Climate Trends and Model Evaluation by Radio Occultation

Detection of anthropogenic climate change requires high quality observations of the Earth`s atmosphere. One of the most challenging tasks in this respect is the investigation of the upper troposphere-lower stratosphere (UTLS), a region reacting sensitively to climate change. Differences in temperature trends stemming from different data records have been subject to vital discussions and some reconciliation has been achieved only recently. Newly homogenized radiosonde data and satellite data from the (Advanced) Microwave Sounding Unit (MSU/AMSU) now show basic agreement in tropospheric warming and in stratospheric cooling being broadly consistent with trends in surface temperature and climate models. But substantial uncertainties remain and the magnitude of upper air temperature trends is still under debate. In this context radio occultation (RO) offers new possibilities by providing independent and high quality observations in the UTLS with global coverage, essentially all-weather capability, long-term stability, and homogeneity. RO data are qualified as a climate benchmark data type since they are based on time measurements with precise atomic clocks, tied to the international definition of the second. Key climate parameters are retrieved with high vertical resolution and high accuracy. Observational and sampling errors are well defined. RO climatologies of bending angle, refractivity, geopotential height, temperature, and specific humidity are well suited to serve as indicators of a changing climate. Because of the relatively short RO record to date, its value for long- term monitoring can not yet be definitely demonstrated but a continuous 10 year RO record will be available in 2011, when trends are expected to be stably detectable. The central aim of the proposed project TRENDEVAL is the assessment of climate trends in the UTLS from a novel multi-year RO climate record and its application for climate change detection and attribution and for climate model evaluation. In a first step we perform an intercomparison of RO climatologies provided by the five main international RO processing centers for quantification of the structural uncertainty to assess the overall quality and reproducibility of RO records. The established RO climate record with full error characterization will then be compared to conventional upper air records of newly homogenized radiosonde data and recent MSU/AMSU satellite data in order to investigate open issues in UTLS temperature trends. Detection of a climate change signal for the record of the RO parameters together with analysis of present day atmospheric variability will be performed using optimal fingerprinting. Accompanied attribution of anthropogenic and natural climate change will also aid the evaluation of climate model performance, which focuses on the evaluation of tropical upper tropospheric water vapor and lapse rate in climate models based on RO data. Addressing these key issues, TRENDEVAL aims to add certainty to estimates of atmospheric climate trends, to contribute to climate model improvement, and to strengthen the value of RO for climate science.

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 50S and 50N 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.