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Wang, X, Zhang GJ.  2019.  Evaluation of the quasi-biweekly oscillation over the South China Sea in early and late summer in CAM5. Journal of Climate. 32:69-84.   10.1175/jcli-d-18-0072.1   AbstractWebsite

Low-frequency intraseasonal oscillations in the tropical atmosphere in general circulation models (GCMs) were studied extensively in many previous studies. However, the simulation of the quasi-biweekly oscillation (QBWO), which is an important component of the intraseasonal oscillations, in GCMs has not received much attention. This paper evaluates the QBWO features over the South China Sea in early [May-June (MJ)] and late [August-September (AS)] summer in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5.3 (CAM5), using observations and reanalysis data. Results show that the major features of the spatial distribution of the QBWO in both MJ and AS are simulated reasonably well by the model, although the amplitude of the variation is overestimated. CAM5 captures the local oscillation in MJ and the westward propagation in AS of the QBWO. Although there are important biases in geographical location and intensity in MJ, the model represents the QBWO horizontal and vertical structure qualitatively well in AS. The diagnosis of the eddy vorticity budget is conducted to better understand the QBWO activities in the model. Both horizontal advection of relative vorticity and that of planetary vorticity (Coriolis parameter) are important for the local evolution of the QBWO in MJ in observations as well as model simulation, whereas advection of planetary vorticity contributes to the westward propagation of QBWO vorticity anomalies in AS. Since the Coriolis parameter f only changes with latitude, this suggests that the correct simulation of anomalous meridional wind is a key factor in the realistic simulation of the QBWO in the model.

Huang, XM, Hu CQ, Huang X, Chu Y, Tseng YH, Zhang GJ, Lin YL.  2018.  A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm. Climate Dynamics. 51:3145-3159.   10.1007/s00382-018-4071-0   AbstractWebsite

Mesoscale convective systems (MCSs) are important components of tropical weather systems and the climate system. Long-term data of MCS are of great significance in weather and climate research. Using long-term (1985-2008) global satellite infrared (IR) data, we developed a novel objective automatic tracking algorithm, which combines a Kalman filter (KF) with the conventional area-overlapping method, to generate a comprehensive MCS dataset. The new algorithm can effectively track small and fast-moving MCSs and thus obtain more realistic and complete tracking results than previous studies. A few examples are provided to illustrate the potential application of the dataset with a focus on the diurnal variations of MCSs over land and ocean regions. We find that the MCSs occurring over land tend to initiate in the afternoon with greater intensity, but the oceanic MCSs are more likely to initiate in the early morning with weaker intensity. A double peak in the maximum spatial coverage is noted over the western Pacific, especially over the southwestern Pacific during the austral summer. Oceanic MCSs also persist for approximately 1h longer than their continental counterparts.

Wang, Y, Zhang GJ, Jiang YQ.  2018.  Linking stochasticity of convection to large-scale vertical velocity to improve Indian Summer Monsoon Simulation in the NCAR CAM5. Journal of Climate. 31:6985-7002.   10.1175/jcli-d-17-0785.1   AbstractWebsite

The Plant-Craig (PC) stochastic convective parameterization scheme is modified by linking the stochastic generation of convective clouds to the change of large-scale vertical pressure velocity at 500 hPa with time so as to better account for the relationship between convection and the large-scale environment. Three experiments using the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5 (CAM5), are conducted: one with the default Zhang-McFarlane deterministic convective scheme, another with the original PC stochastic scheme, and a third with the modified PC stochastic scheme. Evaluation is focused on the simulation of the Indian summer monsoon (ISM), which is a long-standing challenge for all current global circulation models. Results show that the modified stochastic scheme better represents the annual cycle of the climatological mean rainfall over central India and the mean onset date of ISM compared to other simulations. Also, for the simulations of ISM intraseasonal variability for quasi-biweekly and 30-60-day modes, the modified stochastic parameterization produces more realistic propagation and magnitude, especially for the observed northeastward movement of the 30-60-day mode, for which the other two simulations show the propagation in the opposite direction. Causes are investigated through a moisture budget analysis. Compared to the other two simulations, the modified stochastic scheme with an appropriate representation of convection better represents the patterns and amplitudes of large-scale dynamical convergence and moisture advection and thus corrects the monsoon cycle associated with their covariation during the peaks and troughs of intraseasonal oscillation.

Song, FF, Zhang GJ.  2018.  Understanding and improving the scale dependence of trigger functions for convective parameterization using cloud-resolving model data. Journal of Climate. 31:7385-7399.   10.1175/jcli-d-17-0660.1   AbstractWebsite

As the resolution of global climate model increases, whether trigger functions in current convective parameterization schemes still work remains unknown. In this study, the scale dependence of undilute and dilute dCAPE, Bechtold, and heated condensation framework (HCF) triggers is evaluated using the cloud-resolving model (CRM) data. It is found that all these trigger functions are scale dependent, especially for dCAPE-type triggers, with skill scores dropping from similar to 0.6 at the lower resolutions (128, 64, and 32 km) to only similar to 0.1 at 4 km. The average convection frequency decreases from 14.1% at 128 km to 2.3% at 4 km in the CRM data, but it increases rapidly in the dCAPE-type triggers and is almost unchanged in the Bechtold and HCF triggers across resolutions, all leading to large overpredictions at higher resolutions. In the dCAPE-type triggers, the increased frequency is due to the increased rate of dCAPE greater than the threshold (65 J kg(-1) h(-1)) at higher resolutions. The box-and-whisker plots show that the main body of dCAPE in the correct prediction and overprediction can be separated from each other in most resolutions. Moreover, the underprediction is found to be corresponding to the decaying phase of convection. Hence, two modifications are proposed to improve the scale dependence of the undilute dCAPE trigger: 1) increasing the dCAPE threshold and 2) considering convection history, which checks whether there is convection prior to the current time. With these modifications, the skill at 16 km, 8 km, and 4 km can be increased from 0.50, 0.27, and 0.15 to 0.70, 0.61, and 0.53, respectively.

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.

Wang, MC, Zhang GJ.  2018.  Improving the simulation of tropical convective cloud-top heights in CAM5 with CloudSat observations. Journal of Climate. 31:5189-5204.   10.1175/jcli-d-18-0027.1   AbstractWebsite

Using 4 years of CloudSat data, the simulation of tropical convective cloud-top heights (CCTH) above 6 km simulated by the convection scheme in the Community Atmosphere Model, version 5 (CAM5), is evaluated. Compared to CloudSat observations, CAM5 underestimates CCTH by more than 2 km on average. Further analysis of model results suggests that the dilute CAPE calculation, which has been incorporated into the convective parameterization since CAM4, is a main factor restricting CCTH to much lower levels. After removing this restriction, more convective clouds develop into higher altitudes, although convective clouds with tops above 12 km are still underestimated significantly. The environmental conditions under which convection develops in CAM5 are compared with CloudSat observations for convection with similar CCTHs. It is shown that the model atmosphere is much more unstable compared to CloudSat observations, and there is too much entrainment in CAM5. Since CCTHs are closely associated with cloud radiative forcing, the impacts of CCTH on model simulation are further investigated. Results show that the change of CCTH has important impacts on cloud radiative forcing and precipitation. With increased CCTHs, there is more cloud radiative forcing in tropical Africa and the eastern Pacific, but less cloud radiative forcing in the western Pacific. The contribution to total convective precipitation from convection with cloud tops above 9 km is also increased substantially.

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.

Kao, A, Jiang X, Li LM, Trammell JH, Zhang GJ, Su H, Jiang JH, Yung YL.  2018.  A Comparative Study of Atmospheric Moisture Recycling Rate between Observations and Models. Journal of Climate. 31:2389-2398.   10.1175/jcli-d-17-0421.1   AbstractWebsite

Precipitation and column water vapor data from 13 CMIP5 models and observational datasets are used to analyze atmospheric moisture recycling rate from 1988 to 2008. The comparisons between observations and model simulations suggest that most CMIP5 models capture two main characteristics of the recycling rate: 1) long-term decreasing trend of the global-average maritime recycling rate (atmospheric recycling rate over ocean within 608S-608N) and 2) dominant spatial patterns of the temporal variations of the recycling rate (i.e., increasing in the intertropical convergence zone and decreasing in subtropical regions). All models, except one, successfully simulate not only the long-term trend but also the interannual variability of column water vapor. The simulations of precipitation are relatively poor, especially over the relatively short time scales, which lead to the discrepancy of the recycling rate between observations and the CMIP5 models. Comparisons of spatial patterns also suggest that the CMIP5 models simulate column water vapor better than precipitation. The comparative studies indicate the scope of improvement in the simulations of precipitation, especially for the relatively short-time-scale variations, to better simulate the recycling rate of atmospheric moisture, an important indicator of climate change.

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.

Song, XL, Zhang GJ.  2018.  The roles of convection parameterization in the formation of double ITCZ Syndrome in the NCAR CESM: I. Atmospheric Processes. Journal of Advances in Modeling Earth Systems. 10:842-866.   10.1002/2017ms001191   AbstractWebsite

Several improvements are implemented in the Zhang-McFarlane (ZM) convection scheme to investigate the roles of convection parameterization in the formation of double intertropical convergence zone (ITCZ) bias in the NCAR CESM1.2.1. It is shown that the prominent double ITCZ biases of precipitation, sea surface temperature (SST), and wind stress in the standard CESM1.2.1 are largely eliminated in all seasons with the use of these improvements in convection scheme. This study for the first time demonstrates that the modifications of convection scheme can eliminate the double ITCZ biases in all seasons, including boreal winter and spring. Further analysis shows that the elimination of the double ITCZ bias is achieved not by improving other possible contributors, such as stratus cloud bias off the west coast of South America and cloud/radiation biases over the Southern Ocean, but by modifying the convection scheme itself. This study demonstrates that convection scheme is the primary contributor to the double ITCZ bias in the CESM1.2.1, and provides a possible solution to the long-standing double ITCZ problem. The atmospheric model simulations forced by observed SST show that the original ZM convection scheme tends to produce double ITCZ bias in high SST scenario, while the modified convection scheme does not. The impact of changes in each core component of convection scheme on the double ITCZ bias in atmospheric model is identified and further investigated.

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.