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Page 1© Crown copyright 2006 Matt Huddleston With thanks to: Frederic Vitart (ECMWF), Ruth McDonald & Met Office Seasonal forecasting team 14 th March.

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Presentation on theme: "Page 1© Crown copyright 2006 Matt Huddleston With thanks to: Frederic Vitart (ECMWF), Ruth McDonald & Met Office Seasonal forecasting team 14 th March."— Presentation transcript:

1 Page 1© Crown copyright 2006 Matt Huddleston With thanks to: Frederic Vitart (ECMWF), Ruth McDonald & Met Office Seasonal forecasting team 14 th March 2007 Dynamically-Based Seasonal forecasts of Atlantic Tropical-storm Activity

2 Page 2© Crown copyright 2006 Seasonal forecasts of tropical storms  Recent hurricane years in the Tropical Atlantic  Forecasting technology  Forecast skill  Future work

3 Page 3© Crown copyright 2006

4 Page 4© Crown copyright 2006 Atlantic Hurricanes 2004 Four hurricanes struck Florida Unprecedented 10 tropical cyclones struck Japan 2005 Record hurricane activity (28) in the Atlantic Four category 5 hurricanes (Emily, Katrina, Rita, Wilma) Activity in other regions was either quiet or normal 2006 Nothing out of the ordinary – 9 storms Atlantic has been active for last decade, but no change in other regions Natural variations in activity are likely to mask any clear climate change link for the foreseeable future Observational studies suggest no change in frequency, but an increase in intensity in recent decades Historical database is not considered robust enough to use for detailed climate studies c/o & thanks to NASA (also previous animation)

5 Page 5© Crown copyright 2006 2005 tropical cyclone activity

6 Page 6© Crown copyright 2006 Seasonal Forecasting technology

7 Page 7© Crown copyright 2006 Current seasonal tropical storm forecasting: statistical E.g. Gray/Klotzbach – June to November Atlantic season forecasts Use a range of statistical predictors for each forecast Wide range of predictions made: numbers of storms, strength, landfall etc Taken from Klotzbach P.J. and Gray W.M., Extended Range Forecast of Atlantic Seasonal Hurricane Activity and U.S. Landfall Strike Probability

8 Page 8© Crown copyright 2006 The Daily Telegraph – 7 th October 2006 Amaranth Advisors, the US-based hedge fund that lost about $6bn (£3.2bn) betting on gas prices, has sought help as it liquidates its remaining assets. BBC News 2 nd Oct 2006 Impact of long-range forecasts

9 Page 9© Crown copyright 2006 Seasonal forecasting using climate models: Multi-model seasonal forecasting Sea Surface Temperature Recent global atmospheric wind, rain, solar heating etc Global Coupled Climate model Ensembles Ocean observations Including ARGO floats EUROSIP

10 Page 10© Crown copyright 2006 Model Tropical Storms Out flow In flow Average observed typhoon from Gray (1979) Low level cyclonic Single tropical storm from HadAM3 N144 Model Low level Model winds speeds are too low, max is too far out Top row: Gray (1979), Bottom row: McDonald et al. (2005) Climate Dynamics Anticyclonic flow too far from centre Upper level Too strong, too low and confined near centre Upper level anticyclonic Tangential WindsRadial Winds Summary: Despite their low horizontal resolution climate models are able to simulate some of the features of tropical cyclones

11 Page 11© Crown copyright 2006 Examples of model cyclone tracks Tropical Storms for 15 years – AGCM + observed SST Tracks look sensible, despite low resolution (~100Km / N144 ) and poor simulation of individual cyclones

12 Page 12© Crown copyright 2006 Tropical storm genesis in N144 HadAM3 Units = TS per grid box per 10 years Observations:- NHC best track data Model:- 1980s Only one TS observed Too manyToo few

13 Page 13© Crown copyright 2006 Forecast skill

14 Page 14© Crown copyright 2006 Impact of El Niño/wind shear in the Atlantic 1997: 7 tropical storms 3 hurricanes 1 major hurricane Strong El Niño prevented hurricane development due to high wind shear 1995: 19 tropical storms 11 hurricanes 5 major hurricanes

15 Page 15© Crown copyright 2006 Key to forecasting climate – sea surface temperature Pacific (NINO3.4) SSTs  Forecast of August to October SSTs from 1 st June  Correlation of forecast ensemble mean and observed SSTs  0.87 in Pacific  0.81 in Atlantic  Persistence is  0.47 in Pacific  0.73 in Atlantic

16 Page 16© Crown copyright 2006 EUROSIP – June forecast for July-November (95% population)

17 Page 17© Crown copyright 2006 June forecast of number tropical Atlantic storms Jun-Nov EUROSIPTropical Storm Risk Colorado State Uni. Correlation0.78 (0.002) 0.53 (0.055) 0.39 (0.26) RMS error3.14.98 4.84 Met Office + ECMWF TSRCSU Correlation0.80 (0.0002) 0.62 (0.004) 0.53 (0.015) RMS error3.344.39 4.42 1993-2006 1987-2006

18 Page 18© Crown copyright 2006 Recent predictions Model 1Model 2Model 3EUROSIPNOAATSRCSUOBS 200514.3 15 19.416.212-1513.81527 200610.510.7 15.312.113-1615.9179 2005 was an extremely active year 2006 was an (just-below) average

19 Page 19© Crown copyright 2006 Climate forecasts & risk mitigation  Chances of an extreme Atlantic tropical storm season in 2005:  Above 20 storms was forecast as twice as likely  1 st June forecast: 37% chance of being above 20 storms where 1993-2004 average chance was 18%  Above 27 storms was forecast as 3 times as likely  1 st June forecast: 13% chance of being above 27 storms where 1993-2004 average chance was 4.2%

20 Page 20© Crown copyright 2006 DEMETER Probabilistic verification 1959-2001 Forecasts that differ from climatology frequency for above or below normal activity are reliable

21 Page 21© Crown copyright 2006 Future potential  Increasing model resolution  Land fall predictions  Better representation of hurricane intensity  Statistical techniques could be used now:  Calibrate inter-annual variability of ensemble  Calibrate land-falling hurricanes  Assessment in more locations and lead times


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