Humidity and temperature are key meteorological variables and accurate, continuous and highly resolved measurements are required for a better understanding of many atmospheric phenomena. In particular their strong relation to land surface processes leads to high variability in the atmospheric boundary layer, which is difficult to capture from satellite measurements. Unfortunately, instruments available so far do not provide sufficient resolution to describe short time scale processes such as convection, cloud formation or boundary layer turbulence.

In the last years, in order to overcome the specific limitation of a given instrument, scientific community started merging different data from several ground-based instruments. In this work, the synergy of a Microwave Radiometer (MWR) and a Raman Lidar (RL) system is presented.

On the one hand, RL provides high vertically resolved measurements of temperature and humidity profiles, but it presents important weaknesses (i.e. “blindness” in and above clouds, noisy daytime operation) and therefore cannot be considered operational. On the other hand, MWR offers a much more limited vertical resolution on the retrieval of atmospheric profiles. But it is able to provide accurate integrated quantities such as Integrated Water Vapor (IWV) or Liquid Water Path (LWP). This instrument also allows continuous data acquisition in all weather conditions but rain.

The retrieval method that brings together these two instruments is built up in an Optimal Estimation Scheme (OES) that allows a comprehensive uncertainty assessment. The method is applied to field campaigns in different climate regions where auxiliary measurements, e.g. radiosondes, allow evaluation of its performance.

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Up: Hamburg Raman Lidar (left) and MWR (right) at Barbados Clouds Observatory, in Barbados. Down: Examples of the kind of data the two instruments can provide. On the left hand side, Basil raman lidar and MWR operating at Juelich during the HOPE campaign, the 17th of April 2013. RL provides mixing ratio and MWR measures brightness temperatures.

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Result of the joint retrieval between MWR and RL. Integrated water vapor comparison (up) and absolute humidity time series during the 17th of April 2013, a case study in the HOPE campaign (Juelich, Germany).