Abstract
Abstract. Radio occultation (RO) is a new technique to observe the upper troposphere and lower stratosphere (UTLS), a region that reacts particularly sensitive to climate change. Featuring characteristics such as long-term stability, SI traceability, all-weather capability, global coverage, and high accuracy and vertical resolution, RO data fulfill the requirements for climate monitoring in the UTLS. However, while a range of studies has shown the climate utility of RO it has not yet been explored sytematically where to see climate change best in RO variables. Therefore we perform here a systematic trend study for the RO variables refractivity, pressure, and temperature (bending angle, not depending on height but impact parameter, is left for separate study). The trends, given at geopotential height levels and for layer gradients, are explored to determine seasons, geographic regions, and height domains, which show a significant trend signal. Because continuous RO data are available since 2001 only, reanalyses (ERA-40 and ERA-Interim) and global circulation model simulations of the Intergovernmental Panel on Climate Change Assessment Report 4 (CCSM3, ECHAM5, HadCM3) are used as proxy data for RO. It is shown that RO data are sensitive at different height ranges and that thus several indicators of climate change can be retrieved. Refractivity emerges as indicator in the lower stratosphere (LS) and tropopause region at about 14 km to 24 km, pressure over the whole UTLS, and both in all large-scale regions except the polar caps. Temperature qualifies as indicator in the upper troposphere below about 16 km and in the LS above about 21 km. Overall, refractivity and pressure alone are adequate indicators for the UTLS, but temperature as commonly used variable facilitates easy interpretation of results. Layer gradients were found to be further sensitive indicators providing additional information. Besides large-scale global and hemispheric means the tropics and the mid-latitudes appear as regions suitable to track climate change with RO data. The results also point to the value of utilizing in addition to annual means specific seasons, such as northern hemispheric fall and summer, for early climate signal detection. Since RO data feature much better vertical resolution than the proxy data of this study, more detailed insights can be expected when a longer RO record will be available.
Highlights
Noticeable changes in our climate system are not limited to the Earth’s surface, but emerge as well very clearly in the upper troposphere and lower stratosphere (UTLS), where the vertical thermal structure reflects a balance between radiative, convective, and dynamical heating and cooling processes (Andrews et al, 1987; Holton, 2004)
Largest discrepancies occur in the LS at low and mid-latitudes, probably as a consequence of the lack of the quasi-biennial oscillation (QBO) in global circulation models (GCMs)
A roughly realistic tropical and subtropical LS variability is only present in CCSM3, even though the variability maximum is about 5 km lower than in the observations
Summary
Noticeable changes in our climate system are not limited to the Earth’s surface, but emerge as well very clearly in the upper troposphere and lower stratosphere (UTLS), where the vertical thermal structure reflects a balance between radiative, convective, and dynamical heating and cooling processes (Andrews et al, 1987; Holton, 2004). Upper air observations are available since the establishment of radiosondes in the late 1950s and the implementation of spaceborne measurement systems in the late 1970s (Karl et al, 2006). These systems were not intended for climate monitoring and show shortcomings in this respect as discussed, e.g. by Santer et al (2008) or Randel et al (2009). They are widely used in climate research due to the absence of a specific upper air climate monitoring record. A data record suitable for atmospheric climate monitoring has to supply vertically well resolved, accurate, long-term stable and consistent data, which depict the mean state and the variability of the atmosphere with an accuracy better than the expected long-term changes.
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