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Ping Liu
,
Qin Zhang
,
Chidong Zhang
,
Yuejian Zhu
,
Marat Khairoutdinov
,
Hye-Mi Kim
,
Courtney Schumacher
, and
Minghua Zhang

Abstract

This study investigates why OLR plays a small role in the Real-time Multivariate (Madden–Julian oscillation) MJO (RMM) index and how to improve it. The RMM index consists of the first two leading principal components (PCs) of a covariance matrix, which is constructed by combined daily anomalies of OLR and zonal winds at 850 (U850) and 200 hPa (U200) in the tropics after being normalized with their globally averaged standard deviations of 15.3 W m−2, 1.8 m s−1, and 4.9 m s−1, respectively. This covariance matrix is reasoned mathematically close to a correlation matrix. Both matrices substantially suppress the overall contribution of OLR and make the index more dynamical and nearly transparent to the convective initiation of the MJO. A covariance matrix that does not use normalized anomalies leads to the other extreme where OLR plays a dominant role while U850 and U200 are minor. Numerous tests indicate that a simple scaling of the anomalies (i.e., 2 W m−2, 1 m s−1, and 1 m s−1) can better balance the roles of OLR and winds. The revised PCs substantially enhance OLR over the eastern Indian and western Pacific Oceans and change it less notably in other locations, while they reduce U850 and U200 only slightly. Comparisons with the original RMM in spatial structure, power spectra, and standard deviation demonstrate improvements of the revised RMM index.

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Chen-Geng Ma
,
Edmund K. M. Chang
,
Sun Wong
,
Rui Zhang
,
Minghua Zhang
, and
Anthony Del Genio

Abstract

Previous studies have shown that variations in extratropical cyclone activity significantly affect the frequency of extreme precipitation events over the Ohio Valley and northwestern United States. In this study, we examine the similarities and differences between the dynamics governing these events in these two regions. In the Ohio Valley, extreme precipitation events are associated with midlatitude synoptic-scale convergence northeast of cyclones and a southwestward oriented ridge near the Atlantic coast that drives strong water vapor transport from the Gulf of Mexico into the Ohio Valley. In the northwestern United States, extreme precipitation events are associated with a cyclonic and anticyclonic circulation pair aligned northwest to southeast, which together drive a long and strong moisture transport corridor from the lower latitude of the central Pacific Ocean toward the northwestern United States. Moisture budget analysis shows that moisture convergence due to dynamical convergence dominates in the Ohio Valley, whereas moisture advection dominates over the Pacific Northwest. Differences between the cases in the same region are examined by an empirical orthogonal function (EOF) analysis conducted on the vertically integrated moisture flux. Different EOFs highlight shifts in spatial location, orientation, and intensity of the moisture flux but demonstrate consistent roles of dynamics in the two regions. Composites based on these EOFs highlight the range of likely synoptic scenarios that can give rise to precipitation extremes over these two regions.

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Xiping Zeng
,
Wei-Kuo Tao
,
Toshihisa Matsui
,
Shaocheng Xie
,
Stephen Lang
,
Minghua Zhang
,
David O’C Starr
, and
Xiaowen Li

Abstract

The ice crystal enhancement (IE) factor, defined as the ratio of the ice crystal to ice nuclei (IN) number concentrations for any particular cloud condition, is needed to quantify the contribution of changes in IN to global warming. However, the ensemble characteristics of IE are still unclear. In this paper, a representation of the IE factor is incorporated into a three-ice-category microphysical scheme for use in long-term cloud-resolving model (CRM) simulations. Model results are compared with remote sensing observations, which suggest that, absent a physically based consideration of how IE comes about, the IE factor in tropical clouds is about 103 times larger than that in midlatitudinal ones. This significant difference in IE between the tropics and middle latitudes is consistent with the observation of stronger entrainment and detrainment in the tropics. In addition, the difference also suggests that cloud microphysical parameterizations depend on spatial resolution (or subgrid turbulence parameterizations within CRMs).

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Xiping Zeng
,
Wei-Kuo Tao
,
Minghua Zhang
,
Arthur Y. Hou
,
Shaocheng Xie
,
Stephen Lang
,
Xiaowen Li
,
David O’C. Starr
,
Xiaofan Li
, and
Joanne Simpson

Abstract

A three-dimensional cloud-resolving model (CRM) with observed large-scale forcing is used to study how ice nuclei (IN) affect the net radiative flux at the top of the atmosphere (TOA). In all the numerical experiments carried out, the cloud ice content in the upper troposphere increases with IN number concentration via the Bergeron process. As a result, the upward solar flux at the TOA increases whereas the infrared one decreases. Because of the opposite response of the two fluxes to IN concentration, the sensitivity of the net radiative flux at the TOA to IN concentration varies from one case to another.

Six tropical and three midlatitudinal field campaigns provide data to model the effect of IN on radiation in different latitudes. Classifying the CRM simulations into tropical and midlatitudinal and then comparing the two types reveals that the indirect effect of IN on radiation is greater in the middle latitudes than in the tropics. Furthermore, comparisons between model results and observations suggest that observational IN data are necessary to evaluate long-term CRM simulations.

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Richard B. Neale
,
Jadwiga Richter
,
Sungsu Park
,
Peter H. Lauritzen
,
Stephen J. Vavrus
,
Philip J. Rasch
, and
Minghua Zhang

Abstract

The 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 persistent monsoon precipitation biases over the Arabian Peninsula and the southern Indian Ocean. CMT reduces much of the excessive trade-wind biases in eastern ocean basins. CAM4 shows a global reduction in cloud fraction compared to CAM3, primarily as a result of the freeze-drying and improved cloud fraction equilibrium modifications. Regional climate feature improvements include the propagation of stationary waves from the Pacific into midlatitudes and the seasonal frequency of Northern Hemisphere blocking events. A 1° versus 2° horizontal resolution of the FV dynamical core exhibits superior improvements in regional climate features of precipitation and surface stress. Improvements in the fully coupled mean climate between CAM3 and CAM4 are also more substantial than in forced sea surface temperature (SST) simulations.

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Robert D. Cess
,
Minghua Zhang
,
Bruce A. Wielicki
,
David F. Young
,
Xue-Long Zhou
, and
Yuri Nikitenko

Abstract

Clouds cool the climate system by reflecting shortwave radiation and warm it by increasing the atmospheric greenhouse. Previous studies have shown that in tropical regions of deep convection there is a near cancellation between cloud-induced shortwave cooling and longwave warming. The present study investigates the possible influence of the 1998 El Niño upon this near cancellation for the tropical western Pacific’s warm pool; this was accomplished by employing satellite radiometric measurements (Earth Radiation Budget Experiment, and Clouds and the Earth’s Radiant Energy System). With the exclusion of the 1998 El Niño, this study also finds near cancellation between the shortwave and longwave cloud forcings and demonstrates that it refers to the average of different cloud types rather than being indicative of a single cloud type. The shortwave cooling slightly dominates the longwave warming, and there is considerable interannual variability in this modest dominance that appears attributable to interannual variability of tropopause temperature. For the strong 1998 El Niño, however, there is a substantially greater tendency toward net radiative cooling, and the physical mechanism for this appears to be a change in cloud vertical structure. For normal years, as well as for the weaker 1987 El Niño, high clouds dominate the radiation budget over the warm pool. In 1998, however, the measurements indicate the radiation budget is partially governed by middle-level clouds, thus explaining the net cooling over the warm pool during the 1998 El Niño as well as emphasizing differences between this event and the weaker 1987 El Niño.

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Xiping Zeng
,
Wei-Kuo Tao
,
Minghua Zhang
,
Christa Peters-Lidard
,
Stephen Lang
,
Joanne Simpson
,
Sujay Kumar
,
Shaocheng Xie
,
Joseph L. Eastman
,
Chung-Lin Shie
, and
James V. Geiger

Abstract

Two 20-day, continental midlatitude cases are simulated with a three-dimensional (3D) cloud-resolving model (CRM) and are compared to Atmospheric Radiation Measurement Program (ARM) data. Surface fluxes from ARM ground stations and a land data assimilation system are used to drive the CRM. This modeling evaluation shows that the model simulates precipitation well but overpredicts clouds, especially in the upper troposphere. The evaluation also shows that the ARM surface fluxes can have noticeable errors in summertime.

Theoretical analysis reveals that buoyancy damping is sensitive to spatial smoothers in two-dimensional (2D) CRMs, but not in 3D ones. With this theoretical analysis and the ARM cloud observations as background, 2D and 3D simulations are compared, showing that the 2D CRM has not only rapid fluctuations in surface precipitation but also spurious dehumidification (or a decrease in cloud amount). The present study suggests that the rapid precipitation fluctuation and spurious dehumidification be attributed to the sensitivity of buoyancy damping to dimensionality.

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William D. Collins
,
Philip J. Rasch
,
Byron A. Boville
,
James J. Hack
,
James R. McCaa
,
David L. Williamson
,
Bruce P. Briegleb
,
Cecilia M. Bitz
,
Shian-Jiann Lin
, and
Minghua Zhang

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 surface temperatures, surface insolation, and clear-sky surface radiation in polar regions. The variation of cloud radiative forcing during ENSO events exhibits much better agreement with satellite observations. Despite these improvements, several systematic biases reduce the fidelity of the simulations. These biases include underestimation of tropical variability, errors in tropical oceanic surface fluxes, underestimation of implied ocean heat transport in the Southern Hemisphere, excessive surface stress in the storm tracks, and offsets in the 500-mb height field and the Aleutian low.

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Peter R. Gent
,
Gokhan Danabasoglu
,
Leo J. Donner
,
Marika M. Holland
,
Elizabeth C. Hunke
,
Steve R. Jayne
,
David M. Lawrence
,
Richard B. Neale
,
Philip J. Rasch
,
Mariana Vertenstein
,
Patrick H. Worley
,
Zong-Liang Yang
, and
Minghua Zhang

Abstract

The 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 Niño–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 circulation. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than CCSM3, and for several reasons the Arctic sea ice concentration is improved in CCSM4. An ensemble of twentieth-century simulations produces a good match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4°C. This is consistent with the fact that CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of shortwave and longwave cloud forcings.

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