Remote sensing using signals of Global Navigation Satellite Systems (GNSS) is a method providing a new source of observations to study the Earth System including its atmosphere. GNSS Reflectometry (GNSS-R) is element of GNSS Remote Sensing and a novel observation technique. It exploits reflected GNSS signals from land, ice or water bodies to retrieve information about different geophysical parameters. This technique has been increasingly used in ground-based, air- or spaceborne configuration. It is being pursued for a variety of applications over land, ocean and ice. Different processing approaches could be developed and applied to get geophysical information with unprecedented high accuracy and spatiotemporal resolution.

This joint research project of GFZ with University Partners and the German Weather Service, studies the wind retrieval and assimilation of the space-borne reflectometry data into the current global weather models with the purpose of efficient and improved storm predictions. The study will be carried out in retrieving wind information as the prognostic variable of weather models as fast and accurate as possible. Setting up data assimilation algorithms, GNSS reflectometry data assimilation into weather forecast models for storm scale predictions will be addressed.

This cooperation project with DLR focuses on Climatological and Space Weather related features of the E-Layer dominated Ionosphere. It is GNSS radio occultation data from various satellite mission are used as the main data base.

The south-central Andes in NW Argentina are characterized by a strong rainfall asymmetry. In the east-west direction exists one of the steepest rainfall gradients on Earth, resulting from the large topographic differences in this region. In addition, in the north-south direction the rainfall intensity varies as the climatic regime shifts from the tropical central Andes to the subtropical south-central Andes. This study focuses on the investigation of the hydroclimatic extreme events over the south-central Andes .

The central Andes are characterized by a steep climatic gradient where key hydrologic variables change across short distances. One of the largest unknown component in this environment is the storage of water in the atmosphere, soil (soil moisture) and the snow height (or snow water equivalent). Both are parameters that can be quantified using innovative GNSS (Global Navigational Satellite Systems) based remote sensing techniques, which were successfully tested and established and the resulting observations evolved into an important data source for numerous meteorological applications.

Reflected GNSS signals, also called multipath, are unwanted effect for GNSS positioning. But these signals provide oportunities to estimate properties of the reflective surfaces. For ground-based GNSS stations these surfaces can be buildings, soils or water in rivers, lakes or seas. This research is focused on the surface properties of soils and open ground. Thus the reflected signals carry information about soil moisture, as well as about the water content in vegetation.