Measurement uncertainties of scanning microwave radiometers and their influence on temperature profiling

Abstract

Abstract. In order to improve observations of the atmospheric boundary layer (ABL), the European Meteorological Network, EUMETNET, and the Aerosol, Clouds, and Trace Gases Research Infrastructure, ACTRIS, are currently working on building networks of microwave radiometers (MWRs). Elevation-scanning MWRs are well suited to obtain temperature profiles of the atmosphere, especially within the ABL. Understanding and assessing measurement uncertainties of state-of-the-art scanning MWRs is therefore crucial for accurate temperature profiling. In this paper, we discuss measurement uncertainties due to the instrument setup and originating from external sources, namely (1) horizontal inhomogeneities of the atmosphere, (2) pointing errors or a tilt of the instrument, (3) physical obstacles in the line of sight of the instrument, and (4) radio frequency interference (RFI). Horizontal inhomogeneities from observations at the Jülich Observatory for Cloud Evolution (JOYCE) are shown to have a small impact on retrieved temperature profiles (<|0.22K| in the 25th and 75th percentiles below 3000 m). Typical instrument tilts, that could be caused by uncertainties during the instrument setup, also have a very small impact on temperature profiles and are smaller than 0.1 K below 3000 m for up to 1∘ of tilt. Physical obstacles at ambient temperatures and in the line of sight and filling the complete beam of the MWR at the lowest elevation angle of 5.4∘ have to be at least 600 m away from the instrument in order to have an impact of less than 0.1 K on obtained temperature profiles. If the obstacle is 5 K warmer than its surroundings then the obstacle should be at least 2700 m away. Finally, we present an approach on how to detect RFI with an MWR with azimuth and elevation-scanning capabilities. In this study, we detect RFIs in a water vapor channel that does not influence temperature retrievals but would be relevant if the MWR were used to detect horizontal humidity inhomogeneities.