Estimation of the Optical properties of Arctic Cirrus Clouds: Insights fromLIDAR measurements and Monte Carlo simulations

Cirrus clouds play a critical role in Earth's energy balance by influencing radiative
processes, reflecting incoming solar radiation, and trapping outgoing infrared radiation. In the
Arctic, extreme conditions limit the observational networks and hinder direct measurements.
However, among various remote sensing tools, LIght Detection And Ranging (LIDAR)
emerges as one of a reliable tool for long-term monitoring of cirrus cloud optical properties
over the Arctic region. The extinction coefficient, derived from LIDAR measurements and
essential for evaluating the radiative effects of cirrus clouds, is strongly impacted by the
Multiple Scattering Factor (MSF). In this regard, the present study aims to estimate the MSF
by simulating LIDAR signals using the Monte Carlo method. The input parameters for the
Monte Carlo simulations include the geometry of the atmosphere and optical properties
(including extinction and Mueller matrix). Furthermore, the Mueller matrix is estimated based
on the size distribution and particle shape information acquired through the in-situ measurement
from the Balloon-borne Ice Cloud Particle Imager (B-ICI) instrument. The MSF contribution,
at least in part, depends on the characteristics of the LIDAR, particularly its Field of View. As
a result, new simulations are required, and previous results from older studies cannot be directly
applied.
The photon backscatter information obtained from the Analog and Photon
counting channels of the ground-based LIDAR instrument installed at IRF, Kiruna (68ºN,
20ºE), is utilised to estimate the cirrus cloud's optical properties. To address the instrument’s
non-linear behaviour at higher signal intensities, a glueing procedure is performed to merge the
Analog and the Photon counting signal. The resulting glued signal undergoes multiple
corrections, including background noise subtraction, signal-to-noise ratio enhancement, and
range corrections. The Dynamic Wavelet Covariance Transform (DWCT) technique is
deployed to the corrected LIDAR signal to estimate the cloud top and base altitude information.
Subsequently, an inversion technique incorporating MSF, such as the Sassen method, is chosen
for the current analysis.
The estimated cirrus cloud optical properties using the ground-based LIDAR will
subsequently be validated against EarthCARE’s ATmospheric LIDar (ATLID) satellite
observations. This study enhances the accuracy of cirrus cloud parameterisation, contributing
to improved climate models and a deeper understanding of Arctic cloud-radiative interactions.