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This work presents a contribution to the understanding of the ionospheric triggering of L-band scintillation in the region over São Paulo state in Brazil, under high solar activity. In particular, a climatological analysis of Global Navigation Satellite Systems (GNSS) data acquired in 2012 is presented to highlight the relationship between intensity and variability of the total electron content (TEC) gradients and the occurrence of ionospheric scintillation. The analysis is based on the GNSS data acquired by a dense distribution of receivers and exploits the integration of a dedicated TEC calibration technique into the Ground Based Scintillation Climatology (GBSC), previously developed at the Istituto Nazionale di Geofisica e Vulcanologia. Such integration enables representing the local ionospheric features through climatological maps of calibrated TEC and TEC gradients and of amplitude scintillation occurrence. The disentanglement of the contribution to the TEC variations due to zonal and meridional gradients conveys insight into the relation between the scintillation occurrence and the morphology of the TEC variability. The importance of the information provided by the TEC gradients variability and the role of the meridional TEC gradients in driving scintillation are critically described.

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Global Positioning System (GPS) signal-to-noise ratio (SNR) measurements can be employed to retrieve environmental variables in multipath reception conditions, whereby direct or line-of-sight transmission is received simultaneously with coherent reflections thereof. Previous GPS SNR multipath studies of soil moisture and snow depth have focused on the legacy GPS L1 and L2 bands. In the present paper, short-delay, near-grazing incidence multipath from the L5-band GPS SNR is assessed for its value in detecting soil moisture and snow depth. The L5 signal will become more important in the future because of compatibility and interoperability among the different global satellite navigation systems. The L5 results are compared with L2C estimates to determine whether the L2C-L5 differences (given their differing power budgets and their modulation properties) are significant. To address these questions, measurements and simulations were employed. A physically-based multipath simulator was enhanced to investigate the differences between parameter retrievals for the L2C and the L5 GPS signals. Parameter retrievals from synthetic observations for different scenarios were compared. Comparisons included varying reflector height, surface material, and surface roughness. Measurements from two GPS stations in Colorado, USA, were used to retrieve soil moisture and snow depth conditions. Over a 153-day period that encompassed the catastrophic 2013 Colorado flooding event, L2-derived volumetric soil moisture had an RMS difference of 0.042 cm 3 /cm 3 while the L5 RMS difference was 0.034 cm 3 / cm 3 with respect to in-situ data (values of volumetric soil moisture range between 0.04 and 0.34 cm 3 /cm 3 ). In a separate 483-day campaign, L5-derived snow depth estimates were compared to L2C-derived values and found strongly correlated, deviating from a one-toone relationship by only 0.00001 ± 0.0064 cm/cm. These results indicate the absence of any detectable biases in L5 as compared to L2C for retrieving soil moisture and snow depth from GPS SNR multipath observations.

Ionospheric Scintillations are rapid variations on the phase and/or amplitude of a radio signal as it passes through ionospheric plasma irregularities. The ionosphere is a specific layer of the Earth's atmosphere located approximately between 50 km and 1000 km above the Earth's surface. As Global Navigation Satellite Systems (GNSS)such as GPS, Galileo, BDS and GLONASSuse radio signals, these variations degrade their positioning service quality. Due to its location, Brazil is one of the places most affected by scintillation in the world. For that reason, ionosphere monitoring stations have been deployed over Brazilian territory since 2011 through cooperative projects between several institutions in Europe and Brazil. Such monitoring stations compose a network that generates a large amount of monitoring data everyday. GNSS receivers deployed at these stationsnamed Ionospheric Scintillation Monitor Receivers (ISMR)provide scintillation indices and related signal metrics for available satellites dedicated to satellite-based navigation and positioning services. With this monitoring infrastructure, more than ten million observation values are generated and stored every day. Extracting the relevant information from this huge amount of data was a hard process and required the expertise of computer and geoscience scientists. This paper describes the concepts, design and aspects related to the implementation of the software that has been supporting research on ISMR datathe so-called ISMR Query Tool. Usability and other aspects are also presented via examples of application. This web based software has been designed and developed aiming to ensure insights over the huge amount of ISMR data that is fetched every day on an integrated platform. The software applies and adapts time series mining and information visualization techniques to extend the possibilities of exploring and analyzing ISMR data. The software is available to the scientific community through the World Wide Web, therefore constituting an analysis infrastructure that complements the monitoring one, providing support for researching ionospheric scintillation in the GNSS context. Interested researchers can access the functionalities without cost at http://is-cigala-ca libra.fct.unesp.br/, under online request to the Space Geodesy Study Group from UNESP-Univ Estadual Paulista at Presidente Prudente.

A dense Global Navigation Satellite System (GNSS) meteorological network (∼20 stations) in the central Amazon Basin in Brazil is being developed for long-term studies of deep convection/water vapor interactions and feedback. In this article, the network is described and preliminary results are presented: GNSS-derived precipitable water vapor is useful for tracking water vapor advection and in identifying convective events and water vapor convergence timescales. Upon network completion (early 2011), 3D water vapor field analyses and participation in the intensive field campaign GPM-CHUVA will provide unique data sets for initializing, constraining or validating high-resolution models or refining convective parameterizations.

When GNSS receivers capable of collecting dual-frequency data are available, it is possible to eliminate the first-order ionospheric effect in the data processing through the ionosphere-free linear combination. However, the second-and third-order ionospheric effects still remain. The first-, second-and third-order ionospheric effects are directly proportional to the total electron content (TEC), although the second-and third-order effects are influenced, respectively, by the geomagnetic field and the maximum electron density. In recent years, the international scientific community has given more attention to these kinds of effects and some works have shown that for high precision GNSS positioning these effects have to be taken into consideration. We present a software tool called RIN-EX_HO that was developed to correct GPS observables for second-and third-order ionosphere effects. RINEX_HO requires as input a RINEX observation file, then computes the second-and third-order ionospheric effects, and applies the corrections to the original GPS observables, creating a corrected RINEX file. The mathematical models implemented to compute these effects are presented, as well as the transformations involving the earth's magnetic field. The use of TEC from global ionospheric maps and TEC calculated from raw pseudorange measurements or pseudoranges smoothed by phase is also investigated.

Water vapor is an atmospheric component of major interest in atmospheric science because it affects the energy budget and plays a key role in several atmospheric processes. The Amazonian region is one of the most humid on the planet, and land use change is able to affect the hydrologic cycle in several areas and consequently to generate severe modifications in the global climate. Within this context, accessing the error associated with atmospheric humidity measurement and the validation of the integrated water vapor (IWV) quantification from different techniques is very important in this region. Using data collected during the Radiation, Cloud, and Climate Interactions in Amazonia during the Dry-to-Wet Transition Season (RACCI/DRY-TO-WET), an experiment carried out in southwestern Amazonia in 2002, this paper presents quality analysis of IWV measurements from RS80 radiosondes, a suite of GPS receivers, an Aerosol Robotic Network (AERONET) solar radiometer, and humidity sounding from the Humidity Sounder for Brazil (HSB) aboard the Aqua satellite. When compared to RS80 IWV values, the root-mean-square (RMS) from the AERONET and GPS results are of the order of 2.7 and 3.8 kg m Ϫ2, respectively. The difference generated between IWV from the GPS receiver and RS80 during the daytime was larger than that of the nighttime period because of the combination of the influence of high ionospheric activity during the RACCI experiment and a daytime drier bias from the RS80.