A statistical analysis of the occurrence of polar stratospheric ice clouds based on MIPAS satellite observations and the ERA5 reanalysis

• Main Authors: Zou, Ling, Spang, Reinhold, Griessbach, Sabine, Hoffmann, Lars, Khosrawi, Farahnaz, Müller, Rolf, Tritscher, Ines
• Format: Text
• Language: English
• Published: 2024
• Subjects: Antarctic; Arctic; The Antarctic; Antarc*
• Online Access: https://doi.org/10.5194/egusphere-2024-547; https://egusphere.copernicus.org/preprints/2024/egusphere-2024-547/

Small-scale temperature fluctuations can play a crucial role in the occurrence of ice clouds. This study analyzes a decade of ice polar stratospheric clouds (PSCs) occurrence obtained from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS/Envisat) measurements. The points with the smallest temperature difference (Δ T ice_min ) between the frost point temperature ( T ice ) and the environmental temperature along the limb line of sight are proposed here to identify the location of ice PSC observations. In MIPAS observations, we find approximately 56 % of the Arctic and 28 % of the Antarctic ice PSCs are detected at temperatures above the local T ice based on ERA5 data at Δ T ice_min . Ice PSCs above T ice are concentrated around mountain regions and their downwind directions. A backward trajectory analysis deduced from the ERA5 reanalysis is performed to investigate the temperature history of each ice PSC observation. Based on 24-hour backward trajectories, the cumulative fraction of ice PSCs above T ice increases as the trajectory gets closer to the observation point. The most significant change of the fraction of ice PSCs above T ice occurs within the 6h preceding the observations. There is an impact of previous temperature fluctuations on the interpretation of MIPAS ice PSC observations. At the observation point, the mean fractions of ice PSCs above T ice taking into account temperature fluctuations along the backward trajectory are 33 % in the Arctic and 9 % in the Antarctic. The results provide quantitative assessments of the correlation between orographic waves with ice PSCs above T ice based on the Lagrangian model by using MIPAS measurements and ERA5 reanalysis data. Additionally, the observational statistics presented can be utilized for comparison with chemistry-climate simulations.