Intercomparison of SSU temperature data records with Lidar, GPS RO, and MLS observations
Article first published online: 28 FEB 2013
© 2013. American Geophysical Union. All Rights Reserved.
Journal of Geophysical Research: Atmospheres
Volume 118, Issue 4, pages 1747–1759, 27 February 2013
How to Cite
2013), Intercomparison of SSU temperature data records with Lidar, GPS RO, and MLS observations, J. Geophys. Res. Atmos., 118, 1747–1759, doi:10.1002/jgrd.50162., and (
- Issue published online: 17 APR 2013
- Article first published online: 28 FEB 2013
- Accepted manuscript online: 18 JAN 2013 09:06AM EST
- Manuscript Accepted: 3 JAN 2013
- Manuscript Revised: 25 DEC 2012
- Manuscript Received: 2 OCT 2012
- NOAA. Grant Number: NESDISPO20092001589 (SDS0915)
 A consistent long-term stratospheric temperature observation is a crucial part for global change studies. In this study, we compare newly developed Stratospheric Sounding Unit (SSU) layer-averaged stratospheric temperatures with lidar, GPS Radio Occultation (RO), and Microwave Limb Sounder (MLS) stratospheric temperature profiles, each with unique error characteristics, spatial and temporal coverage, and observational principles. The vertical temperature profiles are converted into SSU-equivalent layer temperatures, and diurnal correction is applied to adjust the observations into an identical observational time. The comparison is carried out on pentad grids with a 2.5° latitude × 2.5° longitude resolution. Grid-by-grid comparison of SSU and MLS gives the mean differences between them from August 2004 to May 2006 of -0.041, 0.169, and -0.447 K with standard deviation of 1.180, 1.485, and 1.715 K for SSU channels 1–3, respectively. The correlation of GPS RO and SSU brightness temperature anomalies are 0.943, 0.877, and 0.699 from channels 1–3, respectively, and the correlation decreases with altitude (channels). SSU channel 3 brightness temperature anomalies are correlated with lidar observations with correlation coefficients of 0.839 at the Hohenpeissenberg Observatory in Germany and 0.725 at the Observatoire de Haute-Provence in France. Overall, the comparison results do not show that the newly developed SSU data set is significantly different from any of the three independent data sets based on known limitations and advantages of these data sets.