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Statistical-dynamical Downscaling

Statistical-dynamical Downscaling. Asuka Suzuki-Parker. NCAR Earth System Laboratory National Center for Atmospheric Research. NCAR is Sponsored by NSF and this work is partially supported by the Willis Research Network and the Research Program to Secure Energy for America. Approach.

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Statistical-dynamical Downscaling

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  1. Statistical-dynamical Downscaling Asuka Suzuki-Parker NCAR Earth System Laboratory National Center for Atmospheric Research NCAR is Sponsored by NSF and this work is partially supported by the Willis Research Network and the Research Program to Secure Energy for America

  2. Approach 1. Randomly place a weak storm 3. Calculate intensity based on large-scale info along the trajectory 4. Majority of storms don’t reach TC intensity, but some do 2. Determine trajectory based on large-scale info and probabilistic perturbation Large-scale info from bias corrected CCSM Current: 1950-1999 (20C3M) Future: 2000-2099 (A2)

  3. Genesis Distribution Pretty good agreement with current observation except for tropical Atlantic

  4. North AtlanticTC frequency projection No trend in annual frequency

  5. Intensity projection No change in intensity either

  6. Genesis location projection

  7. Why no trends? Projected large-scale trends Stat-dyn downscale genesis location Less favorable More favorable Compared to observation, stat-dyn downscale technique is producing more storms in high latitutdes, and less in tropics As North Atlantic as a whole, trend gets canceled out

  8. TC duration projection Increasing average TC duration PDI increases

  9. TC size projection Reduction in TC size is projected

  10. Summary Stat-dyn downscaling is successful in reproducing general global TC formation Little TC formation in tropical Atlantic Fails to capture large-scale trend No trend in frequency or intensity as whole North Atlantic Storm size and duration trends in agreement with NRCM

  11. Comparisons among three techniques

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