Representation of the Madden–Julian Oscillation in CAMS-CSM

The Madden–Julian Oscillation(MJO) has a significant impact on global weather and climate and can be used as a predictability resource in extended-term forecasting. We evaluate the ability of the Chinese Academy of Meteorological Sciences Climate System Model(CAMS-CSM) to represent the MJO by using the diagnostic method proposed by the US Climate Variability and Predictability Program(CLIVAR) MJO Working Group(MJOWG). In general,the model simulates some major characteristics of MJO well, such as the seasonality characteristics and geographical dependence, the intensity of intraseasonal variability(ISV), dominant periodicity, propagation characteristics, coherence between outgoing longwave radiation(OLR) and wind, and life cycle of MJO signals. However, there are a few biases in the model when compared with observational/reanalyzed data. These include an overestimate of precipitation in the convergence zone of the North and South Pacific, a slightly weaker eastward propagation, and a shift in the dominant periodicity toward lower frequencies with slower speeds of eastward propagation. The model gives a poor simulation of the northward propagation of MJO in summer and shows less coherence between the MJO convection and wind. The role of moistening in the planetary boundary layer(PBL) in the eastward/northward propagation of MJO was also explored. An accurate representation of the vertical titling structure of moisture anomalies in CAMS-CSM leads to moistening of the PBL ahead of convection, which accounts for the eastward/northward propagation of MJO. Poor simulation of the vertical structure of the wind and moisture anomalies in the western Pacific leads to a poor simulation of the northward propagation of MJO in this area. Budget analysis of the PBL integral moisture anomalies shows that the model gives a good simulation of the moisture charging process ahead of MJO convection and that the zonal advection of moisture convergence term has a primary role in the detour of MJO over the Maritime Continent.     

Arctic sea ice and the Madden–Julian Oscillation (MJO)

Arctic sea ice responds to atmospheric forcing in primarily a top-down manner, whereby near-surface air circulation and temperature govern motion, formation, melting, and accretion. As a result, concentrations of sea ice vary with phases of many of the major modes of atmospheric variability, including the North Atlantic Oscillation, the Arctic Oscillation, and the El Niño-Southern Oscillation. However, until this present study, variability of sea ice by phase of the leading mode of atmospheric intraseasonal variability, the Madden–Julian Oscillation (MJO), which has been found to modify Arctic circulation and temperature, remained largely unstudied. Anomalies in daily change in sea ice concentration were isolated for all phases of the real-time multivariate MJO index during both summer (May–July) and winter (November–January) months. The three principal findings of the current study were as follows. (1) The MJO projects onto the Arctic atmosphere, as evidenced by statistically significant wavy patterns and consistent anomaly sign changes in composites of surface and mid-tropospheric atmospheric fields. (2) The MJO modulates Arctic sea ice in both summer and winter seasons, with the region of greatest variability shifting with the migration of the ice margin poleward (equatorward) during the summer (winter) period. Active regions of coherent ice concentration variability were identified in the Atlantic sector on days when the MJO was in phases 4 and 7 and the Pacific sector on days when the MJO was in phases 2 and 6, all supported by corresponding anomalies in surface wind and temperature. During July, similar variability in sea ice concentration was found in the North Atlantic sector during MJO phases 2 and 6 and Siberian sector during MJO phases 1 and 5, also supported by corresponding anomalies in surface wind. (3) The MJO modulates Arctic sea ice regionally, often resulting in dipole-shaped patterns of variability between anomaly centers. These results provide an important first look at intraseasonal variability of sea ice in the Arctic.     

The interannual variability of the Madden–Julian Oscillation in an ensemble of GCM simulations

The interannual variability of the Madden– Julian Oscillation (MJO) is investigated in an ensemble of 15 experiments performed with the ECHAM4 T30 general circulation model (GCM). The model experiments have been performed with AMIP conditions from January 1979 to December 1993. The MJO signal has been identified applying a principal oscillation pattern (POP) analysis to the 200-mb tropical velocity potential. The results obtained from the model ensemble are compared with 15?y of ECMWF re-analysis and OLR observations. The results suggest that the warm and cold phases of El Niño have some influence on the spatial propagation of the oscillation. Both in the re-analysis and in the model ensemble, the results indicate that during La Niña conditions the MJO is mostly confined west of the date line, with the largest activity located over the Indian Ocean and the western Pacific. In warm El Niño conditions, the convective anomalies associated with the oscillation appear to penetrate farther into the central Pacific. These changes in the MJO convective forcing seem to affect the zonal mean of the rotational component of the flow anomaly, which tends to weaken during warm El Niño periods. Some weak reproducibility of the interannual variability of the MJO activity is found. The results obtained from four-member and eight-member subsamples of the ensemble indicate that the reproducibility of the interannual behaviour of the MJO can be detected by choosing an ensemble of a larger size. Corresponding to the emergence of reproducibility with the increasing size of the sample, the correlation between the MJO activity and the Niño-3 SST anomaly appears to in-tensify.     

Madden–Julian Oscillation simulated in BCC climate models

This study evaluates the ability of four versions BCC (Beijing Climate Center or National Climate Center) models (BCC_AGCM2.1, BCC_AGCM2.2, BCC_CSM1.1 and BCC_CSM1.1m) in simulating the MJO phenomenon using the outputs of the AMIP (Atmospheric Model Intercomparison Project) and historical runs. In general, the models can simulate some major characteristics of the MJO, such as the intensity, the periodicity, the propagation, and the temporal/spatial evolution of the MJO signals in the tropics. There are still some biases between the models and the observation/reanalysis data, such as the overestimated total intraseasonal variability, but underestimated MJO intensity, shorter significant periodicity, and excessive westward propagation. The differences in the ability of simulating the MJO between AMIP and historical experiments are also significant. Compared to the AMIP runs, the total intraseasonal variability is reduced and more realistic, however the ratio between the MJO and its westward counterpart decreases in the historical runs. This unrealistic simulation of the zonal propagation might have been associated with the greater mean precipitation over the Pacific and corresponded to the exaggeration of the South Pacific Convergence Zone structure in precipitation mean state. In contrast to the T42 versions, the improvement of model resolution demonstrate more elaborate topography, but the enhanced westward propagation signals over the Arabia Sea followed. The underestimated (overestimated) MJO variability over eastern Indian Ocean (Pacific) was assumed to be associated with the mean state. Three sets of sensitive experiments using BCC_CSM1.1m turn out to support this argument.     

The skill of atmospheric linear inverse models in hindcasting the Madden–Julian Oscillation

A suite of statistical atmosphere-only linear inverse models of varying complexity are used to hindcast recent MJO events from the Year of Tropical Convection and the Cooperative Indian Ocean Experiment on Intraseasonal Variability/Dynamics of the Madden–Julian Oscillation mission periods, as well as over the 2000–2009 time period. Skill exists for over two weeks, competitive with the skill of some numerical models in both bivariate correlation and root-mean-squared-error scores during both observational mission periods. Skill is higher during mature Madden–Julian Oscillation conditions, as opposed to during growth phases, suggesting that growth dynamics may be more complex or non-linear since they are not as well captured by a linear model. There is little prediction skill gained by including non-leading modes of variability.     

Modulation of tropical ocean surface chlorophyll by the Madden–Julian Oscillation

The MJO modulation of sea surface chlorophyll-a (Chl) examined initially by Waliser et al. in Geophys Res Lett, (2005) is revisited with a significantly longer time-series of observations and a more systematic approach to characterizing the possible mechanisms underlying the MJO-Chl relationships. The MJO composite analysis of Chl and lead-lag correlations between Chl and other physical variables reveal regional variability of Chl and corresponding indicative temporal relationships among variables. Along the path of the MJO convection, wind speed—a proxy for oceanic vertical turbulent mixing and corresponding entrainment—is most strongly correlated with Chl when wind leads Chl by a few days. Composite Chl also displays MJO influences away from the path of the MJO convection. The role of wind speed in those regions is generally the same for Chl variability as that along the path of the MJO convection, although Ekman pumping also plays a role in generating Chl variability in limited regions. However, the wind forcing away from the MJO convection path is less coherent, rendering the temporal link relatively weak. Lastly, the potential for bio-physical feedbacks at the MJO time-scale is examined. The correlation analysis provides tantalizing evidence for local bio-feedbacks to the physical MJO system. Plausible hypothesis for Chl to amplify the MJO phase transition is presented though it cannot be affirmed in this study and will be examined and reported in a future modeling study.     

Influence of Springtime Atlantic SST on ENSO: Role of the Madden–Julian Oscillation

Increased evidence has shown the important role of Atlantic sea surface temperature (SST) in modulating the El Niño–Southern Oscillation (ENSO). Persistent anomalies of summer Madden–Julian Oscillation (MJO) act to link the Atlantic SST anomalies (SSTAs) to ENSO. The Atlantic SSTAs are strongly correlated with the persistent anomalies of summer MJO, and possibly affect MJO in two major ways. One is that an anomalous cyclonic (anticyclonic) circulation appears over the tropical Atlantic Ocean associated with positive (negative) SSTA in spring, and it intensifies (weakens) the Walker circulation. Equatorial updraft anomaly then appears over the Indian Ocean and the eastern Pacific Ocean, intensifying MJO activity over these regions. The other involves a high pressure (low pressure) anomaly associated with the North Atlantic SSTA tripole pattern that is transmitted to the mid- and low-latitudes by a circumglobal teleconnection pattern, leading to strong (weak) convective activity of MJO over the Indian Ocean. The above results offer new viewpoints about the process from springtime Atlantic SSTA signals to summertime atmospheric oscillation, and then to the MJO of tropical atmosphere affecting wintertime Pacific ENSO events, which connects different oceans.     

Evaluation of the Madden–Julian oscillation in HiRAM

The aim of this study was to understand the cause of Madden–Julian oscillation (MJO) bias in the High Resolution Atmospheric Model (HiRAM) driven by observed SST through process-oriented diagnosis. Wavenumber-frequency power spectrum and composite analyses indicate that HiRAM underestimates the spectral amplitude over the MJO band and mainly produces non-propagating rather than eastward-propagating intraseasonal rainfall anomalies, as observed. Column-integrated moist static energy (MSE) budget analysis is conducted to understand the MJO propagation bias in the simulation. It is found that the bias is due to the lack of a zonally asymmetric distribution of the MSE tendency anomaly in respect to the MJO convective center, which is mainly attributable to the bias in vertical MSE advection and surface turbulent flux. Further analysis suggests that it is the unrealistic simulation of MJO vertical circulation anomalies in the upper troposphere as well as overestimation of the Rossby wave response that results in the bias.摘要本研究评估了高分辨率大气环流模式HiRAM模拟的MJO. 结果表明, HiRAM模拟的MJO东传很弱. 我们通过计算整层积分的湿静力能 (MSE) 收支来诊断MJO东传模拟偏差的原因. 结果发现, MSE倾向相对于MJO对流中心的纬向非对称分布很弱是导致东传模拟偏弱的原因, 这主要是由MSE垂直平流和地表湍流通量的模拟偏差造成的. 进一步研究表明, 对流层上层MJO垂直环流结构的模拟偏差和MJO对流西侧的Rossby波环流偏强共同导致了模式的偏差. 本研究中指出的MJO传播模拟偏差的原因与之前基于多模式结果的结论不同, 这意味着要想了解特定模式的模拟偏差, 有必要对该模式进行具体分析.     

The influence of Madden–Julian Oscillation in the genesis of North Indian Ocean tropical cyclones

Cyclonic storms having maximum winds of 34 knots and above that had genesis in north Indian Ocean have been studied with respect to the eastward passage of Madden–Julian Oscillation (MJO). In the three decades (1979–2008), there were a total of 118 cyclones reported in which 96 formed in the region chosen (0–15^oN, 60^oE–100^oE) for the study. Although the percentage of MJO days inducing cyclogenesis is small, it is found that tropical cyclone genesis preferentially occurred during the convective phase of MJO. This accounted for 44 cyclones of the total 54 cyclones (i.e., 81.5%) formed under MJO amplitude 1 and above. The study has shown that, when the enhanced convection of MJO is over the maritime continent and the adjoining eastern Indian Ocean, it creates the highest favorable environment for cyclogenesis in the Bay of Bengal. During this phase, westerlies at 850 hPa are strong in the equatorial region south of Bay of Bengal creating strong cyclonic vorticity in the lower troposphere along with the low vertical wind shear.     

Satellite Measurements of the Madden–Julian Oscillation in Wintertime Stratospheric Ozone over the Tibetan Plateau and East Asia

We investigate the Madden–Julian Oscillation(MJO) signal in wintertime stratospheric ozone over the Tibetan Plateau and East Asia using the harmonized dataset of satellite ozone profiles. Two different MJO indices — the all-season Real-Time multivariate MJO index(RMM) and outgoing longwave radiation-based MJO index(OMI) — are used to compare the MJOrelated ozone anomalies. The results show that there are pronounced eastward-propagating MJO-related stratospheric ozone anomalies(mainly within 20–200 h Pa) over the subtropics. The negative stratospheric ozone anomalies are over the Tibetan Plateau and East Asia in MJO phases 4–7, when MJO-related tropical deep convective anomalies move from the equatorial Indian Ocean towards the western Pacific Ocean. Compared with the results based on RMM, the MJO-related stratospheric column ozone anomalies based on OMI are stronger and one phase ahead. Further analysis suggests that different sampling errors, observation principles and retrieval algorithms may be responsible for the discrepancies among different satellite measurements. The MJO-related stratospheric ozone anomalies can be attributed to the MJO-related circulation anomalies,i.e., the uplifted tropopause and the northward shifted westerly jet in the upper troposphere. Compared to the result based on RMM, the upper tropospheric westerly jet may play a less important role in generating the stratospheric column ozone anomalies based on OMI. Our study indicates that the circulation-based MJO index(RMM) can better characterize the MJOrelated anomalies in tropopause pressure and thus the MJO influence on atmospheric trace gases in the upper troposphere and lower stratosphere, especially over subtropical East Asia.     

The Madden–Julian oscillation wind-convection coupling and the role of moisture processes in the MM5 model

The Madden–Julian oscillation (MJO) produced by a mesoscale model is investigated using standardized statistical diagnostics. Results show that upper- and lower-level zonal winds display the correct MJO structure, phase speed (8 m s^?1) and space–time power spectrum. However, the simulated free atmosphere moisture, outgoing longwave radiation and precipitation do not exhibit any clear MJO signal. Yet, the boundary layer moisture, moist static energy and atmospheric instability, measured using a moist static energy instability index, have clear MJO signals. A significant finding is the ability of the model to simulate a realistic MJO phase speed in the winds without reproducing the MJO wind-convection coupling or a realistic propagation in the free atmosphere water vapor. This study suggests that the convergence of boundary layer moisture and the discharge and recharge of the moist static energy and atmospheric instability may be responsible for controlling the speed of propagation of the MJO circulation.     

On the interannual variability of arctic sea‐level pressure and sea ice

Abstract

Monthly mean sea‐level pressure (SLP) data from the Northern Hemisphere for the period January 1952‐December 1987 are analysed. Fluctuations in this field over the Arctic on interannual time‐scales and their statistical association with fluctuations farther south are determined. The standard deviation of the interannual variability is largest compared with that of the annual cycle along the seaboards of the major land masses. The SLP anomalies are generally in phase over the entire Arctic Basin and extend south over the northern Russia and Canada, but tend to be out of phase with fluctuations at mid‐latitudes. The anomalies are most closely associated with fluctuations over the North Atlantic and Europe except near the Chukchi Sea to the north of Bering Strait. The associations with the North Pacific fluctuations become increasingly more prominent at most Arctic sites (e.g. the Canadian Arctic Archipelago) as the time‐scale increases.

Associations between the SLP fluctuations and atmospheric indices that represent processes affecting sea‐ice drift (wind stress and wind stress curl) are determined. In every case local associations dominate, but some remote ones are also evident. For example, changes in the magnitude of the wind stress curl over the Beaufort Sea are increased if the atmospheric circulation over the North Pacific is intensified; wind stress over the region where sea ice is exchanged between the Beaufort Gyre and the Transpolar Drift Stream is modulated by both the Southern and North Atlantic Oscillations.

Severe sea‐ice conditions in the Greenland Sea (as measured by the Koch Ice Index) coincide with a weakened atmospheric circulation over the North Atlantic.     

The self-organizing map,a new approach to apprehend the Madden–Julian Oscillation influence on the intraseasonal variability of rainfall in the southern African region

The Madden–Julian Oscillation (MJO) is the major mode of intraseasonal variability (30–60 days) in the tropics, having large rainfall impacts globally, and possibly on southern Africa. However, the latter impact is not well understood and needs to be further explored. The life cycle of the MJO, known to be asymmetric, has been nevertheless analyzed usually through methods constrained by both linearity and orthogonality, such as empirical orthogonal function analysis. Here we explore a non-linear classification method, the self-organizing map (SOM), a type of artificial neural network used to produce a low-dimensional representation of high-dimensional datasets, to capture more accurately the life cycle of the MJO and its global impacts. The classification is applied on intraseasonal anomalies of outgoing longwave radiation within the tropical region over the 1980–2009 period. Using the SOM to describe the MJO is a new approach, complimentary to the usual real-time multivariate MJO index. It efficiently captures this propagative phenomenon and its seasonality, and is shown to provide additional temporal and spatial information on MJO activity. For each node, the subtropical convection is analyzed, with a particular focus on the southern Africa region. Results show that the convection activity over the central tropical Indian Ocean is a key factor influencing the intraseasonal convective activity over the southern African region. Enhanced (suppressed) convection over the central Indian Ocean tends to suppress (enhance) convection over the southern African region with a 10-day lag by modulating the moisture transport.     

Different Impacts of Madden–Julian Oscillation on Winter Rainfall over Southern China

Winter rainfall over southern China is usually enhanced when Madden–Julian oscillation(MJO) is active over the Indian Ocean, but it can be weakened under certain conditions. Here, the diversity of MJO impacts on winter rainfall and its mechanisms are explored by using scenarios of enhanced and suppressed rainfall anomalies over southern China when MJO is active over the Indian Ocean. The combined effects of low-frequency background moisture and intraseasonal winds are the major contributors to the different rainfall anomalies. Anomalous circulation in mid–high latitudes, especially on intraseasonal timescales, is almost opposite in the two scenarios, which can modulate the response of extratropical atmosphere to MJO heating and then induces the different circulations over southern China. In the enhanced scenario, mid–high latitudes of Eurasia and southern China are dominated by positive and negative sea level pressure anomalies, respectively. The southerly over southern China and the South China Sea induced by MJO heating promotes the anomalous moisture convergence and ascending motion over southern China, resulting in the enhanced rainfall. In the suppressed scenario, however, the circulation in mid–high latitudes does not favor rainfall over southern China and leads to the northerly response to MJO heating over southern China, which enhances moisture divergence and weakens rainfall over southern China.     

Simulations of the Madden–Julian oscillation in four pairs of coupled and uncoupled global models

The status of the numerical reproduction of the Madden–Julian Oscillation (MJO) by current global models was assessed through diagnoses of four pairs of coupled and uncoupled simulations. Slow eastward propagation of the MJO, especially in low-level zonal wind, is realistic in all these simulations. However, the simulated MJO suffers from several common problems. The MJO signal in precipitation is generally too weak and often eroded by an unrealistic split of an equatorial maximum of precipitation into a double ITCZ structure over the western Pacific. The MJO signal in low-level zonal wind, on the other hand, is sometimes too strong over the eastern Pacific but too weak over the Indian Ocean. The observed phase relationship between precipitation and low-level zonal wind associated with the MJO in the western Pacific and their coherence in general are not reproduced by the models. The seasonal migration in latitude of MJO activity is missing in most simulations. Air–sea coupling generally strengthens the simulated eastward propagating signal, but its effects on the phase relationship and coherence between precipitation and low-level zonal wind, and on their geographic distributions, seasonal cycles, and interannual variability are inconsistent among the simulations. Such inconsistency cautions generalization of results from MJO simulations using a single model. In comparison to observations, biases in the simulated MJO appear to be related to biases in the background state of mean precipitation, low-level zonal wind, and boundary-layer moisture convergence. This study concludes that, while the realistic simulations of the eastward propagation of the MJO are encouraging, reproducing other fundamental features of the MJO by current global models remains an unmet challenge.

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