Cloud micro- and macrophysical properties from ground-based remote sensing during the MOSAiC drift experiment.

In the framework of the Multidisciplinary drifting Observatory for the Study of Arctic Climate Polarstern expedition, the Leibniz Institute for Tropospheric Research, Leipzig, Germany, operated the shipborne OCEANET-Atmosphere facility for cloud and aerosol observations throughout the whole year. OCEANET-Atmosphere comprises, amongst others, a multiwavelength Raman lidar, a microwave radiometer, and an optical disdrometer. A cloud radar was operated aboard Polarstern by the US Atmospheric Radiation Measurement program. These measurements were processed by applying the so-called Cloudnet methodology to derive cloud properties. To gain a comprehensive view of the clouds, lidar and cloud radar capabilities for low- and high-altitude observations were combined. Cloudnet offers a variety of products with a spatiotemporal resolution of 30 s and 30 m, such as the target classification, and liquid and ice microphysical properties. Additionally, a lidar-based low-level stratus retrieval was applied for cloud detection below the lowest range gate of the cloud radar. Based on the presented dataset, e.g., studies on cloud formation processes and their radiative impact, and model evaluation studies can be conducted.

Atmospheric temperature, water vapour and liquid water path from two microwave radiometers during MOSAiC.

The microwave radiometers HATPRO (Humidity and Temperature Profiler) and MiRAC-P (Microwave Radiometer for Arctic Clouds - Passive) continuously measured radiation emitted from the atmosphere throughout the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition on board the research vessel Polarstern. From the measured brightness temperatures, we have retrieved atmospheric variables using statistical methods in a temporal resolution of 1 s covering October 2019 to October 2020. The integrated water vapour (IWV) is derived individually from both radiometers. In addition, we present the liquid water path (LWP), temperature and absolute humidity profiles from HATPRO. To prove the quality and to estimate uncertainty, the data sets are compared to radiosonde measurements from Polarstern. The comparison shows an extremely good agreement for IWV, with standard deviations of 0.08-0.19 kg m-2 (0.39-1.47 kg m-2) in dry (moist) situations. The derived profiles of temperature and humidity denote uncertainties of 0.7-1.8 K and 0.6-0.45 gm-3 in 0-2 km altitude.

Particle backscatter, extinction, and lidar ratio profiling with Raman lidar in south and north China.

Aerosol Raman lidar observations of profiles of the particle extinction and backscatter coefficients and the respective extinction-to-backscatter ratio (lidar ratio) were performed under highly polluted conditions in the Pearl River Delta (PRD) in southern China in October 2004 and at Beijing during a clear period with moderately polluted to background aerosol conditions in January 2005. The anthropogenic haze in the PRD is characterized by volume light-extinction coefficients of particles ranging from approximately 200 to 800 Mm(-1) and lidar ratios mostly between 40 and 55 sr (average of 47+/-6 sr). Almost clean air masses were observed throughout the measurements of the Beijing campaign. These air masses originated from arid desert-steppe-like regions (greater Gobi area). Extinction values usually varied between 100 and 300 Mm(-1), and the lidar ratios were considerably lower (compared with PRD values) with values mostly from 30 to 45 sr (average of 38+/-7 sr). Gobi dust partly influenced the observations. Unexpectedly low lidar ratios of approximately 25 sr were found for a case of background aerosol with a low optical depth of 0.05. The low lidar ratios are consistent with Mie-scattering calculations applied to ground-based observations of particle size distributions.

Daytime operation of a pure rotational Raman lidar by use of a Fabry-Perot interferometer.

We propose to use a Fabry-Perot interferometer (FPI) in a pure rotational Raman lidar to isolate return signals that are due to pure rotational Raman scattering from atmospheric nitrogen against the sky background. The main idea of this instrumental approach is that a FPI is applied as a frequency comb filter with the transmission peaks accurately matched to a comb of practically equidistant lines of a pure rotational Raman spectrum (PRRS) of nitrogen molecules. Thus a matched FPI transmission comb cuts out the spectrally continuous sky background light from the spectral gaps between the PRRS lines of nitrogen molecules while it is transparent to light within narrow spectral intervals about these lines. As the width of the spectral gaps between the lines of the PRRS of nitrogen molecules is -114 times the width of an individual spectral line, cutting out of the sky background from these gaps drastically improves the signal-to-background ratio of the pure rotational Raman lidar returns. This application of the FPI enables one to achieve daytime temperature profiling in the atmosphere with a pure rotational Raman lidar in the visible and near-UV spectral regions. We present an analysis of application of the FPI to filtering out the pure rotational Raman lidar returns against the solar background. To demonstrate the feasibility of the approach proposed, we present temperature profiles acquired during a whole-day measurement session in which a Raman lidar equipped with a FPI was used. For comparison, temperature profiles acquired with Vaisala radiosondes launched from the measurement site are also presented.

Relative-humidity profiling in the troposphere with a Raman lidar.

We describe a Raman-lidar-based approach to acquiring profiles of the relative humidity of air. For this purpose we combined in one instrument the Raman-lidar techniques that are used for the profiling of water vapor and temperature. This approach enabled us to acquire, for the first time to our knowledge, vertical profiles of relative humidity through the entire troposphere exclusively from Raman-lidar data. The methods applied to determining the water-vapor mixing ratio, temperature, and relative humidity and the corresponding uncertainties caused by systematic errors and signal noise are presented. The lidar-derived profiles are compared with profiles measured with radiosondes. Radiosonde observations are also used to calibrate the Raman lidar. Close agreement of the profiles of relative humidity measured with lidar and those measured with radiosonde demonstrates the potential of this novel approach.