Abstract
Abstract. Radio occultation (RO) data are increasingly used in climate research. Accurate phase (change) measurements of Global Positioning System (GPS) signals are the basis for the retrieval of near-vertical profiles of bending angle, microwave refractivity, density, pressure, and temperature. If temperature is calculated from observed refractivity with the assumption that water vapor is zero, the product is called "dry temperature", which is commonly used to study earth's atmosphere, e.g., when analyzing temperature trends due to global warming. Dry temperature is a useful quantity, since it does not need additional background information in its retrieval. However, it can only be safely used as proxy for physical temperature, where moisture is negligible. The altitude region above which water vapor does not play a dominant role anymore, depends primarily on latitude and season. In this study we first investigated the influence of water vapor on dry temperature RO profiles. Hence, we analyzed the maximum altitude down to which monthly mean dry temperature profiles can be regarded as being equivalent to physical temperature. This was done by examining dry temperature to physical temperature differences of monthly mean analysis fields from the European Centre for Medium-Range Weather Forecasts (ECMWF), studied from 2006 until 2010. We introduced cutoff criteria, where maximum temperature differences of −0.1, −0.05, and −0.02 K were allowed (dry temperature is always lower than physical temperature), and computed the corresponding altitudes. As an example, a temperature difference of −0.05 K in the tropics was found at an altitude of about 14 km, while at higher northern latitudes in winter it was found at an altitude of about 9–10 km, in summer at about 11 km. Furthermore, regarding climate change, we expect an increase of absolute humidity in the atmosphere. This possible trend in water vapor could yield a wrongly interpreted dry temperature trend. As a consequence, we performed a model study, investigating the increase in height of the transition region between moist and dry air. We used data from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), analyzing again monthly mean dry temperature to physical temperature differences, now from the years 2006 to 2050. We used the highest emission scenario RCP8.5 (representative concentration pathway), studying all available models of the CMIP5 project, analyzing one internal run per model, with the goal to identify the altitude region where trends in dry temperature can be safely regarded as reflecting trends in physical temperature. From all models we therefore choose a selection of models ("max 8" CMIP5 models), which showed the largest trend differences. As a result, our trend study suggests that the lower boundary of the region where dry temperature is essentially equal to physical temperature rises about 150 m decade−1.
Highlights
The Radio occultation (RO) technique gains information about the physical properties of a planetary atmosphere by detecting a change in a radio signal when it passes through this atmosphere
Based on European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data (2006–2010) we investigated to what extent it is valid to study dry temperature profiles as proxy for physical temperature and we wanted to understand spatial and seasonal dependencies of differences between those two
At 11 km geopotential height, 0◦ latitude, we find in January a trend difference of about −0.1 K decade−1 and a physical temperature trend of about 0.7 K decade−1 leading to a relative error of about 14 % if dry temperature were used as a proxy for physical temperature
Summary
The Radio occultation (RO) technique gains information about the physical properties of a planetary atmosphere by detecting a change in a radio signal when it passes through this atmosphere. Danzer et al.: Influence of humidity on RO dry temperature lower stratosphere (UTLS) since 1995; see e.g., Kursinski et al (1997) It has the advantage of all-weather capability, high vertical resolution, and global coverage. In the analysis of RO data it has become quite common to retrieve dry atmospheric parameters if humidity is negligible. Based on ECMWF analysis data (2006–2010) we investigated to what extent it is valid to study dry temperature profiles as proxy for physical temperature and we wanted to understand spatial and seasonal dependencies of differences between those two. It introduces the dry temperature retrieval in Sect.
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