We analyze data recorded from October 2010 to September 2011, during the ascending phase of the 24th solar cycle, from an Advanced Ionospheric Sounder‐Istituto Nazionale di Geofisica e Vulcanologia ionosonde and a GPS Ionospheric Scintillation and total electron content (TEC) monitor scintillation receiver, colocated at low latitude in the Southern American longitudinal sector (Tucumán, 26.9°S, 294.6°E, magnetic latitude 15.5°S, Argentina). The site offers the opportunity to perform spread‐F and GPS scintillation statistics of occurrence under the southern crest of the equatorial ionospheric anomaly. Spread‐F signatures, classified into four types (strong range spread‐F (SSF), range spread‐F, frequency spread‐F (FSF), and mixed spread‐F), the phase and amplitude scintillation index (σΦ and S4, respectively), the TEC, and the rate of TEC parameter, marker of the TEC gradients, that can cause scintillations, are considered. The seasonal behavior results as follows: the occurrence of all four types of spread‐F is higher in summer and lower in winter, while the occurrence of scintillations peaks at equinoxes in the postsunset sector and shows a minimum in winter. The correspondence between SSF and scintillations seems to be systematic, and a possible correlation between S4 and FSF peaks is envisaged at the terminator. The investigation focused also on two particular periods, from 12 to 16 March 2011 and from 23 to 29 September 2011, both characterized by the simultaneous presence of SSF signatures and scintillation phenomena, allowing to discuss the role of traveling ionospheric disturbances as a strong candidate causing ionospheric irregularities.

Many real‐life signals and, in particular, in the space physics domain, exhibit variations across different temporal scales. Hence, their statistical momenta may depend on the time scale at which the signal is studied. To identify and quantify such variations, a time‐frequency analysis has to be performed on these signals. The dependence of the statistical properties of a signal fluctuation on the space and time scales is the distinctive character of systems with nonlinear couplings among different modes. Hence, assessing how the statistics of signal fluctuations vary with scale will be of help in understanding the corresponding multiscale statistics of such dynamics. This paper presents a new multiscale data analysis technique, the adaptive local iterative filtering (ALIF), which allows to describe the multiscale nature of the geophysical signal studied better than via Fourier transform, and improves scale resolution with respect to discrete wavelet transform. The example of geophysical signal, to which ALIF has been applied, is ionospheric radio power scintillation on L band. ALIF appears to be a promising technique to study the small‐scale structures of radio scintillation due to ionospheric turbulence.