Indications for a potential synchronization between the phase evolution of the Madden–Julian oscillation and the solar 27-day cycle

The Madden–Julian oscillation (MJO) is a major source of intraseasonal variability in the troposphere. Recently, studies have indicated that also the solar 27-day variability could cause variability in the troposphere. Furthermore, it has been indicated that both sources could be linked, and particularly that the occurrence of strong MJO events could be modulated by the solar 27-day cycle.In this paper, we analyze whether the temporal evolution of the MJO phases could also be linked to the solar 27-day cycle. We basically count the occurrences of particular MJO phases as a function of time lag after the solar 27-day extrema in about 38 years of MJO data. Furthermore, we develop a quantification approach to measure the strength of such a possible relationship and use this to compare the behavior for different atmospheric conditions and different datasets, among others. The significance of the results is estimated based on different variants of the Monte Carlo approach, which are also compared.We find indications for a synchronization between the MJO phase evolution and the solar 27-day cycle, which are most notable under certain conditions: MJO events with a strength greater than 0.5, during the easterly phase of the quasi-biennial oscillation, and during boreal winter. The MJO appears to cycle through its eight phases within two solar 27-day cycles. The phase relation between the MJO and the solar variation appears to be such that the MJO predominantly transitions from phase 8 to 1 or from phase 4 and 5 during the solar 27-day minimum. These results strongly depend on the MJO index used such that the synchronization is most clearly seen when using univariate indices like the OLR-based MJO index (OMI) in the analysis but can hardly be seen with multivariate indices like the real-time multivariate MJO index (RMM). One possible explanation could be that the synchronization pattern is encoded particularly in the underlying outgoing longwave radiation (OLR) data. A weaker dependence of the results on the underlying solar proxy is also observed but not further investigated.Although we think that these initial indications are already worth noting, we do not claim to unambiguously prove this relationship in the present study, neither in a statistical nor in a causal sense. Instead, we challenge these initial findings ourselves in detail by varying underlying datasets and methods and critically discuss resulting open questions to lay a solid foundation for further research.</p

Daytime ozone and temperature variations in the mesosphere: A comparison between SABER observations and HAMMONIA model

The scope of this paper is to investigate the latest version 1.07 SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) tropical ozone from the 1.27 μm as well as from the 9.6 μm retrieval and temperature data with respect to daytime variations in the upper mesosphere. For a better understanding of the processes involved we compare these daytime variations to the output of the three-dimensional general circulation and chemistry model HAMMONIA (Hamburg Model of the Neutral and Ionized Atmosphere). The results show good agreement for ozone. The amplitude of daytime variations is in both cases approximately 60% of the daytime mean. During equinox the daytime maximum ozone abundance is for both, the observations and the model, higher than during solstice, especially above 80 km. We also use the HAMMONIA output of daytime variation patterns of several other different trace gas species, e.g., water vapor and atomic oxygen, to discuss the daytime pattern in ozone. In contrast to ozone, temperature data show little daytime variations between 65 and 90 km and their amplitudes are on the order of less than 1.5%. In addition, SABER and HAMMONIA temperatures show significant differences above 80 k

Lower thermospheric nitric oxide concentrations derived from WINDII observations of the green nightglow continuum at 553.1 nm

International audienceVertical profiles of nitric oxide in the altitude range 90 to 105 km are derived from 553 nm nightglow continuum measurements made with the Wind Imaging Interferometer (WINDII) on the Upper Atmosphere Research Satellite (UARS). The profiles are derived under the assumption that the continuum emission is due entirely to the NO+O air afterglow reaction. Vertical profiles of the atomic oxygen density, which are required to determine the nitric oxide concentrations, are derived from coordinated WINDII measurements of the atomic oxygen OI 557.7 nm nightglow emission. Data coverage for local solar times ranging from 20 h to 04 h, and latitudes ranging from 42°S to 42°N, is achieved by zonally averaging and binning data obtained on 18 nights during a two-month period extending from mid-November 1992 until mid-January 1993. The derived nitric oxide concentrations are significantly smaller than those obtained from rocket measurements of the airglow continuum but they do compare well with model expectations and nitric oxide densities measured using the resonance fluorescence technique on the Solar Mesosphere Explorer satellite. The near-global coverage of the WINDII observations and the similarities to the nitric oxide global morphology established from other satellite measurements strongly suggests that the NO+O reaction is the major source of the continuum near 553 nm and that there is no compelling reason to invoke additional sources of continuum emission in this immediate spectral region

Comparison of NLC particle sizes derived from SCIAMACHY/Envisat observations with ground-based LIDAR measurements at ALOMAR (69&deg; N)

SCIAMACHY, the Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY has provided measurements of limb-scattered solar radiation in the 220 nm to 2380 nm wavelength range since summer of 2002. Measurements in the UV spectral range are well suited for the retrieval of particle sizes of noctilucent clouds (NLCs) and have been used to compile the largest existing satellite data base of NLC particle sizes. This paper presents a comparison of SCIAMACHY NLC size retrievals with the extensive NLC particle size data set based on ground-based LIDAR measurements at the Arctic LIDAR Observatory for Middle Atmosphere Research (ALOMAR, 69&deg; N, 16&deg; E) for the Northern Hemisphere NLC seasons 2003 to 2007. Most of the presented SCIAMACHY NLC particle size retrievals are based on cylindrical particles and a Gaussian particle size distribution with a fixed width of 24 nm. If the differences in spatial as well as vertical resolution between SCIAMACHY and the ALOMAR LIDAR are taken into account, very good agreement is found. The mean particle size derived from SCIAMACHY limb observations for the ALOMAR overpasses in 2003 to 2007 is 56.2 nm with a standard deviation of 12.5 nm, and the LIDAR observations yield a value of 54.2 nm with a standard deviation of 17.4 nm

Revisiting the question “Why is the sky blue?”

The common answer to the question “Why is the sky blue?” is usually Rayleigh scattering. In 1953 Edward Hulburt demonstrated that Rayleigh scattering accounts for 1/3 and ozone absorption for 2/3 of the blue colour of the zenith sky at sunset. In this study, an approach to quantify the contribution of ozone to the blue colour of the sky for different viewing geometries is implemented using the radiative transfer model SCIATRAN and the CIE (International Commission on Illumination) XYZ 1931 colour system. The influence of ozone on the blue colour of the sky is calculated for solar zenith angles of 10–90∘ and a wide range of viewing geometries. For small solar zenith angles, the influence of ozone on the blue colour of the sky is minor, as expected. However, the effect of ozone increases with increasing solar zenith angle. The calculations for the Sun at the horizon confirm Hulburt's estimation with remarkably good agreement. More stratospheric aerosols reduce the ozone contribution at and near the zenith for the Sun at the horizon. The exact contribution of ozone depends strongly on the assumed total ozone column. The calculations also show that the contribution of ozone increases with increasing viewing zenith angle and total ozone column. Variations in surface albedo as well as full treatment of polarised radiative transfer were found to have only minor effects on the contribution of ozone to the blue colour of the sky. Furthermore, with an observer at 10 km altitude an increase in the ozone influence can be seen.</p

Impact of a strong volcanic eruption on the summer middle atmosphere in UA-ICON simulations

Explosive volcanic eruptions emitting large amounts of sulfur can alter the temperature of the lower stratosphere and change the circulation of the middle atmosphere. The dynamical response of the stratosphere to strong volcanic eruptions has been the subject of numerous studies. The impact of volcanic eruptions on the mesosphere is less well understood because of a lack of large eruptions in the satellite era and only sparse observations before that period. Nevertheless, some measurements indicated an increase in mesospheric mid-latitude temperatures after the 1991 Pinatubo eruption. The aim of this study is to uncover potential dynamical mechanisms that may lead to such a mesospheric temperature response. We use the Upper-Atmospheric ICOsahedral Non-hydrostatic (UA-ICON) model to simulate the atmospheric response to an idealized strong volcanic injection of 20 Tg S into the stratosphere (about twice as much as the eminent 1991 Pinatubo eruption). Two experiments with differently parameterized effects of sub-grid-scale orography are compared to test the impact of different atmospheric background states. The simulations show a significant warming of the polar summer mesopause of up to 15–21 K in the first November after the eruption. We argue that this is mainly due to intrahemispheric dynamical coupling in the summer hemisphere and is potentially enhanced by interhemispheric coupling with the winter stratosphere. This study focuses on the first austral summer after the eruption because mesospheric temperature anomalies are especially relevant for the properties of noctilucent clouds, whose season peaks around January in the Southern Hemisphere.</p

Validation of IFE-1.6 SCIAMACHY limb ozone profiles

International audienceThe IFE-1.6 scientific data set of SCIAMACHY limb ozone profiles is validated for the period August?December 2002. The data set provides ozone profiles over an altitude range of 15?45 km. The main uncertainty in the profiles is the imprecise knowledge of the pointing of the instrument, leading to retrieved profiles that are shifted in altitude direction. To obtain a first order correction for the pointing error and the remaining uncertainties, the retrieved profiles are compared to their a-priori value and ozone sondes based on absolute distance and equivalent latitude criteria. A vertical shift of the satellite profiles with 2 km downward is found to be an appropriate correction for the data set studied. A total root-mean-square difference between limb profiles and sondes of 10?15% remains for the stratospheric ozone profile after application of the correction. Small biases are left above and below the ozone maximum at mid latitudes, where the vertical gradients in the retrieved product are in general too strong

Detection and mapping of polar stratospheric clouds using limb scattering observations

International audienceSatellite-based measurements of Visible/NIR limb-scattered solar radiation are well suited for the detection and mapping of polar stratospheric clouds (PSCs). This publication describes a method to detect PCSs from limb scattering observations with the Scanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) on the European Space Agency's Envisat spacecraft. The method is based on a color-index approach and requires a priori knowledge of the stratospheric background aerosol loading in order to avoid false PSC identifications by stratospheric background aerosol. The method is applied to a sample data set including the 2003 PSC season in the Southern Hemisphere. The PSCs are correlated with coincident UKMO model temperature data, and with very few exceptions, the detected PSCs occur at temperatures below 195?198 K. Monthly averaged PSC descent rates are about 1.5 km/month for the ?50° S to ?75° S latitude range and assume a maximum between August and September with a value of about 2.5 km/month. The main cause of the PSC descent is the slow descent of the lower stratospheric temperature minimum

Year-round stratospheric aerosol backscatter ratios calculated from lidar measurements above northern Norway

We present a new method for calculating backscatter ratios of the stratospheric sulfate aerosol (SSA) layer from daytime and nighttime lidar measurements. Using this new method we show a first year-round dataset of stratospheric aerosol backscatter ratios at high latitudes. The SSA layer is located at altitudes between the tropopause and about 30 km. It is of fundamental importance for the radiative balance of the atmosphere. We use a state-of-the-art Rayleigh-Mie-Raman lidar at the Arctic Lidar Observatory for Middle Atmosphere Research (ALOMAR) station located in northern Norway (69N, 16E; 380ma.s.l.). For nighttime measurements the aerosol backscatter ratios are derived using elastic and inelastic backscatter of the emitted laser wavelengths 355, 532 and 1064nm. The setup of the lidar allows measurements with a resolution of about 5 min in time and 150 m in altitude to be performed in high quality, which enables the identification of multiple sub-layers in the stratospheric aerosol layer of less than 1 km vertical thickness. We introduce a method to extend the dataset throughout the summer when measurements need to be performed under permanent daytime conditions. For that purpose we approximate the backscatter ratios from color ratios of elastic scattering and apply a correction function. We calculate the correction function using the average backscatter ratio profile at 355nm from about 1700 h of nighttime measurements from the years 2000 to 2018. Using the new method we finally present a year-round dataset based on about 4100 h of measurements during the years 2014 to 2017. © Author(s) 2019