Although the atmosphere contains only up to 4% water vapor by volume, water vapor is one of the central atmospheric gases. Water vapor is a highly effective greenhouse gas that is directly intertwined with global climate change and its implications for natural disasters such as floods, droughts, deluge or glacier melting. As a vital component of the hydrological cycle water vapor represents a major driver for the generation and spatio-temporal distribution of clouds and precipitation. Vertically integrated water vapor exhibits high variability of up to 1 mm within a few kilometers range and sub-hourly intervals (Vogelmann et al. 2015; Steinke et al. 2015). The continuous, extensive quantification of water vapor remains a challenge: while regional atmospheric models enable the simulation of the distribution of hydrometeorological variables in space and time at high resolution, their skill in doing so remains in the great need of improvement. At the same time only limited high resolution atmospheric water vapor validation records exist.
Acting as an important signal in meteorology and climate research, water vapor principally is regarded as a source of noise in Geodesy and Remote Sensing applications. The humidity of the Earth’s atmosphere induces delays and distortions of high temporal and spatial fluctuations in microwave signals, which cannot be eliminated by multi-frequency measurements and have to be quantified during the data processing. Thus observations of Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) provide valuable contributions (GNSS: high temporal resolution; InSAR: high spatial resolution) for reconstructing the integrated water vapor (IWV) along the path from the satellites to the observation site on the Earth’s surface. In addition, the sophisticated tomography-based evaluation of these data even allows generating 3D fields of the water vapor distribution in space and time.
By using GNSS and InSAR based techniques in combination with high resolution regional atmospheric weather models and geostatistical data merging techniques, the proposed project aims at developing and evaluating new approaches to derive improved spatio-temporal estimates of the atmospheric water vapor distribution. In particular, tomography-based approaches in the evaluation of geodetic and remote sensing data will be further developed to improve the vertical and horizontal resolution of the atmospheric state variable under research. The generated products are used for comparison and assimilation with atmospheric model-based information to finally get an optimal estimation of the atmospheric water vapor distribution.
Prof. Dr. Bernhard Heck, KIT/GIK, Geodetic Institute
Prof. Dr. Stefan Hinz, KIT/IPF, Institute of Photogrammetry and Remote Sensing
D-A-CH cooperation partner:
Prof. Dr. Alain Geiger, ETH/IGP, Institute of Geodesy and Photogrammetry
Contacts: Harald Kunstmann