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Beth Ebert BMRC, Melbourne, Australia

Assessment of Tropical Rainfall Potential (TRaP) forecasts during the 2003-04 Australian tropical cyclone season. Beth Ebert BMRC, Melbourne, Australia with thanks to Sheldon Kusselson, Mike Turk, Ralph Ferraro and Bob Kuligowski. 2 nd IPWG Meeting, Monterey, 25-28 October 2004.

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Beth Ebert BMRC, Melbourne, Australia

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  1. Assessment of Tropical Rainfall Potential (TRaP) forecasts during the 2003-04 Australian tropical cyclone season Beth Ebert BMRC, Melbourne, Australia with thanks to Sheldon Kusselson, Mike Turk, Ralph Ferraro and Bob Kuligowski 2nd IPWG Meeting, Monterey, 25-28 October 2004

  2. TRaP - Tropical Rainfall PotentialNESDIS nowcasts of rain in tropical cyclones Generation of TRaP: • Compute areal rain rates from passive microwave sensor (SSM/I, AMSU, or TRMM) • Using operational forecast cyclone track, advect rainfall for 24 h, assuming steady state storm structure • Analyst vets TRaP prior to public release SSM/I "snapshot" DARWIN TRaP DARWIN TC Craig, 10 March 2003

  3. Validation of TRaP over U.S. for 2002 Atlantic hurricane season (Ferraro et al., 2004, Wea. Forecasting, submitted) 42 TRaPs verified against Stage IV radar/gauge analyses at 4 km resolution. TRaP under-estimated rain rate, volume, max. TRaPs from TRMM performed best, closely followed by AMSU. TRaP outperformed Eta NWP model forecasts at 50 km resolution. SSM/I AMSU TRMM

  4. Atlantic vs. South Pacific hurricane rainfall Mean rain rate from TRMM TMI as a function of radial distance from storm center, 1998-2000 Atlantic South Pacific Lonfat et al., 2004, Mon. Wea. Rev.

  5. (19) (29) (3) (9) (25) 2003-2004 Australian tropical cyclones Validation strategies: • maximum 24 h rain at landfall vs. rain gauge observations ±3h (±12 h) • spatial rainfall distribution in 10° box vs. operational 0.25° gauge analysis ±3h • contiguous rain area (CRA) bounded by 20 mm d-1 threshold vs. operational 0.25° gauge analysis ±3h

  6. Tropical Cyclone Fay (17-28 March 2004) • TRaP too great on most days, especially near landfall • Some extreme values for SSM/I and TRMM * Areal TRaP vs gauge observations not ideal but no radar data available landfall

  7. Tropical Cyclone Fay (28 March 2004) OBS AMSU Maximum 24 h rain (mm) Observed 159.4 0100 UTC 28 March 2004 AMSU 111.6 0233 UTC 28 March 2004 SSM/I 478.1 1304 UTC 27 March 2004 TRMM 251.0 0156 UTC 28 March 2004 SSM/I TRMM

  8. Maximum rain at landfall • TRaP estimated maximum rain well for some TCs, overestimated for others • AMSU less likely to overestimate Mean

  9. Spatial validation - TC Fay (28 March 2004) * statistics for land grid boxes only

  10. Aggregated results – all vs. vetted (checked by analyst) TRaPs • Rain area and volume too small by ~50% • POD for heavy rain is ~0.2-0.6, FAR is ~0.2-0.6 • Vetted TRaPs perform better than all (unvetted + vetted) TRaPs

  11. Aggregated results – sensor intercomparison • SSM/I TRaPs had some large errors, AMSU had smallest errors • AMSU TRaPs gave largest rain area • AMSU TRaPs showed best performance, then TRMM, then SSM/I

  12. Related to: ...track errors ...rain retrieval, no growth/decay Observed X Forecast F ...steady state rain structure CRA verification method (Ebert and McBride, 2000) • Define entities using threshold (Contiguous Rain Areas) • Location error determined by • pattern matching (minimum total squared error, maximum correlation, or maximum overlap) • external specification using best track data • Verify properties of CRA (size, mean and maximum intensity, etc.) • Error decomposition MSEtotal = MSEdisplacement + MSEvolume + MSEpattern Version for pattern matching using correlation: (r=correlation, s=std.dev.)

  13. CRA validationTC Fay (0303 UTC 25 March 2004)

  14. CRA validationTC Monty (2216 UTC 1 March 2004)

  15. 150 100 50 0 (km) (%) (%) (%) CRA validation results for vetted TRaPs • Pattern error most important, followed by volume error, then displacement error

  16. Comparison to operational NWP • Mesoscale model (mesoLAPS, 12 km resolution) • TC-centered mesoscale model (TC-LAPS, 15 km resolution) 24 h rain forecasts for TC Monty, ~00 UTC 2 March 2004 Verification on 0.25° grid consistent with TRaP verification

  17. TRaP Comparison to operational NWP • NWP models overestimated rain area and volume • Correlations comparable between TRaP and models • Threat score best for TC-LAPS • Fairer comparison might use vetted TRaPs but not enough days in common

  18. Comparison of Australian and US results (median values for vetted TRaPs)

  19. Reasons for differences

  20. sources of error related to assumptions in the TRaP formulation... that might be improved using a variety of strategies. Improve tracks (multi-model NWP) track forecasts Include storm rotation steady state rain structure Improve satellite rain algorithms Orographic enhancement satellite rain retrieval no growth or decay Statistical filter Adjust for atmospheric moisture, shear CRA validation suggests... Location Error 18% Pattern error 48% Volume error 34%

  21. Living with uncertainty – Ensemble TRaP Perturb or vary: • Cyclone track • Parameters of microwave rain rate retrieval • Satellite sensors included in the ensemble, including VIS/IR • Sources of TC rain forecasts: R-CLIPER, NWP, ... TC Monty, 00 UTC 2 March 2004 Ensemble of 27 TRaP forecasts (15 AMSU, 8 SSM/I, 4 TRMM) valid within ± 12 h Mean includes histogram transformation

  22. Thank you!

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