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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 4, issue 9
Atmos. Meas. Tech., 4, 1965–1977, 2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Observing atmosphere and climate with occultation techniques...

Atmos. Meas. Tech., 4, 1965–1977, 2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 21 Sep 2011

Research article | 21 Sep 2011

An assessment of differences in lower stratospheric temperature records from (A)MSU, radiosondes, and GPS radio occultation

F. Ladstädter1, A. K. Steiner1, U. Foelsche1, L. Haimberger2, C. Tavolato2, and G. Kirchengast1 F. Ladstädter et al.
  • 1Wegener Center for Climate and Global Change (WEGC) and Institute for Geophysics, Astrophysics, and Meteorology/Inst. of Physics (IGAM/IP), University of Graz, Graz, Austria
  • 2Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria

Abstract. Uncertainties for upper-air trend patterns are still substantial. Observations from the radio occultation (RO) technique offer new opportunities to assess the existing observational records there. Long-term time series are available from radiosondes and from the (Advanced) Microwave Sounding Unit (A)MSU. None of them were originally intended to deliver data for climate applications. Demanding intercalibration and homogenization procedures are required to account for changes in instrumentation and observation techniques. In this comparative study three (A)MSU anomaly time series and two homogenized radiosonde records are compared to RO data from the CHAMP, SAC-C, GRACE-A and F3C missions for September 2001 to December 2010. Differences of monthly anomalies are examined to assess the differences in the datasets due to structural uncertainties. The difference of anomalies of the (A)MSU datasets relative to RO shows a statistically significant trend within about (−0.2±0.1) K/10 yr (95% confidence interval) at all latitudes. This signals a systematic deviation of the two datasets over time. The radiosonde network has known deficiencies in its global coverage, with sparse representation of most of the southern hemisphere, the tropics and the oceans. In this study the error that results from sparse sampling is estimated and accounted for by subtracting it from radiosonde and RO datasets. Surprisingly the sampling error correction is also important in the Northern Hemisphere (NH), where the radiosonde network is dense over the continents but does not capture large atmospheric variations in NH winter. Considering the sampling error, the consistency of radiosonde and RO anomalies is improving substantially; the trend in the anomaly differences is generally very small. Regarding (A)MSU, its poor vertical resolution poses another problem by missing important features of the vertical atmospheric structure. This points to the advantage of homogeneously distributed measurements with high vertical resolution.

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