NEWCLIM

Abstrakt:

Although temperature change measurements at the surface are well established, the knowledge about the vertical structure of temperature changes in the free atmosphere is still incomplete. The Global Navigation Satellite System (GNSS) Radio Occultation (RO) technique, however, has the potential of providing benchmark quality data, suitable for climate monitoring in the upper troposphere and lower stratosphere. The RO principle is based on excess phase measurements, from which atmospheric profiles of, e.g., density, pressure and temperature can be derived with high accuracy and high vertical resolution in a long-term stable manner.

Nevertheless, in the process of retrieving geophysical parameters of the Earth’s atmosphere from the initially observed measurements, introduction of background information is necessary by performing a so-called high-altitude initialization of bending angle profiles. This step reduces noise in the data and is commonly realized by a statistical optimization (SO). However, the high-altitude initialization has been identified by the ROtrends collaboration as a major source for structural uncertainties between the RO climate data products from different processing groups.

Another important error source in RO data arises from an incomplete correction of an additional ionospheric excess phase experienced by the GNSS signals. This systematic error depends on the ionization, and therefore, increases with solar activity.

Recently a new approach for the production of climatologies has been proposed, having the decisive advantage of circumventing the sophisticate SO step. The idea is to perform the averaging of individual profiles already in bending angle space, and retrieving climatological data products of density, pressure, and temperature directly. This reduces the noise in the RO data, leads to a cleaner and easier computation, a clear error characteristic, and avoids a potential error source.

This approach has been introduced using COSMIC satellite data. In a follow-up study we showed it is also applicable to (noisier) CHAMP satellite data. In the NEWCLIM project we want to enhance this new averaging approach. The central aim is to perform a careful validation of the new climatologies, in order to test if the new retrieval scheme can be seen as a full valid alternative to the standard retrieval scheme.   Furthermore, we will investigate the residual influence of the ionosphere in these new climatologies. The goal is to reduce the ionospheric residual error by using a new and promising model correction.

NEWCLIM aims to target two central problems of RO data in order to achieve benchmark-quality climatologies, the high-altitude initialization and residual ionospheric errors. The new climatologies have the potential to push current upper limits in altitude, enabling to study stratospheric climate processes.