Minghua Zhang

The Community Climate System Model Version 4

AbstractThe fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all CCSM components, and documents fully coupled preindustrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1° results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4°-resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in CCSM4 producing El Nino–Southern Oscillation variability with a much more realistic frequency distribution than in CCSM3, although the amplitude is too large compared to observations. These changes also improve the Madden–Julian oscillation and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the Gulf Stream path and the North Atlantic Ocean meridional overturning circulati...

The Formulation and Atmospheric Simulation of the Community Atmosphere Model Version 3 (CAM3)

Abstract A new version of the Community Atmosphere Model (CAM) has been developed and released to the climate community. CAM Version 3 (CAM3) is an atmospheric general circulation model that includes the Community Land Model (CLM3), an optional slab ocean model, and a thermodynamic sea ice model. The dynamics and physics in CAM3 have been changed substantially compared to implementations in previous versions. CAM3 includes options for Eulerian spectral, semi-Lagrangian, and finite-volume formulations of the dynamical equations. It supports coupled simulations using either finite-volume or Eulerian dynamics through an explicit set of adjustable parameters governing the model time step, cloud parameterizations, and condensation processes. The model includes major modifications to the parameterizations of moist processes, radiation processes, and aerosols. These changes have improved several aspects of the simulated climate, including more realistic tropical tropopause temperatures, boreal winter land surfac...

Absorption of Solar Radiation by Clouds: Observations Versus Models

There has been a long history of unexplained anomalous absorption of solar radiation by clouds. Collocated satellite and surface measurements of solar radiation at five geographically diverse locations showed significant solar absorption by clouds, resulting in about 25 watts per square meter more global-mean absorption by the cloudy atmosphere than predicted by theoretical models. It has often been suggested that tropospheric aerosols could increase cloud absorption. But these aerosols are temporally and spatially heterogeneous, whereas the observed cloud absorption is remarkably invariant with respect to season and location. Although its physical cause is unknown, enhanced cloud absorption substantially alters our understanding of the atmospheres energy budget.

The mean climate of the Community Atmosphere Model (CAM4) in forced SST and fully coupled experiments

AbstractThe Community Atmosphere Model, version 4 (CAM4), was released as part of the Community Climate System Model, version 4 (CCSM4). The finite volume (FV) dynamical core is now the default because of its superior transport and conservation properties. Deep convection parameterization changes include a dilute plume calculation of convective available potential energy (CAPE) and the introduction of convective momentum transport (CMT). An additional cloud fraction calculation is now performed following macrophysical state updates to provide improved thermodynamic consistency. A freeze-drying modification is further made to the cloud fraction calculation in very dry environments (e.g., the Arctic), where cloud fraction and cloud water values were often inconsistent in CAM3. In CAM4 the FV dynamical core further degrades the excessive trade-wind simulation, but reduces zonal stress errors at higher latitudes. Plume dilution alleviates much of the midtropospheric tropical dry biases and reduces the persist...

Constrained Variational Analysis of Sounding Data Based on Column-Integrated Budgets of Mass, Heat, Moisture, and Momentum: Approach and Application to ARM Measurements

For the purpose of deriving grid-scale vertical velocity and advective tendencies from sounding measurements, an objective scheme is developed to process atmospheric soundings of winds, temperature, and water vapor mixing ratio over a network of a small number of stations. Given the inevitable uncertainties in the original data, state variables of the atmosphere are adjusted by the smallest possible amount in this scheme to conserve column-integrated mass, moisture, static energy, and momentum. The scheme has the capability of incorporating a variety of supplemental measurements to constrain large-scale vertical velocity and advective tendencies derived from state variables. The method has been implemented to process the Atmospheric Radiation Measurement Program’s (ARM) soundings of winds, temperature, and water vapor mixing ratio at the boundary facilities around the Cloud and Radiation Testbed site in northern Oklahoma in April 1994. It is found that state variables are adjusted by an amount comparable to their measurement uncertainties to satisfy the conservation requirements of mass, water vapor, heat, and momentum. Without these adjustments, spurious residual sources and sinks in the column budget of each quantity have the same magnitudes as other leading components. Sensitivities of the diagnosed vertical velocity and apparent heat, moisture, and momentum sources to the number of conservation constraints are presented. It is shown that constraints of column budget of moisture and dry static energy can make large differences to these diagnostics, especially when some original sounding data are missing and have to be interpolated. Analysis of the moisture budget shows that large-scale convergence often corresponds to precipitation, but there are occasions when precipitation corresponds to a large reduction of column precipitable water and columnmoisture divergence. Analysis of momentum budget shows large magnitudes of subgrid-scale momentum sources and sinks (about 4 m s21 h21) in the convective events.

Stratiform Precipitation, Vertical Heating Profiles, and the Madden-Julian Oscillation

The observed profile of heating through the troposphere in the Madden‐Julian oscillation (MJO) is found to be very top heavy: more so than seasonal-mean heating and systematically more so than all of the seven models for which intraseasonal heating anomaly profiles have been published. Consistently, the Tropical Rainfall Measuring Mission (TRMM) precipitation radar shows that stratiform precipitation (known to heat the upper troposphere and cool the lower troposphere) contributes more to intraseasonal rainfall variations than it does to seasonal-mean rainfall. Stratiform rainfall anomalies lag convective rainfall anomalies by a few days. Reasons for this lag apparently include increased wind shear and middle‐upper tropospheric humidity, which also lag convective (and total) rainfall by a few days. A distinct rearward tilt is seen in anomalous heating time‐height sections, in both the strong December 1992 MJO event observed by the Tropical Ocean Global Atmosphere Coupled Ocean‐Atmosphere Response Experiment (TOGA COARE) and a composite MJO constructed from multiyear datasets. Interpretation is aided by a formal partitioning of the COARE heating section into convective, stratiform, and radiative components. The tilted structure after the maximum surface rainfall appears to be largely contributed by latent and radiative heating in enhanced stratiform anvils. However, the tilt of anomalous heating ahead of maximum rainfall is seen within the convective component, suggesting a change from shallower to deeper convective heating as the wet phase of the MJO approached the longitude of the observations.

Objective Analysis of ARM IOP Data: Method and Sensitivity

Abstract Motivated by the need to obtain accurate objective analysis of field experimental data to force physical parameterizations in numerical models, this paper first reviews the existing objective analysis methods and interpolation schemes that are used to derive atmospheric wind divergence, vertical velocity, and advective tendencies. Advantages and disadvantages of different methods are discussed. It is shown that considerable uncertainties in the analyzed products can result from the use of different analysis. The paper then describes a hybrid approach to combine the strengths of the regular grid and the line-integral methods, together with a variational constraining procedure for the analysis of field experimental data. In addition to the use of upper-air data, measurements at the surface and at the top of the atmosphere (TOA) are used to constrain the upper-air analysis to conserve column-integrated mass, water, energy, and momentum. Analyses are shown for measurements taken in the Atmospheric Ra...

An intercomparison of cloud-resolving models with the atmospheric radiation measurement summer 1997 intensive observation period data

SUMMARY This paper reports an intercomparison study of midlatitude continental cumulus convection simulated by eight two-dimensional and twothree-dimensional cloud-resolving models (CRMs), driven by observed large-scale advective temperature and moisture tendencies, surface turbulent euxes, and radiative-heating proe les during three sub-periods of the summer 1997 Intensive Observation Period of the US Department of Energy’s Atmospheric Radiation Measurement (ARM) program. Each sub-period includes two or three precipitation events of various intensities over a span of 4 or 5 days. The results can be summarized as follows. CRMs can reasonably simulate midlatitude continental summer convection observed at the ARM Cloud and Radiation Testbed site in terms of the intensity of convective activity, and the temperature and specie c-humidity evolution. Delayed occurrences of the initial precipitation events are a common feature for all three sub-cases among the models. Cloud mass e uxes, condensate mixing ratios and hydrometeor fractions produced by all CRMs are similar. Some of the simulated cloud properties such as cloud liquid-water path and hydrometeor fraction are rather similar to available observations. All CRMs produce large downdraught mass euxes with magnitudes similar to those of updraughts, in contrast to CRM results for tropical convection. Some inter-model differences in cloud properties are likely to be related to those in the parametrizations of microphysical processes. There is generally a good agreement between the CRMs and observations with CRMs being signie cantly better than single-column models (SCMs), suggesting that current results are suitable for use in improving parametrizations in SCMs. However, improvements can still be made in the CRM simulations; these include the proper initialization of the CRMs and a more proper method of diagnosing cloud boundaries in model outputs for comparison with satellite and radar cloud observations.

Interpretation of Snow-Climate Feedback as Produced by 17 General Circulation Models

Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer Earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

Intercomparison and evaluation of cumulus parametrizations under summertime midlatitude continental conditions

This study reports the Single-Column Model (SCM) part of the Atmospheric Radiation Measurement (ARM)/the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) joint SCM and Cloud-Resolving Model (CRM) Case 3 intercomparison study, with a focus on evaluation of cumulus parametrizations used in SCMs. Fifteen SCMs are evaluated under summertime midlatitude continental conditions using data collected at the ARM Southern Great Plains site during the summer 1997 Intensive Observing Period. Results from ten CRMs are also used to diagnose problems in the SCMs. It is shown that most SCMs can generally capture well the convective events that were well-developed within the SCM domain, while most of them have difficulties in simulating the occurrence of those convective events that only occurred within a small part of the domain. All models significantly underestimate the surface stratiform precipitation. A third of them produce large errors in surface precipitation and thermodynamic structures. Deficiencies in convective triggering mechanisms are thought to be one of the major reasons. Using a triggering mechanism that is based on the vertical integral of parcel buoyant energy without additional appropriate constraints results in overactive convection, which in turn leads to large systematic warm/dry biases in the troposphere. It is also shown that a non-penetrative convection scheme can underestimate the depth of instability for midlatitude convection, which leads to large systematic cold/moist biases in the troposphere. SCMs agree well quantitatively with CRMs in the updraught mass fluxes, while most models significantly underestimate the downdraught mass fluxes. Neglect of mesoscale updraught and downdraught mass fluxes in the SCMs contributes considerably to the discrepancies between the SCMs and the CRMs. In addition, uncertainties in the diagnosed mass fluxes in the CRMs and deficiencies with cumulus parametrizations are not negligible. Similar results are obtained in the sensitivity tests when different forcing approaches are used. Finally, sensitivity tests from an SCM indicate that its simulations can be greatly improved when its triggering mechanism and closure assumption are improved.