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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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