ALBERT

Description: Organic Letters DOI: 10.1021/ol5004324

Description: This study documents the detailed characteristics of the tropical intraseasonal variability (TISV) in the MRI-20km60L AGCM that uses a variant of the Arakawa–Schubert cumulus parameterization. Mean states, power spectra, propagation features, leading EOF modes, horizontal and vertical structures, and seasonality associated with the TISV are analyzed. Results show that the model reproduces the mean states in winds realistically and in convection comparable to that of the observations. However, the simulated TISV is less realistic. It shows low amplitudes in convection and low-level winds in the 30–60-day band. Filtered anomalies have standing structures. Power spectra and lag correlation of the signals do not propagate dominantly either in the eastward direction during boreal winter or in the northward direction during boreal summer. A combined EOF (CEOF) analysis shows that winds and convection have a loose coupling that cannot sustain the simulated TISV as realistically as that observed. In the composited mature phase of the simulated MJO, the low-level convergence does not lead convection clearly so that the moisture anomalies do not tilt westward in the vertical, indicating that the low-level convergence does not favor the eastward propagation. The less realistic TISV suggests that the representation of cumulus convection needs to be improved in this model.

Description: The quasi-biweekly oscillation (QBW: here defined as a 12–20-day oscillation) is one of the major systems that affect tropical and subtropical weather and seasonal mean climate. However, knowledge is limited concerning its temporal and spatial structures and dynamics, particularly in a global perspective. To advance understanding of the QBW, its life cycle is documented using a tracking method and extended EOF analysis. Both methods yield consistent results. The analyses reveal a wide variety of QBW activity in terms of initiation, movement, development, and dissipation. The convective anomalies associated with the QBW are predominant in the latitude bands between 10° and 30° in both hemispheres. The QBW modes tend to occur regionally and be associated with monsoons. Three boreal summer modes are identified in the Asia–Pacific, Central America, and subtropical South Pacific regions. Five austral summer modes are identified in the Australia–southwest Pacific, South Africa–Indian Ocean, South America–Atlantic, subtropical North Pacific, and North Atlantic–North Africa regions. The QBW modes are classified into two categories: westward- and eastward-propagating modes. The westward mode is found in the Asia–Pacific and Central America regions during boreal summer; it originates in the tropics and dissipates in the subtropics. The behavior of the westward-propagating mode can be understood in terms of equatorial Rossby waves in the presence of monsoon mean flow and convective coupling. The eastward-propagating mode, on the other hand, connects with upstream extratropical Rossby wave trains and propagates primarily eastward and equatorward. Barotropic Rossby wave trains play an essential role in controlling initiation, development, and propagation of the eastward QBW mode in the subtropics. The results therefore suggest that not only tropical but also extratropical dynamics are required for fully understanding the behavior of the QBW systems worldwide. The new conceptual picture of QBW obtained here based on long-term observation provides valuable information on the behavior of QBW systems in a global perspective, which is important for a thorough understanding of tropical variability on a time scale between day-to-day weather and the Madden–Julian oscillation.

Description: Diurnal variations of the global tropical precipitation are documented by using two complementary Tropical Rainfall Measuring Mission (TRMM) datasets (3B42 and 3G68) for 1998–2006 in an attempt to provide a unified view of the diurnal cycle and a metric for evaluating numerical model performance. The 3B42 data have better spatial coverage; the 3G68 data offer more accurate diurnal phase information. The first and second empirical orthogonal function (EOF) modes represent the diurnal cycle and account for 89% of the total variance in 3B42. The third and fourth EOF modes, which account for 10% of the total variance, represent the semidiurnal cycle. Both datasets yield consistent spatial structures and temporal evolution, but they have different advantages: the patterns derived from 3B42 exhibit less noise, while 3G68 yields an arguably more accurate diurnal phase. The diurnal phase derived from 3G68 systematically leads 3B42 by about 3 h. Three tropical diurnal cycle regimes (oceanic, continental, and coastal) are identified according to the amplitude, peak time, and phase propagation characteristics of the diurnal precipitation. The oceanic regime is characterized by moderate amplitude and an early morning peak [0600–0900 Local Solar Time (LST)], found primarily in the oceanic convergence zones in the Pacific, Atlantic, and Indian Oceans. In contrast, the continental regime features a large amplitude and an afternoon peak (1500–1800 LST), which is particularly pronounced in South America and equatorial Africa near Lake Victoria. Both the oceanic and continental regimes show little spatial phase propagation. The coastal regime, however, shows not only large amplitude but also prominent phase propagation. Two subregimes can also be recognized, often concurring along the same land–sea boundary. The seaside coastal regime is characterized by offshore phase propagation, with peaks occurring from late evening to noon of the next day (2100–1200 LST), whereas the landside coastal regime has landward phase propagation with peaks occurring from noon to evening (1200–2100 LST). The coastal regime is prominent along the land–sea boundaries of the Maritime Continent, the Indian subcontinent, northern Australia, the west coast of America extending from Mexico to Ecuador, the west coast of equatorial Africa, and Northeast Brazil. Note that the amplitude of the diurnal cycle is dependent on season, but the diurnal phase characteristics are not. The underlying mechanism suggested by this analysis, especially over the coastal areas, is also discussed.

Description: Meteorological and geophysical phenomena involve multiple-scale processes. Here the spatiotemporal wavelet transform (STWT) is applied to detect significant, nonstationary, wave propagation signals from a time–space domain. One of the major advantages of the STWT is the capability to localize the wave properties in both space and time, which facilitates the study of interactions among multiple-scale disturbances by providing relevant information about energy concentration at a given time and space. The global wavelet spectrum (scalogram) of the STWT, which gives an integrated view of the spectrum as wavenumber and frequency, provides a lucid picture of the spectral power distribution that is consistent with the result obtained from the Fourier-based space–time power spectrum. The STWT has also the capability of reconstruction and thus can be used as a spatiotemporal wave filter. The STWT analysis is applied to analyze the multiscale structure of the Madden–Julian oscillation (MJO) studied by Nakazawa. All types of convectively coupled equatorial waves were identified. The analysis results reveal the structural differences between the MJO and Kelvin waves and their different relationships with the embedded westward propagating inertio-gravity (WIG) waves: for the Kelvin wave the enhanced activity of the WIG waves coincides with the most active convective area, whereas for the MJO the enhanced WIG waves occur to the east of the MJO convective center. In addition, the WIG waves in the MJO have shorter wavelengths and periods, but those in the Kelvin waves have longer wavelengths and periods. This difference may hold a key to understanding the propagation speed difference between the MJO and Kelvin waves. The possible “upscale feedback” of the WIG waves on the MJO and Kelvin waves is also discussed.

Description: Convective initiation processes in the Madden–Julian oscillation (MJO) events that occurred during the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY2011)/Dynamics of the Madden–Julian Oscillation (DYNAMO) intensive observation period (IOP) were investigated. Two episodes that were initiated in mid-October (MJO1) and mid-November (MJO2) 2011 were analyzed using European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and satellite data. Moisture budgets in the equatorial Indian Ocean (IO) domain (10°S–10°N, 60°–90°E) were analyzed in detail by separating each variable into basic-state (〉80 day), intraseasonal (20–80 day), and high-frequency (

Description: Two univariate indices of the Madden–Julian oscillation (MJO) based on outgoing longwave radiation (OLR) are developed to track the convective component of the MJO while taking into account the seasonal cycle. These are compared with the all-season Real-time Multivariate MJO (RMM) index of Wheeler and Hendon derived from a multivariate EOF of circulation and OLR. The gross features of the OLR and circulation of composite MJOs are similar regardless of the index, although RMM is characterized by stronger circulation. Diversity in the amplitude and phase of individual MJO events between the indices is much more evident; this is demonstrated using examples from the Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign and the Year of Tropical Convection (YOTC) virtual campaign. The use of different indices can lead to quite disparate conclusions concerning MJO timing and strength, and even as to whether or not an MJO has occurred. A disadvantage of using daily OLR as an EOF basis is that it is a much noisier field than the large-scale circulation, and filtering is necessary to obtain stable results through the annual cycle. While a drawback of filtering is that it cannot be done in real time, a reasonable approximation to the original fully filtered index can be obtained by following an endpoint smoothing method. When the convective signal is of primary interest, the authors advocate the use of satellite-based metrics for retrospective analysis of the MJO for individual cases, as well as for the analysis of model skill in initiating and evolving the MJO.

Description: Previous observational analysis and modeling studies indicate that air–sea coupling plays an essential role in improving MJO simulations and extending MJO forecasting skills. However, whether the SST feedback plays an indispensable role for the existence of the MJO remains controversial, and the precise physical processes through which the SST feedback may lead to better MJO simulations and forecasts remain elusive. The DYNAMO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY) field campaign recently completed over the Indian Ocean reveals a new perspective and provides better data to improve understanding of the MJO. It is found that among the five MJO events that occurred during the DYNAMO/CINDY field campaign, only two MJO events (the November and March ones) have robust SST anomalies associated with them. For the other three MJO events (the October, December, and January ones), no coherent SST anomalies are observed. This observational scenario suggests that the roles of air–sea coupling on the MJO vary greatly from event to event. To elucidate the varying roles of air–sea coupling on different MJO events, a suite of hindcast experiments was conducted with a particular focus on the October and November MJO events. The numerical results confirm that the October MJO is largely controlled by atmospheric internal dynamics, while the November MJO is strongly coupled with underlying ocean. For the November MJO event, the positive SST anomalies significantly improve MJO forecasting by enhancing the response of a Kelvin–Rossby wave couplet, which prolongs the feedback between convection and large-scale circulations, and thus favors the development of stratiform rainfall, in turn, facilitating the production of eddy available potential energy and significantly amplifying the intensity of the model November MJO.

Description: Observational studies have shown that, on average, the quasi-biennial oscillation (QBO) exhibits a faster phase progression and shorter period during El Niño than during La Niña. Here, the possible mechanism of QBO modulation associated with ENSO is investigated using the MIROC-AGCM with T106 (~1.125°) horizontal resolution. The MIROC-AGCM simulates QBO-like oscillations without any nonorographic gravity wave parameterizations. A 100-yr integration was conducted during which annually repeating sea surface temperatures based on the composite observed El Niño conditions were imposed. A similar 100-yr La Niña integration was also conducted. The MIROC-AGCM simulates realistic differences between El Niño and La Niña, notably shorter QBO periods, a weaker Walker circulation, and more equatorial precipitation during El Niño than during La Niña. Near the equator, vertical wave fluxes of zonal momentum in the uppermost troposphere are larger and the stratospheric QBO forcing due to interaction of the mean flow with resolved gravity waves (particularly for zonal wavenumber ≥43) is much larger during El Niño. The tropical upwelling associated with the Brewer–Dobson circulation is also stronger in the El Niño simulation. The effects of the enhanced tropical upwelling during El Niño are evidently overcome by enhanced wave driving, resulting in the shorter QBO period. The integrations were repeated with another model version (MIROC-ECM with T42 horizontal resolution) that employs a parameterization of nonorographic gravity waves in order to simulate a QBO. In the MIROC-ECM the average QBO periods are nearly identical in the El Niño and La Niña simulations.