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Topic 1.5: Operational guidance and skill in forecasting structure change Presented by John Knaff CIRA/CSU Working Group:C. Guard, J. Kossin, T. Marchok,

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Presentation on theme: "Topic 1.5: Operational guidance and skill in forecasting structure change Presented by John Knaff CIRA/CSU Working Group:C. Guard, J. Kossin, T. Marchok,"— Presentation transcript:

1 Topic 1.5: Operational guidance and skill in forecasting structure change Presented by John Knaff CIRA/CSU Working Group:C. Guard, J. Kossin, T. Marchok, B. Sampson, T. Smith, N. Surgi

2 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 2 Presentation Outline Review Typical Measures of TC structure Review Typical Measures of TC structure Operational TC Structure Guidance Operational TC Structure Guidance Intensity verification Intensity verification –Long-term operational –Long-term guidance Wind Radii Verification Wind Radii Verification –2005 Atlantic Summary and Recommendations Summary and Recommendations

3 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 3 Measures of TC Structure Intensity Intensity –Minimum Sea Level Pressure (MSLP) –Maximum Surface Winds (MSW)* Wind Structure Wind Structure –Radii of significant winds/wind speed thresholds (e.g., Radii of 34-, 50-, 64-kt winds) * Pressure Distribution Pressure Distribution –Outer closed or outer closed & circular isobar * Are used for the verification presented here

4 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 4 Current TC Intensity Guidance Methods Few Methods 24-h Dvorak extrapolation – subjective/statistical 24-h Dvorak extrapolation – subjective/statistical Purely statistical models based on historical best tracks (CLIPER, climatology, analogs) Purely statistical models based on historical best tracks (CLIPER, climatology, analogs) Statistical-dynamical models that use NWP forecasts of environmental conditions to make statistical forecasts Statistical-dynamical models that use NWP forecasts of environmental conditions to make statistical forecasts Numerical Weather Prediction (NWP) methods that make deterministic forecasts. Numerical Weather Prediction (NWP) methods that make deterministic forecasts. Consensus Methods, combination of skillful forecast methods Consensus Methods, combination of skillful forecast methodsWeaknesses Short-term, subjective Short-term, subjective Do not use current synoptic information, conservative best used for verification Do not use current synoptic information, conservative best used for verification Conservative - cannot predict rapid intensity changes, timing at long leads, over intensify weak systems, poorly handle high latitude decay Conservative - cannot predict rapid intensity changes, timing at long leads, over intensify weak systems, poorly handle high latitude decay Spin-up issues, over intensify some systems, poor physical initialization, parameterized physics Spin-up issues, over intensify some systems, poor physical initialization, parameterized physics Only as good as the independent guidance Only as good as the independent guidance

5 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 5 Current Operational TC Wind Structure Guidance Fewer methods Fewer methods Climatology (tabular, equation form as a function of intensity) Climatology (tabular, equation form as a function of intensity) –Vary among forecast centers Simple Statistical (CLIPER models) Simple Statistical (CLIPER models) –Basin dependent Numerical Weather Prediction. Numerical Weather Prediction.Weaknesses Only as good as the climatology, not documented Only as good as the climatology, not documented Based on past operational estimates (are they good?) Based on past operational estimates (are they good?) –Scatterometry, aircraft? Effected by resolution, and vortex initialization Effected by resolution, and vortex initialization

6 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 6 Operational Intensity Verification Caveats: Datasets come from the RSMC, Miami (NOAA/TPC) and USA/Joint Typhoon Warning Center. Datasets come from the RSMC, Miami (NOAA/TPC) and USA/Joint Typhoon Warning Center. –1-minute sustained 10-m wind –Post season re-analyzed intensities making use of all available intensity estimates (i.e., Dvorak, AMSU, Quickscat, Aircraft (flight-level, MSLP) etc.) Measurements for Verification Measurements for Verification –All intensities 1.Mean Absolute Errors (MAE) 2.Percent Reduction in Variance (PRV)

7 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 7 Long-Term Operational Intensity Verification (MAE) All intensities Forecasts from RSMC, Miami (NOAA/TPC)

8 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 8 Long-Term Operational Intensity Verification (MAE) All intensities Forecasts from USA/JTWC

9 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 9 Intensity Verification other RSMCs Range0h12h24h48h72h Average error (kt) RMSE (kt) Bias (kt) Skill against persistence 6%31%43%50% Sample (number of forecasts verified) h48-h72-h (9.9)7.1 (13.8)8.1 (15.8) (9.5)6.5 (12.7)7.6 (14.8) (9.7)7.0 (13.6)N/A (10.1)6.9 (13.4)N/A (11.5)N/A Tropical Storm Intensity RSMC, La Reunion RSMC, Tokyo m/s & (kt) Taken from annual reports

10 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 10 Trends in MAE 24-h48-h72-h ATL ( ) EPAC ( ) SHEM ( )2.02.8N/A WPAC ( ) kt per decade Significance is marginal (70%) using annual number of degrees of freedom

11 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 11 Long-Term Operational Intensity Verification (PRV) Where o is the observed intensity and p is the predicted intensity and the overbar represents a mean value. Can be negative if the numerator (forecast error variance) is larger than the denominator (climatological variance) This methodology penalizes forecasts methodologies for having non- random errors (e.g., bias) Variance of the forecast errors Variance climatological errors

12 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 12 Long-Term Operational Intensity Verification (PRV) All intensities Forecasts from RSMC, Miami (NOAA/TPC) in EP and ATL All intensities Forecasts from USA/JTWC in WP and SH

13 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 13 Long-Term Operational Intensity Verification (PRV)

14 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 14 Trends in PRV 24-h48-h72-h ATL ( ) EPAC ( ) SHEM ( )2.02.8N/A WPAC ( ) Percent per decade Significant (95%) in the Atlantic, marginally significant (70%) in the other basins when based on annual number of degrees of freedom

15 Intensity Guidance Methods Atlantic and East Pacific SHIFOR (1988-present) Statistical Hurricane Intensity FORecast, which uses simple climatology and persistence parameters SHIPS (1991-present, ATLC) Statistical Hurricane Intensity Prediction Scheme, (1996-present, EPAC)which uses climatology, persistence and real- time atmospheric and oceanic parameters GFDL (1995-present)Operational version of the Geophysical Fluid Dynamics Laboratory hurricane model GFDN (2001-present)GFDL model initialized from Navy global model fields SHIFOR5 (2001-present)Updated version of SHIFOR with 5 day forecasts West Pacific CLIM (1985-present)Climatological analog model STIFOR (1991-present)Statistical Typhoon FORecast Model, similar to SHIFOR GFDN (1995-present)GFDL model initialized from Navy global model fields AFW (2000-present)MM5 mesoscale model adapted to typhoon forecasts JTYM(2001-present)Japanese Meteorological Agency limited area typhoon model ST5D (2002-present)Updated STIFOR model and extended to 5 days STIPS (2003-present)Statistical Typhoon Intensity Prediction Scheme, similar to SHIPS ST10 (2005-present)Ensemble version of STIPS Southern Hemisphere CLIM(2000- present)Climatological analog. GFDN (2000- present)GFDL model initialized from Navy global model fields TC-LAPS (2001-present)BOM limited area prediction system ST5D (2004 –present)5-day Climatology and persistence STIPS(2005 – present)STIPS SH (experimental run at NRLM) ST10 (2005 – present)STIPS SH ensemble (experimental, run at NRLM)

16 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 16 Comparison with Best 48-hr Intensity Guidance

17 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 17 Comparison with Best 48-hr Intensity Guidance

18 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 18 Best Guidance (Atlantic, E. Pacific and W. Pacific) AtlanticEast Pacific West Pacific 1991SHIPSSHIFORCLIM 1992SHIFORSHIFORCLIM 1993SHIFORSHIFORCLIM 1994SHIFORSHIFORCLIM 1995SHIFORSHIFORCLIM 1996SHIPSSHIFORGFDN 1997GFDLSHIPSSTIFOR 1998SHIPSSHIPSSTIFOR 1999SHIPSSHIPSSTIFOR 2000SHIPSSHIFORSTIFOR 2001SHIPSSHIPSST5D 2002SHIPSGFDLST5D 2003SHIPSSHIFORSTIPS 2004SHIPSGFDLSTIPS 2005SHIPSSHIPSST preliminaryGFDLSHIPS/ICONST10

19 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 19 Summary: Intensity Forecasting There is evidence that forecasts, in general, are improving very slowly There is evidence that forecasts, in general, are improving very slowly Operational forecast improvements are being driven by improvements in guidance methods Operational forecast improvements are being driven by improvements in guidance methods Statistical-dynamical and regional/specialized NWP guidance are most skillful Statistical-dynamical and regional/specialized NWP guidance are most skillful Global models do not have skill and have larger errors than climatology and persistence based forecasts Global models do not have skill and have larger errors than climatology and persistence based forecasts Consensus methods created from skillful guidance have been demonstrated to produce better forecasts than single methods Consensus methods created from skillful guidance have been demonstrated to produce better forecasts than single methods

20 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 20 Wind Radii verification Caveats: Post-season reanalyzed estimates of R34 used for verification Post-season reanalyzed estimates of R34 used for verification –These make use of the best available data (variable) QuickScat, AMSU, SSMI QuickScat, AMSU, SSMI Flight-level winds Flight-level winds SFMR SFMR Ships/buoys Ships/buoys One year, Atlantic only One year, Atlantic onlyMethods: MAE in n. mi MAE in n. mi Hit & False alarm rates. Hit & False alarm rates.

21 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 21 Wind Radii Guidance/Forecasts OFCL – Official RSMC, Miami forecast OFCL – Official RSMC, Miami forecast AVNI – NOAA Global Forecast System AVNI – NOAA Global Forecast System GFTI – NOAA/GFDL model forecasts GFTI – NOAA/GFDL model forecasts MRCL – Multiple linear regression CLIPER Model, 3-days MRCL – Multiple linear regression CLIPER Model, 3-days DRCL – Statistical-Parametric CLIPER model, 5-days DRCL – Statistical-Parametric CLIPER model, 5-days

22 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 22 Wind Radii Verification (R-34 kt)

23 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 23 Wind Structure Verification Probability of Detection Radii of 34-kt winds Probability of False Detection Radii of 34-kt winds MAE vs. False Alarm Trade off

24 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 24 Influence of Intensity Forecast Errors on Wind Radii Forecasts using Best Track Intensities Forecasts using Forecast intensities

25 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 25 Influence of Intensity Forecast Errors on Wind Radii False Alarm Decrease Hit Rate Increase

26 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 26 Summary: Wind Radii Forecasting There are very few models There are very few models –poor understanding of processes –poor developmental datasets There are no skillful models There are no skillful models –No higher level statistical models –NWP does not initialize the vortex properly, have sufficient resolution (global) More accurate intensity forecasts will improve wind radii forecasts More accurate intensity forecasts will improve wind radii forecasts There is a trade off between false alarm rates and MAE in current forecasts schemes (i.e. symmetric forecasts produce smaller MAE statistics) There is a trade off between false alarm rates and MAE in current forecasts schemes (i.e. symmetric forecasts produce smaller MAE statistics)

27 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 27 Summary TC Structure Forecasting Overall Forecasting of TC structure change is rather poor. The forecasting process is still subjective The forecasting process is still subjective –Best intensity forecasts are used as a baseline that is modified by the forecaster –Skillful wind radii guidance is unavailable Intensity forecasts are improving very slowly and are being driven by improved guidance Intensity forecasts are improving very slowly and are being driven by improved guidance Wind radii forecasting is in its infancy and is hindered by Wind radii forecasting is in its infancy and is hindered by –Poor developmental datasets –Poor physical understanding –Has not been an operational priority –Only recently have such forecasts been verified.

28 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 28 Future/Current Research and Development 1. Making better use of existing technology and datasets. Examples include : –Diagnostic studies to understand tropical cyclone wind field growth –Development of models to predict structure change using environmental and storm conditions –Model output statistics to predict wind radii –Indices to predict rapid intensification, annular hurricanes, secondary eyewall formation, etc. –Forecast techniques to improve short-term intensity forecasts that leverage existing and longstanding satellite technologies –Probabilistic models that account for track, intensity and wind radii error distributions –… Items for discussion

29 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 29 Future/Current Research and Development 2. Development of new technology. Next Generation Hurricane Forecast Model, the Hurricane – Weather Research and Forecasting (H-WRF) Model is being tested/developed Next Generation Hurricane Forecast Model, the Hurricane – Weather Research and Forecasting (H-WRF) Model is being tested/developed –Physical initialization using a 3D-var framework that can make use of Dopplar radar information (WR-88D, airborne) and new instrument packages on the G-IV, and satellite data. –Coupling with waves via the Wavewatch III wave model –Parameterizations developed using the recent results of the CBLAST experiment New instrumentation on operational aircraft New instrumentation on operational aircraft –like the SFMR. –Others etc. Discussion?

30 20-30 November 2006 San Jose, Costa Rica SIXTH INTERNATIONAL WORKSHOP ON TROPICAL CYCLONES 30 Recommendations Continued development of consensus methods to improve intensity forecasts. Continued development of consensus methods to improve intensity forecasts. Use of model output statistics, particularly in wind radii prediction. Use of model output statistics, particularly in wind radii prediction. Greater effort toward high resolution NWP that has physical initialization and advanced data assimilation capabilities Greater effort toward high resolution NWP that has physical initialization and advanced data assimilation capabilities Effort to make the newest technology/instrumentation and resulting observations available to real-time operational centers and tropical cyclone researchers. Effort to make the newest technology/instrumentation and resulting observations available to real-time operational centers and tropical cyclone researchers. Additional recommendation based on knowledge gained during the process of writing the topic summary There is a need for more operational scatterometry and similar active remote sensing instrumentation to detect tropical cyclone wind fields. None is currently planned. There is a need for more operational scatterometry and similar active remote sensing instrumentation to detect tropical cyclone wind fields. None is currently planned.


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