Analysis of Typhoon Tropical Cyclogenesis in an Atmospheric General Circulation Model

1. Analysis of Typhoon Tropical Cyclogenesis in an Atmospheric General Circulation Model Suzana J. Camargo and Adam H. Sobel

2. Introduction • Tropical Cyclones in AGCMs • Detecting and tracking model tropical cyclones in AGCMs • Composites of western North Pacific model tropical cyclones • Properties of the composites • Conclusions 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

3. Introduction • Large impacts hurricanes, typhoons and tropical cyclones on society. • Forecasting of seasonal tropical cyclone activity is important. • Routine seasonal forecasts of tropical storm frequency in the Atlantic and other regions (Western North Pacific, Australia) are produced using STATISTICAL methods. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

4. DYNAMICAL forecasting of seasonal hurricane activity is another promising approach. • Dynamical forecasts of tropical cyclone activity are currently produced experimentally at ECMWF using a coupled ocean-atmosphere model. • Possible approaches to dynamical forecasts: - Seasonal prediction of large-scale variables known to affect tropical storm activity using AGCMs. - Detection of tropical cyclone-like structures in low-resolution AGCMs and coupled models. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

5. Tropical Cyclones in AGCMs • Numerous studies showed that AGCMs can create model tropical cyclones with strong similarities to observed tropical cyclones: • Cyclonic vorticity, convergence and high moisture content at lower levels. • Heavy precipitation and local maximum of surface winds. • Strong upward motion, positive local temperature anomaly throughout the troposphere. • Anti-cyclonic vorticity and divergency at upper levels. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

6. Development in areas of SSTs above 26oC. • Vertical structure similar to observed tropical cyclones composites. • Model tropical cyclones in LOW resolution AGCMs have deficiencies: • Lack the presence of an eye, eye-wall and rainbands. • Horizontal extension larger than observed tropical cyclones. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

7. Deficiencies mostly impact the intensityof the model tropical cyclones. • Unlikely to have a strong impact on the seasonal variability of the tropical cyclone activity. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

8. Typical model tropical cyclone -Vorticity 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

9. Typical model tropical cyclone – Surface Pressure 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

10. Typical model tropical cyclone – Surface wind speed 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

11. Typical model tropical cyclone - Precipitation 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

12. Detectingand tracking model tropical cyclones • The detection algorithm requires that: • 850hPa relative vorticity, • the surface wind speed, • the local temperature anomaly at different pressure levels throughout the troposphere; • and the sea level pressure simultaneously satisfy a set of threshold criteria, which are defined using the model statistics. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

13. A model tropical cyclone must satisfy all the criteria above for at least 1.5 days. • The model tropical cyclone is then tracked using a relaxed criteria for the 850hPa relative vorticity. • The storm center is defined by the vorticity centroid. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

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15. Number of tropical cyclones - Annualcycle 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

16. Number of Tropical Cyclones – Interannual variability 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

17. Tracks – 3 years 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

18. Composites of western North Pacific model tropical cyclones • 13 ensemble members of ECHAM4.5 • Period: 1979-1995, observed SSTs • Only western North Pacific model tropical cyclones included in the composites. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

19. Composites period : June – November. • Total of 5701 model tropical cyclones included in the composites. • Composites: averaging of simulated fields from different storms in a storm-centered coordinate. • Storms are aligned on the first day the pass the detection criteria (day 0) and extend backward and forward for 15 days. • Not all storms can be tracked for the whole period. • Besides composite means, extreme values (maximum and minimum), standard deviation and skewness among all storms used in the composite were calculated. • Composites were formed in an area around the center of each storm of size 7x7 grid boxes, corresponding to a square box with sides of approximately 16.8 degrees. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

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31. Conclusions • In most composite time series, a sharp increase (or decrease) in the mean value of the variable occurs over a period of several days centered on day 0. • In many variables, the intensification occurs simultaneously with a similar temporal structure: low-level vorticity, surface wind speed, surface pressure, precipitation. • The low-level humidity, however, begins to intensify a few days later. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.

32. The vortex structure intensifies simultaneously at all levels from the middle troposphere down to the surface. • The presence of a minimum intensity prior to development is reminiscent of observed cyclogenesis. • The environmental wind shear varies monotonically over the storm trajectory, primarily because the mean storm trajectory moves to a region of relatively low shear. • For a period of several days centered on the minimum in other variables (genesis), the skewness of the low-level relative humidity is positive, excluding low values of RH from the distribution, suggesting that a moist lower troposphere is a prerequisite for development, as in observations. 27th Annual Climate Diagnostics and Prediction Workshop, October 2002.