The Madden-Julian oscillation (MJO) is characterized by eastward propagating convection anomalies in the Indian and Pacific tropical oceans with a period of 30-60 days (Madden & Julian, 1971, 1972. In addition to being a dominant intraseasonal variability in the tropics, the state of the MJO has also been connected to weather at higher latitudes (e.g., Arcodia et al., 2020;Henderson et al., 2016), among many other aspects of global atmospheric circulation. Reviews on the significance of the MJO appear in Jiang et al. (2020) andZhang (2005).The influence of the MJO on the global climate system is dependent on the spatial pattern and amplitude of the MJO signal, which are often quantified using an index generated by empirical orthogonal functions (EOFs). The phase of the MJO, based on these indices, is used to predict or otherwise characterize the influence of the MJO on various atmospheric phenomena (J. Wang et al., 2020). One frequently used index is the real-time multivariate (RMM) index (M. C. Wheeler & Hendon, 2004). The RMM is based on the zonal structure of OLR and zonal wind at 200 and 850 hPa, and can be used for real-time monitoring of the MJO. However, Straub (2013) showed that the RMM underrepresents convection compared to zonal wind, causing the RMM to miss some MJO-like convective signals. In addition, the lack of meridional structure confounds the MJO signal with equatorial Kelvin waves (Roundy et al., 2009).An OLR-based MJO index (OMI) was developed to counteract some of these issues, since it incorporates the zonal and meridional structure of OLR into a pair of propagating EOFs over the course of the year (Kiladis et al., 2014) (hereafter K14). Incorporation of meridional structure helps separate the MJO signal from Kelvin waves, and using solely OLR more directly tracks the convective signal. Since OLR can be measured directly by satellites, the OMI provides a reliable long-term record of tropical convective patterns (S. Wang, 2019).Due to these benefits, the OMI is a widespread index used for MJO analyses. However, there remain a few small but important issues with the original OMI. Since the EOFs of the OMI represent propagating waves of the MJO, the leading EOF pair are of a similar magnitude (North et al., 1982), resulting in a somewhat arbitrary choice when assigning the EOFs as EOF1 or EOF2. In the original OMI calculation, the leading pair of eigenvalues
In discussions of extreme weather trends, the subject of atmospheric blocking remains an open question, in part because of the inability of climate models to accurately reproduce blocking frequency patterns for the current climate. A number of factors have been proposed to explain this failure, including specific problems with model physics and inadequate resolution. In this paper, we show that, in the case of the National Center for Atmospheric Research Community Atmosphere Model (NCAR CAM), its underestimation of blocking frequency is caused by its mean state bias and that correcting that bias increases blocking frequency estimates over Europe and decreases the root‐mean‐square error versus reanalysis from 0.015 to 0.011.
Various indices have been defined to characterize the phase and amplitude of the Madden-Julian oscillation (MJO). One widely used index is the Outgoing Longwave Radiation (OLR) based MJO index (OMI), which is calculated using the spatial pattern of 30-96-day eastward-filtered OLR. The EOFs used to calculate the OMI in observations are prone to degeneracy and exhibit oscillations on the order of 10-20 days, despite initial filtering of the OLR. We propose a simple modification to the OMI that involves aligning the EOFs between neighboring days while retaining the spatial pattern described by the EOFs. This rotation method is implemented as a postprocessing step of the current OMI calculation and cleanly removes the spurious oscillations and degeneracy issues seen in the standard method. A similar rotation procedure can be implemented in calculations of other MJO indices.
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