Superparameterized Community Atmosphere Model Research Articles

“Super‐parameterization”: A better way to simulate regional extreme precipitation?

Extreme precipitation is generally underestimated by current climate models relative to observations of present‐day rainfall distributions. Possible causes of this systematic error include the convective parameterization in these models that have been designed to reproduce measurements of climatological mean precipitation. One possible approach to improve the interaction of subgrid‐scale physical processes and large‐scale climate is to replace the conventional convective parameterizations with a high‐resolution cloud‐system resolving model. A “super‐parameterized” Community Atmosphere Model (SP‐CAM) utilizing this approach is used in this study to investigate the distribution of extreme precipitation in the United States. Results show that SP‐CAM better simulates the distributions of both light and intense precipitation compared to the standard version of CAM based upon conventional parameterizations. The improvements are mostly seen in regions dominated by convective precipitation, suggesting that super‐parameterization provides a better representation of subgrid convective processes.

Monsoon intraseasonal oscillations as simulated by the superparameterized Community Atmosphere Model

The relative success of the Community Atmosphere Model with superparameterized convection (SP-CAM) in simulating the space-time characteristics of the Madden Julian Oscillation encourages us to examine its simulation of the Indian summer monsoon and monsoon intraseasonal oscillations (MISOs). While the model simulates the onset and withdrawal of the Indian monsoon realistically, it has a significant wet bias in boreal summer precipitation over the Asian monsoon region. The space-time characteristics of the MISOs simulated by the SP-CAM are examined in detail and compared with those of the observed MISO to gain insight into the model's bias in simulating the seasonal mean. During northern summer, the model simulates a 20 day mode and a 60 day mode in place of the observed 15 and 45 day modes, respectively. The simulated 20 day mode appears to have no observed analog with a baroclinic vertical structure and strong northward propagation over Indian longitudes. The simulated 60 day mode seems to be a lower-frequency version of the observed 45 day mode with relatively slower northward propagation. The model's underestimation of light rain events and overestimation of heavy rain events are shown to be responsible for the wet bias of the model. More frequent occurrence of heavy rain events in the model is, in turn, related to the vertical structure of the higher-frequency modes. Northward propagation of the simulated 20 day mode is associated with a strong cyclonic vorticity at low levels north of the heating maximum associated with a smaller meridional scale of the simulated mode. The simulated vertical structure of heating indicates a strong maximum in the upper troposphere between 200 and 300 hPa. Such a heating profile seems to generate a higher-order baroclinic mode response with smaller meridional structure, stronger low-level cyclonic vorticity, enhanced low-level moisture convergence, and higher precipitation. Therefore, the vertical structure of heating simulated by the cloud-resolving model within SP-CAM may hold the key for improving the precipitation bias in the model.

The Asian Monsoon in the Superparameterized CCSM and Its Relationship to Tropical Wave Activity

Three general circulation models (GCMs) are used to analyze the impacts of air–sea coupling and superparameterized (SP) convection on the Asian summer monsoon: Community Climate System Model (CCSM) (coupled, conventional convection), SP Community Atmosphere Model (SP-CAM) (uncoupled, SP convection), and SP-CCSM (coupled, SP). In SP-CCSM, coupling improves the basic-state climate relative to SP-CAM and reduces excessive tropical variability in SP-CAM. Adding SP improves tropical variability, the simulation of easterly zonal shear over the Indian and western Pacific Oceans, and increases negative sea surface temperature (SST) biases in that region. SP-CCSM is the only model to reasonably simulate the eastward-, westward-, and northward-propagating components of the Asian monsoon. CCSM and SP-CCSM mimic the observed phasing of northward-propagating intraseasonal oscillation (NPISO), SST, precipitation, and surface stress anomalies, while SP-CAM is limited in this regard. SP-CCSM produces a variety of tropical waves with spectral characteristics similar to those in observations. Simulated equatorial Rossby (ER) and mixed Rossby–gravity (MRG) waves may lead to different simulations of the NPISO in each model. Each model exhibits some northward propagation for ER waves but only SP-CCSM produces northward-propagating MRG waves, as in observations. The combination of ER and MRG waves over the Indian Ocean influences the spatiotemporal structure of the NPISO and contributes to the differences seen in each model. The role of ocean coupling must be considered in terms of the time scale of the SST response compared to the time scale of tropical variability. High-frequency disturbances experience coupling via its changes to the basic state, while lower-frequency disturbances may respond directly to SST fluctuations.

Temperature and Water Vapor Variance Scaling in Global Models: Comparisons to Satellite and Aircraft Data

AbstractObservations of the scale dependence of height-resolved temperature T and water vapor q variability are valuable for improved subgrid-scale climate model parameterizations and model evaluation. Variance spectral benchmarks for T and q obtained from the Atmospheric Infrared Sounder (AIRS) are compared to those generated by state-of-the-art numerical weather prediction “analyses” and “free-running” climate model simulations with spatial resolution comparable to AIRS. The T and q spectra from both types of models are generally too steep, with small-scale variance up to several factors smaller than AIRS. However, the two model analyses more closely resemble AIRS than the two free-running model simulations. Scaling exponents obtained for AIRS column water vapor (CWV) and height-resolved layers of q are also compared to the superparameterized Community Atmospheric Model (SP-CAM), highlighting large differences in the magnitude of CWV variance and the relative flatness of height-resolved q scaling in SP-CAM. Height-resolved q spectra obtained from aircraft observations during the Variability of the American Monsoon Systems Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) demonstrate changes in scaling exponents that depend on the observations’ proximity to the base of the subsidence inversion with scale breaks that occur at approximately the dominant cloud scale (~10–30 km). This suggests that finer spatial resolution requirements must be considered for future satellite observations of T and q than those currently planned for infrared and microwave satellite sounders.

Impacts of Idealized Air–Sea Coupling on Madden–Julian Oscillation Structure in the Superparameterized CAM

Abstract Air–sea interactions and their impact on intraseasonal convective organization are investigated by comparing two 5-yr simulations from the superparameterized Community Atmosphere Model version 3.0 (SP-CAM). The first is forced using prescribed sea surface temperatures (SSTs). The second is identical except that a simplified oceanic mixed-layer model is used to predict tropical SST anomalies that are coupled to the atmosphere. This partially coupled simulation allows SSTs to respond to anomalous surface fluxes. Implementation of the idealized slab ocean model in the SP-CAM results in significant changes to intraseasonal convective variability and organization. The more realistic treatment of air–sea interactions in the coupled simulation improves many aspects of tropical convection on intraseasonal scales, from the relationships between precipitation and SSTs to the space–time structure and propagation of the Madden–Julian oscillation (MJO). This improvement is associated with a more realistic convergence structure and longitudinal gradient of SST relative to MJO deep convection. In the uncoupled SP-CAM, SST is roughly in phase with the MJO convective center and the development of the Kelvin wave response and boundary layer convergence east of the convective center is relatively weak. In the coupled SP-CAM, maxima in SST lead maxima in MJO convection by cycle. Coupling produces warmer SSTs, a stronger Kelvin wave response, enhanced low-level convergence, and increased convective heating ahead (east) of the MJO convective center. Convective development east of the MJO precipitation center is more favorable in the coupled versus the uncoupled version, resulting in more realistic organization and clearer eastward propagation of the MJO in the coupled SP-CAM.

Orogenic Propagating Precipitation Systems over the United States in a Global Climate Model with Embedded Explicit Convection

Abstract In the lee of major mountain chains worldwide, diurnal physics of organized propagating convection project onto seasonal and climate time scales of the hydrologic cycle, but this phenomenon is not represented in conventional global climate models (GCMs). Analysis of an experimental version of the superparameterized (SP) Community Atmosphere Model (CAM) demonstrates that propagating orogenic nocturnal convection in the central U.S. warm season is, however, representable in GCMs that use the embedded explicit convection model approach [i.e., multiscale modeling frameworks (MMFs)]. SP-CAM admits propagating organized convective systems in the lee of the Rockies during synoptic conditions similar to those that generate mesoscale convective systems in nature. The simulated convective systems exhibit spatial scales, phase speeds, and propagation speeds comparable to radar observations, and the genesis mechanism in the model agrees qualitatively with established conceptual models. Convective heating and condensate structures are examined on both resolved scales in SP-CAM, and coherently propagating cloud “metastructures” are shown to transcend individual cloud-resolving model arrays. In reconciling how this new mode of diurnal convective variability is admitted in SP-CAM despite the severe idealizations in the cloud-resolving model configuration, an updated discussion is presented of what physics may transcend the re-engineered scale interface in MMFs. The authors suggest that the improved diurnal propagation physics in SP-CAM are mediated by large-scale first-baroclinic gravity wave interactions with a prognostic organization life cycle, emphasizing the physical importance of preserving “memory” at the inner resolved scale.

Application of MJO Simulation Diagnostics to Climate Models

Abstract The ability of eight climate models to simulate the Madden–Julian oscillation (MJO) is examined using diagnostics developed by the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group. Although the MJO signal has been extracted throughout the annual cycle, this study focuses on the boreal winter (November–April) behavior. Initially, maps of the mean state and variance and equatorial space–time spectra of 850-hPa zonal wind and precipitation are compared with observations. Models best represent the intraseasonal space–time spectral peak in the zonal wind compared to that of precipitation. Using the phase–space representation of the multivariate principal components (PCs), the life cycle properties of the simulated MJOs are extracted, including the ability to represent how the MJO evolves from a given subphase and the associated decay time scales. On average, the MJO decay (e-folding) time scale for all models is shorter (∼20–29 days) than observations (∼31 days). All models are able to produce a leading pair of multivariate principal components that represents eastward propagation of intraseasonal wind and precipitation anomalies, although the fraction of the variance is smaller than observed for all models. In some cases, the dominant time scale of these PCs is outside of the 30–80-day band. Several key variables associated with the model’s MJO are investigated, including the surface latent heat flux, boundary layer (925 hPa) moisture convergence, and the vertical structure of moisture. Low-level moisture convergence ahead (east) of convection is associated with eastward propagation in most of the models. A few models are also able to simulate the gradual moistening of the lower troposphere that precedes observed MJO convection, as well as the observed geographical difference in the vertical structure of moisture associated with the MJO. The dependence of rainfall on lower tropospheric relative humidity and the fraction of rainfall that is stratiform are also discussed, including implications these diagnostics have for MJO simulation. Based on having the most realistic intraseasonal multivariate empirical orthogonal functions, principal component power spectra, equatorial eastward propagating outgoing longwave radiation (OLR), latent heat flux, low-level moisture convergence signals, and vertical structure of moisture over the Eastern Hemisphere, the superparameterized Community Atmosphere Model (SPCAM) and the ECHAM4/Ocean Isopycnal Model (OPYC) show the best skill at representing the MJO.

Structure of the Madden–Julian Oscillation in the Superparameterized CAM

Abstract The detailed dynamic and thermodynamic space–time structures of the Madden–Julian oscillation (MJO) as simulated by the superparameterized Community Atmosphere Model version 3.0 (SP-CAM) are analyzed. Superparameterization involves substituting conventional boundary layer, moist convection, and cloud parameterizations with a configuration of cloud-resolving models (CRMs) embedded in each general circulation model (GCM) grid cell. Unlike most GCMs that implement conventional parameterizations, the SP-CAM displays robust atmospheric variability on intraseasonal space and time (30–60 days) scales. The authors examine a 19-yr SP-CAM simulation based on the Atmospheric Model Intercomparison Project protocol, forced by prescribed sea surface temperatures. Overall, the space–time structures of MJO convective disturbances are very well represented in the SP-CAM. Compared to observations, the model produces a similar vertical progression of increased moisture, warmth, and heating from the boundary layer to the upper troposphere as deep convection matures. Additionally, important advective and convective processes in the SP-CAM compare favorably with those in observations. A deficiency of the SP-CAM is that simulated convective intensity organized on intraseasonal space–time scales is overestimated, particularly in the west Pacific. These simulated convective biases are likely due to several factors including unrealistic boundary layer interactions, a lack of weakening of the simulated disturbance over the Maritime Continent, and mean state differences.