Observing the water vapor distribution on the troposphere remains a challenge for the weather forecast. Radiosondes provide precise water vapor profiles of the troposphere, but lack geographical and temporal coverage, while satellite meteorological maps have good spatial resolution but even poorer temporal resolution. GPS has proved its capacity to measure the integrated water vapor in all weather conditions with high temporal sampling frequency. However these measurements lack a vertical water vapor discretization. Reconstruction of the slant path GPS observation to the satellite allows oblique water vapor measurements. Implementation of a 3D grid of voxels along the troposphere over an area where GPS stations are available enables the observation ray tracing. A relation between the water vapor density and the distanced traveled inside the voxels is established, defining GPS tomography. An inverse problem formulation is needed to obtain a water vapor solution. The combination of precipitable water vapor (PWV) maps obtained from MODIS satellite data with the GPS tomography is performed in this work. The MODIS PWV maps can have 1 or 5 km pixel resolution, being obtained 2 times per day in the same location at most. The inclusion of MODIS PWV maps provides an enhanced horizontal resolution for the tomographic solution and benefits the stability of the inversion problem. A 3D tomographic grid was adjusted over a regional area covering Lisbon, Portugal, where a GNSS network of 9 receivers is available. Radiosonde measurements in the area are used to evaluate the 3D water vapor tomography maps.
The electromagnetic signal transmitted by the global navigation and positioning systems (GNSS) suffers a delay which is
mainly caused by the water vapor in the atmosphere. Estimating the delay affecting the signal propagation, it is possible
to estimate the water vapor column on the troposphere above each station. The aim of this study is to characterize the
water vapor field on the troposphere over time by GNSS techniques. It is expected that can also come to assist in the
Nowcasting particularly in the prediction of severe meteorological phenomena. Several events of strong, intense and
short precipitation, observed in the Lisbon region throughout 2012 were analyzed. The choice of these events was based
on the analysis of hourly precipitation given by a meteorological station located on Lisbon center. This region is
monitored by a network of 15 GNSS stations covering about 100 square kilometers. The relationship between the GPS
precipitable water vapor (PWV) and the hourly accumulated precipitation was evaluated over time (1D closest GPSmeteorological
station plots) and spatially (2D maps) interpolated over the GNSS and meteorological stations. It was
verified that there were a high and sudden increment of the GPS PWV prior to severe precipitation events. The PWV
increment starts 6 to 10 hours before the rain and the value has increased between 57% and 75% relatively to the PWV
value observed previously. In this study is shown that GPS data has good potential for forecasting severe rain events and
high moisture flux situations.