Hurricanes and Atlantic Surface Flux Variability Mark A. Bourassa 1,2, Paul J. Hughes 1,2, Jeremy Rolph 1, and Shawn R. Smith 1 1. Center for Ocean-Atmospheric Prediction Studies 2. Department of Meteorology The Florida State University

The Florida State University COD 5 th Annual Rev 2 Stresses Storm Surge Forecast  Storm surge in Apalachee Bay was underforecast by 4 ft.  The local surge model was OK, but the extra 4ft came for distant forcing.  A coastally trapped wave propagated up the coast with the storm.

The Florida State University COD 5 th Annual Rev 3 Objectives  SST minus 10m air temperature?  ‘Surface’ humidity minus 10m humidity?  Can these changes be linked to Atlantic Tropical Cyclone variability drought or other things that impact people and businesses?  Examine Atlantic Ocean surface turbulent energy fluxes for multi- decadal variability.  Latent heat flux  Sensible heat flux  What related variables are changing with the fluxes  Sea surface temperature (SST)  Near surface (10m) wind?  Near surface (10m) air temperature  Near surface (10m) humidity

The Florida State University COD 5 th Annual Rev 4 What are surface turbulent fluxes? Latent Heat Flux (E)  Vertical transport of energy associated with the phase change of water  Forced by wind speed and air/sea temperature differences Sensible Heat Flux (H)  Vertical transport of energy associated with heating, but without a phase change  Forced by wind speed and vertical moisture differences Stress (  )  Vertical transport of horizontal momentum  Forced by vertical momentum differences E+E+ E-E-H+H+H-H- -- ++ Ocean Atmosphere

The Florida State University COD 5 th Annual Rev 5 Relevance of Surface Turbulent Fluxes  Modulations in the above induce changes in the latent and sensible heat fluxes OR modulations in heat fluxes change the above variables.  Sensitive indicators of changes in the climate system, integrating changes in the following variables.  Wind Speed  Air/Sea temperature difference  Vertical moisture differences

The Florida State University COD 5 th Annual Rev 6 Forcing Product Inconstancies: Zonal Averaged Latent Heat Flux  NWP Products:  NCEPr2  JRA  Satellite Product:  HOAPS  NWP/Satellite Hybrid  WHOI  In Situ  NOC (AKA SOC)  FSU Wm -2 Latitude

The Florida State University COD 5 th Annual Rev 7 Forcing Product Inconstancies: Zonal Averaged Sensible Heat Flux  NWP Products:  NCEPr2  JRA  Satellite Product:  HOAPS  NWP/Satellite Hybrid  WHOI  In Situ  NOC (AKA SOC)  FSU3 Latitude Wm -2

The Florida State University COD 5 th Annual Rev Wm Wm -2 Latent Heat Flux: January 1989Sensible Heat Flux: January 1989 Latent heat flux:Sensible heat flux:

The Florida State University COD 5 th Annual Rev 9 Input Data for Our Flux Product (FSU3 Winds and Fluxes)  International Comprehensive Ocean-Atmosphere Data Set (ICOADS; Woodruff et al. 1987; Worley et al. 2005)  Reynolds SSTs (Reynolds 1988)  Bias corrections for ship based SSTs is difficult because it varies greatly on ship to ship basis

The Florida State University COD 5 th Annual Rev >81 January August Average Number of Ship Observations

The Florida State University COD 5 th Annual Rev 11 Creating the FSU3 Fluxes  Beaufort speeds converted to 10 m values (Lindau 1995)  Buoys height adjusted to 10m winds (Bourassa et al. 1999)  Ship anemometers treated as 20m winds, and height adjusted.  These data are input into a variational technique (Bourassa et al. 2005) Wind Speed Height  We currently have research quality fields for 1978 through 2004  Atlantic Basin & Indian Ocean  The bias corrected observations of winds, temperatures, and humidities are averaged monthly, and in 1x1  bins.  Bias adjustments  Air temperature for heat of the superstructure (Berry et al. 2004)  SST adjusted from bulk to skin temperature (Donlon and Robinson 1997)  Winds

The Florida State University COD 5 th Annual Rev 12 Is Our Gridding Technique Effective? Validation of Wind Fields  Biases (not shown) are very small.  Random errors small over most of be basin.  Larger in areas of relatively poor sampling  Larger in areas with more natural variability ms -1  Monthly mean Winds from August 1999 through Dec are compared to similarly averaged fields from SeaWinds on QSCAT.

The Florida State University COD 5 th Annual Rev 13 Atlantic Mulitdecadal Oscillation (AMO)  Thought to be forced by fluctuations in the thermohaline circulation (Schlesinger and Ramankutty 1994; Kerr 2000; Delworth and Mann 2000)  Period of years  Linked to anomalous precipitation patterns and North Atlantic hurricane activity (Enfield et al. 2001; Sutton and Hodson 2005; Goldenberg et al. 2001) Enfield et al. 2001

The Florida State University COD 5 th Annual Rev 14 Tropical North Atlantic  Recall that we have a research quality time series for the period 1978 through  This is slightly longer than the satellite period for which has arguably been called good for NCEP reanalyses.  A longer time series would be better!

The Florida State University COD 5 th Annual Rev 15 Stretching Our Time Series  The density of in situ (Volunteer Observing Ship) data from the Atlantic Ocean peaks in the 1980s.  A data set based on in situ data could be extended much further back in time.  We used ICOADS data from Jan through Dec to extend our data set.  All our automated procedures were used; however, we did not apply the visual quality control step.  Skipping this step is analogous to adding noise.  We reduce this noise by applying spatial averages in Hovmueller diagrams.

The Florida State University COD 5 th Annual Rev 16 Latent Heat Flux: Northern Tropical Atlantic  There is a 11 to 13 year cycle superimposed on a longer term trend or cycle.  The trend largely due to the changing anemometer heights.  AMO related variability is suggested by the change in  Hints of ENSO-related variability.  Recall that peak hurricane count happened in , and the early sixties had an atypically large fraction of strong hurricanes.  These years have positive AMO anomalies and are near the peak of the 11 to 13 year cycle.

The Florida State University COD 5 th Annual Rev 17 Tropical North Atlantic Air/Sea Humidity Differences  Considerable matching variability on the 11 to 13 year scale.  AMO related variability is suggested.  11 to 13 year variability is apparent, but harder to see on this color scale.

The Florida State University COD 5 th Annual Rev 18 Summary  Changes in LHF due to changes in wind speed are convoluted with changing anemometer heights.  There is variability in heat fluxes associated with the AMO  Larger heat input into the atmosphere for the periods associated with increased hurricane activity.  An 11 to 13 year cycle is found in the latent heat fluxes and in the air/sea moisture differences.  This 11 to 13 year variability is not nearly as apparent in time series of q air or q sfc.  Future work will look into what is causing the 11 to 13 year cycle.  Changes in tropical Atlantic latent heat fluxes are closely linked to changes in air/sea moisture difference.

Hurricanes and Atlantic Surface Flux Variability Mark A. Bourassa 1,2, Paul J. Hughes 1,2, Jeremy Rolph 1, and Shawn R. Smith 1 1. Center for Ocean-Atmospheric Prediction Studies 2. Department of Meteorology The Florida State University

The Florida State University COD 5 th Annual Rev 20 Air/Sea Temperature Difference: SST  T air

The Florida State University COD 5 th Annual Rev 21 SHF???