Year-round stratospheric aerosol backscatter ratios calculated from lidar measurements above northern Norway

• Main Authors: Langenbach, A., Baumgarten, G., Fiedler, J., Lübken, F.-J., Von Savigny, C., Zalach, J.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Göttingen : Copernicus GmbH 2019
• Subjects: aerosol; backscatter; correction; data set; lidar; observatory; stratosphere; sulfate; Norway; 550; Arctic; Alomar; Northern Norway
• Online Access: https://doi.org/10.34657/4620; https://oa.tib.eu/renate/handle/123456789/5991

We present a new method for calculating backscatter ratios of the stratospheric sulfate aerosol (SSA) layer from daytime and nighttime lidar measurements. Using this new method we show a first year-round dataset of stratospheric aerosol backscatter ratios at high latitudes. The SSA layer is located at altitudes between the tropopause and about 30 km. It is of fundamental importance for the radiative balance of the atmosphere. We use a state-of-the-art Rayleigh-Mie-Raman lidar at the Arctic Lidar Observatory for Middle Atmosphere Research (ALOMAR) station located in northern Norway (69N, 16E; 380ma.s.l.). For nighttime measurements the aerosol backscatter ratios are derived using elastic and inelastic backscatter of the emitted laser wavelengths 355, 532 and 1064nm . The setup of the lidar allows measurements with a resolution of about 5 min in time and 150 m in altitude to be performed in high quality, which enables the identification of multiple sub-layers in the stratospheric aerosol layer of less than 1 km vertical thickness. We introduce a method to extend the dataset throughout the summer when measurements need to be performed under permanent daytime conditions. For that purpose we approximate the backscatter ratios from color ratios of elastic scattering and apply a correction function. We calculate the correction function using the average backscatter ratio profile at 355nm from about 1700 h of nighttime measurements from the years 2000 to 2018. Using the new method we finally present a year-round dataset based on about 4100 h of measurements during the years 2014 to 2017. © Author(s) 2019. Leibniz_Fonds publishedVersion