Abstract Ionospheric modeling across the Indian low latitudes continues to be a challenging task because of the day-to-day variability pertaining to the underlying complex equatorial and low latitude electrodynamics. In this paper, we aimed at developing an ionospheric Total Electron Content (TEC) model based on Singular Spectrum Analysis (SSA) using the Global Positioning System (GPS)-TEC observations (from 2009 to 2019) at Bengaluru (Geographic: 13.02° N, 77.57° E; Dip Angle: 13.77° N), a low latitude station in India. SSA has the most significant advantage of extracting information from the noisy time-series data with the first-four SSA modes in the decomposition, almost converging to total variance of about 99%. The proposed SSA-TEC model has been assessed by comparing it with the GPS-TEC observations as well as the outcomes from the latest version of the International Reference Ionosphere model (IRI-2016) and International GNSS Services Global Ionosphere Maps (IGS-GIM). The results demonstrate excellent outcomes with the Root Mean Square Error (RMSE) values between observed and model estimations laying at 1.58 TECU (SSA), 7.04 TECU (IRI-2016), and 8.89 TECU (GIM) with the respective correlation coefficients 0.99, 0.91, and 0.94. The model outcomes are in good agreement with the GPS-TEC observations, presenting relatively better estimates of TEC than the IRI-2016 and GIM during the geomagnetically quiet and disturbed daytime and nighttime conditions under different seasons and solar activity. Moreover, the proposed SSA-TEC model replicates the significant changes and time distribution characteristics of the ionosphere over the low latitude location, foreseeing the scopes for its regional implementation with a wide range of operations.

中文翻译：

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在第 24 个太阳周期期间使用 SSA 模型对来自 GPS-TEC 测量的电离层 TEC 变异性进行建模和分析

摘要 印度低纬度地区的电离层建模仍然是一项具有挑战性的任务，因为与潜在的复杂赤道和低纬度地区电动力学有关的日常变化。在本文中，我们旨在开发基于奇异谱分析 (SSA) 的电离层总电子含量 (TEC) 模型，使用全球定位系统 (GPS)-TEC 观测（从 2009 年到 2019 年）在班加罗尔（地理：北纬 13.02° , 77.57° E；倾角：13.77° N)，印度的一个低纬度站。SSA 最显着的优势是在分解中使用前四种 SSA 模式从嘈杂的时间序列数据中提取信息，几乎收敛到大约 99% 的总方差。通过将提议的 SSA-TEC 模型与 GPS-TEC 观测以及最新版本的国际参考电离层模型 (IRI-2016) 和国际 GNSS 服务全球电离层地图 (IGS-GIM) 的结果进行比较，对其进行了评估. 结果表明，观测值和模型估计值之间的均方根误差 (RMSE) 值分别为 1.58 TECU (SSA)、7.04 TECU (IRI-2016) 和 8.89 TECU (GIM)，相关系数分别为 0.99、0.91 , 和 0.94。模型结果与 GPS-TEC 观测结果非常吻合，在不同季节和太阳活动下地磁安静和干扰的白天和夜间条件下，对 TEC 的估计比 IRI-2016 和 GIM 更好。而且，