Empirical modeling of ionospheric F2 layer critical frequency over Wakkanai under geomagnetic quiet and disturbed conditions

作     者：LIU Jing LIU LiBo ZHAO BiQiang WAN WeiXing CHEN YiDing 

作者机构：Beijing National Observatory of Space EnvironmentInstitute of Geology and GeophysicsChinese Academy of Sciences Beijing 100029China Graduate University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Space WeatherCenter for Space Science and Applied ResearchChinese Academy of SciencesBeijing 100190China 

出 版 物：《Science China(Technological Sciences)》 (中国科学（技术科学英文版）)

年 卷 期：2012年第55卷第5期

页      面：1169-1177页

核心收录：

学科分类：070801[理学-固体地球物理学] 07[理学] 0708[理学-地球物理学] 070402[理学-天体测量与天体力学] 0704[理学-天文学] 

基　　金：supported by the CMA (Grant No. GYHY201106011) the National Basic Research Program of China ("973" Project) (Grant No. 2012CB- 825604) the National Natural Science Foundation of China (Grant Nos. 41074112, 41174137, 41174138) the Specialized Research Fund for State Key Laboratories 

主　　题：Empirical modeling Kalman f＇dter ionospheric storm 

摘      要：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 vari- ability 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 diumal and semidiumal waves, which are modulated by a modified magnetic activity index, the Kf index, reflecting the delayed responses of foF2 to geomagnetic activity forcing. The coeffi- cients 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.