G44A-01 INVITED
Modernized GPS Signals and Ionospheric Scintillation
One of the major threats to accurate and reliable navigation, positioning, and timing (PNT) using the L1 CA code is scintillation produced by ionospheric irregularities. The introduction of new civilian PRN codes on L2 and L5 promise more accurate and reliable PNT, but these new signals are also vulnerable to scintillation. Recently we have developed GPS software receivers for examining the details of amplitude and phase scintillations on L1 and L2. These software receivers demonstrate that on L1, amplitude and phase scintillations are not independent and are strongly correlated. That is, the fastest phase shifts occur during the deepest fades. This leads to a similar question, are scintillations independent on L1 and L2? An experiment to address this question was conducted in January 2007. Signals were collected from the L1CA code and the L2C code during moderate scintillations using a software receiver located at Natal, Brazil. The answer to the question is that scintillations are strongly correlated between L1 and L2 for this example. The consequence of this strong correlation is that tracking will be unable to switch between the L1 and L2 signals when one of the signals is challenged by a fade for at least moderate scintillation levels. Earlier experiments at L band frequencies suggest that during strong scintillation fading may be less well correlated between L1 and L2. We present simulations to examine this hypothesis.
G44A-02 INVITED
Mesoscale ionospheric tomography at the Auroral region
FMI (Finnish Meteorological Institute) has used observations from the dense GNSS network in Finland for high resolution regional ionospheric tomography. The observation system used in this work is the VRS (Virtual Reference Station) network in Finland operated by Geotrim Ltd. This network contains 86 GNSS ground stations providing two frequency GPS and GLONASS observations with the sampling rate of 1 Hz. The network covers the whole Finland and the sampling of the ionosphere is very good for observing mesoscale ionospheric structures at the Auroral region. The ionospheric tomography software used by FMI is the MIDAS (Multi-Instrument Data Analysis System) algorithm developed and implemented by the University of Bath (Mitchell and Spencer, 2003). MIDAS is a 3-D extension of the 2-D tomography algorithm originally presented by Fremouw et al. (1992). The research at FMI is based on ground based GNSS data collected in December 2006. The impacts of the two geomagnetic storms during the month are clearly visible in the retrieved electron density and TEC maps and they can be correlated with the magnetic field disturbances measured by the IMAGE magnetometer network. This is the first time that mesoscale structures in the ionospheric plasma can be detected from ground based GNSS observations at the Auroral region. The continuous high rate observation data from the Geotrim network allows monitoring of the temporal evolution of these structures throughout the storms. Validation of the high resolution electron density and TEC maps is a challenge as independent reference observations with a similar resolution are not available. FMI has compared the 3-D electron density maps against the 2-D electron density plots retrieved from the observations from the Ionospheric Tomography Chain operated by the Sodankylä Geophysical Observatory (SGO). Additional validation has been performed with intercomparisons with observations from the ground based magnetometer and auroral camera network (MIRACLE), riometers, and the ionosonde station at SGO. This presentation will show the results from the ionospheric tomography research at FMI. References: Fremouw, E., J. Secan and B. Howe (1992): Application of stochastic inverse theory to ionospheric tomography, Radio Sci., 27(5), 721-732. Mitchell, C.N. and Spencer, P.S.J. (2003): A three-dimensional time-dependent algorithm for ionospheric imaging using GPS, Ann. Geophys., 46, 687–696.
G44A-03 INVITED
GPS Ionospheric Scintillation Monitoring and Investigation at High Latitude
Perturbations in solar-terrestrial phenomena can propagate from high to middle latitudes and may seriously degrade technological systems relying on trans-ionospheric radio propagation. The reliability of some of these systems is vital for safety-of-life applications. Consequently, upper atmosphere monitoring from ground base stations is needed to investigate and model ionospheric variability and to subsequently optimize forecasting techniques. Here the exiting network of specially modify GPS receivers for TEC and ionospheric scintillation monitoring (GISTM) at northern and southern high latitude regions is presented. Data are structured in a proper data base and examples of data accessibility and treatment are shown. The importance and the amount of data collected are highlighted by original investigations on the formation of the ionospheric irregularities causing scintillations and on the dynamics of the high latitude plasma under disturbed conditions. Statistical analysis is also performed on the occurrence of scintillation events as function of the magnetic local time and of the corrected magnetic latitude to characterize the climatology of the scintillation conditions. Relevant results of these works are here described and critically discussed. Finally, to reduce the impact of scintillation on Global Navigation Satellite Systems (GNSS), the IPDM (Ionospheric Perturbation Detection and Monitoring) European idea is introduced on the establishment of a network to coordinate and integrate ionospheric monitoring services already existing or planned to be established on national level.
G44A-04 INVITED
JPL/USC GAIM: Validating COSMIC and Ground-Based GPS Assimilation Results to Estimate Ionospheric Electron Densities
We seem to be in the midst of a revolution in ionospheric remote sensing driven by the abundance of ground and space-based GPS receivers, new UV remote sensing satellites, and the advent of data assimilation techniques for space weather. In particular, the COSMIC 6-satellite constellation was launched in April 2006. COSMIC now provides unprecedented global coverage of GPS occultations measurements, each of which yields electron density information with unprecedented ~1 km vertical resolution. Calibrated measurements of ionospheric delay (total electron content or TEC) suitable for input into assimilation models is currently made available in near real-time (NRT) from the COSMIC with a latency of 30 to 120 minutes. The University of Southern California (USC) and the Jet Propulsion Laboratory (JPL) have jointly developed a real-time Global Assimilative Ionospheric Model (GAIM) to monitor space weather, study storm effects, and provide ionospheric calibration for DoD customers and NASA flight projects. JPL/USC GAIM is a physics- based 3D data assimilation model that uses both 4DVAR and Kalman filter techniques to solve for the ion and electron density state and key drivers such as equatorial electrodynamics, neutral winds, and production terms. Daily (delayed) GAIM runs can accept as input ground GPS TEC data from 1200+ sites, occultation links from CHAMP, SAC-C, and the COSMIC constellation, UV limb and nadir scans from the TIMED and DMSP satellites, and in situ data from a variety of satellites (DMSP and C/NOFS). Real-Time GAIM (RTGAIM) ingests multiple data sources in real time, updates the 3D electron density grid every 5 minutes, and solves for improved drivers every 1-2 hours. Since our forward physics model and the adjoint model were expressly designed for data assimilation and computational efficiency, all of this can be accomplished on a single dual- processor Unix workstation. Customers are currently evaluating the accuracy of JPL/USC GAIM 'nowcasts' for ray tracing applications and trans-ionospheric path delay calibration. In the presentation, we will discuss the expected impact of NRT COSMIC occultation and NRT ground-based measurements and present validation results for ingest of COSMIC data into GAIM using measurements from World Days. We will quality check our COSMIC-derived products by comparing Abel profiles and JPL- processed results. Furthermore, we will validate GAIM assimilation results using Incoherent Scatter Radar measurements from Arecibo, Jicamarca and Millstone Hill datasets. We will conclude by characterizing the improved electron density states using dual-frequency altimeter-derived Jason vertical TEC measurements.
G44A-05
Impact of Different Modeling on Long-Time Series of Reprocessed Troposphere Zenith Delays
Troposphere zenith delays estimated from observations of the Global Positioning System (GPS) provide valuable information about the neutral atmosphere. On the other hand, troposphere long time series of operational GPS analyses are degraded by model changes, in particular as regards the tropospheric mapping function, hydrostatic a priori delays, the elevation cut-off angle and the reference frame used for datum definition. Therefore, a homogeneous reprocessing starting with the raw observation data is essential for a proper interpretation of these long-time series. This contribution studies the impact of different analysis options on long-time series of homogeneously reprocessed GPS troposphere zenith delays. The following analysis options are compared: (1) hydrostatic a priori delays (Global Pressure and Temperature model vs. delays from the ECMWF numerical weather model); (2) tropospheric mapping functions (Global Mapping Function vs. Vienna Mapping Function 1); and (3) GPS antenna phase center models (relative vs. absolute). The impact of these different modeling options on systematic biases, annual signals and the long-term drift behavior are analyzed. Finally, the diurnal and semidiurnal variations in the hydrostatic delay (due to the S1 and S2 pressure tides) and the wet delay are studied.
G44A-06 INVITED
The Atmospheric Water Vapor Content in Fennoscandia Measured by GPS 1996- 2006
We have used 10 years of ground-based GPS data to estimate time series of the water vapor content above each one of 33 GPS receiver sites in Finland and Sweden. Although a 10 year period is much too short to search for climate change we use the data set to assess the stability and consistency of the linear trend of the water vapor content that can be estimated from the data. The linear trends in the integrated water vapor content range from -0.2 to +1.0 kg m-2 decade-1. As one may expect we find different systematic patterns for summer and winter data. The formal uncertainty of these trends, taking the temporal correlation of the variability about the estimated model into account, are of the order of 0.4 kg m-2 decade-1. Mostly, this uncertainty is due to the natural short-term variability in the water vapor content, while the formal uncertainties in the GPS measurements have only a small impact on the trend errors. The overall goal for the possible use of GPS data in climate research is to determine to which extent these independent data can be used to discriminate between different climate models --- both in terms of absolute values as well as long term trends --- thereby improving the quality of the models and increasing the probability to produce realistic scenarios of the future climate. It seems reasonable to assume that such applications will require uncertainties of less than 0.1 kg m-2 decade-1. In addition to GPS also additional global navigational satellite systems (GNSS), such as the European Galileo and the finalization of the Russian GLONASS, can be used in the future. This will significantly improve the spatial sampling of the atmosphere, and also reduce the relative influence of orbit errors for individual satellites. On the other hand such changes can introduce new systematic effects in the estimated water vapor time series and care must be taken in order to understand and correct for such effects.
G44A-07
Impact of High-Resolution Data Assimilation of GPS Zenith Delay on Mediterranean Heavy Rainfall Forecasting
Mesoscale moisture fields are highly variable in space and time and ground-based GPS networks are unique to provide tropospheric water vapour observations at spatial and temporal resolutions that cope with that high variability. GPS Zenith delays data are thus good candidate for data assimilation and verification of mesoscale atmospheric models that have the capacity to reproduce the fine scale variability of the moisture fields. Assimilation of GPS ZTD has been recently developed in the variational data assimilation systems of Météo-France. Yan et al. (2008) revealed the benefit gained in prediction of intense rain when GPS ZTD observations are assimilated in the 3D-Var ALADIN system at 9.5 km. Here we investigate the impact of assimilating GPS data in a higher resolution data assimilation system, e.g. the 3DVAR AROME system running at 2.5 km. Two sets of three-hourly forecast-analysis have been run with the 3D-Var AROME data assimilation system. In the first data assimilation experiment, the GPS data are assimilated whereas in the second they are not assimilated. The data assimilation experiments cover two 15-day periods in order to include two case studies (29-30 September and 20-22 November 2007) of Mediterranean heavy precipitation events. The impact of assimilating GPS data on the AROME short-range forecast is examined for the accumulated rain. Preliminary results are encouraging, showing that the assimilation of GPS data improves the short range forecast of light precipitation on the 29-30 September 2007 case. The second case confirms this result. Yan, X., Ducrocq, V., Poli, P., Jaubert, G., and Walpersdorf, A.: Mesoscale GPS Zenith Delay assimilation during a Mediterranean heavy precipitation event, Advances in Geosciences, 17, 71–77, http://www.adv- geosci.net/17/71/2008/, 2008.
G44A-08
Regional Comparison and Study of Water Vapor as Measured by AIRS and GPS, Using ECMWF Surface Parameters
We compare tropospheric precipitable water vapor (PWV) measurements from the Atmospheric InfraRed Sounder (AIRS) satellite instrument to those from ground Global Positioning System (GPS) stations on a regional basis, with a mind toward mitigation of atmospheric effects in regional Interferometric Synthetic Aperture Radar (InSAR) studies. AIRS offers superior vertical atmospheric profiles from twice daily passes, whereas GPS-derived PWV estimates are available at high temporal resolution, typically 5 minute intervals. These complementary qualities suggest potential synergistic use in InSAR correction products. Computing GPS PWV from the Zenith Wet Delay (ZWD) estimated in Precise Point Positioning (PPP) analysis requires concurrently measured surface pressure and temperature at the GPS station. We turn to the European Center for Medium-Range Weather Forecasting (ECMWF) model for surface pressure estimates, since dense regional GPS networks do not always feature meteorological equipment co-located with the GPS stations. ECMWF pressures are given at a stated elevation that in the presence of orography may significantly differ from the elevation of a GPS station within the ECMWF grid square; we therefore account for this elevation difference in calculating a GPS station pressure based on the ECMWF surface pressure. We will present results of such regional studies, including the correlation between GPS and AIRS PWV estimates, biases, and dependence on the amount of water vapor in the atmosphere and other parameters. In one study in Southern California, we find the difference between AIRS and GPS PWV estimates calculated with corrected ECMWF pressures is independent of elevation. GPS PWV estimates are slightly drier than AIRS estimates in the relatively dry southern California atmosphere in winter and spring, consistent with previous continental-scale studies.