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Zhou, ZQ, Xie SP, Zhang GJ, Zhou WY.  2018.  Evaluating AMIP Skill in Simulating Interannual Variability over the Indo-Western Pacific. Journal of Climate. 31:2253-2265.   10.1175/jcli-d-17-0123.1   AbstractWebsite

Local correlation between sea surface temperature (SST) and rainfall is weak or even negative in summer over the Indo-western Pacific warm pool, a fact often taken as indicative of weak ocean feedback on the atmosphere. An Atmospheric Model Intercomparison Project (AMIP) simulation forced by monthly varying SSTs derived from a parallel coupled general circulation model (CGCM) run is used to evaluate AMIP skills in simulating interannual variability of rainfall. Local correlation of rainfall variability between AMIP and CGCMsimulations is used as a direct metric of AMIP skill. This "perfect model'' approach sidesteps the issue of model biases that complicates the traditional skill metric based on the correlation between AMIP and observations. Despite weak local SST-rainfall correlation, the AMIP-CGCM rainfall correlation exceeds a 95% significance level over most of the Indo-western Pacific warm pool, indicating the importance of remote (e.g., El Nino in the equatorial Pacific) rather than local SST forcing. Indeed, the AMIP successfully reproduces large-scale modes of rainfall variability over the Indo-western Pacific warm pool. Compared to the northwest Pacific east of the Philippines, the AMIP-CGCMrainfall correlation is low from the Bay of Bengal through the South China Sea, limited by internal variability of the atmosphere that is damped in CGCM by negative feedback from the ocean. Implications for evaluating AMIP skill in simulating observations are discussed.

Jiang, X, Waliser DE, Xavier PK, Petch J, Klingaman NP, Woolnough SJ, Guan B, Bellon G, Crueger T, DeMott C, Hannay C, Lin H, Hu WT, Kim D, Lappen CL, Lu MM, Ma HY, Miyakawa T, Ridout JA, Schubert SD, Scinocca J, Seo KH, Shindo E, Song XL, Stan C, Tseng WL, Wang WQ, Wu TW, Wu XQ, Wyser K, Zhang GJ, Zhu HY.  2015.  Vertical structure and physical processes of the Madden-Julian oscillation: Exploring key model physics in climate simulations. Journal of Geophysical Research-Atmospheres. 120:4718-4748.   10.1002/2014jd022375   AbstractWebsite

Aimed at reducing deficiencies in representing the Madden-Julian oscillation (MJO) in general circulation models (GCMs), a global model evaluation project on vertical structure and physical processes of the MJO was coordinated. In this paper, results from the climate simulation component of this project are reported. It is shown that the MJO remains a great challenge in these latest generation GCMs. The systematic eastward propagation of the MJO is only well simulated in about one fourth of the total participating models. The observed vertical westward tilt with altitude of the MJO is well simulated in good MJO models but not in the poor ones. Damped Kelvin wave responses to the east of convection in the lower troposphere could be responsible for the missing MJO preconditioning process in these poor MJO models. Several process-oriented diagnostics were conducted to discriminate key processes for realistic MJO simulations. While large-scale rainfall partition and low-level mean zonal winds over the Indo-Pacific in a model are not found to be closely associated with its MJO skill, two metrics, including the low-level relative humidity difference between high- and low-rain events and seasonal mean gross moist stability, exhibit statistically significant correlations with the MJO performance. It is further indicated that increased cloud-radiative feedback tends to be associated with reduced amplitude of intraseasonal variability, which is incompatible with the radiative instability theory previously proposed for the MJO. Results in this study confirm that inclusion of air-sea interaction can lead to significant improvement in simulating the MJO.

Park, HS, Chiang JCH, Lintner BR, Zhang GJ.  2010.  The delayed effect of major El Nino events on Indian monsoon rainfall. Journal of Climate. 23:932-946.   10.1175/2009jcli2916.1   AbstractWebsite

Previous studies have shown that boreal summer Indian monsoon rainfall is, on average, significantly above normal after major El Nino events. In this study, the underlying causes of this rainfall response are examined using both observational analysis and atmospheric general circulation model (AGCM) simulations. Moist static energy budgets for two strong El Nino events (1982/83 and 1997/98), estimated from monthly 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40), suggest that stronger low-level moisture transport and reduced moist stability associated with a warmer north Indian Ocean (NIO) can increase monsoon rainfall, despite a weakened monsoon circulation. The trade-off between a dynamically weaker monsoon and moist processes favoring enhanced monsoonal rainfall is broken during the late monsoon season (August-September) as the warm NIO enhances surface latent heat flux and the monsoon circulation relaxes back to the climatological mean. The monsoon circulation strength and the moist processes work together in the late season, which explains the observed tendency for monsoonal rainfall increases during the late monsoon season after strong winter El Nino conditions. Idealized AGCM experiments with a fixed-depth ocean mixed layer demonstrate that the remnant but weaker-than-peak warm SSTs in the eastern equatorial Pacific during spring and the early summer following winter El Ninos substantially contribute to the NIO warming. The results suggest that local air-sea interactions in the tropical Indian Ocean after winter El Nino are strongly dependent on the details of El Nino's decaying trend.

Kim, D, Sperber K, Stern W, Waliser D, Kang IS, Maloney E, Wang W, Weickmann K, Benedict J, Khairoutdinov M, Lee MI, Neale R, Suarez M, Thayer-Calder K, Zhang G.  2009.  Application of MJO Simulation Diagnostics to Climate Models. Journal of Climate. 22:6413-6436.   10.1175/2009jcli3063.1   AbstractWebsite

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 (similar to 20-29 days) than observations (similar to 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.

Zhang, GJ.  1994.  Effects of cumulus convection on the simulated monsoon circulation in a general circulation model. Monthly Weather Review. 122:2022-2038.   10.1175/1520-0493(1994)122<2022:eoccot>;2   AbstractWebsite

The effect of cumulus convection on the Asian summer monsoon circulation is investigated, using a general circulation model. Two simulations for the summer months (June. July, and August) are performed, one para meterizing convection using a mass Bur scheme and the other without convective parameterization. The results show that convection has significant effects on the monsoon circulation and its associated precipitation. In the simulation with the mass flux convictive parameterization, precipitation in the western Pacific is decreased, together with a decrease in surface evaporation and wind speed. In the Indian monsoon region it is almost the opposite. Comparison with a simulation using moist convective adjustment to parameterize convection shows that the monsoon circulation and precipitation distribution in the no-convection simulation are very similar to those in the simulation with moist convective adjustment. The difference in the large-scale circulation with and without convective parameterization is interpreted in terms of convective stabilization of the atmosphere by convection, using dry and moist static energy budgets. It is shown that weakening of the low-level convergence in the western Pacific in the simulation with convection is closely associated with the stabilization of the atmosphere by convection, mostly through drying of the lower troposphere; changes in low-level convergence lead to changes in precipitation. The precipitation increase in the Indian monsoon region can be explained similarly.