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Collier, JC, Zhang GJ.  2009.  Aerosol direct forcing of the summer Indian monsoon as simulated by the NCAR CAM3. Climate Dynamics. 32:313-332.   10.1007/s00382-008-0464-9   AbstractWebsite

In this study, the effects of aerosols on the simulation of the Indian monsoon by the NCAR Community Atmosphere Model CAM3 are measured and investigated. Monthly mean 3D mass concentrations of soil dust, black and organic carbons, sulfate, and sea salt, as output from the GOCART model, are interpolated to mid-month values and to the horizontal and vertical grids of CAM3. With these mid-month aerosol concentrations, CAM3 is run for a period of approximately 16 months, allowing for one complete episode of the Indian monsoon. Responses to the aerosols are measured by comparing the mean of an ensemble of aerosol-induced monsoon simulations to the mean of an ensemble of CAM3 simulations in which aerosols are omitted, following the method of Lau et al. (2006) in their experiment with the NASA finite volume general circulation model. Additionally, an ensemble of simulations of CAM3 using climatological mid-month aerosol concentrations from the MATCH model is composed for comparison. Results of this experiment indicate that the inclusion of aerosols results in drops in surface temperature and increases in precipitation over central India during the pre-monsoon months of March, April, and May. The presence of aerosols induces tropospheric shortwave heating over central India, which destabilizes the atmosphere for enhanced convection and precipitation. Reduced shortwave heating and enhanced evaporation at the surface during April and May results in reduced terrestrial emission to cool the lower troposphere, relative to simulations with no aerosols. This effect weakens the near-surface cyclonic circulation and, consequently, has a negative feedback on precipitation during the active monsoon months of June and July.

Liu, YC, Fan JW, Xu KM, Zhang GJ.  2018.  Analysis of cloud-resolving model simulations for scale dependence of convective momentum transport. Journal of the Atmospheric Sciences. 75:2445-2472.   10.1175/jas-d-18-0019.1   AbstractWebsite

We use 3D cloud-resolving model (CRM) simulations of two mesoscale convective systems at midlatitudes and a simple statistical ensemble method to diagnose the scale dependency of convective momentum transport (CMT) and CMT-related properties and evaluate a parameterization scheme for the convection-induced pressure gradient (CIPG) developed by Gregory et al. Gregory et al. relate CIPG to a constant coefficient multiplied by mass flux and vertical mean wind shear. CRM results show that mass fluxes and CMT exhibit strong scale dependency in temporal evolution and vertical structure. The upgradient-downgradient CMT characteristics for updrafts are generally similar between small and large grid spacings, which is consistent with previous understanding, but they can be different for downdrafts across wide-ranging grid spacings. For the small to medium grid spacings (4-64 km), Gregory et al. reproduce some aspects of CIPG scale dependency except for underestimating the variations of CIPG as grid spacing decreases. However, for large grid spacings (128-512 km), Gregory et al. might even less adequately parameterize CIPG because it omits the contribution from either the nonlinear-shear or the buoyancy forcings. Further diagnosis of CRM results suggests that inclusion of nonlinear-shear forcing in Gregory et al. is needed for the large grid spacings. For the small to median grid spacings, a modified Gregory et al. with the three-updraft approach help better capture the variations of CIPG as grid spacing decreases compared to the single updraft approach. Further, the optimal coefficients used in Gregory et al. seem insensitive to grid spacings, but they might be different for updrafts and downdrafts, for different MCS types, and for zonal and meridional components.

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.

Yun, YX, Fan JW, Xiao H, Zhang GJ, Ghan SJ, Xu KM, Ma PL, Gustafson WI.  2017.  Assessing the resolution adaptability of the Zhang-McFarlane cumulus parameterization with spatial and temporal averaging. Journal of Advances in Modeling Earth Systems. 9:2753-2770.   10.1002/2017ms001035   AbstractWebsite

With increasing computational capabilities, cumulus parameterizations that are adaptable to the smaller grid spacing and temporal interval for high-resolution climate model simulations are needed. In this study, we propose a method to improve the resolution adaptability of the Zhang-McFarlane (ZM) scheme, by implementing spatial and temporal averaging to the CAPE tendency. This method allows for a more consistent application of the quasi-equilibrium (QE) hypothesis at high spatial and temporal resolutions. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with spatiotemporal averaging at 4-32 km grid spacings are assessed using the Weather Research and Forecasting (WRF) model by comparing to cloud resolving model (CRM) simulation results coarse-grained to these same grid spacings. We show the original ZM scheme has poor resolution adaptability, with spatiotemporally averaged subgrid convective transport and convective precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves total transport and total precipitation. Temporal averaging further improves the resolution adaptability of the scheme. With better constrained (although smoothed) convective transport and precipitation, both the spatial distribution and time series of total precipitation at 4 and 8 km grid spacings are improved with the averaging methods. The results could help develop resolution adaptability for other cumulus parameterizations that are based on the QE assumption.