Abstract. In this study the climatology of ionospheric scintillations and the zonal drift velocities of scintillationproducing irregularities are depicted for a station located under the southern crest of the equatorial ionization anomaly. Then, the α−µ ionospheric fading model is used for the firstand second-order statistical characterization of amplitude scintillations. In the statistical analyzes, data are used from single-frequency GPS receivers acquired during ∼ 17 years (September 1997-November 2014 at Cachoeira Paulista (22.4 • S; 45.0 • W), Brazil. The results reveal that the nocturnal occurrence of scintillations follows the seasonal distribution of plasma bubble irregularities observed in the longitudinal sector of eastern South America. In addition to the solar cycle dependence, the results suggest that the occurrence climatology of scintillations is also modulated by the secular variation in the dip latitude of Cachoeira Paulista, since the maximum occurrence of scintillations during the peak of solar cycle 24 was ∼ 20 % lower than that observed during the maximum of solar cycle 23. The dynamics of the irregularities throughout a solar cycle, as investigated from the estimates of the mean zonal drift velocities, presented a good correlation with the EUV and F10.7 cm solar fluxes. Meanwhile, the seasonal behavior showed that the magnitude of the zonal drift velocities is larger during the December solstice months than during the equinoxes. In terms of modeling, the results for the α − µ distribution fit quite well with the experimental data and with the temporal characteristics of fading events independently of the solar activity level.

Irregularly structured ionospheric regions may cause amplitude and phase fluctuations of radio signals. Such distortion is called ionospheric scintillation. These ionospheric irregularities occur as part of depleted plasma density regions that are generated at the magnetic equator after sunset by equatorial ionospheric plasma instability mechanism. Also known as ionospheric bubbles, they drift upward to high altitudes at the equator and extend/expand to low latitudes along the Earth magnetic field lines. Ionospheric irregularities affect the space weather since they present large variations with the solar cycle and during solar flares and coronal mass ejections. In general, navigation systems such as the Global Positioning System and telecommunications systems are also affected by the scintillation. The aim of this work is to apply data mining for the prediction of ionospheric scintillation. Data mining can be divided into two categories: descriptive or predictive. The first one describes a data set in a concise and summarized way, while the second one, used in this work, analyzes the data to build a model and tries to predict the behavior of a new data set. In this study we employed data series of ionospheric scintillation and other parameters such as the level of solar activity, vertical drift velocity of the plasma at the magnetic equator, and magnetic activity. The results show that prediction of the ionospheric scintillation occurrence during the analyzed period was possible regardless of the high variability of the ionospheric parameters that affect the generation of such irregularities.

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During its transit through a region of equatorial ionospheric irregularities, sensors on board the Communication/Navigation Outage Forecasting System (C/NOFS) satellite provide a one‐dimensional description of the medium, which can be extended to two dimensions if the structures are assumed to be elongated in the direction of the magnetic field lines. The C/NOFS scintillation calculation approach assumes that the medium is equivalent to a diffracting screen with random phase fluctuations that are proportional to the irregularities in the total electron content, specified through the product of the directly measured electron density by an estimated extent of the irregularity layer along the raypaths. Within the international collaborative effort anticipated by the C/NOFS Science Definition Team, the present work takes the vertical structure of the irregularities into more detailed consideration, which could lead to improved predictions of scintillation. Initially, it describes a flexible model for the power spectral density of the equatorial ionospheric irregularities, estimates its shape parameters from C/NOFS in situ data and uses the signal‐to‐noise ratio S/N measurements by the São Luís coherent scatter radar to estimate the mean square electron density fluctuation 〈ΔN2〉 within the corresponding sampled volume. Next, it presents an algorithm for the wave propagation through a three‐dimensional irregularity layer which considers the variations of 〈ΔN2〉 along the propagation paths according to observations by the radar. Data corresponding to several range‐time‐intensity maps from the radar is used to predict time variations of the scintillation index S4 at the L1 Global Positioning System (GPS) frequency (1575.42 MHz). The results from the scintillation calculations are compared with corresponding measurements by the colocated São Luís GPS scintillation monitor for an assessment of the prediction capability of the present formulation.

Ionospheric plasma irregularities or bubbles, that are regions with depleted density, are generated at the magnetic equator after sunset due to plasma instabilities, and as they move upward they map along the magnetic field lines to low latitudes. To analyse the temporal and spatial evolution of the bubbles over Brazilian territory, the mapping of ionospheric plasma bubbles for the night of 17/18 March 2002 was generated using data collected from one GPS receiver array, and applying interpolation techniques. The impact on the performance of Global Navigation Satellites System (GNSS) and on the Space Based Augmentation System (SBAS) in the tropical regions of the GPS signal losses of lock and of the signal amplitude fades during ionospheric irregularities is presented.

Abstract. The climate in the Amazon region is particularly sensitive to surface processes and properties such as heat fluxes and vegetation coverage. Rainfall is a key expression of the land surface–atmosphere interactions in the region due to its strong dependence on forest transpiration. While a large number of past studies have shown the impacts of large-scale deforestation on annual rainfall, studies on the isolated effects of elevated atmospheric CO2 concentrations (eCO2) on canopy transpiration and rainfall are scarcer. Here, for the first time, we systematically compare the plant physiological effects of eCO2 and deforestation on Amazon rainfall. We use the CPTEC Brazilian Atmospheric Model (BAM) with dynamic vegetation under a 1.5×CO2 experiment and a 100 % substitution of the forest by pasture grasslands, with all other conditions held similar between the two scenarios. We find that both scenarios result in equivalent average annual rainfall reductions (Physiology: −257 mm, −12 %; Deforestation: −183 mm, −9 %) that are above the observed Amazon rainfall interannual variability of 5 %. The rainfall decreases predicted in the two scenarios are linked to a reduction of approximately 20 % in canopy transpiration but for different reasons: the eCO2-driven reduction of stomatal conductance drives the change in the Physiology experiment, and the smaller leaf area index of pasturelands (−72 % compared to tropical forest) causes the result in the Deforestation experiment. The Walker circulation is modified in the two scenarios: in Physiology due to a humidity-enriched free troposphere with decreased deep convection due to the heightening of a drier and warmer (+2.1 ∘C) boundary layer, and in Deforestation due to enhanced convection over the Andes and a subsidence branch over the eastern Amazon without considerable changes in temperature (−0.2 ∘C in 2 m air temperature and +0.4 ∘C in surface temperature). But again, these changes occur through different mechanisms: strengthened west winds from the Pacific and reduced easterlies entering the basin affect the Physiology experiment, and strongly increased easterlies influence the result of the Deforestation experiment. Although our results for the Deforestation scenario agree with the results of previous observational and modelling studies, the lack of direct field-based ecosystem-level experimental evidence regarding the effect of eCO2 on moisture fluxes in tropical forests confers a considerable level of uncertainty to any projections of the physiological effect of eCO2 on Amazon rainfall. Furthermore, our results highlight the responsibilities of both Amazonian and non-Amazonian countries to mitigate potential future climatic change and its impacts in the region, driven either by local deforestation or global CO2 emissions.

Abstract. On 11 April 2001, a large magnetic storm occurred with SSC at 13:43 UT, and D st reached below −200 nT after two southward B z excursions. The K p index during this storm reached 8 and remained high (>4) for about 21 h, and the São Luís magnetometer H component presented simultaneous oscillations and decreased substantially relative to the previous magnetically quiet days. This storm triggered strong ionospheric irregularities, as observed by a recently installed 30 MHz coherent scatter radar, a digisonde, and a GPS scintillation receiver, all operating at the São Luís equatorial station (2.33 • S, 44 •

Ionospheric scintillation refers to amplitude and phase fluctuations in radio signals due to electron density irregularities associated to structures named ionospheric plasma bubbles. The phenomenon is more pronounced around the magnetic equator where, after sunset, plasma bubbles of varying sizes and density depletions are generated by plasma instability mechanisms. The bubble depletions are aligned along Earth's magnetic field lines, and they develop vertically upward over the magnetic equator so that their extremities extend in latitude to north and south of the dip equator. Over Brazil, developing bubbles can extend to the southern peak of the Equatorial Ionization Anomaly, where high levels of ionospheric scintillation are common. Scintillation may seriously affect satellite navigation systems, such as the Global Navigation Satellite Systems. However, its effects may be mitigated by using a predictive model derived from a collection of extended databases on scintillation and its associated variables. This work proposes the use of a classification and regression decision tree to perform a study on the correlation between the occurrence of scintillation at the magnetic equator and that at the southern peak of the equatorial anomaly. Due to limited size of the original database, a novel resampling heuristic was applied to generate new training instances from the original ones in order to improve the accuracy of the decision tree. The correlation analysis presented in this work may serve as a starting point for the eventual development of a predictive model suitable for operational use.