Stochastic simulations of the Madden�CJulian oscillation activity

The Madden?CJulian oscillation (MJO) is the most prominent form of tropical intraseasonal variability. This study investigated the following questions. Do interannual-to-decadal variations in tropical sea surface temperature (SST) lead to substantial changes in MJO activity? Was there a change in the MJO in the 1970s? Can this change be associated to SST anomalies? What was the level of MJO activity in the pre-reanalysis era? These questions were investigated with a stochastic model of the MJO. Reanalysis data (1948?C2008) were used to develop a nine-state first order Markov model capable to simulate the non-stationarity of the MJO. The model is driven by observed SST anomalies and a large ensemble of simulations was performed to infer the activity of the MJO in the instrumental period (1880?C2008). The model is capable to reproduce the activity of the MJO during the reanalysis period. The simulations indicate that the MJO exhibited a regime of near normal activity in 1948?C1972 (3.4?events?year^?1) and two regimes of high activity in 1973?C1989 (3.9 events) and 1990?C2008 (4.6 events). Stochastic simulations indicate decadal shifts with near normal levels in 1880?C1895 (3.4 events), low activity in 1896?C1917 (2.6 events) and a return to near normal levels during 1918?C1947 (3.3 events). The results also point out to significant decadal changes in probabilities of very active years (5 or more MJO events): 0.214 (1880?C1895), 0.076 (1896?C1917), 0.197 (1918?C1947) and 0.193 (1948?C1972). After a change in behavior in the 1970s, this probability has increased to 0.329 (1973?C1989) and 0.510 (1990?C2008). The observational and stochastic simulations presented here call attention to the need to further understand the variability of the MJO on a wide range of time scales.     

Processes controlling the surface temperature signature of the Madden�CJulian Oscillation in the thermocline ridge of the Indian Ocean

During boreal winter, there is a prominent maximum of intraseasonal sea-surface temperature (SST) variability associated with the Madden?CJulian Oscillation (MJO) along a Thermocline Ridge located in the southwestern Indian Ocean (5°S?C10°S, 60°E?C90°E; TRIO region). There is an ongoing debate about the relative importance of air-sea heat fluxes and oceanic processes in driving this intraseasonal SST variability. Furthermore, various studies have suggested that interannual variability of the oceanic structure in the TRIO region could modulate the amplitude of the MJO-driven SST response. In this study, we use observations and ocean general circulation model (OGCM) experiments to quantify these two effects over the 1997?C2006 period. Observational analysis indicates that Ekman pumping does not contribute significantly (on average) to intraseasonal SST variability. It is, however, difficult to quantify the relative contribution of net heat fluxes and entrainment to SST intraseasonal variability from observations alone. We therefore use a suite of OGCM experiments to isolate the impacts of each process. During 1997?C2006, wind stress contributed on average only about 20% of the intraseasonal SST variability (averaged over the TRIO region), while heat fluxes contributed about 70%, with forcing by shortwave radiation (75%) dominating the other flux components (25%). This estimate is consistent with an independent air-sea flux product, which indicates that shortwave radiation contributes 68% of intraseasonal heat flux variability. The time scale of the heat-flux perturbation, in addition to its amplitude, is also important in controlling the intraseasonal SST signature, with longer periods favouring a larger response. There are also strong year-to-year variations in the respective role of heat fluxes and wind stress. Of the five strong cooling events identified in both observations and the model (two in 1999 and one in 2000, 2001 and 2002), intraseasonal-wind stress dominates the SST signature during 2001 and contributes significantly during 2000. Interannual variations of the subsurface thermal structure associated with the Indian Ocean Dipole or El Ni?o/La Ni?a events modulate the MJO-driven SST signature only moderately (by up to 30%), mainly by changing the temperature of water entrained into the mixed layer. The primary factor that controls year-to-year changes in the amplitude of TRIO, intraseasonal SST anomalies is hence the characteristics of intraseasonal surface flux perturbations, rather than changes in the underlying oceanic state.     

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.     

Analysis of rainfall characteristics of the Madden–Julian oscillation using TRMM satellite data

Rainfall characteristics of the Madden–Julian oscillation (MJO) are analyzed primarily using tropical rainfall measuring mission (TRMM) precipitation radar (PR), TRMM microwave imager (TMI) and lighting imaging sensor (LIS) data. Latent heating structure is also examined using latent heating data estimated with the spectral latent heating (SLH) algorithm.The zonal structure, time evolution, and characteristic stages of the MJO precipitation system are described. Stratiform rain fraction increases with the cloud activity, and the amplitude of stratiform rain variation associated with the MJO is larger than that of convective rain by a factor of 1.7. Maximum peaks of both convective rain and stratiform rain precede the minimum peak of the outgoing longwave radiation (OLR) anomaly which is often used as a proxy for the MJO convection. Stratiform rain remains longer than convective rain until ∼4000 km behind the peak of the mature phase. The stratiform rain contribution results in the top-heavy heating profile of the MJO.Associated with the MJO, there are tri-pole convective rain top heights (RTH) at 10–11, ∼7 and ∼3 km, corresponding to the dominance of afternoon showers, organized systems, and shallow convections, respectively. The stratiform rain is basically organized with convective rain, having similar but slightly lower RTH and slightly lags the convective rain maximum. It is notable that relatively moderate (∼7 km) RTH is dominant in the mature phase of the MJO, while very tall rainfall with RTH over 10 km and lightning frequency increase in the suppressed phase. The rain-yield-per flash (RPF) varies about 20–100% of the mean value of ∼2–10 × 10⁹ kg fl⁻¹ over the tropical warm ocean and that of ∼2–5 × 10⁹ kg fl⁻¹ over the equatorial Islands, between the convectively suppressed phase and the active phase of MJO, in the manner that RPF is smaller in the suppressed phase and larger in the active phase.     

Critical roles of convective momentum transfer in sustaining the multi-scale Madden–Julian oscillation

To understand the nature and role of multi-scale interaction involved in the Madden–Julian oscillation (MJO), a dynamical model is built based on two essential processes: the convective complex of the MJO modulates the strength and location of synoptic-scale motions, which in turn feed back to the MJO through the convective momentum transfer (CMT). Our results exhibit that: (1) The lower tropospheric easterly CMT coming from the 2-day waves slows down the MJO dramatically; (2) although the lower tropospheric westerly CMT coming from the superclusters can produce the horizontal quadrupole vortex and vertical westerly wind-burst structures of the MJO, it drives the large-scale motions to propagate eastward too fast; (3) the planetary boundary layer provides an instability source for the MJO and pulls the MJO to propagate eastward at a speed of 0～10?ms^?1; and (4) the optimal structure of the multi-scale MJO should be: the stronger superclusters/2-day waves prevail in the rear/front part of the MJO and produce lower tropospheric westerly/easterly CMT there. These theoretical results emphasize the role of CMT and encourage further observations in the multi-scale MJO.     

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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Mean dynamical characteristics of the Asian summer monsoon with a global analysis — Forecast system

Summary The dynamical characteristics of Asian summer monsoon are examined with a global spectral model. In addition to the seasonal circulation features, the large scale budgets of kinetic energy, vorticity and angular momentum are examined making use of mean analysis and forecast fields (upto day 5) for summer season comprising June, July and August, (JJA) 1994. Apart from elucidating the systematic errors over the monsoon region, the study expounded the influence of these errors on associated dynamics.The significant errors in the low level flow (850 hPa) evince (i) weakening of south easterly trades and cross equatorial flow into the Northern Hemisphere and (ii) weakening of westerly flow over the North Indian Ocean. Similarly, in the upper level flow (200 hPa) they indicate (i) weakening of Tibetan anti-cyclone and (ii) reduction of return flow into the Southern Hemisphere.The balance requirements in the mean analysis as well as forecast fields are fairly in agreement with the observed over the summer monsoon. The monsoon domain is discerned as the source region of kinetic energy and vorticity. Both are produced in the monsoon region and transported horizontally across. The model forecasts fail to retain the analyzed atmospheric variability in terms of mean as well as transient circulations which is revealed by kinetic energy budget. This is further corroborated by vorticity and angular momentum budgets. It is noticed that the forecasts in all ranges produce feeble monsoon circulation which weakens considerably with increase in the forecast period.With 16 Figures     

Ocean temperature and salinity components of the Madden–Julian oscillation observed by Argo floats

New diagnostics of the Madden–Julian oscillation (MJO) cycle in ocean temperature and, for the first time, salinity are presented. The MJO composites are based on 4 years of gridded Argo float data from 2003 to 2006, and extend from the surface to 1,400 m depth in the tropical Indian and Pacific Oceans. The MJO surface salinity anomalies are consistent with precipitation minus evaporation fluxes in the Indian Ocean, and with anomalous zonal advection in the Pacific. The Argo sea surface temperature and thermocline depth anomalies are consistent with previous studies using other data sets. The near-surface density changes due to salinity are comparable to, and partially offset, those due to temperature, emphasising the importance of including salinity as well as temperature changes in mixed-layer modelling of tropical intraseasonal processes. The MJO-forced equatorial Kelvin wave that propagates along the thermocline in the Pacific extends down into the deep ocean, to at least 1,400 m. Coherent, statistically significant, MJO temperature and salinity anomalies are also present in the deep Indian Ocean.     

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.     

Modulating synoptic scale convective activity and boundary layer dissipation in the IPESD models of the Madden–Julian oscillation

A self-contained derivation of the IPESD models [Majda, A.J., Klein, R., 2003. Systematic multi-scale models for the tropics. J. Atmos. Sci. 60, 393–408] governing synoptic and planetary scale tropical flows is provided. This derivation demonstrates the analytic tractability of the model and the effect of zonally and meridionally tilted synoptic scale heating on the forcing of planetary scale flows through upscale momentum and temperature fluxes. Exploiting the analytic tractability of the models, different aspects of the planetary scale forcing are traced to meridional and vertical tilts in the synoptic scale heating profile. Variants of the archetypal IPESD models for the Madden–Julian oscillation (MJO) presented in Majda and Biello [Majda, A.J., Biello, J.A., 2004. A multi-scale model for tropical intraseasonal oscillations. Proc. Natl. Acad. Sci. 101, 4736–4741; Biello, J.A., Majda, A.J., 2005. A new multi-scale model for the Madden–Julian oscillation. J. Atmos. Sci. 62, 1694–1721] are studied. In addition to vertically tilted synoptic scale heating, the models discussed herein incorporate upscale zonal momentum flux due to meridional flux convergence arising from meridionally tilted heating. The effect of a boundary layer momentum drag at the base of the free troposphere is also systematically incorporated into the IPESD models. Both meridional tilts and lower boundary layer drag are shown to meridionally confine the MJO westerly wind burst and drive a planetary scale barotropic flow. Meridionally tilted heating can also greatly strengthen the wind burst at the base of the troposphere and modify its vertical profile. The competing effects of meridionally tilted, and off-equatorial heating can also significantly weaken the MJO winds. Appendices are provided which discuss generalizations and a solution algorithm for the IPESD models.     

Spatial prediction of urban�Crural temperatures using statistical methods

Spatial information on climatic characteristics is beneficial in e.g. regional planning, building construction and urban ecology. The possibility to spatially predict urban?Crural temperatures with statistical techniques and small sample sizes was investigated in Turku, SW Finland. Temperature observations from 36 stationary weather stations over a period of 6?years were used in the analyses. Geographical information system (GIS) data on urban land use, hydrology and topography served as explanatory variables. The utilized statistical techniques were generalized linear model and boosted regression tree method. The results demonstrate that temperature variables can be robustly predicted with relatively small sample sizes (n????20?C40). The variability in the temperature data was explained satisfactorily with few accessible GIS variables. Statistically based spatial modelling provides a cost-efficient approach to predict temperature variables on a regional scale. Spatial modelling may aid also in gaining novel insights into the causes and impacts of temperature variability in extensive urbanized areas.     

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.     

Impacts of upscale heat and momentum transfer by moist Kelvin waves on the Madden–Julian oscillation: a theoretical model study

The Madden–Julian oscillation (MJO) is observed to interact with moist Kelvin waves. To understand the role of this interaction, a simple scale-interaction model is built, which describes the MJO modulation of moist Kelvin waves and the feedback from moist Kelvin waves through upscale eddy heat and momentum transfer. The backward-tilted moist Kelvin waves produce eddy momentum transfer (EMT) characterized by the lower-tropospheric westerly winds and eddy heat transfer (EHT) that warms the mid-troposphere. The EHT tends to induce the lower-tropospheric easterly winds and low pressure, which is located in front of the “westerly wind burst” induced by the EMT. Adding the eddy forcing to a neutral MJO skeleton model, we show that the EHT provides an instability source for the MJO by warming up the mid-troposphere, and the EMT offers an additional instability source by enhancing the lower-tropospheric westerly winds. The eddy forcing selects eastward propagation for the unstable mode, because it generates positive/negative eddy available potential energy for the eastward/westward modes by changing their thermal and dynamical structures. The present results show that moist Kelvin waves can provide a positive feedback to the MJO only when they are located within (or near) the convective complex (center) of the MJO. The EHT and EMT feedback works positively in the front and rear part of the MJO, respectively. These theoretical results suggest the potential importance of moist Kelvin waves in sustaining the MJO and encourage further observations to document the relationship between moist Kelvin waves and the MJO.     

Seasonal prediction of global sea level anomalies using an ocean–atmosphere dynamical model

Advanced warning of extreme sea level events is an invaluable tool for coastal communities, allowing the implementation of management policies and strategies to minimise loss of life and infrastructure damage. This study is an initial attempt to apply a dynamical coupled ocean–atmosphere model to the prediction of seasonal sea level anomalies (SLA) globally for up to 7 months in advance. We assess the ability of the Australian Bureau of Meteorology’s operational seasonal dynamical forecast system, the Predictive Ocean Atmosphere Model for Australia (POAMA), to predict seasonal SLA, using gridded satellite altimeter observation-based analyses over the period 1993–2010 and model reanalysis over 1981–2010. Hindcasts from POAMA are based on a 33-member ensemble of seasonal forecasts that are initialised once per month for the period 1981–2010. Our results show POAMA demonstrates high skill in the equatorial Pacific basin and consistently exhibits more skill globally than a forecast based on persistence. Model predictability estimates indicate there is scope for improvement in the higher latitudes and in the Atlantic and Southern Oceans. Most characteristics of the asymmetric SLA fields generated by El-Nino/La Nina events are well represented by POAMA, although the forecast amplitude weakens with increasing lead-time.     

Prediction of the Asian-Australian Monsoon Interannual Variations with the Grid-Point Atmospheric Model of IAP LASG （GAMIL）

Seasonal prediction of Asian-Australian monsoon （A-AM） precipitation is one of the most important and challenging tasks in climate prediction. In this paper, we evaluate the performance of Grid Atmospheric Model of IAP LASG （GAMIL） on retrospective prediction of the A-AM interannual variation （IAV）, and determine to what extent GAMIL can capture the two major observed modes of A-AM rainfall IAV for the period 1979-2003. The first mode is associated with the turnabout of warming （cooling） in the Nifio 3.4 region, whereas the second mode leads the warming/cooling by about one year, signaling precursory conditions for ENSO.
We show that the GAMIL one-month lead prediction of the seasonal precipitation anomalies is primarily able to capture major features of the two observed leading modes of the IAV, with the first mode better predicted than the second. It also depicts the relationship between the first mode and ENSO rather well. On the other hand, the GAMIL has deficiencies in capturing the relationship between the second mode and ENSO. We conclude： （1） successful reproduction of the E1 Nifio-excited monsoon-ocean interaction and E1 Nifio forcing may be critical for the seasonal prediction of the A-AM rainfall IAV with the GAMIL; （2） more efforts are needed to improve the simulation not only in the Nifio 3.4 region but also in the joining area of Asia and the Indian-Pacific Ocean; （3） the selection of a one-tier system may improve the ultimate prediction of the A-AM rainfall IAV. These results offer some references for improvement of the GAMIL and associated seasonal prediction skill.