SF53A-0721 1340h
Comparison and Validation of Ionospheric GPS Occultation Measurements With Arecibo ISR Data
The ionosphere is a dynamic region capable of adversely impacting a variety of space-based systems. Thus, it is imperative that accurate global monitoring of ionospheric conditions exists. Occultation measurements of GPS signals from receivers on Low Earth Orbiting (LEO) satellites are capable of supplying accurate, global monitoring of the ionosphere at a high vertical resolution. Each LEO satellite with a GPS receiver experiences nearly 500 ionospheric occultations a day globally. This paper presents several occultations from the IOX and CHAMP instruments that correspond to the approximate location and days of operation of the Arecibo Observatory (AO) Incoherent Scatter Radar (ISR). There are forty-three ISR World Day observations since 2000 that are the focus of the following study. During the same observation periods, the IOX instrument observed over forty occultation events approximately co-located to AO. The closely circular and polar orbit of the CHAMP satellite routinely provides a global and homogenous observation of the near Earth's atmosphere. Thus, the possibility of co-located occultation events with AO on the specific days of interest increases further with the CHAMP instrument. Specific TEC data and Ne profiles from the GPS and ISR measurements are shown and compared. This paper also discusses limited statistics using the ISR and the two satellite data sets
SF53A-0722 1340h
Preliminary Attempts to Connect Ocean Reflected GNSS Signals Detected From Low Earth Orbit With Sea Winds
Most people are generally aware of the fact that the GPS receivers used on boats and airplanes use signals transmitted by a constellation of satellites to determine their locations. What is less obvious is that the same signals are constantly being scattered off the surrounding seas and land, and these signals contain valuable and varied information on the Earth's environment. The GNSS bi-static radar experiment carried on the UK disaster monitoring constellation satellite has been collecting and down linking raw data containing ocean reflected GPS signals since its successful commissioning in March of 2004. It is our aim to connect the delay and Doppler shapes of the received ocean scattered waveforms to an observable ocean phenomenon. This has been shown to be possible based on numerous ground and aircraft experiments utilising the same concept. In these cases it was important to obtain a truth measurement to coincide with the experiment data, such as collecting data while flying underneath TOPEX/POSIEDEN as it passes overhead. In the case of collecting data on an orbiting satellite it becomes more complicated. Sea wind estimates have been obtained from the QuickSCAT and JASON satellites as well as from buoy's and weather models. To what extent these independent measurements provide a degree of "truth" depends on several factors. The most obvious of these are the spatial and temporal coincidence with the signal detections. These and other issues will be discussed and the steps that have been taken to improve the validation procedure will be presented. Despite the obstacles encountered, it can be shown that ocean reflected signals from the GPS navigation satellite constellation can be tracked from a low-earth orbiting satellite and that these signals show rough correlation with independent measurements of the sea winds. This breakthrough has the potential to influence a wide range of applications including the determination of sea surface roughness, ocean wind speed and potentially sea surface altimetry. From low Earth orbit, these types of measurements could provide high-density sampling over meso-scale ocean features, which could significantly impact global climate modelling. Based on our initial results, satellite ocean remote sensing using passive ocean scattered signals is now possible.
SF53A-0723 1340h
Soil Moisture and Vegetation Effects on GPS Reflectivity From Land
While originally designed as a navigation system, the GPS signal has been used to achieve a number of useful scientific measurements. One of these measurements utilizes the reflection of the GPS signal from land to determine soil moisture. The study of GPS reflections is based on a bistatic configuration that utilizes forward reflection from the surface. The strength of the GPS signal varies in proportion to surface parameters such as soil moisture, soil type, vegetation cover, and topography. This paper focuses on the effects of soil water content and vegetation cover on the surface based around a reflectivity. A two-part method for calibrating the GPS reflectivity was developed that permits the comparison of the data with surface parameters. The first part of the method relieves the direct signal from any multipath effects, the second part is an over-water calibration that yields a reflectivity independent of the transmitting satellite. The sensitivity of the GPS signal to water in the soil is shown by presenting the increase in reflectivity after rain as compared to before rain. The effect of vegetation on the reflected signal is also presented by the inclusion of leaf area index as a fading parameter in the reflected signal from corn and soy bean fields. The results are compared to extensive surface measurements made as part of the Soil Moisture Experiment 2002 (SMEX 2002) in Iowa and SMEX 2003 in Georgia.
SF53A-0724 1340h
Real-time monitoring of crustal deformation using large GPS geodetic networks - Japanese GEONET's potential as a natural hazards mitigation system
Dense regional GPS geodetic networks have been successfully established to monitor crustal deformation and associated natural hazards. Procedures for early warning and rapid damage assessment, which are especially important in heavily populated areas, however, have, in most cases, not yet been fully incorporated into the data analysis of these networks. The GPS Earth Observation Network System (GEONET) in Japan, maintained by the Geographical Survey Institute (GSI), consists of an analysis center and an array of 1200 GPS stations that cover the entire country with an average spacing of about 20 km. In the past, precise site positions were calculated only once per day. Since 2001 GSI has been working toward real-time observations and analysis. Now, most sites sample at 1 Hz and transmit the measurements in real time to the analysis center. Using GEONET data from the time of the Mw=8.0 Tokachi-Oki earthquake (September 25, 2003) as a test case, this study focuses on a real-time applicable bootstrapping method to determine accurate absolute static and dynamic station motion. For this method we divide 121 stations from the northeastern part of Japan into 12 clusters; each cluster consists of 11 stations one of which is shared with the neighboring cluster. For each cluster, we calculate instantaneous baseline components for all stations of that cluster, using the Geodetics RTD software. Based on absolute (ITRF) coordinates of stations from clusters sufficiently remote from the epicenter we adjust the components of the shared stations and by means of the computed baselines then for all stations. This method thus yields absolute (ITRF) motion of stations within the epicentral region in real time. Using instantaneous position solutions from the day before and after the earthquake and comparing them to daily positions, we quantify error propagation introduced by our method. We find that for the sequence of 12 clusters spanning about 1000 km, RMS errors approximately double from the initial to the final cluster. Instantaneous coordinate accuracy is about 1-2 cm in the horizontal and 10-20 cm in the vertical, compared to the known ITRF coordinates of the stations. Theoretically this sequence can be extended to cover the entire Japanese archipelago keeping the above error rate. We conclude that coherent instantaneous (horizontal) position changes detected by a dense GPS network (like GEONET) could be used as part of an early warning system for mitigating natural hazards.
SF53A-0725 1340h
Computationally Efficient Inversion of Scattered GPS Signals for the Retrieval of Surface Winds or Roughness from an Airborne Receiver
An approximation is presented for the forward model relating the correlation waveform of a reflected GPS signal to the statistics of the reflecting surface slopes. This approximation eliminates the need to numerically integrate over the reflecting surface to generate waveforms for assumed surface conditions. The inverse problem, estimation of the surface slope statistics from measurements of the waveform, is substantially faster through the use of this approximate model and its gradient. Prior work has shown that the bistatic scattering model can be formulated as a convolution between the GPS code autocorrelation function and the distribution of scattered power with delay. A change of variables in the surface integral, from a Cartesian system, to delay and an angular coordinate, the scattered waveform can be computed as a single integral over the angular coordinate, and a convolution in delay. If Doppler spreading is ignored, a good approximation at aircraft speeds, the second integral is shown to scale with altitude, thereby allowing a single calculation to be performed, with the result scaled to the appropriate aircraft altitude. Finally, an exponential series, with numerically-determined coefficients, is found to approximate this integral very well, and can be computed with substantially lower processing time. This reduced model is demonstrated by processing a long series of aircraft data using a recursive least squares method, to generate estimates of the mean square slope of the ocean surface. A number of empirical models can then be applied to produce a wind speed estimate from this mean square slope. The processing time for this demonstration is low enough to justify its application to an onboard real time wind speed sensor, which could have operational uses in weather monitoring, or search and rescue.
SF53A-0726 1340h
Detection and Investigation of Ionospheric Disturbances using the SCIGN Network
Ionospheric perturbations associated with atmospheric disturbances, such as earthquakes, large explosions, or rocket launches have been detected in the past, through filtering of dual-frequency GPS phase data. To further study these phenomena, we extract GPS data from the SCIGN network in Southern California, and attempt to identify the direction and speed of propagation, particularly for examples in which no obvious source could be identified. The processing of data from about 250 stations in the SCIGN followed three general steps. First the IEC (Integrated Electron Contents) time series was bandpass-filtered between 3 and 8 minutes. Second, the filtered time series from each pair of two SIPs (Sub-ionospheric points) were cross-correlated, to detect the degree of similarity between the perturbations, and to estimate the time of travel between the SIP. Finally, the travel times, for all pairs of SIP's for which a disturbance was detected, were used to estimate the propagation velocity (speed and direction) of the disturbance using a least squares method. An effect, which is similar to the Doppler effect, is predicted to result from the motion of the SIP during the time in which the perturbations are recorded. Since the speeds of the SIPs, due to satellite motion, are on the same order of magnitude as the propagation speed of ionospheric disturbances, an apparent shift in the observed frequency of the disturbances would result, depending upon the orientation between the propagation directions of the SIP's and the ionospheric disturbance. In addition to experimental data, recorded on 07/07/2000, simulated data was also used to validate the data processing algorithms, and to assess their sensitivity.
SF53A-0727 1340h
Near Sea Surface Wind Estimations Using Airborne GPS Systems
Studies have shown that airborne GPS remote sensing techniques can be used to retrieve near sea surface wind speeds. Methods for determining directions of the winds using the GPS techniques, however, have not been fully developed. This study tries to use the GPS signals reflected from the sea surface to estimate not only near sea surface wind speeds but also directions. The method in estimating sea surface winds utilizes aircraft-received multiple path length GPS signals reflected from the sea surface. The intensity and waveform of these sea surface reflected GPS signals are dependent on the roughness (or slope) and spatial anisotropy of the rough sea surfaces caused by near sea surface winds. A theoretical model based on Cox and Munk's sea surface slope probability and the GPS signal transfer and reflection process is used to simulate airborne GPS signals. The modeled GPS waveforms are generally a function of the wind speed and direction, aircraft altitude, and GPS satellite elevation angle. Using a matched filter, these simulated GPS signal waveforms are compared with actual airborne data that is simultaneously measured from two GPS satellites at different elevation and azimuth angles. The best match of the simulated GPS signals and the measurements from the GPS satellites provides estimated values for near sea surface wind speed and direction. The GPS estimated results have been compared to buoy recordings and TOPEX satellite measurements. The retrieved wind speeds are generally within 2 m/s of buoy recordings and other satellite measurements. The wind direction retrievals deviate from about 0° to 35° away from corresponding buoy data. 180° ambiguity was found in the directional retrievals. To overcome this ambiguity, a third set of simultaneous GPS satellite measurements may be needed, which is left for future studies.
SF53A-0728 1340h
Climate Monitoring With CHAMP Radio Occultation Data: The CHAMPCLIM Project
The radio occultation (RO) technique is based on a satellite-to-satellite limb sounding concept using microwave signals to probe the Earth's atmosphere. The propagation of Global Navigation Satellite System (GNSS) signals is influenced by the atmospheric refractivity field resulting in slowing and bending of the signal. The atmospheric phase delay as the principle observable is measured with millimetric accuracy. It is the basis for high-quality retrievals of atmospheric key variables, particularly of temperature profiles. Highest temperature accuracies of $<$~1~K are obtained in the upper troposphere and lower stratosphere. The long-term stability, self-calibrated nature, all-weather capability, high vertical resolution, global coverage, and high accuracy of RO data suggests them as a promising tool for global short- and long-term monitoring of atmospheric temperature change. The German/US research satellite CHAMP (CHAllenging Minisatellite Payload for geoscientific research) continuously records RO profiles since March 2002. The mission is expected to last at least until 2007, thus CHAMP RO data provide the first opportunity to create real RO based climatologies on a longer term. CHAMPCLIM is a joint project of the Institute for Geophysics, Astrophysics, and Meteorology (IGAM) in Graz and the GeoForschungsZentrum (GFZ) in Potsdam. It aims at exploiting the CHAMP RO data in the best possible manner for climate research. For this purpose, all CHAMP RO profiles provided by GFZ on excess phase level are currently processed at IGAM to obtain atmospheric profiles of refractivity, geopotential height, and dry temperature. The IGAM retrieval scheme is tailored to minimizing biases and yields a new atmospheric data set especially tuned for monitoring climate variability and change. The retrieved atmospheric profiles (150-160 profiles/day) are used to create climatologies on a monthly, seasonal, and annual basis. After focus on optimizing the RO data processing for climate applications and validation of the retrieval results using various reference data sources (now continued as "background" activity), the main emphasis is currently on the setup of a pre-operational system, processing of the complete 2002-2004 data, and on the creation of global climatologies including error estimates. After an overview on the status of the CHAMPCLIM project, we will focus on dry temperature climatologies from seasons within spring (MAM) 2002 to winter (DJF) 2003/2004, obtained by averaging-and-binning. Our results show that useful dry temperature climatologies resolving horizontal scales $>$~1000~km can be obtained even with data from a single RO receiver. RO based climatologies have the potential to improve modern operational climatologies, especially in regions where the data coverage and/or the vertical resolution and accuracy of RO data is superior to traditional data sources.
SF53A-0729 1340h
Monitoring Moisture in the Planetary Boundary Layer Using GPS Ground Stations
Atmospheric water vapor is exceedingly variable over both space and time, with the vast majority residing in the planetary boundary layer. Remote sensing of the atmosphere with the Global Positioning System (GPS) offers the ability to resolve fine scale structure of these low-level moisture fields. High frequency sampling provides nearly continuous monitoring. Spatial resolution is controlled by the density of the receiving network, especially when using slant path retrieval techniques. Results from dense networks of GPS stations in the Great Plains of the United States and around Beijing, China indicate that large fluctuations in water vapor amounts can occur over time scales of less than 12 hours. These networks also reveal high spatial variability in water vapor over horizontal distances of less than a few 10's of kilometers. Spatial variability is often times found to be as large as 10-20% of the total integrated amount of water vapor. Convergence fields associated with convective initiation, localized rain, and sharp boundaries in the moisture field are observed. These results indicate that GPS can improve the description of the planetary boundary moisture, and that observations of this type have a direct application in numerical weather prediction over time scales of less than 12 hours.
SF53A-0730 1340h
Assimilation of Ground-based GPS Precipitable Water Into WRF 3DVAR System: Impact on Weather Forecast and Applicability of its Gridded Point Values to GPS Analysis
The Weather Research and Forecasting (WRF) model is a new generation advanced mesoscale (10km-1km) model for both operational numerical weather prediction (NWP) and atmospheric research and it is the successor of the MM5, Eta, and RUC model system. GPS precipitable water (PW) which was obtained from dense ground-based GPS networks in Japan and the U.S. was assimilated into the WRF 3DVAR System. The two networks used are (1) GEONET in Japan: one of the densest operational networks in the world with averaged spacing of about 20km, and (2) U.S. GPS network (FLSNET, SUOMINET, and CORSNET): these networks cover the continental U.S. with station spacing from several ten km in some dense regions to several hundred km. The horizontal resolution in the WRF simulation is 5km and 10km for domains of the Japanese islands and the continental U.S., respectively. We have tuned the optimal scale length of specific humidity used in the recursive filter in the 3DVAR for each network. Several cases of dynamic weather conditions from synoptic to mesoscale phenomena from the summer of 2003 to the summer of 2004 were chosen for the data assimilation experiment. Improved rainfall forecast due to assimilation of GPS PW were observed for several hours into the forecast. The impact for longer forecasts was neutral. Our results suggest that GEONET PW can be used for short term forecasts. Long-term forecasts do not seem to benefit from GPS PW presumably because no observations are available from the oceans surrounding Japan. The results of the model simulations in each case will be presented and discussed. The tropospheric gradient parameters estimated by using ray-traced slant delay in the model grid show similar variations with those estimated by GPS analysis in the dynamic weather condition, suggesting the gridded point value (GPV) of the NWP with the high space and temporal (1 hour) resolution may be helpful information for GPS analysis. The positive feedback system between NWP system and GPS analysis system will be also discussed.
http://ted.web.infoseek.co.jp/
SF53A-0731 1340h
Coastal Ocean Topography and Low-Atmospheric Profiling from GPS Ground-Based Reflections
The uncertainty in the global carbon budget from processes in coastal margins is due in part to inadequate remote topographic measurement of upwelling structures and surface roughness near the coast. A 3-week experiment near Santa Cruz, California, with ground-based and simultaneous airborne GPS receivers, measured the GPS signals directly from the satellites as well as those that reflected off the ocean. This paper focuses on the ground-based measurements. These measurements respond to both the ocean surface topography in the first 20 km off the coast as well as refractivity profiles of the atmosphere. The ground-based observations were taken from 5 degrees elevation to below the horizon. The accuracy of the topographic measurement is potentially at the few-cm level, with resolutions of 0.5 to 5 km. This paper will show the evidence for observing persistent ocean topographic features over a few days. Improper averaging of small-scale surface roughness is an error in determining broad (few-km) topographic features. The unmodeled features of the atmospheric refractivity profile are also an error source for the surface topographic measurement. The level of these topographic errors as well as the potential for measuring atmospheric refractivity features of the lower atmosphere will be explored.
SF53A-0732 1340h
GPS Polarimeter for Sea State Sensing
Recent studies regarding sea surface wind estimation from spaceborne platforms have identified the Global Positioning System (GPS) constellation as a useful tool for measuring ocean wave topography. The twenty-four operational GPS satellites present a continuous, gratis radar source from which sea roughness can be derived accurately with unparalleled temporal resolution. However, existing GPS anemometers operate by recording the differing arrival times of direct (satellite--receiver) and reflected (satellite--sea surface--receiver) radar signals collected at a single elevated location. As this method is viable only at altitudes greater than 3 kilometers, such instruments are limited in real-time applications. A new variation on GPS wind sensing has been developed with the goal of acquiring real-time wind data at distances from a few meters to one kilometer from a water surface. Titled the GPS Polarimeter for Sea State Sensing (GPS3), this instrument operates by measuring changes in the GPS signal's polarization that occur instantaneously at the atmosphere-sea interface, thereby eliminating the requirement for a large receiver height. The GPS3's resulting portability, low cost, and simplified data recovery are well suited to a variety of recreational, scientific, and meteorological uses for which real-time local wind data is essential. Results of testing the GPS3 in controlled environments and on the open waters of the San Francisco Bay are presented in this poster. In all cases the GPS3 successfully received GPS signals reflected from water surfaces, and often the instrument's polarization-based measurement of the water roughness showed agreement with wind speeds determined by conventional means.
http://pangea.stanford.edu/~mrf12/GPS3.pdf
SF53A-0733 1340h
Inverting observations of GPS refractivies to reveal dynamical structures for climate model testing
Refractivities derived from measurements of GPS radio occultation, with an optimal choice of orbits, can provide a globally homogeneous record of the state of the climate. These refractivities contribute information in both the troposphere and stratosphere, sensitive to temperature, water vapor, and pressure in all weather conditions. This submission describes a method to extract information directly from these space observations to diagnose climate model dynamics. Although traditionally remotely sensed variables (such as refractivities) have been inverted to produce profiles of more familiar atmospheric state variables such as temperature, pressure, or water vapor, the refractivities themselves provide an ideal state vector for analysis by linear inverse modeling (LIM). The success of LIM for ENSO and seasonal climate forecasting (Penland and Magorian 1993; Winkler et al. 2001) reveals that inverting selected observations for dynamics is a powerful methodology compared with approximating dynamics of complex processes from first principles. Development of this approach based on observation state space reconstruction is motivated in part by the realization that identifying model error and improving model parameterizations is a very difficult task to accomplish by appeal to physical argument and first principle reasoning alone, as the variety of cloud parameterizations testifies. Continued progress in model refinement requires developing methods to systematize parameterization improvement. A benchmark for model improvement, therefore, is that the model reproduce the LIM dynamics in appropriate variables.
SF53A-0734 1340h
Microwave Crosslink in the Active Limb Sounding of Atmospheric Water: A Simulation Study
The success of GPS/GNSS radio occultation in retrieving refractivity profile of high vertical resolution from active limb sounding of the atmosphere has led to the novel concepts of microwave crosslink remote sensing. A microwave crosslink system consists of spaceborne receivers and at least one spaceborne transmitter with frequencies designed to be sensitive to the absorption lines of water vapor and possibly other trace species. Microwave crosslinks can yield high vertical resolution profiles of the atmosphere like GPS radio occultation, but with the much desired ability of retrieving water vapor unambiguously throughout the troposphere. In this work, we discuss a simulation study of the accuracy and vertical resolution of the technique. Using a diffraction-based forward simulation and inversion method, we examine the limitations due to noise, amplitude drift, atmospheric turbulence, and horizontal inhomogeneity.
SF53A-0735 1340h
Formation Flying of LEO Satellites Using GPS
The GRACE satellites can be considered as the first formation flying of two LEO satellites in space equipped with GPS receivers used for precise orbit determination. Since the distance between these two satellites is relatively small, the GRACE satellites allow for the first time to form a highly accurate GPS baseline in space that is uninterrupted and continues in time. In the case of several LEO satellites in space like, e.g., GRACE, COSMIC and SWARM, the GPS baselines form a LEO network in space independent of the ground network. We show different zero- and double-difference, kinematic and reduced-dynamic POD approaches for the GRACE formation flying over two years. We compare several ambiguity resolution strategies for the GPS baseline in space likeMelbourne-Wübbena wide-laning with narrow-lane bootstrapping and the quasi-ionosphere-free (QIF) approach and demonstrate that 95%-100% of all ambiguities can be resolved. The ambiguity-free and ambiguity-fixed results for kinematic and reduced-dynamic POD are compared with the K-band measurements (KBR). The best POD approaches show an agreement on the level of 3 mm with KBR, which is an improvement by a factor of about 7 compared to the zero-difference and ambiguity-free cases, where both satellites are estimated independently. Since the signals received by a LEO GPS receiver are not affected by tropospheric refraction, the GRACE GPS baseline in combination with the K-band is suitable to study the impact of higher-order terms of the ionospheric refraction, use of signal-to-noise ratio and the effects of GPS receiver antenna patterns on LEO POD.
SF53A-0736 1340h
GPS Data Products for Solid Earth Science
Over the past decade, regional and global networks of continuously operating GPS ground stations have been deployed to monitor Solid Earth deformation, and to support NASA Earth Science Enterprise (ESE) priorities and flight projects. At the forefront, and the focus of this project, is the 250-station Southern California Integrated GPS Network (SCIGN), a multi-agency effort jointly sponsored by NASA, NSF, USGS, and the W.M. Keck Foundation, under the umbrella of the Southern California Earthquake Center (SCEC). Over the next five years, SCIGN will become an integral part of the multi-agency, multi-disciplinary Plate Boundary Observatory (PBO), an observatory of high-precision geodetic instruments spanning western North America. This project was selected under the NASA REASoN CAN in 2003 to enhance the delivery of GPS data and metadata products using modern IT methodology, and to produce and disseminate an entirely new set of higher-level data products to a larger community, including scientists, government agencies (Federal, State, and Local), surveyors, and GIS professionals building on current capabilities within SCIGN for data archiving, information systems, and data analysis. While the project focus is on producing data and products from SCIGN, the tools developed will be designed to be extensible to other and larger GPS and other networks of geophysical instrument.