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John Molinari and Michael Dudek

Abstract

Current approaches for incorporating cumulus convection into mesoscale numerical models are divided into three groups. The traditional approach utilizes cumulus parameterization at convectively unstable points and explicit (nonparameterized) condensation at convectively stable points, The fully explicit approach uses explicit methods regardless of stability. The hybrid approach parameterizes convective scale updrafts and downdrafts, but “detrains” a fraction of parameterized cloud and precipitation particles to the grid scale. This allows the path and phase changes of such particles to be explicitly predicted over subsequent time steps.

The traditional approach provides the only alternative for numerical models with grid spacing too large to resolve mesoscale structure. As grid spacing falls below 50 km, the traditional approach becomes increasingly likely to violate fundamental scale-separation requirements of parameterization, particularly if mesoscale organization of convection is parameterized as well. The fully explicit approach has no such limits, but it has repeatedly failed in mesoscale models in the presence of large convective instability. Although it is preferable under certain specialized circumstances, the fully explicit approach cannot provide a general solution for models with grid spacing above 5–10 km.

The hybrid approach most cleanly separates convective-scale motions from the slow growth, fallout, and phase changes of detrained hydrometeors that produces mesoscale organization of convection. It is argued that this characteristic removes the need to parameterize the mesoscale and thus reduces the scale-separation problems that may arise when the traditional approach is used. The hybrid approach provides in principle the preferred solution for mesoscale models, though such promise has yet to be fully realized.

In the absence of large rotation, the fundamental assumptions of cumulus parameterization begin to break down once grid spacing falls below 20–25 km. For models with such resolution, the time scale of the convection being parameterized approaches the characteristic time scale of the grid, and parameterized and unparameterized convective clouds often exist simultaneously in a grid column. Under such ambiguous circumstances, successful simulations have been produced only because parameterized convection rapidly gives way in the, model to its grid-scale counterpart. It is essential to understand the interactions between implicit and explicit clouds that produce this transition, and whether they represent physical processes in nature, before cumulus parameterization can be widely used in such high-resolution models. In a broader sense, more detailed analysis of why convective parameterizations succeed and fall is needed.

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John Molinari and Michael Dudek

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John Molinari and Michael Dudek

Abstract

The ability of several explicit formulations of convective heating to predict the precipitation associated with a mesoscale convective complex was compared to that of a cumulus parameterization on a ½ deg latitude-longitude mesh. In the explicit approaches, prediction equations were present for both water vapor and cloud water, or vapor alone. The simplest explicit approach, for which any condensed water was assumed to fall immediately as rain, produced localized excessive rainfall. This explicit heating instability arose as a result of the requirements of saturation prior to rainfall, which delayed condensation and allowed excessive convective instability to build, and neglect of fluxes, which prevented the instability from being released in a realistic manner. These results, combined with those of previous investigators, indicate that the simplest form of explicit heating is prone to instability and unsuitable for mesoscale models.

Instability problems were significantly reduced by the inclusion of the inhibiting effects of rainwater evaporation and a cloud phase with hydrostatic water loading, Nevertheless, bemuse significant nor occurred in nature in the absence of area-averaged saturation, rainfall was unrealistically delayed when a 100 percent saturation criterion was used. Reducing the saturation criterion improved the phase error of the rainfall prediction, but sometimes reintroduced local instability.

Although only simple explicit formulations were used, inclusion of more sophisticated microphysical parameterizations from cloud models may be unrepresentative of processes in nature for meso-α scale models, for which the grid spacing exceeds 50 km. It is proposed for such models that implicit approaches offer the greatest potential for improvement. For meso-β scale models the optimum choice remains uncertain.

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Xin-Zhong Liang, Wei-Chyung Wang, and Michael P. Dudek

Abstract

Observed and general circulation climate model (GCM) simulated interannual teleconnection patterns in the Northern Hemisphere are compared on a monthly basis. The study was based on 1946–1991 observations and two separate 100-year simulations corresponding to the present climate and a greenhouse warming climate. The teleconnection patterns are characterized by action centers and composite extreme anomaly (CEA) distributions. The definition and comparison of observed and simulated patterns include examination of time persistence, spatial coherence as well as consistent signatures between 500-mb height, sea level pressure, and surface air temperature.

For the present climate simulation, the GCM reproduces observed spatial and temporal variations of the action centers of four principal teleconnection patterns: the North Atlantic oscillation, the North Pacific oscillation, the Pacific/North American pattern, and the Eurasian pattern. Substantial model biases exist in the magnitude, regional structure as well as monthly transition of anomalies. The CEA regional characteristics are better simulated over land than over the oceans. For example, the model most accurately simulates the Eurasian pattern, which has its dominant action centers over Eurasia. In addition, all three climate variables exhibit substantial anomalies for each land-based action center. In contrast, over the oceans, the model systematically underestimates sea level pressure and 500-mb height CEAs, while it produces small surface temperature responses. It is suggested that atmospheric dynamics associated with flow instability is likely to be the dominant mechanism that generates these teleconnections, while the lack of interactive ocean dynamics may be responsible for small responses over the oceans.

In the greenhouse warming climate, the GCM continues to simulate the four interannual teleconnection patterns. Systematic changes, however, are found for the Pacific/North American and Eurasian patterns in winter, where the action centers shift to the east and the CEAs weaken over land. These results must be considered to be exploratory because of the use of a mixed layer ocean that does not include oceanic dynamics.

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Michael P. Dudek, Xin-Zhong Liang, and Wei-Chyung Wang

Abstract

The scale dependence of cloud-radiation interaction associated with the parameterizations for fractional cloudiness and radiation used in a global climate model is studied by examining the averages, for different spatial scales, of detailed structure of cloudiness and radiation simulated from a regional climate model that incorporates these parameterizations. The regional model simulation is conducted over an area about (360 km)2 located on the southern Great Plains for the period 10–17 April 1994 during which both satellite and surface measurements of radiation fluxes and clouds are available from the Intensive Observing Period of the Atmospheric Radiation Measurement program. The area corresponds approximately to one gridpoint size of a global climate model with horizontal resolution T31.

The regional model simulates well the overall cloud and radiation temporal features when averaged over the entire region. However, specific biases exist in the spatial patterns such as the high clouds, the TOA upwelling solar radiation under cloudy conditions, and the net longwave surface flux under clear conditions at night. The cloud and radiation parameterizations are found to be sensitive to the spatial scale of the computation. The diagnosed total cloudiness shows a strong horizontal resolution dependence that leads to large changes in the surface and TOA radiation budgets. An additional experiment, in which the diagnosed cloud at each level is held constant while the radiation parameterization is recalculated, still produces a substantial sensitivity to spatial scale in the calculated radiation quantities. This is because the nature of the cloud vertical overlapping assumption changes as the horizontal scale of the computation varies.

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