On the Regionality of Moist Kelvin Waves and the MJO: The Critical Role of the Background Zonal Flow

A global model with superparameterized physics is used to shed light on the observed regionality of convectively coupled Kelvin waves and the Madden-Julian Oscillation (MJO). A series of aquaplanet simulations over zonally uniform sea-surface temperatures is performed, in which the axisymmetric structure of the background zonal flow is altered through nudging, while maintaining a quasi-fixed rainfall climatology. Results show that nudging at the equator to match profiles typical of the Indo-Pacific or eastern Pacific sectors yields eastward-moving tropical rain spectra typical of those sectors. Two different mechanistic pathways are identified as being responsible for this mean-flow dependence, in addition to Doppler shifting effects. The first is through shifts of the Rossby wave critical line in the subtropical upper troposphere that affect the lateral forcing of Kelvin-mode circulations at the equator by eastward and equatorward-propagating eddies impinging on the tropics from higher latitudes. The second is through changes in the strength of the mean cyclonic shear in the lower tropical troposphere that affect the degree to which intraseasonal fluctuations in Kelvin-mode zonal winds modulate the activity of higher-frequency equatorial Rossby-type eddies. In cases where the mean low-level cyclonic shear is enhanced, the strength of this modulation, referred to as &ldquo;shear-induced eddy modulation&rdquo; or SIEM, is also seen to be enhanced, such that MJO-like modes of variability are rendered either unstable or near neutral, depending on the strength of the shear. &nbsp;</p

A Python Package to Calculate the OLR-Based Index of the Madden- Julian-Oscillation (OMI) in Climate Science and Weather Forecasting

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

Seasonal cycle of precipitation variability in South America on intraseasonal timescales

The seasonal cycle of the intraseasonal (IS) variability of precipitation in South America is described through the analysis of bandpass filtered outgoing longwave radiation (OLR) anomalies. The analysis is discriminated between short (10--30 days) and long (30--90 days) intraseasonal timescales. The seasonal cycle of the 30--90-day IS variability can be well described by the activity of first leading pattern (EOF1) computed separately for the wet season (October--April) and the dry season (May--September). In agreement with previous works, the EOF1 spatial distribution during the wet season is that of a dipole with centers of actions in the South Atlantic Convergence Zone (SACZ) and southeastern South America (SESA), while during the dry season, only the last center is discernible. In both seasons, the pattern is highly influenced by the activity of the Madden--Julian Oscillation (MJO). Moreover, EOF1 is related with a tropical zonal-wavenumber-1 structure superposed with coherent wave trains extended along the South Pacific during the wet season, while during the dry season the wavenumber-1 structure is not observed. The 10--30-day IS variability of OLR in South America can be well represented by the activity of the EOF1 computed through considering all seasons together, a dipole but with the stronger center located over SESA. While the convection activity at the tropical band does not seem to influence its activity, there are evidences that the atmospheric variability at subtropical-extratropical regions might have a role. Subpolar wavetrains are observed in the Pacific throughout the year and less intense during DJF, while a path of wave energy dispersion along a subtropical wavetrain also characterizes the other seasons. Further work is needed to identify the sources of the 10--30-day-IS variability in South America

Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: Convective signals

This study evaluates the tropical intraseasonal variability, especially the fidelity of The results show that current state-of-the-art GCMs still have significant problems and display a wide range of skill in simulating the tropical intraseasonal variability. The total intraseasonal (2-128 day) variance of precipitation is too weak in most of the models. About half of the models have signals of convectively coupled equatorial waves, with Kelvin and MRG-EIG waves especially prominent. However, the variances are generally too weak for all wave modes except the EIG wave, and the phase speeds are generally too fast, being scaled to excessively deep equivalent depths. An interesting result is that this scaling is consistent within a given model across modes, in that both the symmetric and antisymmetric modes scale similarly to a certain equivalent depth. Excessively deep equivalent depths suggest that these models may not have a large enough reduction in their &quot;effective static stability&quot; due to diabatic heating. 3 The MJO variance approaches the observed value in only two of the 14 models, but is less than half of the observed value in the other 12 models. The ratio between the eastward MJO variance and the variance of its westward counterpart is too small in most of the models, which is consistent with the lack of highly coherent eastward propagation of the MJO in many models. Moreover, the MJO variance in 13 of the 14 models does not come from a pronounced spectral peak, but usually is associated with an overreddened spectrum, which in turn is associated with a too strong persistence of equatorial precipitation. The two models that arguably do best at simulating the MJO are the only ones having convective closures/triggers linked in some way to moisture convergence

Observing convective aggregation

Convective self-aggregation, the spontaneous organization of initially scattered convection into isolated convective clusters despite spatially homogeneous boundary conditions and forcing, was first recognized and studied in idealized numerical simulations. While there is a rich history of observational work on convective clustering and organization, there have been only a few studies that have analyzed observations to look specifically for processes related to self-aggregation in models. Here we review observational work in both of these categories and motivate the need for more of this work. We acknowledge that self-aggregation may appear to be far-removed from observed convective organization in terms of time scales, initial conditions, initiation processes, and mean state extremes, but we argue that these differences vary greatly across the diverse range of model simulations in the literature and that these comparisons are already offering important insights into real tropical phenomena. Some preliminary new findings are presented, including results showing that a self-aggregation simulation with square geometry has too broad a distribution of humidity and is too dry in the driest regions when compared with radiosonde records from Nauru, while an elongated channel simulation has realistic representations of atmospheric humidity and its variability. We discuss recent work increasing our understanding of how organized convection and climate change may interact, and how model discrepancies related to this question are prompting interest in observational comparisons. We also propose possible future directions for observational work related to convective aggregation, including novel satellite approaches and a ground-based observational network

The role of convectively coupled equatorial Rossby waves in the West African monsoon

International audienceThe intra-seasonal scale variability of rainfall and convection in the African monsoon has been investigated in the recent past years, highlighting the importance of 10-30-day periodicities in rainfall and convective activity over West and Central Africa during the summer. Two independent modes of variability have been detected in the 10-30-day range. One of these two modes, called here the Sahelian mode, is characterized by a westward propagative envelop of convection from eastern Africa to the western tropical Atlantic, associated with a cyclonic circulation ahead of this envelop contributing to enhanced moisture advection and increased convection. In this study we have investigated the relationships between this mode and the occurrence of convectively coupled equatorial Rossby (ER) waves during northern summer. The ER signal has been extracted from the NOAA OLR data by filtering within a box delineated by the dispersion curves of the theoretical ER waves following the Wheeler and Kiladis (1999) techniques. The main EOF mode of the 10-30-day part of this ER signal has been computed and projected onto the unfiltered OLR and atmospheric fields. It displays over sub-Saharan Africa a pattern very similar to the theoretical ER, then demonstrating the occurrence of such wave within the African summer monsoon. This pattern shows a high similarity with the pattern related to the Sahelian mode but also some differences on its southern part. The correlation between the time variation of these two signals is higher than +0.6, meaning that the Sahelian mode can be partly explained by the occurrence of ER waves