TRENDEVAL
| Project name: | TRENDEVAL - Klimatrends und Modelevaluation mittels Radio-Okkultation |
| Project leader: | Andrea K. Steiner |
| Project team: | Andrea K. Steiner
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| Partners: | L. Haimberger, Dep. of Meteorology and Geophysics, Univ. of Vienna, Austria S.-P. Ho, COSMIC Program, Univ. Corporation for Atmospheric Research (UCAR), Boulder, CO, USA M. A. Ringer, Met Office Hadley Centre for Climate Change, Exeter, UK Advisory Partners: G. C. Hegerl, School of GeoSciences, Univ. of Edinburgh, Edinburgh, UK B. Kuo, COSMIC Program, UCAR, Boulder, CO, USA K. B. Lauritsen, Danish Meteorological Institute (DMI), Copenhagen, Denmark A. Mannucci, Jet Propulsion Laboratory, California Institute of Technology (JPL/CalTech), Pasadena, CA, USA A. von Engeln, Satellite Atmospheric Science Group, EUMETSAT, Darmstadt, Germany J. Wickert, Dep.1 Geodesy and Remote Sensing, German Research Centre for Geosciences (GFZ), Potsdam, Germany |
Sponsor: | FWF - Fonds zur Förderung der wissenschaftlichen Forschung |
Abstract:
Observations for atmospheric climate monitoring and change detection have to meet stringent quality requirements as defined by the Global Climate Observing System (GCOS) program. Conventional measurements from weather satellites and balloons have several shortcomings since they were not intended to serve climate monitoring needs. Radio Occultation (RO) based on Global Positioning System (GPS) signals provides a new upper-air record with beneficial characteristics including long-term stability, all-weather capability, global coverage, high accuracy and vertical resolution in the upper troposphere and lower stratosphere.
Knowledge of errors is an important prerequisite for the use of data in climate trend studies. The central aim of the project TRENDEVAL was the assessment of uncertainties in the RO climate record and its application for climate change detection and for climate model evaluation. We investigated available RO data for 1995/1997 and for 2001 onwards from several satellite missions for the atmospheric variables bending angle, refractivity, pressure, geopotential height, temperature, and specific humidity.
We provided error estimates for individual RO profiles and gridded climatological fields. Climatologies from different RO missions were found highly consistent. This allows for combining them to a single record, which is a key feature of climate benchmark data. We quantified the structural uncertainty of the RO record from six processing centers. Structural uncertainty in trends was found lowest within 50°S and 50°N from 8 km to 25 km meeting the GCOS stability requirements.
The assessment of lower stratospheric temperatures from different observation systems (microwave sounders (AMSU), radiosondes, and RO) revealed a significant difference between AMSU and RO. Analysis of error sources and the good agreement with radiosondes indicated that the difference is not caused by RO.
The validation of the representation of tropical convective regions in the HadGEM2 climate model (Met Office Hadley Centre) with RO revealed a cold bias of the model near the tropical tropopause. Our results showed the high utility of RO data for the evaluation of observations and climate models.
RO parameters were shown to provide useful indicators of climate change. We demonstrated the utility of RO for climate change detection. An emerging climate change signal for geopotential height and temperature was detected in the RO record, reflecting warming of the troposphere and cooling of the lower stratosphere. Overall, the quality, consistency, and reproducibility of RO data was found favorable for becoming a climate benchmark record for use in climate monitoring and change detection.
