2018, Dai, Guangyao, Althausen, Dietrich, Hofer, Julian, Engelmann, Ronny, Seifert, Patric, Bühl, Johannes, Mamouri, Rodanthi-Elisavet, Wu, Songhua, Ansmann, Albert

We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar PollyXT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the PollyXT Raman lidar is 6.56 g kg−1 ± 0.72 g kg−1 (with a statistical uncertainty of 0.08 g kg−1 and an instrumental uncertainty of 0.72 g kg−1). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.

2019, Toledano, Carlos, Torres, Benjamín, Velasco-Merino, Cristian, Althausen, Dietrich, Groß, Silke, Wiegner, Matthias, Weinzierl, Bernadett, Gasteiger, Josef, Ansmann, Albert, González, Ramiro, Mateos, David, Farrel, David, Müller, Thomas, Haarig, Moritz, Cachorro, Victoria E.

The Saharan Aerosol Long-Range Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE) was devoted to the investigation of Saharan dust properties over the Caribbean. The campaign took place in June-July 2013. A wide set of ground-based and airborne aerosol instrumentation was deployed at the island of Barbados for a comprehensive experiment. Several sun photometers performed measurements during this campaign: two AERONET (Aerosol Robotic Network) Cimel sun photometers and the Sun and Sky Automatic Radiometer (SSARA). The sun photometers were co-located with the ground-based multi-wavelength lidars BERTHA (Backscatter Extinction lidar Ratio Temperature Humidity profiling Apparatus) and POLIS (Portable Lidar System). Aerosol properties derived from direct sun and sky radiance observations are analyzed, and a comparison with the co-located lidar and in situ data is provided. The time series of aerosol optical depth (AOD) allows identifying successive dust events with short periods in between in which the marine background conditions were observed. The moderate aerosol optical depth in the range of 0.3 to 0.6 was found during the dust periods. The sun photometer infrared channel at the 1640nm wavelength was used in the retrieval to investigate possible improvements to aerosol size retrievals, and it was expected to have a larger sensitivity to coarse particles. The comparison between column (aerosol optical depth) and surface (dust concentration) data demonstrates the connection between the Saharan Air Layer and the boundary layer in the Caribbean region, as is shown by the synchronized detection of the successive dust events in both datasets. However the differences of size distributions derived from sun photometer data and in situ observations reveal the difficulties in carrying out a column closure study. © 2019 All rights reserved.