GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system

Abstract

We present a new approach to remote sensing of water vapor based on the global positioning system (GPS). Geodesists and geophysicists have devised methods for estimating the extent to which signals propagating from GPS satellites to ground‐based GPS receivers are delayed by atmospheric water vapor. This delay is parameterized in terms of a time‐varying zenith wet delay (ZWD) which is retrieved by stochastic filtering of the GPS data. Given surface temperature and pressure readings at the GPS receiver, the retrieved ZWD can be transformed with very little additional uncertainty into an estimate of the integrated water vapor (IWV) overlying that receiver. Networks of continuously operating GPS receivers are being constructed by geodesists, geophysicists, government and military agencies, and others in order to implement a wide range of positioning capabilities. These emerging GPS networks offer the possibility of observing the horizontal distribution of IWV or, equivalently, precipitable water with unprecedented coverage and a temporal resolution of the order of 10 min. These measurements could be utilized in operational weather forecasting and in fundamental research into atmospheric storm systems, the hydrologic cycle, atmospheric chemistry, and global climate change. Specially designed, dense GPS networks could be used to sense the vertical distribution of water vapor in their immediate vicinity. Data from ground‐based GPS networks could be analyzed in concert with observations of GPS satellite occultations by GPS receivers in low Earth orbit to characterize the atmosphere at planetary scale.

A multi-site intercomparison of integrated water vapour observations for climate change analysis

“…Using surface measurements of pressure and temperature, these ZTD values can be turned into IWV values (Bevis et al, 1992(Bevis et al, , 1994Rocken et al, 1995;Ware et al, 1997) and used for atmospheric research.…”

“…In a second step, the ZWD is converted into IWV (in kg m −2 or mm) using the following relationship (Hogg et al, 1981;Askne and Nordius, 1987;Bevis et al, 1992Bevis et al, , 1994:…”

“…with κ(T m ) a proportionality factor containing constants like the specific gas constant of water vapour, the density of liquid water, atmospheric refraction constants and varying with the water vapour weighted mean temperature of the atmosphere T m (Bevis et al, 1992(Bevis et al, , 1994. T m can be either calculated from vertical profile data provided by radiosondes or global reanalyses, or estimated from surface temperature (T s ) observations using a linear empirical relationship (e.g.…”

Assimilação do IWV-GPS no Brasil: otimização das estimativas do atraso zenital troposférico em tempo real

“…A relação entre os valores do D Z W e a quantidade de vapor d'água atmosférico (IWV) existente no momento em que foram feitas as observações GPSé função da temperatura média troposférica (T m). Essa relação pode ser expressa pela seguinte equação (Bevis et al, 1992): As efemérides utilizadas na simulação do processamento em tempo real foram as do tipo ultra-rápida produzida pelo JPL (Jet Propulsion Laboratory ) (Gregorius, 1996). Essas efemérides diferem das fornecidas por outros centros em dois aspectos.…”

“…Para o caso dos valores do IWV a partir das observações GPS, além dos fatores responsáveis pela latência já mencionados, existe também o tempo de processamento dos dados para a estimativa de valores do ZTD (Zenithal Tropospheric DelayAtraso Zenital Troposférico) em tempo real (Rocken et al, 1997b), os quais são convertidos em valores do IWV (Bevis et al, 1992). Para que tais valores tenham a menor latênciaé necessário que o método de processamento seja otimizado, de forma que o melhor resultado seja obtido com o menor custo computacional.…”