Abstract

The Community Climate System Model, version 2 (CCSM2) is briefly described. A 1000-yr control simulation of the present day climate has been completed without flux adjustments. Minor modifications were made at year 350, which included all five components using the same physical constants. There are very small trends in the upper-ocean, sea ice, atmosphere, and land fields after year 150 of the control simulation. The deep ocean has small but significant trends; however, these are not large enough that the control simulation could not be continued much further. The equilibrium climate sensitivity of CCSM2 is 2.2 K, which is slightly larger than the Climate System Model, version 1 (CSM1) value of 2.0 K.

Several aspects of the control simulation's mean climate and interannual variability are described, and good and bad properties of the control simulation are documented. In particular, several aspects of the simulation, especially in the Arctic region, are much improved over those obtained in CSM1. Other aspects, such as the tropical Pacific region simulation, have not been improved much compared to those in CSM1. Priorities for further model development are discussed in the conclusions section.

Abstract

The Madden–Julian oscillation (MJO) significantly modulates eastern tropical Pacific sea surface temperatures (SSTs) during Northern Hemisphere summer. Typical SST variations during an MJO life cycle are 0.4°–0.5°C. Considerably higher variations occur with the strongest events (1°–2°C). The magnitudes of these variations are comparable to those associated with west Pacific MJO variability during NH winter. SST anomalies to the north of 4°N, where the strongest modulation of east Pacific convection by the MJO occurs, are 180° out of phase with equatorial anomalies. These SST variations are responsible for variations in surface saturation equivalent potential temperatures of greater than 3°C. The highest SSTs lead maximum convection by about 10 days, and SSTs begin to cool with the onset of enhanced convection.

Off-equatorial SST anomalies are most likely due to variations in surface latent heat flux, although shortwave flux anomalies are important in the heart of the MJO convective region. Decreased surface evaporation and increased shortwave fluxes lead maximum SSTs by 10–15 days. Longwave and sensible heat fluxes do not significantly contribute to MJO-related SST variations. MJO-related SST changes on the equator cannot be explained by surface fluxes, and are most likely caused by ocean dynamics.

The effects of eastern Pacific MJO SST anomalies on the surface wind field are explored using the diagnostic primitive equation model of Nigam and Chung. Intraseasonal SST anomalies induce enhanced surface convergence (divergence) about 10 days before maximum (minimum) convection. The combined effects of increased surface convergence and increased equivalent potential temperature may create favorable conditions for MJO convection during periods of warm SST anomalies. A model with interactive convection is needed to fully explore these SST–convection feedbacks.

Abstract

Coupling the NCAR Community Climate Model version 3.6 (CCM3.6) with relaxed Arakawa–Schubert convection to a slab ocean model (SOM) improves the simulation of eastern Pacific convection during a composite June–November intraseasonal oscillation (ISO) life cycle. Intraseasonal oscillations in the SOM simulation produce convective variability over the tropical northeastern Pacific that is similar to that produced by the observed Madden–Julian oscillation (MJO). A composite ISO life cycle in the SOM simulation exhibits stronger, more coherent, and more widespread eastern Pacific warm pool convective anomalies than in a control simulation using climatological SSTs. Competing convective forcings over land and ocean make eastern Pacific low-level circulation anomalies more complex in the SOM simulation than in the observed MJO.

Off-equatorial eastern Pacific SST variations of more than 0.6°C are associated with the June–November SOM simulation ISO. These variations are similar to those observed with the MJO. No significant equatorial east Pacific SST anomalies occur in the model, supporting the contention that observed MJO SST anomalies on the equator are caused by ocean dynamics. Positive off-equatorial SOM simulation SST anomalies are nearly in phase with enhanced precipitation during significant MJO events, whereas observed SST anomalies lead enhanced precipitation by just under 10 days. Latent heat flux and surface shortwave radiation anomalies are the dominant terms in controlling east Pacific intraseasonal SST in the SOM simulation, as in observations. Positive latent heat flux and shortwave radiation anomalies (positive defined as downward into the ocean) lead enhanced SST by about 10 days during significant ISO events in the SOM simulation.

Abstract

In this study, it is shown that the NCAR and GFDL GCMs exhibit a marked difference in climate sensitivity of clouds and radiative fluxes in response to doubled CO₂ and ±2-K SST perturbations. The GFDL model predicted a substantial decrease in cloud amount and an increase in cloud condensate in the warmer climate, but produced a much weaker change in net cloud radiative forcing (CRF) than the NCAR model. Using a multiple linear regression (MLR) method, the full-sky radiative flux change at the top of the atmosphere was successfully decomposed into individual components associated with the clear sky and different types of clouds. The authors specifically examined the cloud feedbacks due to the cloud amount and cloud condensate changes involving low, mid-, and high clouds between 60°S and 60°N. It was found that the NCAR and GFDL models predicted the same sign of individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate for all three types of clouds (low, mid, and high) despite the different cloud and radiation schemes used in the models. However, since the individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate generally have the opposite signs, the net cloud feedback is a subtle residual of all. Strong cancellations between individual cloud feedbacks may result in a weak net cloud feedback. This result is consistent with the findings of the previous studies, which used different approaches to diagnose cloud feedbacks. This study indicates that the proposed MLR approach provides an easy way to efficiently expose the similarity and discrepancy of individual cloud feedback processes between GCMs, which are hidden in the total cloud feedback measured by CRF. Most importantly, this method has the potential to be applied to satellite measurements. Thus, it may serve as a reliable and efficient method to investigate cloud feedback mechanisms on short-term scales by comparing simulations with available observations, which may provide a useful way to identify the cause for the wide spread of cloud feedbacks in GCMs.

Abstract

Climate models differ in their responses to imposed forcings, such as increased greenhouse gas concentrations, due to different climate feedback strengths. Feedbacks in NCAR’s Community Atmospheric Model (CAM) are separated into two components: the change in climate components in response to an imposed forcing and the “radiative kernel,” the effect that climate changes have on the top-of-the-atmosphere (TOA) radiative budget. This technique’s usefulness depends on the linearity of the feedback processes. For the case of CO₂ doubling, the sum of the effects of water vapor, temperature, and surface albedo changes on the TOA clear-sky flux is similar to the clear-sky flux changes directly calculated by CAM. When monthly averages are used rather than values from every time step, the global-average TOA shortwave change is underestimated by a quarter, partially as a result of intramonth correlations of surface albedo with the radiative kernel. The TOA longwave flux changes do not depend on the averaging period. The longwave zonal averages are within 10% of the model-calculated values, while the global average differs by only 2%. Cloud radiative forcing (ΔCRF) is often used as a diagnostic of cloud feedback strength. The net effect of the water vapor, temperature, and surface albedo changes on ΔCRF is −1.6 W m⁻², based on the kernel technique, while the total ΔCRF from CAM is −1.3 W m⁻², indicating these components contribute significantly to ΔCRF and make it more negative. Assuming linearity of the ΔCRF contributions, these results indicate that the net cloud feedback in CAM is positive.

An update is provided on the Earth's global annual mean energy budget in the light of new observations and analyses. In 1997, Kiehl and Trenberth provided a review of past estimates and performed a number of radiative computations to better establish the role of clouds and various greenhouse gases in the overall radiative energy flows, with top-of-atmosphere (TOA) values constrained by Earth Radiation Budget Experiment values from 1985 to 1989, when the TOA values were approximately in balance. The Clouds and the Earth's Radiant Energy System (CERES) measurements from March 2000 to May 2004 are used at TOA but adjusted to an estimated imbalance from the enhanced greenhouse effect of 0.9 W m⁻². Revised estimates of surface turbulent fluxes are made based on various sources. The partitioning of solar radiation in the atmosphere is based in part on the International Satellite Cloud Climatology Project (ISCCP) FD computations that utilize the global ISCCP cloud data every 3 h, and also accounts for increased atmospheric absorption by water vapor and aerosols.

Surface upward longwave radiation is adjusted to account for spatial and temporal variability. A lack of closure in the energy balance at the surface is accommodated by making modest changes to surface fluxes, with the downward longwave radiation as the main residual to ensure a balance.

Values are also presented for the land and ocean domains that include a net transport of energy from ocean to land of 2.2 petawatts (PW) of which 3.2 PW is from moisture (latent energy) transport, while net dry static energy transport is from land to ocean. Evaluations of atmospheric reanalyses reveal substantial biases.

Abstract

This study examines the response of the climate simulation by the National Center for Atmospheric Research Community Climate Model (CCM3) to the introduction of the Zhang and McFarlane convective parameterization in the model. It is shown that in the CCM3 the simulated surface climate in the tropical convective regimes, especially in the western Pacific warm pool, is markedly improved, yielding a much better agreement with the recent observations. The systematic bias in the surface evaporation, surface wind stress over the tropical Pacific Ocean in previous model simulations is significantly reduced, owing to the better simulation of the surface flow.

Experiments using identical initial and boundary conditions, but different convection schemes, are performed to isolate the role of the convection schemes and to understand the interaction between convection and the large-scale circulation in a convecting atmosphere. The comparison of the results from these experiments in the western Pacific warm pool suggests that use of the Zhang and McFarlane scheme makes a significant contribution to the improved climate simulation in CCM3. The simulated atmosphere using the Zhang and McFarlane scheme exhibits a quasi-equilibrium between convection and the large-scale processes. When this scheme is removed from the CCM3, such a quasi-equilibrium is no longer observed. In addition, the simulated thermodynamic structures, the surface evaporation, and surface winds in the Pacific warm pool become very similar to those in the CCM2 climate.

Examination of the temporal evolution of the various fields demonstrates that the stabilization of the atmosphere using the new convection scheme takes place during the transition from nonequilibrium to quasi equilibrium at the beginning of the time integration. After quasi equilibrium is reached, the atmosphere is warmer and more stable compared to the run without the new scheme. Associated with the more stable stratification, the atmospheric circulation becomes weaker, thus the surface winds and evaporation are weaker because of the coupling between thermodynamics and dynamics in the tropical troposphere.

Abstract

Climatological properties for selected aspects of the thermodynamic structure and hydrologic cycle are presented from a 15-yr numerical simulation conducted with the National Center for Atmospheric Research Community Climate Model, version 3 (CCM3), using an observed sea surface temperature climatology. In most regards, the simulated thermal structure and hydrologic cycle represent a marked improvement when compared with earlier versions of the CCM. Three major modifications to parameterized physics are primarily responsible for the more notable improvements in the simulation: modifications to the diagnosis of cloud optical properties, modifications to the diagnosis of boundary layer processes, and the incorporation of a penetrative formulation for deep cumulus convection. The various roles of these physical parameterization changes will be discussed in the context of the simulation strengths and weaknesses.

Abstract

The effects of the south Asian haze on the regional climate are assessed using the National Center for Atmospheric Research Community Climate Model version 3 (CCM3) at the T42/L18 resolution. This haze, as documented during the Indian Ocean Experiment (INDOEX) campaign (1995–2000), consists mainly of anthropogenic aerosols, and spans over most of south Asia and the north Indian Ocean. It reduces the net solar flux at the surface by as much as 20–40 W m⁻² on a monthly mean basis and heats the lowest 3-km atmosphere by as much as 0.4–0.8 K day⁻¹, which enhances the solar heating of this layer by 50%–100%. This widespread haze layer is a seasonal phenomenon limited to the dry period between November and May.

The imposed haze radiative forcing leads to several large and statistically significant climate changes during the dry monsoon season, which include cooling of the land surface, and warming of the atmosphere. These temperature change features lead to the stabilization of the boundary layer that results in a reduction of evaporation and sensible heat flux from the land. The dynamical response to the aerosol forcing is surprisingly large. The aerosol forcing weakens the north–south temperature gradient in the lower level, which results in an enhancement of the area mean low-level convergence and a northward shift of the ITCZ. The increase in low-level convergence leads to increased convective rainfall and latent heat release, which in turn leads to a further increase in low-level convergence. This positive feedback between the low-level convergence and deep convective heating increases the average precipitation over the haze area by as much as 20%. The ocean surface undergoes a suppression of evaporation. Because of this decreased evaporation accompanied by the increase in the haze-area precipitation, the precipitation over the rest of the Tropics decreases, with a large fraction of this decrease concentrated over the Indonesian and the western Pacific warm pool region. The prescribed dry monsoon haze effect affects the summertime wet monsoon too, but a detailed analysis has to await the availability of year-round aerosol data.

The major inference from this study is that the effects of absorbing aerosols on the regional climate can be quite large. The simulated surface temperature response was very sensitive to the ratio (R) of the surface aerosol forcing to the atmospheric forcing. The R itself varies from −1.5 in clear skies to about −0.5 in overcast skies over ocean, and available experimental data are not sufficient to constrain its value more narrowly.

Abstract

Climate model simulations of the latter part of the twentieth century indicate a warming of the troposphere that is equal to or larger than the warming at the surface, while satellite observations from the Microwave Sounding Unit (MSU) indicate little warming of the troposphere relative to surface observations. Recently, Fu et al. proposed a new approach to retrieving free tropospheric temperature trends from MSU data that better accounts for stratospheric cooling, which contaminates the tropospheric signal and leads to a smaller trend in tropospheric warming. In this study, climate model simulations are used as a self-consistent dataset to test these retrieval algorithms. The two methods of retrieving tropospheric temperature trends are applied to three climate model simulations of the twentieth century. The Fu et al. algorithm is found to be in very good agreement with the model-simulated tropospheric warming, indicating that it accurately accounts for cooling from the lower stratosphere.