Impact of Short-Term Solar Variability on the Polar Summer Mesopause and Noctilucent Clouds

Abstract

AbstractThe Earth’s middle atmosphere is affected by short-term solar variability in a variety of ways. This chapter focuses on the investigation of two different short-term solar effects on the polar summer mesopause region and on noctilucent clouds (NLCs). First, the effect of solar proton events (SPEs) on the thermal conditions near the polar summer mesopause and consequently on NLCs is discussed. An analysis of the SBUV(/2) time series to identify examples of NLC depletion due to SPEs shows that NLCs are probably frequently affected during strong SPEs. As part of this study a physical mechanism explaining a dynamically induced warming at the polar summer mesopause during and after SPEs is investigated using model simulations with the Kühlungsborn Mechanistic General Circulation Model (KMCM). A second aspect related to the effect of SPEs on NLCs is on the SPE-induced ion-chemical conversion of H2O to HO x , leading to a possible sublimation of NLCs. However, this effect was found to be of minor importance compared to the dynamically induced temperature effect. Second, we discuss the recently discovered 27-day solar cycle signature in NLCs, which was identified in SCIAMACHY as well as SBUV satellite observations of NLCs using cross correlation analysis and the superposed epoch method. NLC occurrence rate and albedo anomalies are anti-correlated with Lyman-α anomalies with a time-lag of 1 day at most. The sensitivities of the NLC albedo anomalies to Lyman-α forcing in terms of the 27-day and the 11-year solar cycle were found to agree within their uncertainties. This finding suggests that the same underlying physical mechanism drives the 27-day as well as the 11-year solar cycle signature in NLCs. The exact mechanism is still unknown, however.KeywordsDiabatic HeatingMiddle AtmosphereSolar Proton EventCatalytic OzoneMicrowave Limb SoundThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.