Extending Stratospheric Temperature Climate Data Records by Merging SSU with AIRS

Long-term changes in stratospheric temperatures are important for climate trend monitoring and interpreting the radiative effects of anthropogenic emissions of ozone-depleting substances and greenhouse gases. The Stratospheric Sounding Unit (SSU) onboard the historical NOAA Polar Orbiting Environmental Satellite (POES) series was a three-channel infrared radiometer designed to measure temperature profiles in the middle and upper stratospheres. Although the SSU observations were designed primarily for weather monitoring; however, due to continuity, long-term availability, and global coverage, they comprised an indispensable climate data record that had been playing a key role in estimating temperature trends in the middle and upper stratospheres for the period of 1979–2006 (Wang et al. 2012; Zou et al. 2014).  On the other hand, since 2002, the hyperspectral infrared sounding measurements including the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) provides decades of infrared hyperspectral observations. Owing to their hyperspectral nature and accurate radiometric and spectral calibration, these datasets provide modern period measurements of stratospheric temperature with high data quality.

This study presents recent efforts of merging of the SSU stratospheric temperature data with AIRS. We generated the training datasets of SSU and AIRS from the UMBC 48 profiles with different scan angles using the Community Radiative Transfer Model (CRTM). A linear regression method with considering weighting function and instrument noise as constrains is developed to convert AIRS into equivalent SSU based on training datasets.  By taking advantage of their overlapping period of SSU and AIRS in 2003-2006, the residual biases are further removed along the scan angels. The effects of increases in atmospheric CO2 concentration on stratosphere temperature records are also removed to make the dataset suitable for stratospheric temperature monitoring. Finnlay, the SSU-AIRS dataset is compared with the existing SSU/AMSU/ATMS dataset (Zou and Qian 2016). The differences of their variability and trend are presented. The new SSU/AIRS dataset provides another long-term observation for stratospheric temperature monitoring.