The ability of eight climate models to simulate the Madden–Julian oscillation (MJO) is examined using diagnostics developed by the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group. Although the MJO signal has been extracted throughout the annual cycle, this study focuses on the boreal winter (November–April) behavior. Initially, maps of the mean state and variance and equatorial space–time spectra of 850-hPa zonal wind and precipitation are compared with observations. Models best represent the intraseasonal space–time spectral peak in the zonal wind compared to that of precipitation. Using the phase–space representation of the multivariate principal components (PCs), the life cycle properties of the simulated MJOs are extracted, including the ability to represent how the MJO evolves from a given subphase and the associated decay time scales. On average, the MJO decay (e-folding) time scale for all models is shorter (∼20–29 days) than observations (∼31 days). All models are able to produce a leading pair of multivariate principal components that represents eastward propagation of intraseasonal wind and precipitation anomalies, although the fraction of the variance is smaller than observed for all models. In some cases, the dominant time scale of these PCs is outside of the 30–80-day band. Several key variables associated with the model’s MJO are investigated, including the surface latent heat flux, boundary layer (925 hPa) moisture convergence, and the vertical structure of moisture. Low-level moisture convergence ahead (east) of convection is associated with eastward propagation in most of the models. A few models are also able to simulate the gradual moistening of the lower troposphere that precedes observed MJO convection, as well as the observed geographical difference in the vertical structure of moisture associated with the MJO. The dependence of rainfall on lower tropospheric relative humidity and the fraction of rainfall that is stratiform are also discussed, including implications these diagnostics have for MJO simulation. Based on having the most realistic intraseasonal multivariate empirical orthogonal functions, principal component power spectra, equatorial eastward propagating outgoing longwave radiation (OLR), latent heat flux, low-level moisture convergence signals, and vertical structure of moisture over the Eastern Hemisphere, the superparameterized Community Atmosphere Model (SPCAM) and the ECHAM4/Ocean Isopycnal Model (OPYC) show the best skill at representing the MJO.

This study examines the impacts of convective parameterization and moisture convective trigger on convectively coupled equatorial waves simulated by the Seoul National University (SNU) atmospheric general circulation model (AGCM). Three different convection schemes are used, including the simplified Arakawa–Schubert (SAS) scheme, the Kuo (1974) scheme, and the moist convective adjustment (MCA) scheme, and a moisture convective trigger with variable strength is added to each scheme. The authors also conduct a “no convection” experiment with deep convection schemes turned off. Space–time spectral analysis is used to obtain the variance and phase speed of dominant convectively coupled equatorial waves, including the Madden–Julian oscillation (MJO), Kelvin, equatorial Rossby (ER), mixed Rossby–gravity (MRG), and eastward inertio-gravity (EIG) and westward inertio-gravity (WIG) waves. The results show that both convective parameterization and the moisture convective trigger have significant impacts on AGCM-simulated, convectively coupled equatorial waves. The MCA scheme generally produces larger variances of convectively coupled equatorial waves including the MJO, more coherent eastward propagation of the MJO, and a more prominent MJO spectral peak than the Kuo and SAS schemes. Increasing the strength of the moisture trigger significantly enhances the variances and slows down the phase speeds of all wave modes except the MJO, and usually improves the eastward propagation of the MJO for the Kuo and SAS schemes, but the effect for the MCA scheme is small. The no convection experiment always produces one of the best signals of convectively coupled equatorial waves and the MJO.

This study evaluates the subseasonal variability associated with the Asian summer monsoon in 14 coupled general circulation models (GCMs) participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Eight years of each model’s twentieth-century climate simulation are analyzed. The authors focus on the three major components of Asian summer monsoon: the Indian summer monsoon (ISM), the western North Pacific summer monsoon (WNPSM), and the East Asian summer monsoon (EASM), together with the two dominant subseasonal modes: the eastward- and northward-propagating boreal summer intraseasonal oscillation (BSIO) and the westward-propagating 12–24-day mode. The results show that current state-of-the-art GCMs still have difficulties and display a wide range of skill in simulating the subseasonal variability associated with Asian summer monsoon. During boreal summer (May–October), most of the models produce reasonable seasonal-mean precipitation over the ISM region, but excessive precipitation over the WNPSM region and insufficient precipitation over the EASM region. In other words, models concentrate their rain too close to the equator in the western Pacific. Most of the models simulate overly weak total subseasonal (2–128 day) variance, as well as too little variance for BSIO and the 12–24-day mode. Only 4–5 models produce spectral peaks in the BSIO and 12–24-day frequency bands; instead, most of the models display too red a spectrum, that is, an overly strong persistence of precipitation. For the seven models with three-dimensional data available, five reproduce the preconditioning of moisture in BSIO but often with a too late starting time, and only three simulate the phase lead of low-level convergence. Interestingly, although models often have difficulty in simulating the eastward propagation of BSIO, they tend to simulate well the northward propagation of BSIO, together with the westward propagation of the 12–24-day mode. The northward propagation in these models is thus not simply a NW–SE-tilted tail protruding off of an eastward-moving deep-tropical intraseasonal oscillation.

This study investigates the interannual variation of heat wave frequency (HWF) in South Korea during the past 42 years (1973–2014) and examines its connection with large‐scale atmospheric circulation changes. Korean heat waves tend to develop most frequently in late summer during July and August. The leading Empirical Orthogonal Function accounting for 50% of the total variance shows a mono‐signed pattern over South Korea, suggesting that the dominant mechanisms responsible for the heat wave are linked in a spatial scale much larger than the nation. It also exhibits a regional variation with more occurrences in the southeastern inland area. The regression of the leading principal component (PC) time series of HWF with large‐scale atmospheric circulation identifies a north–south dipole pattern between the South China Sea and Northeast Asia. When this large‐scale circulation mode facilitates deep convection in South China Sea, it tends to weaken moisture transport from the South China Sea to Northeast Asia. Enhanced deep convection in the South China Sea triggers a source of Rossby wave train along southerly wind that generates positive geopotential height anomalies around Korea. The anomalous high pressure pattern is accompanied by large‐scale subsidence in Korea, thereby providing a favourable condition for extreme hot and dry days in Korea. This study highlights that there is a decadal change of the relationship between Korean heat waves and large‐scale atmospheric circulation patterns. The tropical forcing tends to be weakened in the recent decade, with more influences from the Arctic variability from the mid‐1990s.