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Alexander E. MacDonald, Yuanfu Xie, and Randolph H. Ware

Abstract

In recent years techniques have been developed to obtain integrated water vapor along slant paths between ground-based Global Positioning System (GPS) receivers and the GPS satellites. Results are presented of an observing system simulation (OSS) to determine whether three-dimensional water vapor fields could be recovered from a high-resolution network (e.g., with 40-km spacing) of GPS receivers, in combination with surface moisture observations and a limited number of moisture soundings. The paper describes a three-dimensional variational analysis (3DVAR) that recovers the moisture field from the slant integrated water vapor and other observations. Comparisons between “nature” moisture fields taken from mesoscale models and fields recovered using 3DVAR are presented. It is concluded that a high-resolution network of GPS receivers may allow diagnosis of three-dimensional water vapor, with applications for both positioning and mesoscale weather prediction.

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Steven E. Koch, Randolph Ware, Hongli Jiang, and Yuanfu Xie

Abstract

This study documents a very rapid increase in convective instability, vertical wind shear, and mesoscale forcing for ascent leading to the formation of a highly unusual tornado as detected by a ground-based microwave radiometer and wind profiler, and in 1-km resolution mesoanalyses. Mesoscale forcing for the rapid development of severe convection began with the arrival of a strong upper-level jet streak with pronounced divergence in its left exit region and associated intensification of the low-level flow to the south of a pronounced warm front. The resultant increase in stretching deformation along the front occurred in association with warming immediately to its south as low-level clouds dissipated. This created a narrow ribbon of intense frontogenesis and a rapid increase in convective available potential energy (CAPE) within 75 min of tornadogenesis. The Windsor, Colorado, storm formed at the juncture of this warm frontogenesis zone and a developing dryline. Storm-relative helicity suddenly increased to large values during this pretornadic period as a midtropospheric layer of strong southeasterly winds descended to low levels. The following events also occurred simultaneously within this short period of time: a pronounced decrease in midtropospheric equivalent potential temperature θ e accompanying the descending jet, an increase in low-level θ e associated with the surface sensible heating, and elimination of the capping inversion and convective inhibition. The simultaneous nature of these rapid changes over such a short period of time, not fully captured in Storm Prediction Center mesoanalyses, was likely critical in generating this unusual tornadic event.

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Laura Bianco, Domenico Cimini, Frank S. Marzano, and Randolph Ware

Abstract

A self-consistent remote sensing physical method to retrieve atmospheric humidity high-resolution profiles by synergetic use of a microwave radiometer profiler (MWRP) and wind profiler radar (WPR) is illustrated. The proposed technique is based on the processing of WPR data for estimating the potential refractivity gradient profiles and their optimal combination with MWRP estimates of potential temperature profiles in order to fully retrieve humidity gradient profiles. The combined algorithm makes use of recent developments in WPR signal processing, computing the zeroth-, first-, and second-order moments of WPR Doppler spectra via a fuzzy logic method, which provides quality control of radar data in the spectral domain. On the other hand, the application of neural network to brightness temperatures, measured by a multichannel MWRP, can provide continuous estimates of tropospheric temperature and humidity profiles. Performance of the combined algorithm in retrieving humidity profiles is compared with simultaneous in situ radiosonde observations (raob’s). The empirical sets of WPR and MWRP data were collected at the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site. Combined microwave radiometer and wind profiler measurements show encouraging results and significantly improve the spatial vertical resolution of atmospheric humidity profiles. Finally, some of the limitations found in the use of this technique and possible future improvements are also discussed.

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Steven R. Chiswell, Steven Businger, Michael Bevis, Fredrick Solheim, Christian Rocken, and Randolph Ware

Abstract

Water vapor radiometer (WVR) retrieval algorithms require a priori information on atmospheric conditions along the line of sight of the radiometer in order to derive opacities from observed brightness temperatures. This paper's focus is the mean radiating temperature of the atmosphere (T mr), which is utilized in these algorithms to relate WVR measurements to integrated water vapor. Current methods for specifying T mr rely on the climatology of the WVR site-for example, a seasonal average-or information from nearby soundings to specify T mr. However, values of T mr, calculated from radiosonde data, not only vary according to site and season but also exhibit large fluctuations in response to local weather conditions. By utilizing output from numerical weather prediction (NWP) models, T mr can be accurately prescribed for an arbitrary WVR site at a specific time. Temporal variations in local weather conditions can he resolved by NWP models on timescales shorter than standard radiosonde soundings.

Currently used methods for obtaining T mr are reviewed. Values of T mr obtained from current methods and this new approach are compared to those obtained from in situ radiosonde soundings. The improvement of the T mr calculation using available model forecast data rather than climatological values yields a corresponding improvement of comparable magnitude in the retrieval of atmospheric opacity. Use of forecast model data relieves a WVR site of its dependency on local climatology or the necessity of a nearby sounding, allowing more accurate retrieval of observed conditions and increased flexibility in choosing site location. Furthermore, it is found that the calculation of precipitable water by means of atmospheric opacities does not require time-dependent tuning parameters when model data are used. These results were obtained using an archived subset of the full nested grid model output. The added horizontal and vertical resolution of operational data should further improve this approach.

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Michael Bevis, Steven Businger, Steven Chiswell, Thomas A. Herring, Richard A. Anthes, Christian Rocken, and Randolph H. Ware

Abstract

Emerging networks of Global Positioning System (GPS) receivers can be used in the remote sensing of atmospheric water vapor. The time-varying zenith wet delay observed at each GPS receiver in a network can be transformed into an estimate of the precipitable water overlying that receiver. This transformation is achieved by multiplying the zenith wet delay by a factor whose magnitude is a function of certain constants related to the refractivity of moist air and of the weighted mean temperature of the atmosphere. The mean temperature varies in space and time and must be estimated a priori in order to transform an observed zenith wet delay into an estimate of precipitable water. We show that the relative error introduced during this transformation closely approximates the relative error in the predicted mean temperature. Numerical weather models can be used to predict the mean temperature with an rms relative error of less than 1%.

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Christian Rocken, Teresa Van Hove, James Johnson, Fred Solheim, Randolph Ware, Mike Bevis, Steve Chiswell, and Steve Businger

Abstract

Atmospheric water vapor was measured with six Global Positioning System (GPS) receivers for 1 month at sites in Colorado, Kansas, and Oklahoma. During the time of the experiment from 7 May to 2 June 1993, the area experienced severe weather. The experiment, called “GPS/STORM,” used GPS signals to sense water vapor and tested the accuracy of the method for meteorological applications. Zenith wet delay and precipitable water (PW) were estimated, relative to Platteville, Colorado, every 30 min at five sites. At three of these five sites the authors compared GPS estimates of PW to water vapor radiometer (WVR) measurements. GPS and WVR estimates agree to 1–2 mm rms. For GPS/STORM site spacing of 500–900 km, high-accuracy GPS satellite orbits are required to estimate 1–2-mm-level PW. Broadcast orbits do not have sufficient accuracy. It is possible, however, to estimate orbit improvements simultaneously with PW. Therefore, it is feasible that future meteorological GPS networks provide near-real-time high-resolution PW for weather forecasting.

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Steven Businger, Steven R. Chiswell, Michael Bevis, Jingping Duan, Richard A. Anthes, Christian Rocken, Randolph H. Ware, Michael Exner, T. VanHove, and Fredrick S. Solheim

This paper provides an overview of applications of the Global Positioning System (GPS) for active measurement of the Earth's atmosphere. Microwave radio signals transmitted by GPS satellites are delayed (refracted) by the atmosphere as they propagate to Earth-based GPS receivers or GPS receivers carried on low Earth orbit satellites.

The delay in GPS signals reaching Earth-based receivers due to the presence of water vapor is nearly proportional to the quantity of water vapor integrated along the signal path. Measurement of atmospheric water vapor by Earth-based GPS receivers was demonstrated during the GPS/STORM field project to be comparable and in some respects superior to measurements by ground-based water vapor radiometers. Increased spatial and temporal resolution of the water vapor distribution provided by the GPS/STORM network proved useful in monitoring the moisture-flux convergence along a dryline and the decrease in integrated water vapor associated with the passage of a midtropospheric cold front, both of which triggered severe weather over the area during the course of the experiment.

Given the rapid growth in regional networks of continuously operating Earth-based GPS receivers currently being implemented, an opportunity exists to observe the distribution of water vapor with increased spatial and temporal coverage, which could prove valuable in a range of operational and research applications in the atmospheric sciences.

The first space-based GPS receiver designed for sensing the Earth's atmosphere was launched in April 1995. Phase measurements of GPS signals as they are occluded by the atmosphere provide refractivity profiles (see the companion article by Ware et al. on page 19 of this issue). Water vapor limits the accuracy of temperature recovery below the tropopause because of uncertainty in the water vapor distribution. The sensitivity of atmospheric refractivity to water vapor pressure, however, means that refractivity profiles can in principle yield information on the atmospheric humidity distribution given independent information on the temperature and pressure distribution from NWP models or independent observational data.

A discussion is provided of some of the research opportunities that exist to capitalize on the complementary nature of the methods of active atmospheric monitoring by GPS and other observation systems for use in weather and climate studies and in numerical weather prediction models.

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Jingping Duan, Michael Bevis, Peng Fang, Yehuda Bock, Steven Chiswell, Steven Businger, Christian Rocken, Frederick Solheim, Terasa van Hove, Randolph Ware, Simon McClusky, Thomas A. Herring, and Robert W. King

Abstract

A simple approach to estimating vertically integrated atmospheric water vapor, or precipitable water, from Global Positioning System (GPS) radio signals collected by a regional network of ground-based geodetic GPS receiver is illustrated and validated. Standard space geodetic methods are used to estimate the zenith delay caused by the neutral atmosphere, and surface pressure measurements are used to compute the hydrostatic (or “dry”) component of this delay. The zenith hydrostatic delay is subtracted from the zenith neutral delay to determine the zenith wet delay, which is then transformed into an estimate of precipitable water. By incorporating a few remote global tracking stations (and thus long baselines) into the geodetic analysis of a regional GPS network, it is possible to resolve the absolute (not merely the relative) value of the zenith neutral delay at each station in the augmented network. This approach eliminates any need for external comparisons with water vapor radiometer observations and delivers a pure GPS solution for precipitable water. Since the neutral delay is decomposed into its hydrostatic and wet components after the geodetic inversion, the geodetic analysis is not complicated by the fact that some GPS stations are equipped with barometers and some are not. This approach is taken to reduce observations collected in the field experiment GPS/STORM and recover precipitable water with an rms error of 1.0–1.5 mm.

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Randolph H. Ware, David W. Fulker, Seth A. Stein, David N. Anderson, Susan K. Avery, Richard D. Clark, Kelvin K. Droegemeier, Joachim P. Kuettner, J. Bernard Minster, and Soroosh Sorooshian

“SuomiNet,” a university-based, real-time, national Global Positioning System (GPS) network, is being developed for atmospheric research and education with funding from the National Science Foundation and with cost share from collaborating universities. The network, named to honor meteorological satellite pioneer Verner Suomi, will exploit the recently shown ability of ground-based GPS receivers to make thousands of accurate upper- and lower-atmospheric measurements per day. Phase delays induced in GPS signals by the ionosphere and neutral atmosphere can be measured with high precision simultaneously along a dozen or so GPS ray paths in the field of view. These delays can be converted into integrated water vapor (if surface pressure data or estimates are available) and total electron content (TEC), along each GPS ray path. The resulting continuous, accurate, all-weather, real-time GPS moisture data will help advance university research in mesoscale modeling and data assimilation, severe weather, precipitation, cloud dynamics, regional climate, and hydrology. Similarly, continuous, accurate, all-weather, real-time TEC data have applications in modeling and prediction of severe terrestrial and space weather, detection and forecasting of low-altitude ionospheric scintillation activity and geomagnetic storm effects at ionospheric midlatitudes, and detection of ionospheric effects induced by a variety of geophysical events. SuomiNet data also have potential applications in coastal meteorology, providing ground truth for satellite radiometry, and detection of scintillation associated with atmospheric turbulence in the lower troposphere. The goal of SuomiNet is to make large amounts of spatially and temporally dense GPS-sensed atmospheric data widely available in real time, for academic research and education. Information on participation in SuomiNet is available via www.unidata.ucar.edu/suominet.

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