One of the most popular indices for monitoring the occurrence and intensity of ionospheric L-band irregularities is the Rate of TEC Index (ROTI). Due to low TEC in the mid-latitude ionosphere, ROTI has received significantly less attention than the equatorial and polar ionosphere. On the other hand, spread F is an established ionogram irregularity signature. The present study aims to correlate ROTI and spread F activity over European Digisonde stations for a low-to-moderate solar activity year (2011). With a focus on the latitude-dependent occurrence, the analysis demonstrates that range spread F (RSF) has been identified for all notable ROTI (>0.15 TECU/min) cases which also coincide with MSTID activity over the stations, suggesting induced gravity waves or polarization electric fields as the driving mechanism for enhanced ROTI activity. The diurnal and seasonal features are also presented. Maximum irregularity occurrence was observed around the 45° N from 18:00 to 05:00 UT with the seasonal maximum occurrence in January. Over lower mid-latitude Digisonde stations (latitude < 45° N), the diurnal and seasonal occurrence was observed from 19:00 to 04:30 UT in July.

This study investigates the diurnal, seasonal, and latitudinal variations of Spread F and the Rate of TEC Index (ROTI) over North America during the high solar activity period of 2014. Using GNSS-based ROTI measurements and Digisonde ionograms from multiple stations, we systematically analyze the relationship between Spread F occurrences and ROTI enhancements. The analysis incorporated Diurnal and seasonal variations to determine dominant trends and potential driving mechanisms, such as medium-scale traveling ionospheric disturbances (MSTIDs) and polarization electric fields. Seasonal and latitudinal variations of Spread F occurrences and ROTI fluctuations are found to be strongly linked to MSTIDs and geomagnetic activity. A clear seasonal dependence was observed at the stations situated under the transitional and mid-latitude regions of the ionosphere. The maximum irregularity occurred in April for transitional region stations and in November for mid-latitudinal stations. Additionally, Spread F and ROTI exhibit similar diurnal and seasonal trends, with maximum irregularity occurrences during nighttime (20:00–02:00 LT). A distinct seasonal dependence is observed, with transitional region stations peaking in winter and mid-latitude stations in summer. Notably, spread F was consistently associated with notable ROTI values (>0.15 TECU/min), suggesting gravity waves and polarization electric fields as driving mechanisms. Through detailed case studies, we demonstrated that MSTIDs, likely driven by gravity wave dynamics, play a crucial role in generating plasma irregularities, which in turn enhance ROTI values and contribute to Spread F formation. Under quiet geomagnetic conditions, these irregularities exhibit a strong daytime preference. Conversely, during disturbed geomagnetic conditions (e.g., the geomagnetic storm), the spatial extent of ionospheric irregularities increased significantly, affecting both transitional and mid-latitude stations for both daytime and nighttime. By demonstrating a persistent relationship between Spread F and ROTI, this study advances ionospheric modelling efforts and supports the development of improved space weather forecasting techniques, crucial for GNSS-based navigation and communication systems.

Lightning is a significant atmospheric event and has a wide-ranging influence on the Earth’s climate. Recently a sensor station of World Wide Lightning Location Network (WWLLN) is hosted at Dhaka (23.81°N, 90.41°E) and one year (Jan 2021 to Dec 2021) lightning strokes energy data is investigated. In an effort to switch the analysis from descriptive to predictive, WWLLN lightning strokes energy data is modeled using time series analysis. The autoregressive integrated moving average (ARIMA) model has been applied to predict the data. According to the process of model selection, the auto-correlation function (ACF) and partial auto-correlation function (PACF) are examined to determine the auto-regressive (AR) and moving-average (MA) terms. Standard diagnostic tests are performed to ensure the goodness of fit of the chosen model. After necessary diagnostic tests, ARIMA (3,1,0)×(2,1,0)₁₂ is selected as the best fitted model.