Long term trends of mesopheric ice layers: A model study

Abstract

Trends derived from the Leibniz-Institute Middle Atmosphere Model (LIMA) and the MIMAS ice particle model (Mesospheric Ice Microphysics And tranSport model) are presented for a period of 138 years (1871–2008) and for middle, high, and arctic latitudes, namely 58°N, 69°N, and 78°N, respectively. We focus on the analysis of mesospheric ice layers (NLC, noctilucent clouds) in the main summer season (July) and on yearly mean values. Model runs with and without an increase of carbon dioxide and water vapor (from methane oxidation) concentrations are performed. Trends are most prominent after ~1960 when the increase of both CO2 and H2O accelerates. It is important to distinguish between tendencies on geometric altitudes and on given pressure levels converted to altitudes (‘pressure altitudes’). Negative trends of (geometric) NLC altitudes are primarily due to cooling below NLC altitudes caused by CO2 increase. Increases of ice particle radii and NLC brightness with time are mainly caused by an enhancement of water vapor. Several ice layer and background parameter trends are similar at high and arctic latitudes but are substantially different at middle latitudes. This concerns, for example, occurrence rates, ice water content (IWC), and number of ice particles in a column. Considering the time period after 1960, geometric altitudes of NLC decrease by approximately 260 m per decade, and brightness increases by roughly 50% (1960–2008), independent of latitude. NLC altitudes decrease by approximately 15–20 m per increase of CO2 by 1 ppmv. The number of ice particles in a column and also at the altitude of maximum backscatter is nearly constant with time. At all latitudes, yearly mean NLC appear at altitudes where temperatures are close to 145±1 K. Ice particles are present nearly all the time at high and arctic latitudes, but are much less common at middle latitudes. Ice water content and maximum backscatter (βmax) are highly correlated, where the slope depends on latitude. This allows to combine data sets from satellites and lidars. Furthermore, IWC and the concentration of water vapor at βmax are also strongly correlated. Nearly all trends depend on a lower limit applied for βmax, e.g., IWC and occurrence rates. Results from LIMA/MIMAS are in very good agreement with observations.