Zhun Guo

A multiscale modeling framework model (superparameterized CAM5) with a higher‐order turbulence closure: Model description and low‐cloud simulations

In this study, a higher-order turbulence closure scheme, called Cloud Layers Unified By Binormals (CLUBB), is implemented into a Multiscale Modeling Framework (MMF) model to improve low-cloud simulations. The performance of CLUBB in MMF simulations with two different microphysics configurations (one-moment cloud microphysics without aerosol treatment and two-moment cloud microphysics coupled with aerosol treatment) is evaluated against observations and further compared with results from the Community Atmosphere Model, Version 5 (CAM5) with conventional cloud parameterizations. CLUBB is found to improve low-cloud simulations in the MMF, and the improvement is particularly evident in the stratocumulus-to-cumulus transition regions. Compared to the single-moment cloud microphysics, CLUBB with two-moment microphysics produces clouds that are closer to the coast and agrees better with observations. In the stratocumulus-to-cumulus transition regions, CLUBB with two-moment cloud microphysics produces short-wave cloud forcing in better agreement with observations, while CLUBB with single-moment cloud microphysics overestimates short-wave cloud forcing. CLUBB is further found to produce quantitatively similar improvements in the MMF and CAM5, with slightly better performance in the MMF simulations (e.g., MMF with CLUBB generally produces low clouds that are closer to the coast than CAM5 with CLUBB). Improved low-cloud simulations in MMF make it an even more attractive tool for studying aerosol-cloud-precipitation interactions.

A sensitivity analysis of cloud properties to CLUBB parameters in the single-column Community Atmosphere Model (SCAM5)

In this study, we investigate the sensitivity of simulated shallow cumulus and stratocumulus to selected tunable parameters of Cloud Layers Unified by Binormals (CLUBB) in the single-column version of Community Atmosphere Model version 5 (SCAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is adopted to study the responses of simulated cloud fields to tunable parameters. One stratocumulus and two shallow cumulus cases are configured at both coarse and fine vertical resolutions in this study. Our results show that most of the variance in simulated cloud fields can be explained by a small number of tunable parameters. The parameters related to Newtonian and buoyancy-damping terms of total water flux are found to be the most influential parameters for stratocumulus. For shallow cumulus, the most influential parameters are those related to skewness of vertical velocity, reflecting the strong coupling between cloud properties and dynamics in this regime. The influential parameters in the stratocumulus case are sensitive to the vertical resolution while little sensitivity is found for the shallow cumulus cases, as eddy mixing length (or dissipation time scale) plays a more important role and depends more strongly on the vertical resolution in stratocumulus than in shallow convections. The influential parameters remain almost unchanged when the number of tunable parameters increases from 16 to 35. This study improves understanding of the CLUBB behavior associated with parameter uncertainties and provides valuable insights for other high-order turbulence closure schemes.

Impact of cloud radiative heating on East Asian summer monsoon circulation

The impacts of cloud radiative heating on the East Asian Summer Monsoon (EASM) over southeastern China (105°–125°E, 20°–35°N) are addressed by using the Community Atmosphere Model version 5 (CAM5). Sensitivity experiments demonstrate that the radiative heating of clouds leads to a positive effect on the local EASM circulation over southeastern China. Without the radiative heating of clouds, the EASM circulation and precipitation would be much weaker than that in normal conditions. The longwave heating of clouds dominates the changes of EASM circulation. The positive effect of clouds on EASM circulation is explained by the thermodynamic energy equation, i.e. the different heating rate between cloud base and cloud top enhances the convective instability over southeastern China, which consequently enhances updraft. The strong updraft would further result in a southward meridional wind above the center of the updraft through Sverdrup vorticity balance.

Why Does FGOALS-gl Reproduce a Weak Medieval Warm Period But a Reasonable Little Ice Age and 20th Century Warming?

To understand the strengths and limitations of a low-resolution version of Flexible Global Ocean-Atmosphere-Land-Sea-ice (FGOALS-gl) to simulate the climate of the last millennium, the energy balance, climate sensitivity and absorption feedback of the model are analyzed. Simulation of last-millennium climate was carried out by driving the model with natural (solar radiation and volcanic eruptions) and anthropogenic (greenhouse gases and aerosols) forcing agents. The model feedback factors for (model sensitivity to) different forcings were calculated. The results show that the system feedback factor is about 2.5 (W m−2) K−1 in the pre-industrial period, while 1.9 (W m−2) K−1 in the industrial era. Thus, the model’s sensitivity to natural forcing is weak, which explains why it reproduces a weak Medieval Warm Period. The relatively reasonable simulation of the Little Ice Age is caused by both the specified radiative forcing and unforced linear cold drift. The model sensitivity in the industrial era is higher than that of the pre-industrial period. A negative net cloud radiative feedback operates during whole-millennial simulation and reduces the model’s sensitivity to specified forcing. The negative net cloud radiative forcing feedback under natural forcing in the period prior to 1850 is due to the underestimation (overestimation) of the response of cloudiness (in-cloud water path). In the industrial era, the strong tropospheric temperature response enlarges the effective radius of ice clouds and reduces the fractional ice content within cloud, resulting in a weak negative net cloud feedback in the industrial period. The water vapor feedback in the industrial era is also stronger than that in the pre-industrial period. Both are in favor of higher model sensitivity and thus a reasonable simulation of the 20th century global warming.

Improved Performance of High-Resolution Atmospheric Models in Simulating the East Asian Summer Monsoon Rain Belt

AbstractSimulating the East Asian summer monsoon (EASM) rain belt has been proven challenging for climate models. In this study, the impacts of high resolution to the simulation of spatial distributions and rainfall intensity of the EASM rain belt are revealed based on Atmospheric Model Intercomparison Project (AMIP) simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) models. A set of sensitivity experiments is further performed to eliminate the potential influences of differences among CMIP5 models. The results show that the high-resolution models improve the intensity and the spatial pattern of the EASM rainfall compared to the low-resolution models, further valid in the sensitivity experiments. The diagnosis of moist static energy (MSE) balance and moisture budgets is further performed to understand the mechanisms underlying the enhancements. Both analyses indicate that the improved EASM rainfall benefits from the intensified meridional convergence along the EASM rain belt sim...

Seasonal variation and physical properties of the cloud system over southeastern China derived from CloudSat products

Based on the National Centers for Environmental Prediction (NCEP) and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) data and CloudSat products, the seasonal variations of the cloud properties, vertical occurrence frequency, and ice water content of clouds over southeastern China were investigated in this study. In the CloudSat data, a significant alternation in high or low cloud patterns was observed from winter to summer over southeastern China. It was found that the East Asian Summer Monsoon (EASM) circulation and its transport of moisture leads to a conditional instability, which benefits the local upward motion in summer, and thereby results in an increased amount of high cloud. The deep convective cloud centers were found to coincide well with the northward march of the EASM, while cirrus lagged slightly behind the convection center and coincided well with the outflow and meridional wind divergence of the EASM. Analysis of the radiative heating rates revealed that both the plentiful summer moisture and higher clouds are effective in destabilizing the atmosphere. Moreover, clouds heat the mid-troposphere and the cloud radiative heating is balanced by adiabatic cooling through upward motion, which causes meridional wind by the Sverdrup balance. The cloud heating-forced circulation was observed to coincide well with the EASM circulation, serving as a positive effect on EASM circulation.

The asymmetric effects of El Niño and La Niña on the East Asian winter monsoon and their simulation by CMIP5 atmospheric models

El Niño–Southern Oscillation (ENSO) events significantly affect the year-by-year variations of the East Asian winter monsoon (EAWM). However, the effect of La Niña events on the EAWM is not a mirror image of that of El Niño events. Although the EAWM becomes generally weaker during El Niño events and stronger during La Niña winters, the enhanced precipitation over the southeastern China and warmer surface air temperature along the East Asian coastline during El Niño years are more significant. These asymmetric effects are caused by the asymmetric longitudinal positions of the western North Pacific (WNP) anticyclone during El Niño events and the WNP cyclone during La Niña events; specifically, the center of the WNP cyclone during La Niña events is westward-shifted relative to its El Niño counterpart. This central-position shift results from the longitudinal shift of remote El Niño and La Niña anomalous heating, and asymmetry in the amplitude of local sea surface temperature anomalies over the WNP. However, such asymmetric effects of ENSO on the EAWM are barely reproduced by the atmospheric models of Phase 5 of the Coupled Model Intercomparison Project (CMIP5), although the spatial patterns of anomalous circulations are reasonably reproduced. The major limitation of the CMIP5 models is an overestimation of the anomalous WNP anticyclone/cyclone, which leads to stronger EAWM rainfall responses. The overestimated latent heat flux anomalies near the South China Sea and the northern WNP might be a key factor behind the overestimated anomalous circulations.

A Robustness Analysis of CMIP5 Models over the East Asia-Western North Pacific Domain

Abstract The Coupled Model Intercomparison Project (CMIP) is an international community-based infrastructure that supports climate model intercomparison, climate variability, climate prediction, and climate projection. Improving the performance of climate models over East Asia and the western North Pacific has been a challenge for the climate-modeling community. In this paper, we provide a synthesis robustness analysis of the climate models participating in CMIP-Phase 5 (CMIP5). The strengths and weaknesses of the CMIP5 models are assessed from the perspective of climate mean state, interannual variability, past climate change during the mid-Pliocene (MP) and the last millennium, and climate projection. The added values of regional climate models relative to the driving global climate models are also assessed. Although an encouraging increase in credibility and an improvement in the simulation of mean states, interannual variability, and past climate changes are visible in the progression from CMIP3 to CMIP5, some previously noticed biases such as the ridge position of the western North Pacific subtropical high and the associated rainfall bias are still evident in CMIP5 models. Weaknesses are also evident in simulations of the interannual amplitude, such as El Nino-Southern Oscillation (ENSO)-monsoon relationships. Coupled models generally show better results than standalone atmospheric models in simulating both mean states and interannual variability. Multi-model intercomparison indicates significant uncertainties in the future projection of climate change, although precipitation increases consistently across models constrained by the Clausius-Clapeyron relation. Regional ocean-atmosphere coupled models are recommended for the dynamical downscaling of climate change projections over the East Asia-western North Pacific domain.

Improved simulation of the East Asian winter monsoon interannual variation by IAP/LASG AGCMs

Abstract The simulation of the East Asian winter monsoon (EAWM) has been a challenge for climate models. In this study, the performances of two versions of the AGCM developed at the IAP, versions 1 and 2 of the Grid-point Atmospheric Model of the IAP/LASG (GAMIL1 and GAMIL2), are evaluated in the context of mean state and interannual variation. Significant improvements are shown for GAMIL2 in comparison to GAMIL1. The simulated interannual variability of the EAWM, measured by the regional average of 1000 hPa meridional wind over East Asia, has evidently improved; the correlation coefficient with reanalysis data changes from 0.37 in GAMIL1 to 0.71 in GAMIL2. The associated interannual precipitation anomalies are also improved, in terms of both spatial pattern and magnitude. Analysis demonstrates that the improvements result from the better simulation of the El Niño-related Philippine Sea anticyclone (PSAC) in GAMIL2. The improved moist processes, including the stratiform condensation and evaporation in GAMIL2, lead to a reasonable atmospheric heating associated with El Niño in the tropical Pacific, which further drives the PSAC as a Rossby-wave response.

Cloud Microphysical Factors Affecting Simulations of Deep Convection During the Presummer Rainy Season in Southern China

The sensitivity of subtropical deep convection to the parameterization of cloud microphysics is elucidated through high-resolution modeling of extreme presummer rainfall over southern China. An ensemble of physics configuration experiments is used to identify several drivers of model errors in comparison to radar observations from the South China Monsoon Rainfall Experiment (SCMREX) and remotely sensed estimates of cloud, precipitation, and radiation from satellites in the A-train constellation. The benefits of increasing the number of prognostic variables in the microphysics scheme is assessed, relative to the effects of the parameterization of cloud microphysical properties and cloud fraction diagnosis. By matching individual parameterizations between the microphysical configurations, it is shown that a small subset of the parameterization changes can reproduce most of the dependence of model performance on physics configuration. In particular, biases that are due to the low-level clouds and rain are strongly influenced by cloud fraction diagnosis and raindrop size distribution, whereas variations in the effects of high clouds are strongly influenced by differences in the parameterization of ice crystal sedimentation. Hence, for the case studied here, these parameterizations give more insight into the causes of variability in model performance than does the number of model prognostics per se.