John J. Braun

GPS Multipath and Its Relation to Near-Surface Soil Moisture Content

Measurements of soil moisture at various spatial and temporal scales are needed to study the water and carbon cycles. While satellite missions have been planned to measure soil moisture at global scales, these missions also need ground-based soil moisture data to validate their observations and retrieval algorithms. Here, we demonstrate that signals routinely recorded by Global Positioning System (GPS) receivers installed to measure crustal deformation for geophysical studies could be used to provide a global network of soil moisture sensors. The sensitivity to soil moisture is seen in reflected GPS signals, which are quantified by using the GPS signal to noise ratio data. We show that these data are sensitive to soil moisture variations for areas of 1000 m2 horizontally and 1-6 cm vertically. It is demonstrated that GPS signals penetrate deeper when the soil is dry than when it is wet. This change in penetration or ¿reflector¿ depth, along with the change in dielectric constant, causes the GPS signal strength to change its frequency and amplitude. Comparisons with conventional water content reflectometer sensors show good agreement (r2=0.9 to 0.76) with the variation in frequencies of the reflected GPS signals over a period of 7 months, with most of the disagreement occurring when soil moisture content is less than 0.1 cm3/cm3.

A Physical Model for GPS Multipath Caused by Land Reflections: Toward Bare Soil Moisture Retrievals

Reflected Global Positioning System (GPS) signals can be used to infer information about soil moisture in the vicinity of the GPS antenna. Interference of direct and reflected signals causes the composite signal, observed using signal-to-noise ratio (SNR) data, to undulate with time while the GPS satellite ascends or descends at relatively low elevation angles. The soil moisture change affects both the phase of the SNR modulation pattern and its magnitude. In order to more thoroughly understand the mechanism of how the soil moisture change leads to a change in the SNR modulation, we built an electrodynamic model of GPS direct and reflected signal interference, i.e., multipath, that has a bare-soil model as the input and the total GPS received power as the output. This model treats soil as a continuously stratified medium with a specific composition of material ingredients having complex dielectric permittivity according to well-known mixing models. The critical part of this electrodynamic model is a numerical algorithm that allows us to calculate polarization-dependent reflection coefficients of such media with various profiles of dielectric permittivity dictated by the soil type and moisture. In this paper, we demonstrate how this model can reproduce and explain the main features of experimental multipath modulation patterns such as changes in phase and amplitude. We also discuss the interplay between true penetration depth and effective reflector depth. Based on these modeling comparisons, we formulate recommendations to improve the performance of bare soil moisture retrievals from the data obtained using GPS multipath modulation.

Quality-Controlled Upper-Air Sounding Dataset for DYNAMO/CINDY/AMIE: Development and Corrections

AbstractThe upper-air sounding network for Dynamics of the Madden–Julian Oscillation (DYNAMO) has provided an unprecedented set of observations for studying the MJO over the Indian Ocean, where coupling of this oscillation with deep convection first occurs. With 72 rawinsonde sites and dropsonde data from 13 aircraft missions, the sounding network covers the tropics from eastern Africa to the western Pacific. In total nearly 26 000 soundings were collected from this network during the experiment’s 6-month extended observing period (from October 2011 to March 2012). Slightly more than half of the soundings, collected from 33 sites, are at high vertical resolution. Rigorous post–field phase processing of the sonde data included several levels of quality checks and a variety of corrections that address a number of issues (e.g., daytime dry bias, baseline surface data errors, ship deck heating effects, and artificial dry spikes in slow-ascent soundings).Because of the importance of an accurate description of ...

Validation of line-of-sight water vapor measurements with GPS

We present a direct comparison of nonisotropic, integrated water vapor measurements between a ground-based Global Positioning System (GPS) receiver and a water vapor radiometer (WVR). These line-of-sight water vapor observations are made in the straight line path between a ground station and a GPS satellite. GPS double-difference observations are processed, and the residual line-of-sight water vapor delays are extracted from the double-difference residuals. These water vapor delays contain the nonisotropic component of the integrated water vapor signal. The isotropic component is represented by the zenith precipitable water vapor measurement and can be scaled to a specific elevation angle based on a mapping function. The GPS observations are corrected for station-dependent errors using site-specific multipath maps. The resulting measurements are validated using a WVR which pointed in the direction of the observed satellites. The double-difference technique used to make these water vapor observations does not depend on accurate satellite clock estimates. Therefore it is especially well suited for near-real-time application in weather prediction and allows for sensing atmospheric structure that is below the noise level of current satellite and receiver clock errors. This paper describes the analysis technique and provides precision estimates for the GPS-measured nonisotropic water vapor as a function of elevation angle for use with data assimilation systems.

REFRACTT 2006: Real-time retrieval of high-resolution, low-level moisture fields from operational NEXRAD and research radars

High-resolution moisture fields retrieved for the first time from both operational and research radars illustrate the low-level moisture variability associated with boundary layer processes and the prethunderstorm environment.

Comparisons of line-of-sight water vapor observations using the Global Positioning System and a pointing microwave radiometer

Line-of-sight measurements of integrated water vapor from a global positioning system (GPS) receiver and a microwave radiometer are compared. These two instruments were collocated at the central facility of the Department of Energy’s Atmospheric Radiation Measurement Program’s Southern Great Plains region, near Lamont, Oklahoma. The comparison was made using 47 days of observations in May and June of 2000. Weather conditions during this time period were variable with total integrated water vapor ranging from less than 10 to more than 50 mm. To minimize errors in the microwave radiometer observations, observations were compared during conditions when the liquid water measured by the radiometer was less than 0.1 mm. The linear correlation of the observations between the two instruments is 0.99 with a root-mean-square difference of the GPS water vapor to a linear fit of the microwave radiometer of 1.3 mm. The results from these comparisons are used to evaluate the ability of networks of GPS receivers to measure instantaneous line-of-sight integrals of water vapor. A discussion and analysis is provided regarding the additional information of the water vapor field contained in these observations compared to time- and space-averaged zenith and gradient measurements.

Observing System Simulation Experiment Study on Imaging the Ionosphere by Assimilating Observations From Ground GNSS, LEO-Based Radio Occultation and Ocean Reflection, and Cross Link

In this paper, a global ionospheric data assimilation model is constructed based on the empirical international-reference-ionosphere model and the Kalman filter. A sparse matrix method is used to militate the huge computation and storage problems. A series of observing system simulation experiments has been performed based on the existing global ground-based global navigation satellite system (GNSS) network, the planned Constellation Observing System for Meteorology, Ionosphere, and Climate #2/Formosa Satellite Mission #7 (COSMIC-2/FORMOSAT-7) orbits, and the real global position system and GLObal NAvigation Satellite System (GLONASS) orbits. Specifically, the COSMIC-2 will have six 24° inclination satellites in 500-km altitude and six 72° inclination satellites in 800-km altitude. The slant total electron content of ground-based GNSS, radio occultation and ocean reflection (OR) of 12 low-Earth-orbit satellites, and cross-link between COSMIC-2 low and high inclination satellites are simulated by the NeQuick model. The ORs show great impacts in specifying the ionosphere except over the inland area. It complements the existing ground-based GNSS network, which mainly observes the ionosphere over the land area. The 24° and 72° satellites can complement each other to optimize the global ionospheric specification. The COSMIC-2 mission is expected to contribute significantly to the accurate ionospheric nowcast. Its potential ability in ionospheric short-term forecast is also discussed.

Focused study of interweaving hazards across the Caribbean

The Caribbean is a region of lush vegetation, beaches, active volcanoes, and significant mountain ranges, all of which create a natural aesthetic that is recognized globally. Yet these very same features, molded through geological, oceanic, and atmospheric processes, also pose natural hazards for the developing countries in the Caribbean. The rise in population density, migration to coastal areas, and substandard building practices, combined with the threat of natural hazards, put the regions human population at risk for particularly devastating disasters. These demographic and social characteristics exist against a backdrop of the threat of an evolving climate, which produces a more vigorous hurricane environment and a rising average sea level.

Precipitable water from GPS over the continental United States: Diurnal cycle, intercomparisons with NARR, and link with convective initiation

AbstractThe variation of precipitable water vapor (PW) over the continental United States is examined at various time scales using spatial maps of a column-averaged mixing ratio (CAMR) that is derived from integrated column PW from both observations and reanalysis data. CAMR spatial maps are generated utilizing PW measurements obtained from a network of ground-based global positioning system (GPS) receivers and the North American Regional Reanalysis (NARR) over a time span of 4 yr (February 2009–January 2013). The effect of topography on PW is mitigated by vertically averaging the mixing ratio instead of integrating the absolute humidity. An ordinary kriging interpolation technique is used to generate spatial maps of CAMR. The observed and predicted PW derived by GPS and NARR correlate well with each other at annual and monthly scales. When focusing on its diurnal cycle, moisture peaks in the late afternoon over the Great Plains and late night over the Rockies. It is also found that atmospheric moisture w...

Mexican GPS Tracks Convection From North American Monsoon

The North American monsoon (NAM) is a dominant feature of the climate of northwest Mexico and the southwest United States. The annual monsoon, which usually lasts from July to September, contributes more than half of the yearly precipitation for much of the region. Thunderstorms brought on by the monsoon are routinely responsible for severe weather, including flooding, hail, wind, dust storms, and lightning. Tropical storms and hurricanes during the NAM season can also wreak havoc on a much larger scale.