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The influence of the Madden–Julian oscillation (MJO) on the middle atmosphere (MA) and particularly on MA temperature is of interest for both the understanding of MJO-induced teleconnections and research on the variability of the MA. We analyze statistically the connection of the MJO and the MA zonal mean temperature based on observations by the Microwave Limb Sounder (MLS) satellite instrument. We consider all eight MJO phases, different seasons and the state of the quasi-biennial oscillation (QBO). We show that MA temperature anomalies are significantly related to the MJO and its temporal development. The MJO signal in the zonal mean MA temperature is characterized by a particular spatial pattern in the MA, which we link to the interhemispheric coupling (IHC) mechanism, as a major outcome of this study. The signal with the largest magnitude is found in the polar MA during boreal winter with temperature deviations on the order of ±10 K when the QBO at 50 hPa is in its easterly phase. Other atmospheric conditions and locations also exhibit temperature signals, which are, however, weaker or noisier. We also analyze the change in the temperature signal while the MJO progresses from one phase to the next. We find a gradual altitude shift in parts of the IHC pattern, which can be seen more or less clearly depending on the atmospheric conditions.
The statistical link between the MJO and the MA temperature highlights illustratively the far-reaching connections across different atmospheric layers and geographical regions in the atmosphere. Additionally, it highlights close linkages of known dynamical features of the atmosphere, particularly the MJO, the IHC, the QBO and sudden stratospheric warmings (SSWs). Because of the wide coverage of atmospheric regions and included dynamical features, the results might help to further constrain the underlying dynamical mechanisms and could be used as a benchmark for the representation of atmospheric couplings on the intraseasonal timescale in atmospheric models.
The idea of estimating stratospheric aerosol optical thickness from the twilight colours in historic paintings – particularly under conditions of volcanically enhanced stratospheric aerosol loading – is very tantalizing because it would provide information on the stratospheric aerosol loading over a period of several centuries. This idea has in fact been applied in a few studies in order to provide quantitative estimates of the aerosol optical depth after some of the major volcanic eruptions that occurred during the past 500 years. In this study we critically review this approach and come to the conclusion that the uncertainties in the estimated aerosol optical depths are so large that the values have to be considered questionable. We show that several auxiliary parameters – which are typically poorly known for historic eruptions – can have a similar effect on the red–green colour ratio as a change in optical depth typically associated with eruptions such as, for example, Tambora in 1815 or Krakatoa in 1883. Among the effects considered here, uncertainties in the aerosol particle size distribution have the largest impact on the colour ratios and hence the aerosol optical depth estimate. For solar zenith angles exceeding 80∘, uncertainties in the stratospheric ozone amount can also have a significant impact on the colour ratios. In addition, for solar zenith angles exceeding 90∘ the colour ratios exhibit a dramatic dependence on solar zenith angle, rendering the estimation of aerosol optical depth highly challenging. A quantitative determination of the aerosol optical depth may be possible for individual paintings for which all relevant parameters are sufficiently well constrained in order to reduce the related errors.
The Madden-Julian Oscillation (MJO) is a prominent feature of the intraseasonal variability of the atmosphere. The MJO strongly modulates tropical precipitation and has implications around the globe for weather, climate and basic atmospheric research. The time-dependent state of the MJO is described by MJO indices, which are calculated through sometimes complicated statistical approaches from meteorological variables. One of these indices is the OLR-based MJO Index (OMI; OLR stands for outgoing longwave radiation). The Python package mjoindices, which is described in this paper, provides the first open source implementation of the OMI algorithm, to our knowledge. The package meets state-of-the-art criteria for sustainable research software, like automated tests and a persistent archiving to aid the reproducibility of scientific results. The agreement of the OMI values calculated with this package and the original OMI values is also summarized here. There are several reuse scenarios; the most probable one is MJO-related research based on atmospheric models, since the index values have to be recalculated for each model run.
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.