Abstract. The Global Positioning System/Meteorology (GPS/MET) Program was established in 1993 by the University Corporation for Atmospheric Research (UCAR) to demonstrate active limb sounding of the Earth's atmosphere using the radio occultation technique. The demonstration system observes occulted GPS satellite signals received by a low Earth orbiting (LEO) satellite, MicroLab-1, launched April 3, 1995. The system can profile ionospheric electron density and neutral atmospheric properties. Neutral atmospheric refractivity, density, pressure, and temperature are derived at altitudes where the amount of water vapor is low. At lower altitudes, vertical profiles of density, pressure, and water vapor pressure can be derived from the GPS/MET refractivity profiles if temperature data from an independent source are available. This paper describes the GPS/MET data analysis procedures and validates GPS/MET data with statistics and illustrative case studies. We compare more than 1200 GPS/MET neutral atmosphere soundings to correlative data from operational global weather analyses, radiosondes, and the GOES, TOVS, UARS/MLS and HALOE orbiting atmospheric sensors. Even though many GPS/MET soundings currently fail to penetrate the lowest 5 km of the troposphere in the presence of significant water vapor, our results demonstrate iøC mean temperature agreement with the best correlative data sets between 1 and 40 km. This and the fact that GPS/MET observations are all-weather and self-calibrating suggests that radio occultation technology has the potential to make a strong contribution to a global observing system supporting weather prediction and weather and climate research.

This paper provides an overview of the methodology of and describes preliminary results from an experiment called GPS/MET (Global Positioning System/Meteorology), in which temperature soundings are obtained from a low Earthorbiting satellite using the radio occultation technique. Launched into a circular orbit of about 750-km altitude and 70° inclination on 3 April 1995, a small research satellite, MicroLab 1, carried a laptop-sized radio receiver. Each time this receiver rises and sets relative to the 24 operational GPS satellites, the GPS radio waves transect successive layers of the atmosphere and are bent (refracted) by the atmosphere before they reach the receiver, causing a delay in the dualfrequency carrier phase observations sensed by the receiver. During this occultation, GPS limb sounding measurements are obtained from which vertical profiles of atmospheric refractivity can be computed. The refractivity is a function of pressure, temperature, and water vapor and thus provides information on these variables that has the potential to be useful in weather prediction and weather and climate research. Because of the dependence of refractivity on both temperature and water vapor, it is generally impossible to compute both variables from a refractivity sounding. However, if either temperature or water vapor is known from independent measurements or from model predictions, the other variable may be calculated. In portions of the atmosphere where moisture effects are negligible (typically above 5-7 km), temperature may be estimated directly from refractivity. This paper compares a representative sample of 11 temperature profiles derived from GPS/MET soundings (assuming a dry atmosphere) with nearby radiosonde and high-resolution balloon soundings and the operational gridded analysis of the National Centers for Environmental Prediction (formerly the National Meteorological Center). One GPS/MET profile was obtained at a location where a temperature profile from the Halogen Occultation Experiment was available for comparison. These comparisons show that accurate vertical temperature profiles may be obtained using the GPS limb sounding technique from approximately 40 km to about 5-7 km in altitude where moisture effects are negligible. Temperatures in this region usually agree within 2°C with the independent sources of data. The GPS/MET temperature profiles show vertical resolution of about 1 km and resolve the location and minimum temperature of the tropopause very well. Theoretical temperature accuracy is better than 0.5°C at the tropopause, degrading to about 1°C at 40-km altitude. Above 40 km and below 5 km, these preliminary temperature retrievals show difficulties. In the upper atmosphere, the errors result from initial temperature and pressure assumptions in this region and initial ionospheric refraction assumptions. In the lower troposphere, the errors appear to be associated with multipath effects caused by large gradients in refractivity primarily due to water vapor distribution.

A new remote sensing concept extrapolated from the GPS occultation concept is presented in which the signal frequencies are chosen to determine atmospheric water, temperature, and the geopotential of atmospheric pressure surfaces. Using frequencies near the 22-and 183-GHz water lines allows not only the speed of light to be derived as a GPS occultation but also derivation of profiles of absorption caused by atmospheric water. Given the additional water information, moisture and temperature as well as the geopotential of pressure surfaces can be separated and solved for. Error covariance results indicate that the accuracies of individual water profiles will be 0.5%-3% extending from roughly 1-75-km altitude. Temperature accuracies of individual profiles will be sub-Kelvin from ϳ1to 70-km altitude depending on latitude and season. Accuracies of geopotential heights of pressure will be 10-20 m from the surface to 60-km altitude. These errors are random such that climatological averages derived from this data will be significantly more accurate. Owing to the limb-viewing geometry, the along-track resolution is comparable to the 200-300 km of the GPS occultation observations, but the shorter 22-and 183-GHz wavelengths improve the diffraction-limited vertical resolution to 100-300 m. The technique can be also used to determine profiles of other atmospheric constituents such as upper-tropospheric and stratospheric ozone by using frequencies near strong lines of that constituent. The combined dynamic range, accuracy, vertical resolution, and ability to penetrate clouds far surpass that of any present or planned satellite sensors. A constellation of such sensors would provide an all-weather, global remote sensing capability including full sampling of the diurnal cycle for process studies related to water, climate research, and weather prediction in general.

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Present Global Positioning System Meteorology (GPS/MET) refractivity profiles cannot distinguish between refractivity effects due to water vapor and those due to air density. Current methods of resolving the ambiguity rely heavily on ancillary upper-air data, such as National Centers for Environmental Prediction and European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. However, the accuracy of these ancillary sources suffers in regions where upper-air data are sparse. A method of separating the water vapor and temperature effects in GPS/MET-derived refractivity profiles with the addition of only ancillary surface pressure and temperature data and the hydrostatic assumption is discussed. Water vapor and temperature data derived from this method are presented and compared with accepted values. This method allows for the construction of temperature profiles with a mean bias of 0.33 K and a mean standard deviation of 1.86 K when compared with ECMWF data from 30 to 1000 mb. Height fields can also be corrected to within an average bias of 6 m and a standard deviation of 31 m. These corrected profiles result in retrieved water vapor pressure profiles with an average bias of 0.19 mb and a standard deviation of 0.53 mb.

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