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Yang, MM, Zhang GJ, Sun DZ.  2018.  Precipitation and moisture in four leading CMIP5 models: Biases across large-scale circulation regimes and their attribution to dynamic and thermodynamic factors. Journal of Climate. 31:5089-5106.   10.1175/jcli-d-17-0718.1   AbstractWebsite

As key variables in general circulation models, precipitation and moisture in four leading models from CMIP5 (phase 5 of the Coupled Model Intercomparison Project) are analyzed, with a focus on four tropical oceanic regions. It is found that precipitation in these models is overestimated in most areas. However, moisture bias has large intermodel differences. The model biases in precipitation and moisture are further examined in conjunction with large-scale circulation by regime-sorting analysis. Results show that all models consistently overestimate the frequency of occurrence of strong upward motion regimes and peak descending regimes of 500-hPa vertical velocity JCLI-D-17-0718.1 regime, models produce too much precipitation compared to observation and reanalysis. But for moisture, their biases differ from model to model and also from level to level. Furthermore, error causes are revealed through decomposing contribution biases into dynamic and thermodynamic components. For precipitation, the contribution errors in strong upward motion regimes are attributed to the overly frequent . In the weak upward motion regime, the biases in the dependence of precipitation on probability density function (PDF) make comparable contributions, but often of opposite signs. On the other hand, the biases in column-integrated water vapor contribution are mainly due to errors in the frequency of occurrence of , while thermodynamic components contribute little. These findings suggest that errors in the frequency of occurrence are a significant cause of biases in the precipitation and moisture simulation.

Song, XL, Zhang GJ, Cai M.  2014.  Quantifying contributions of climate feedbacks to tropospheric warming in the NCAR CCSM3.0. Climate Dynamics. 42:901-917.   10.1007/s00382-013-1805-x   AbstractWebsite

In this study, a coupled atmosphere-surface "climate feedback-response analysis method" (CFRAM) was applied to the slab ocean model version of the NCAR CCSM3.0 to understand the tropospheric warming due to a doubling of CO2 concentration through quantifying the contributions of each climate feedback process. It is shown that the tropospheric warming displays distinct meridional and vertical patterns that are in a good agreement with the multi-model mean projection from the IPCC AR4. In the tropics, the warming in the upper troposphere is stronger than in the lower troposphere, leading to a decrease in temperature lapse rate, whereas in high latitudes the opposite it true. In terms of meridional contrast, the lower tropospheric warming in the tropics is weaker than that in high latitudes, resulting in a weakened meridional temperature gradient. In the upper troposphere the meridional temperature gradient is enhanced due to much stronger warming in the tropics than in high latitudes. Using the CFRAM method, we analyzed both radiative feedbacks, which have been emphasized in previous climate feedback analysis, and non-radiative feedbacks. It is shown that non-radiative (radiative) feedbacks are the major contributors to the temperature lapse rate decrease (increase) in the tropical (polar) region. Atmospheric convection is the leading contributor to temperature lapse rate decrease in the tropics. The cloud feedback also has non-negligible contributions. In the polar region, water vapor feedback is the main contributor to the temperature lapse rate increase, followed by albedo feedback and CO2 forcing. The decrease of meridional temperature gradient in the lower troposphere is mainly due to strong cooling from convection and cloud feedback in the tropics and the strong warming from albedo feedback in the polar region. The strengthening of meridional temperature gradient in the upper troposphere can be attributed to the warming associated with convection and cloud feedback in the tropics. Since convection is the leading contributor to the warming differences between tropical lower and upper troposphere, and between the tropical and polar regions, this study indicates that tropical convection plays a critical role in determining the climate sensitivity. In addition, the CFRAM analysis shows that convective process and water vapor feedback are the two major contributors to the tropical upper troposphere temperature change, indicating that the excessive upper tropospheric warming in the IPCC AR4 models may be due to overestimated warming from convective process or underestimated cooling due to water vapor feedback.

Yang, B, Qian Y, Lin G, Leung LR, Rasch PJ, Zhang GJ, McFarlane SA, Zhao C, Zhang YC, Wang HL, Wang MH, Liu XH.  2013.  Uncertainty quantification and parameter tuning in the CAM5 Zhang-McFarlane convection scheme and impact of improved convection on the global circulation and climate. Journal of Geophysical Research-Atmospheres. 118:395-415.   10.1029/2012jd018213   AbstractWebsite

In this study, we applied an uncertainty quantification (UQ) technique to improve convective precipitation in the global climate model, the Community Atmosphere Model version 5 (CAM5), in which the convective and stratiform precipitation partitioning is very different from observational estimates. We examined the sensitivity of precipitation and circulation to several key parameters in the Zhang-McFarlane deep convection scheme in CAM5, using a stochastic importance-sampling algorithm that can progressively converge to optimal parameter values. The impact of improved deep convection on the global circulation and climate was subsequently evaluated. Our results show that the simulated convective precipitation is most sensitive to the parameters of the convective available potential energy consumption time scale, parcel fractional mass entrainment rate, and maximum downdraft mass flux fraction. Using the optimal parameters constrained by the observed Tropical Rainfall Measuring Mission, convective precipitation improves the simulation of convective to stratiform precipitation ratio and rain-rate spectrum remarkably. When convection is suppressed, precipitation tends to be more confined to the regions with strong atmospheric convergence. As the optimal parameters are used, positive impacts on some aspects of the atmospheric circulation and climate, including reduction of the double Intertropical Convergence Zone, improved East Asian monsoon precipitation, and improved annual cycles of the cross-equatorial jets, are found as a result of the vertical and horizontal redistribution of latent heat release from the revised parameterization. Positive impacts of the optimal parameters derived from the 2 degrees simulations are found to transfer to the 1 degrees simulations to some extent. Citation: Yang, B. et al. (2013), Uncertainty quantification and parameter tuning in the CAM5 Zhang-McFarlane convection scheme and impact of improved convection on the global circulation and climate, J. Geophys. Res. Atmos., 118, 395-415, doi:10.1029/2012JD018213.

Collier, JC, Zhang GJ.  2006.  Simulation of the North American monsoon by the NCAR CCM3 and its sensitivity to convection parameterization. Journal of Climate. 19:2851-2866.   10.1175/jcli3732.1   AbstractWebsite

Two 9-yr runs of the NCAR Community Climate Model version 3 (CCM3) are compared in their simulations of the North American summer monsoon. In a control simulation, the Zhang-McFarlane deep convection scheme is used. For an experimental simulation, the following modifications to the scheme are implemented. The closure is based on the large-scale forcing of virtual temperature, and a relative humidity threshold on convective parcels lifted from the boundary layer is applied. The sensitivity to these modifications for simulating the North American monsoon is investigated. Model validation relies on hourly precipitation rates from surface gauges over the United States, hourly precipitation rates derived from the combination of microwave and radar measurements from NASA's Tropical Rainfall Measuring Mission (TRMM) satellite over Mexico, and CAPE values as calculated from temperature, specific humidity, and pressure fields from the NCEP-NCAR reanalysis. Results show that the experimental run improves the timing of the monsoon onset and peak in the regions of core monsoon influence considered here, though it increases a negative bias in the peak monsoon intensity in one region of northern Mexico. Sensitivity of the diurnal cycle of precipitation to modifications in the convective scheme is highly geographically dependent. Using a combination of gauge-based rainfall rates and reanalysis-based CAPE, it is found that improvements in the simulated diurnal cycle are confined to a convective regime in which the diurnal evolution of precipitation is observed to lag that of CAPE. For another regime, in which CAPE is observed to be approximately in phase with precipitation, model phase biases increase nearly everywhere. Some of the increased phase biases in the latter regime are primarily because of application of the relative humidity threshold.

Zhang, GJ, Zurovac-Jevtic D, Boer ER.  1999.  Spatial characteristics of the tropical cloud systems: comparison between model simulation and satellite observations. Tellus Series a-Dynamic Meteorology and Oceanography. 51:922-936.   10.1034/j.1600-0870.1999.00026.x   AbstractWebsite

A Lagrangian cloud classification algorithm is applied to the cloud fields in the tropical Pacific simulated by a high-resolution regional atmospheric model. The purpose of this work is to assess the model's ability to reproduce the observed spatial characteristics of the tropical cloud systems. The cloud systems are broadly grouped into three categories: deep clouds, mid-level clouds and low clouds. The deep clouds are further divided into mesoscale convective systems and non-mesoscale convective systems. It is shown that the model is able to simulate the total cloud cover for each category reasonably well. However, when the cloud cover is broken down into contributions from cloud systems of different sizes, it is shown that the simulated cloud size distribution is biased toward large cloud systems, with contribution from relatively small cloud systems significantly under-represented in the model for both deep and mid-level clouds. The number distribution and area contribution to the cloud cover from mesoscale convective systems are very well simulated compared to the satellite observations, so are low clouds as well. The dependence of the cloud physical properties on cloud scale is examined. It is found that cloud liquid water path, rainfall, and ocean surface sensible and latent heat fluxes have a clear dependence on cloud types and scale. This is of particular interest to studies of the cloud effects on surface energy budget and hydrological cycle. The diurnal variation of the cloud population and area is also examined. The model exhibits a varying degree of success in simulating the diurnal variation of the cloud number and area. The observed early morning maximum cloud cover in deep convective cloud systems is qualitatively simulated. However, the afternoon secondary maximum is missing in the model simulation. The diurnal variation of the tropospheric temperature is well reproduced by the model while simulation of the diurnal variation of the moisture held is poor. The implication of this comparison between model simulation and observations on cloud parameterization is discussed.