A GNSS water vapour tomography system developed to reconstruct spatially resolved humidity fields in the troposphere is described. The tomography system was designed to process the slant path delays of about 270 German GNSS stations in near real-time with a temporal resolution of 30 minutes, a horizontal resolution of 40 km and a vertical resolution of 500 m or better. After a short introduction to the GPS slant delay processing the framework of the GNSS tomography is described in detail. Different implementations of the iterative algebraic reconstruction techniques (ART) used to invert the linear inverse problem are discussed. It was found that the multiplicative techniques (MART) provide the best results with least processing time, i. e. a tomographic reconstruction of about 26000 slant delays on a 8280 cell grid can be obtained in less than 10 minutes. Different iterative reconstruction techniques are compared with respect to their convergence behaviour and some numerical parameters. The inversion can be considerably stabilized by using additional non-GNSS observations and implementing various constraints. Different strategies for initialising the tomography and utilizing extra information are discussed. At last an example of a reconstructed field of the wet refractivity is presented and compared to the corresponding distribution of the integrated water vapour, an analysis of a numerical weather model (COSMO-DE) and some radiosonde profiles.

Abstract. The GPS water vapour tomography is a new technique which provides spatially resolved water vapour distributions in the atmosphere under all weather conditions. This work investigates the information contained in a given set of GPS signals as a precondition to an optimal tomographic reconstruction. The spatial distribution of the geometric intersection points between different ray paths is used to estimate the information density. Different distributions of intersection points obtained from hypothetical GPS networks with varying densities of GPS stations are compared with respect to the horizontal and vertical resolution of a subsequent tomographic reconstruction. As a result some minimum requirements for continuously operating extensive GPS networks for meteorological applications are given.

Acoustic travel-time tomography is a remote sensing technique that uses the dependence of sound speed in air on temperature and wind speed along the sound propagation path. Travel-time measurements of acoustic signals between several sound sources and receivers travelling along different paths through a measuring area give information on the spatial distribution of temperature and flow fields within the area. After a separation of the two influences, distributions of temperature and flow can be reconstructed using inverse algorithms. As a remote sensing method, one advantage of acoustic travel-time tomography is its ability to measure temperature and flow field quantities without disturbing the area under investigation due to insertion of sensors. Furthermore, the two quantities—temperature and flow velocity—can be recorded simultaneously with this measurement method. In this paper, an acoustic tomographic measurement system is introduced which is capable of resolving three-dimensional distributions of temperature and flow fields in air within a certain volume (1.3 m × 1.0 m × 1.2 m) using 16 acoustic transmitter–receiver pairs. First, algorithms for the 3D reconstruction of distributions from line-integrated measurements are presented. Moreover, a measuring apparatus is introduced which is suited for educational purposes, for demonstration of the method as well as for indoor investigations. Example measurements within a low-speed wind tunnel with different incident flow situations (e.g. behind bluff bodies) using this system are shown. Visualizations of the flow illustrate the plausibility of the tomographically reconstructed flow structures. Furthermore, alternative individual measurement methods for temperature and flow speed provide comparable results.

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