Topic 3.2: Tropical Cyclone Variability on Seasonal Time Scales (Observations and Forecasting)

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1 Topic 3.2: Tropical Cyclone Variability on Seasonal Time Scales (Observations and Forecasting) Phil Klotzbach 7 th International Workshop on Tropical Cyclones November 18, 2010 Working Group: Maritza Ballester (INSMET), Tony Barnston (IRI), Gerry Bell (NOAA/CPC), Joanne Camp (UKMET), Johnny Chan (City University of Hong Kong), David Jones (BOM Australia), Yuriy Kuleshov (BOM Australia), Tim LaRow (Florida State University), Mark Saunders (Tropical Storm Risk), O. P. Singh (India BOM), Frederic Vitart (ECMWF)

2 Outline Observations Forecasts

3 Key Areas of Research (North Atlantic) El Niño Southern Oscillation Atlantic Meridional Mode Relative SST Quasi Biennial Oscillation

4 Anomalous 200 mb Outflow Associated with El Niño Events Gray (1984)

5 El Niño Modoki Hypothesized Influence on North Atlantic TCs Kim et al. (2009)

6 Atlantic Meridional Mode Atlantic TC Relationship Kossin and Vimont (2007)

7 Relative SST (North Atlantic Tropical SST Tropical SST) Atlantic TC Relationship Cat. 4 5 Hurricane Tracks Vecchi et al. (2008)

8 Quasi Biennial Oscillation Atlantic TC Relationship Failure in Recent Years Camargo and Sobel (2010, in press)

9 Key Areas of Research (North Pacific) El Niño Southern Oscillation Northeast Pacific North Atlantic Inverse Relationship Quasi Biennial Oscillation

10 El Niño La Niña North Pacific Impacts Camargo et al a) Genesis, b) Track a) 850 mb Vorticity, b) mb Vertical Shear, c) Potential Intensity, d) 600 mb RH

11 Northeast Pacific North Atlantic Inverse Relationship Correlation between North Atlantic ACE and Vertical Wind Shear Correlation between North Atlantic ACE and East North Pacific ACE Wang and Lee (2010)

12 QBO Impacts in the North Pacific Correlation Analysis Basin Named Storms Hurricanes Major Hurricanes Hurricane Days ACE Northeast Pacific ( ) Northeast Pacific ( ) Northeast Pacific ( ) Central Pacific ( ) Central Pacific ( ) Central Pacific ( ) Northwest Pacific ( ) Northwest Pacific ( ) Northwest Pacific ( ) Correlations significant at the 95% level are bold faced Camargo and Sobel (2010)

13 Key Areas of Research (North Indian) El Niño Southern Oscillation Monsoon Onset Time

14 El Niño La Niña North Indian Ocean Impacts Camargo et al a) Genesis, b) Track a) 850 mb Vorticity, b) mb Vertical Shear, c) Potential Intensity, d) 600 mb RH

15 Arabian Sea Storms Active May Conditions Active June Conditions Evan and Camargo (2010, in press)

16 Key Areas of Research (South Indian) El Niño Southern Oscillation

17 South Indian Ocean TC ENSO Relationship November April anomalous 500 mb RH in a) El Niño, b) La Niña Kuleshov et al. (2009)

18 Key Areas of Research (South Pacific/Australia) El Niño Southern Oscillation

19 Correlation between Nov Apr Nino 3.4 and a) mb vertical shear and b) 850 mb relative vorticity Ramsay et al. (2008)

20 Camargo et al. (2007) January March Genesis Potential Anomaly a) El Niño, b) La Niña, c) (El Niño La Niña) January March El Niño La Niña Difference for a) 850 mb vorticity, b) mb vertical wind shear, c) potential intensity, d) 600 mb relative humidity

21 Seasonal Tropical Cyclone Forecasts Statistical Statistical/Dynamical Dynamical

22 Statistical Forecasting Groups Colorado State University (North Atlantic) Tropical Storm Risk (North Atlantic, Northwest Pacific, Australia) Cuban Institute of Meteorology (North Atlantic) City University of Hong Kong (Northwest Pacific, Australia) Bureau of Meteorology Australia (Australia, South Pacific)

23 Post 1 August Seasonal Forecast Predictors (CSU) Pre 1 August NSD S of 23.5 N, E of 75 W 3 June July SST 4 June July SST 1 2 EQ. June July SLP

24 12 10 Colorado State University Predicted vs. Observed Post 31 July North Atlantic Hurricanes ( ) Predicted Observed r =

25 Tropical Storm Risk U.S. Landfall Prediction Methodology and Hindcast Skill a) July mb vector wind average, b) August October mb vector wind average difference between active vs. inactive US landfall ACE seasons Saunders and Lea (2005)

26 Comparison between estimated probability of at least one hurricane forming and reaching hurricane intensity within the Caribbean Sea and mean annual probability 100 Forecast Update real Clim. Probability (%) Forecast: 2nd 4th May Update: 1st August

27 South China Landfall Forecast 2010 Observation (Canonical Post El Niño Year) Japan/Korea Landfall Forecast City University of Hong Kong Forecasts

28 BOM Australia Forecast for Australian Region TCs ( E)

29 Statistical/Dynamical Forecasting Groups National Oceanic and Atmospheric Administration (North Atlantic, Northeast Pacific) Bureau of Meteorology Australia (Australia, South Pacific) in the near future

30 Statistical Analysis Dynamical Model Forecasts Climate Forecast System (CFS) ECMWF UKMET European Seasonal to Interannual Prediction ensemble (EUROSIP)

31 Dynamical Forecasting Groups United Kingdom Met Office Hadley Centre (North Atlantic) European Centre for Medium Range Weather Forecasts (North Atlantic, Northeast Pacific, Northwest Pacific, Southern Hemisphere) International Research Institute for Climate and Society (North Atlantic, Northeast Pacific, Northwest Pacific, South Pacific, Australia) Florida State University (North Atlantic)

UK Met Office Dynamical Forecast Forecast Total Number of TCs and ACE Uses GloSea4 system and ECMWF system Count TC like vortices and calculate ACE

32 UK Met Office Dynamical Forecast Forecast Total Number of TCs and ACE Uses GloSea4 system and ECMWF system Count TC like vortices and calculate ACE generated by vortices June Named Storm Forecast Verification ( ) 2007: Predicted 10, Observed : Predicted 15, Observed : Predicted 6, Observed 9

33 ECMWF Dynamical Forecast Forecast Total Named Storms, Hurricanes, ACE, and Mean Genesis Location Tracks TCs in the ECMWF atmospheric component using tracking procedure described in Vitart et al. (1997, 2003) Model integrated for seven months

34 IRI Dynamical Forecast Two Tiered Forecast System: 1) Predict SSTs using combination of statistical and dynamical models, 2) Run ensemble integrations of the ECHAM 4.5 AGCM Track TC like vortices in the ECHAM 4.5 model

35 FSU Dynamical Forecast Forecast SSTs using the Climate Forecast System (CFS) Track TC like vortices in the FSU/COAPS AGCM Larow et al. (2010)

36 It's tough to make predictions, especially about the future Yogi Berra

37 Questions???

Topic 5.2: Seasonal Forecasts

Topic 5.2: Seasonal Forecasts Contributions from: Maritza Ballester, Eric Blake, Suzanna Camargo, Joanne Camp, Johnny Chan, Phil Klotzbach, Yuriy Kuleshov, Mark Saunders, O. P. Singh, Gabriel Vecchi and