State Key Laboratories
文摘The hourly values of the ionospheric F2 layer critical frequency, foF2, recorded at Wakkanai ionosonde station (45.4°N, 141.7°E) have been collected to construct a middle-latitude single-station model for forecasting foF2 under geomagnetic quiet and disturbed conditions. The module for the geomagnetic quiet conditions incorporates local time, seasonal, and solar variability of climatological foF2 and its upper and lower quartiles. It is the first attempt to predict the upper and lower quartiles of foF2 to account for the notable day-to-day variability in ionospheric foF2. The validation statistically verifies that the model captures the climatological variations of foF2 with higher accuracy than IRI does. The storm-time module is built to capture the geomagnetic storm induced relative deviations of foF2 from the quiet time references. In the geomagnetically disturbed module, the storm-induced deviations are described by diurnal and semidiurnal waves, which are modulated by a modified magnetic activity index, the Kf index, reflecting the delayed responses of foF2 to geomagnetic activity forcing. The coefficients of the model in each month are determined by fitting the model formula to the observation in a least-squares way. We provide two options for the geomagnetic disturbed module, including or not including Kalman filter algorithm. The Kalman filter algorithm is introduced to optimize these coefficients in real time. Our results demonstrate that the introduction of the Kalman filter algorithm in the storm time module is promising for improving the accuracy of predication. In addition, comparisons indicate that the IRI model prediction of the F2 layer can be improved to provide better performances over this region.
