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1. Introduction The Madden–Julian oscillation (MJO; Madden and Julian 1972 ) is a dominant feature in the tropical ocean–atmosphere, linking weather and climate variability. Theories and observational characteristics of MJO and its influence on tropical cyclones, midlatitude weather, monsoon variability, air–sea interaction, relationships with atmospheric angular momentum and El Niño, and predictability have been reported in a large number of previous studies. [See Lau and Waliser (2005) for
1. Introduction The Madden–Julian oscillation (MJO; Madden and Julian 1972 ) is a dominant feature in the tropical ocean–atmosphere, linking weather and climate variability. Theories and observational characteristics of MJO and its influence on tropical cyclones, midlatitude weather, monsoon variability, air–sea interaction, relationships with atmospheric angular momentum and El Niño, and predictability have been reported in a large number of previous studies. [See Lau and Waliser (2005) for
and Tiwi Islands subdomains shown by dashed lines in Fig. 1 ) since those systems occupied only small regions of the experiment domain as will be shown in the next section. Both continental/coastal and island systems were mainly driven by sea breezes, but the continental coastal systems were also influenced by several squall lines crossing Darwin in the evening and early morning during TWP-ICE. Therefore, it would be interesting to examine similarities and differences in the structural
and Tiwi Islands subdomains shown by dashed lines in Fig. 1 ) since those systems occupied only small regions of the experiment domain as will be shown in the next section. Both continental/coastal and island systems were mainly driven by sea breezes, but the continental coastal systems were also influenced by several squall lines crossing Darwin in the evening and early morning during TWP-ICE. Therefore, it would be interesting to examine similarities and differences in the structural
) showed that the horizontal variation of the vertical distribution of heating, calculated from TRMM PR observations using a simple method, is also very important in simulating the large-scale tropical circulation correctly. During the past four decades, cloud-resolving models (CRMs) have advanced sufficiently to allow the study of dynamic and microphysical processes associated with MCSs (see a review by Tao 2007 ). Chief among many significant improvements has been the addition of ice microphysical
) showed that the horizontal variation of the vertical distribution of heating, calculated from TRMM PR observations using a simple method, is also very important in simulating the large-scale tropical circulation correctly. During the past four decades, cloud-resolving models (CRMs) have advanced sufficiently to allow the study of dynamic and microphysical processes associated with MCSs (see a review by Tao 2007 ). Chief among many significant improvements has been the addition of ice microphysical
dominated by phase changes between water vapor and small liquid or frozen cloud-sized particles. It consists of the condensation of cloud droplets, evaporation of cloud droplets and raindrops, freezing of cloud droplets and raindrops, melting of snow and graupel/hail, and the deposition and sublimation of ice particles. In addition, eddy heat flux convergence from cloud motions can also redistribute the heating or cooling vertically and horizontally. LH cannot be measured directly with current
dominated by phase changes between water vapor and small liquid or frozen cloud-sized particles. It consists of the condensation of cloud droplets, evaporation of cloud droplets and raindrops, freezing of cloud droplets and raindrops, melting of snow and graupel/hail, and the deposition and sublimation of ice particles. In addition, eddy heat flux convergence from cloud motions can also redistribute the heating or cooling vertically and horizontally. LH cannot be measured directly with current
( Krishnamurti 1971 ), also exhibits diurnally driven large-scale circulations similar to those over Asia ( Tang and Reiter 1984 ; Tucker 1999 ). Embedded within these larger-scale circulation features are diurnally forced mesoscale flows, such as land–sea and mountain–valley winds, which control the location and timing of convective precipitation in the monsoons of Asia ( Johnson 2006 ) and North America ( Douglas et al. 1993 ; Dai et al. 1999 ). The 2004 North American Monsoon Experiment (NAME) was
( Krishnamurti 1971 ), also exhibits diurnally driven large-scale circulations similar to those over Asia ( Tang and Reiter 1984 ; Tucker 1999 ). Embedded within these larger-scale circulation features are diurnally forced mesoscale flows, such as land–sea and mountain–valley winds, which control the location and timing of convective precipitation in the monsoons of Asia ( Johnson 2006 ) and North America ( Douglas et al. 1993 ; Dai et al. 1999 ). The 2004 North American Monsoon Experiment (NAME) was
affect the intertropical convergence zone (ITCZ) by modifying the moisture and temperature stratification of the air flowing into the ITCZ ( Neggers et al. 2007 ). The majority of rainfall from congestus is warm rain because the tops of most congestus are near the 0°C level and considered not to be frozen. Johnson et al. (1999) also showed that the number of shallow cumulus and congestus clouds was correlated positively with sea surface temperature (SST) during the two cruises of the R/V Vickers
affect the intertropical convergence zone (ITCZ) by modifying the moisture and temperature stratification of the air flowing into the ITCZ ( Neggers et al. 2007 ). The majority of rainfall from congestus is warm rain because the tops of most congestus are near the 0°C level and considered not to be frozen. Johnson et al. (1999) also showed that the number of shallow cumulus and congestus clouds was correlated positively with sea surface temperature (SST) during the two cruises of the R/V Vickers
passive microwave observations to cloud ice. These TRMM-based condensed water products are coupled with temperature, humidity, and ozone profiles from the National Centers for Environmental Prediction (NCEP) reanalysis ( Kalnay et al. 1996 ) that have been further constrained by TMI-based sea surface temperature and column-integrated water vapor estimates from remote sensing systems ( Wentz 1997 ; Wentz et al. 2000 ). The concentrations of less variable gases, such as carbon dioxide, are assumed to
passive microwave observations to cloud ice. These TRMM-based condensed water products are coupled with temperature, humidity, and ozone profiles from the National Centers for Environmental Prediction (NCEP) reanalysis ( Kalnay et al. 1996 ) that have been further constrained by TMI-based sea surface temperature and column-integrated water vapor estimates from remote sensing systems ( Wentz 1997 ; Wentz et al. 2000 ). The concentrations of less variable gases, such as carbon dioxide, are assumed to
, nonprecipitating cloud ice, snow, and graupel. Precipitation and latent + eddy heating profiles are evaluated every hour of simulation time at each model horizontal gridpoint. The model is run for three 30-day periods, nudged by the large-scale advective forcing of temperature, humidity, and horizontal winds, using the method described in Tao et al. (2003b) . Advective forcings are derived from rawinsonde array observations from the South China Sea Monsoon Experiment (SCSMEX) Northern Enhanced Sounding Array
, nonprecipitating cloud ice, snow, and graupel. Precipitation and latent + eddy heating profiles are evaluated every hour of simulation time at each model horizontal gridpoint. The model is run for three 30-day periods, nudged by the large-scale advective forcing of temperature, humidity, and horizontal winds, using the method described in Tao et al. (2003b) . Advective forcings are derived from rawinsonde array observations from the South China Sea Monsoon Experiment (SCSMEX) Northern Enhanced Sounding Array
Pool International Cloud Experiment (TWP-ICE), the South China Sea Monsoon Experiment’s Northern and Southern Enhanced Arrays (SCSMEX-N and SCSMEX-S), the Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA), and the Mirai Indian Ocean Cruise for the Study of the MJO-Convection Onset (MISMO). The locations and durations, as well as references of these field campaigns, are listed in Table 1 . In calculating Q 1 , vertical velocity is first derived from the horizontal wind and pressure by
Pool International Cloud Experiment (TWP-ICE), the South China Sea Monsoon Experiment’s Northern and Southern Enhanced Arrays (SCSMEX-N and SCSMEX-S), the Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA), and the Mirai Indian Ocean Cruise for the Study of the MJO-Convection Onset (MISMO). The locations and durations, as well as references of these field campaigns, are listed in Table 1 . In calculating Q 1 , vertical velocity is first derived from the horizontal wind and pressure by
1. Introduction Over the tropical and subtropical oceans, destabilization of the atmosphere by warm sea surface temperatures (SSTs) and the stabilization by subsidence and horizontal transport may be compared. As a result, although a large precipitation amount is observed with very high SSTs, it does not significantly correlate with SST over moderately warm sea surfaces. Various studies indicate that SST works as a threshold for the precipitation activity (e.g., Gadgil et al. 1984 ). In the
1. Introduction Over the tropical and subtropical oceans, destabilization of the atmosphere by warm sea surface temperatures (SSTs) and the stabilization by subsidence and horizontal transport may be compared. As a result, although a large precipitation amount is observed with very high SSTs, it does not significantly correlate with SST over moderately warm sea surfaces. Various studies indicate that SST works as a threshold for the precipitation activity (e.g., Gadgil et al. 1984 ). In the
