Investigating long-term changes in polar stratospheric clouds above Antarctica during past decades: a temperature-based approach using spaceborne lidar detections

Abstract

Abstract. Polar stratospheric clouds play a significant role in the seasonal thinning of the ozone layer by facilitating the activation of stable chlorine and bromine reservoirs into reactive radicals, as well as prolonging the ozone depletion by removing HNO3 and H2O from the stratosphere by sedimentation. In a context of climate change, the cooling of the lower polar stratosphere could enhance polar stratospheric cloud (PSC) formation and by consequence cause more ozone depletion. There is thus a need to document the evolution of the PSC cover to better understand its impact on the ozone layer. In this article we present a statistical model based on the analysis of the CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations) PSC product from 2006 to 2020. The model predicts the daily regionally averaged PSC density by pressure level derived from stratospheric temperatures. Applied to stratospheric temperatures from the CALIPSO PSC product, our model reproduces observed and interannual variations in PSC density well between 10 and 150 hPa over the 2006–2020 period. The model reproduces the PSC seasonal progression well, even during disruptive events like stratospheric sudden warmings, except for years characterized by volcanic eruptions. We also apply our model to gridded temperatures from Modern Era Retrospective analysis for Research and Application (MERRA-2) reanalyses over the complete South Pole region to evaluate changes in PSC season duration over the 1980–2021 period. We find that over the 1980–2000 period, the PSC season gets significantly longer between 30 and 150 hPa. Lengthening of the PSC season from 22 d (30–50 hPa) to 32 d (100–150 hPa) is possibly related to volcanic eruptions occurring over this period. Over 1980–2021, we find that the PSC season gets significantly longer between 30 and 100 hPa, but due to biases in MERRA-2 temperatures, the reliability of these trends is hard to evaluate.