Abstract
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 ∼1- to 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.
Corresponding author address: Dr. E. R. Kursinski, Dept. of Atmospheric Science, The University of Arizona, P.O. Box 210081, Tucson, AZ 85721-0081. Email: kursinsk@atmo.arizona.edu
