EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND U.S. LANDFALL STRIKE PROBABILITY FOR 2007

 

We continue to call for a very active Atlantic basin hurricane season in 2007.  Landfall probabilities for the United States coastline are well above their long-period averages.

 

(as of 31 May 2007)

 

 

 

By Philip J. Klotzbach[1] and William M. Gray[2]

 

with special assistance from William Thorson[3]

 

 

 

This forecast as well as past forecasts and verifications are available via the World Wide Web at http://hurricane.atmos.colostate.edu/Forecasts


Emily Wilmsen, Colorado State University Media Representative, (970-491-6432) is available to answer various questions about this forecast

 

 

 

Department of Atmospheric Science

Colorado State University

Fort Collins, CO 80523

Email: amie@atmos.colostate.edu

 

 

 

 

ATLANTIC BASIN SEASONAL HURRICANE FORECAST FOR 2007

 

Forecast Parameter and 1950-2000

Climatology (in parentheses)

Issue Date

8 December 2006

Issue Date

3 April 2007

Issue Date

31 May 2007

Named Storms (NS) (9.6)

14

17

17

Named Storm Days (NSD) (49.1)

70

85

85

Hurricanes (H) (5.9)

7

9

9

Hurricane Days (HD) (24.5)

35

40

40

Intense Hurricanes (IH) (2.3)

3

5

5

Intense Hurricane Days (IHD) (5.0)

8

11

11

Accumulated Cyclone Energy (ACE) (96.2)

130

170

170

Net Tropical Cyclone Activity (NTC) (100%)

140

185

185

 

 

 

 


PROBABILITIES FOR AT LEAST ONE MAJOR (CATEGORY 3-4-5) HURRICANE LANDFALL ON EACH OF THE FOLLOWING COASTAL AREAS:

 

1)      Entire U.S. coastline - 74% (average for last century is 52%)

 

2)      U.S. East Coast Including Peninsula Florida - 50% (average for last century is 31%)

 

3)      Gulf Coast from the Florida Panhandle westward to Brownsville - 49% (average for last century is 30%)

 

4)      Above-average major hurricane landfall risk in the Caribbean

ABSTRACT

 

Information obtained through May 2007 continues to indicate that the 2007 Atlantic hurricane season will be much more active than the average 1950-2000 season.  We estimate that 2007 will have about 9 hurricanes (average is 5.9), 17 named storms (average is 9.6), 85 named storm days (average is 49.1), 40 hurricane days (average is 24.5), 5 intense (Category 3-4-5) hurricanes (average is 2.3) and 11 intense hurricane days (average is 5.0).  The probability of U.S. major hurricane landfall is estimated to be about 140 percent of the long-period average.  We expect Atlantic basin Net Tropical Cyclone (NTC) activity in 2007 to be about 185 percent of the long-term average. 

This late May forecast is based on a newly devised extended range statistical forecast procedure which utilizes 40 years of past global reanalysis data and is then tested on an additional 15 years of global reanalysis data. Analog predictors are also utilized. We have maintained our forecast from our early April prediction due largely to the continued trend towards cooler equatorial Pacific sea surface temperatures.  Currently, neutral ENSO conditions are observed.  We expect either cool neutral or weak-to-moderate La Niña conditions to be present during the upcoming hurricane season.  Tropical and North Atlantic sea surface temperatures remain well above their long-period averages.

 


Acknowledgment


We are grateful to the National Science Foundation (NSF) and Lexington Insurance Company (a member of the American International Group (AIG)) for providing partial support for the research necessary to make these forecasts.  We also thank the GeoGraphics Laboratory at Bridgewater State College (MA) for their assistance in developing the United States Landfalling Hurricane Probability Webpage (available online at http://www.e-transit.org/hurricane).  We thank Jim Kossin and Dan Vimont of the University of Wisconsin-Madison for providing the data for the Atlantic Meridional Mode prediction used in this forecast.  We also thank Amato Evan of the University of Wisconsin-Madison for providing us with the African dust data.

 

The second author gratefully acknowledges valuable input to his CSU research project over many years by former project members and now colleagues Chris Landsea, John Knaff and Eric Blake.  We also thank Professors Paul Mielke and Ken Berry of Colorado State University for much statistical analysis and advice over many years.



Notice of Author Changes

 

By William Gray


The order of the authorship of these forecasts was reversed in 2006 from Gray and Klotzbach to Klotzbach and Gray.  After 22 years (since 1984) of making these forecasts, it is appropriate that I step back and have Phil Klotzbach assume the primary responsibility for our project’s seasonal, monthly and landfall probability forecasts.  Phil has been a member of my research project for the last seven years and has been second author on these forecasts for the last six years.  I have greatly profited and enjoyed our close personal and working relationships. 

Phil is now devoting more time to the improvement of these forecasts than I am.  I am now giving more of my efforts to the global warming issue and in synthesizing my projects’ many years of hurricane and typhoon studies.

 Phil Klotzbach is an outstanding young scientist with a superb academic record.  I have been amazed at how far he has come in his knowledge of hurricane prediction since joining my project in 2000.  I foresee an outstanding future for him in the hurricane field.  I expect he will make many new forecast innovations and skill improvements in the coming years. 


 

Additional Note

 

Subtropical storm Andrea formed off the southeast coast of the United States on May 9.  Since Andrea was never classified as a tropical storm by the National Hurricane Center, it will not be counted as a named storm in our seasonal statistics. 



DEFINITIONS

 



1        Introduction

 

This is the 24th year in which the CSU Tropical Meteorology Project has made forecasts of the upcoming season’s Atlantic basin hurricane activity.  Our research team has shown that a sizable portion of the year-to-year variability of Atlantic tropical cyclone (TC) activity can be hindcast with skill exceeding climatology.  These forecasts are based on statistical methodologies derived from 55 years of past data and a separate study of analog years which have similar precursor circulation features to the current season.  Qualitative adjustments are added to accommodate additional processes which may not be explicitly represented by our statistical analyses.  These evolving forecast techniques are based on a variety of climate-related global and regional predictors previously shown to be related to the forthcoming seasonal Atlantic basin tropical cyclone activity and landfall probability.  We believe that seasonal forecasts must be based on methods that show significant hindcast skill in application to long periods of prior data.  It is only through hindcast skill that one can demonstrate that seasonal forecast skill is possible.  This is a valid methodology provided that the atmosphere continues to behave in the future as it has in the past. 

 

A variety of atmosphere-ocean conditions interact with each other to cause year-to-year and month-to-month hurricane variability.  The interactive physical linkages between these many physical parameters and hurricane variability are complicated and cannot be well elucidated to the satisfaction of the typical forecaster making short range (1-5 days) predictions where changes in the momentum fields are the crucial factors.  Seasonal and monthly forecasts, unfortunately, must deal with the much more complicated interaction of the energy-moisture fields with the momentum fields. 

 

We find that there is a rather high (50-60 percent) degree of year-to-year hurricane forecast potential if one combines 3-4 semi-independent atmospheric-oceanic parameters together.  The best predictors (out of a group of 3-4) do not necessarily have the best individual correlations with hurricane activity.  The best forecast parameters are those that explain the portion of the variance of seasonal hurricane activity that is not associated with the other variables.  It is possible for an important hurricane forecast parameter to show little direct relationship to a predictand by itself but to have an important influence when included with a set of 2-3 other predictors. 

 

In a four-predictor empirical forecast model, the contribution of each predictor to the net forecast skill can only be determined by the separate elimination of each parameter from the full four predictor model while noting the hindcast skill degradation.  When taken from the full set of predictors, one parameter may degrade the forecast skill by 25-30 percent, while another degrades the forecast skill by only 10-15 percent.  An individual parameter that, through elimination from the forecast, degrades a forecast by as much as 25-30 percent may, in fact, by itself, show much less direct correlation with the predictand.  A direct correlation of a forecast parameter may not be the best measure of the importance of this predictor to the skill of a 3-4 parameter forecast model.  This is the nature of the seasonal or climate forecast problem where one is dealing with a very complicated atmospheric-oceanic system that is highly non-linear.  There is a maze of changing physical linkages between the many variables.  These linkages can undergo unknown changes from weekly to decadal time scales.  It is impossible to understand how all these processes interact with each other.  It follows that any seasonal or climate forecast scheme showing significant hindcast skill must be empirically derived.  No one can completely understand the full complexity of the atmosphere-ocean system or develop a reliable scheme for forecasting the myriad non-linear interactions in the full-ocean-atmosphere system.

 

 

2        Early June Forecast Methodology

 

As was done with our early December and early April forecasts, a new statistical scheme has been developed for the June 2007 prediction.  This new scheme utilizes a similar technique to what was utilized for our recent early December and early April 2007 forecasts.  This new scheme utilizes a total of only three predictors.  Two of these predictors are derived from sea surface temperature data obtained from the NCEP/NCAR reanalysis.  The third predictor is the previous year’s early December prediction of the Atlantic Meridional Mode (AMM).  The Atlantic Meridional Mode has been briefly discussed in this season’s early December and early April forecasts. 

 

As was done with the new early December and early April statistical prediction schemes, these three predictors were selected based on dependent data from 1950-1989 and then tested on independent data from 1990-2004.  The combination of these three predictors explained 42 percent of the variance in NTC on dependent data (1950-1989), and using these same equations, 54 percent of the variance in NTC was explained using independent data (1990-2004).  When evaluated over the complete 1950-2004 time period, 49 percent of the variance was explained using these three predictors.

 

The reader will note that the variance explained in the early June statistical scheme is actually slightly less than that achieved in either early December or early April.  However, we feel that utilizing a statistical scheme that only includes data from the two months immediately prior to the forecast date is critical for evaluating the current state of the atmosphere/ocean system. 

 

As with all of the other new forecast schemes that have been outlined in previous forecasts, this new scheme only predicts Net Tropical Cyclone (NTC) activity, and the other predictors are then derived from this NTC prediction.   Table 1 provides the locations of these new predictors, while Figure 1 displays the locations of these predictors on a map.  Table 2 displays values of these predictors for the 2007 hurricane season.  Our statistical forecast calls for a very active hurricane season in 2007. 

 

Table 1:  Predictors used in the new early June forecast.  The sign of the predictor associated with increased tropical cyclone activity during the hurricane season is in parentheses.   

 

Predictor Name

Location

1) April-May SST in the eastern Atlantic (+)

(25º-60ºN, 30º-15ºW)

2) April-May SST in the eastern and central tropical Pacific – Nino 3.4 index (-)

(5°S-5°N, 170°-120°W)

3) July-November Predicted AMM Index (+)

 (21°S-32°N, South American Coastline – West African Coastline)

 

 

Figure 1:  Location of predictors for the current early June forecast scheme. 

 

Table 2: Listing of 31 May 2007 predictors for this year’s hurricane activity.  A plus (+) means that positive values of the parameter indicate increased hurricane activity this year, and a minus (-) means that positive values of the parameter indicate decreased hurricane activity this year.  The combination of these three predictors calls for an active hurricane season this year.

 

Predictor

Values for 2007 Forecast

1) April-May SST (25-60°N, 30-15°W) (+)

+0.5 SD

2) April-May SST (5°S-5°N, 170-120°W) (-)

-0.3 SD

3) July-November Predicted AMM Index (21°S-32°N, South American Coastline – West African Coastline) (+)

+1.9 SD

2.1              Physical Associations among Predictors Listed in Table 1

 

Brief descriptions of our late May predictors follow:

 

Predictor 1:  April-May SST in the eastern Atlantic (+):


(25-60°N, 30-15°W)

 

Above-normal sea surface temperatures (SSTs) in the eastern Atlantic during April-May are associated with a weaker-than-normal Azores high and reduced trade wind strength during the boreal spring (Knaff 1997).  As was observed with warm SSTs in the subtropical eastern Atlantic during February and March, above-average SSTs in April-May are strongly correlated with weaker trade winds, lower-than-normal sea level pressures and above-average SSTs in the tropical Atlantic during the following August-October period.  All three of these August-October features are commonly associated with active Atlantic basin hurricane seasons, through reductions in vertical wind shear, increased vertical instability and increased surface latent and sensible heat fluxes, respectively.  In addition, warmer-than-normal sea surface temperatures in the eastern Atlantic are typically associated with a positive phase of the Atlantic Multidecadal Oscillation (AMO) and a strong thermohaline circulation (Klotzbach and Gray 2007, manuscript submitted to Geophys. Res. Lett.). 

 

Predictor 2:  April-May SST – Nino 3.4 index (-):


(5°S-5°N, 170-120°W)

 

When sea surface temperatures in the Nino 3.4 region during April-May are below average, it indicates that a La Niña event is likely taking place.  Typically, by the end of May, the springtime ENSO predictability barrier (e.g., Samelson and Tziperman 2001) has passed, and therefore the persistence of either warm or cold anomalies is likely to continue through the upcoming Atlantic basin hurricane season.  As has been discussed extensively in previous forecasts, El Niño conditions during the summer and fall tend to decrease Atlantic hurricane activity by increasing vertical wind shear across the area where Atlantic tropical cyclones develop (e.g., Gray 1984a). 

 

Predictor 3:  July-November AMM Prediction (+):


(21°S-32°N, South American Coastline – West African Coastline)

 

The Atlantic Meridional Mode (AMM) evaluates the strength of the SST gradient between the northern tropical and southern tropical Atlantic, spanning from 21°S-32°N and the South American coastline to the West African coastline.  A positive AMM is in place when the meridional gradient of SST between the northern tropical Atlantic and southern tropical Atlantic is greater than the long-period average.  When the AMM is positive, the Intertropical Convergence Zone (ITCZ) shifts northward.  Consequently, convergence is enhanced in the northern tropical Atlantic, while trade wind strength and vertical wind shear in the tropical Atlantic are reduced.  Also associated with a northward-shifted ITCZ are enhanced low-level vorticity and below-normal sea level pressures (Knaff 1997).  When all these conditions occur, more active Atlantic basin tropical cyclone seasons are typically observed (Klotzbach and Gray 2006, Kossin and Vimont 2007, Vimont and Kossin 2007).  This AMM prediction, issued in early December of the previous year, explains approximately 40% of the variance of the observed AMM during the following year’s July-November period. 

 

 

3                   Analog-Based Predictors for 2007 Hurricane Activity

 

Certain years in the historical record have global oceanic and atmospheric trends which are substantially similar to 2007.  These years also provide useful clues as to likely trends in activity that the forthcoming 2007 hurricane season may bring.  For this late May forecast, we project atmospheric and oceanic conditions for August through October 2007 and determine which of the prior years in our database have distinct trends in key environmental conditions which are similar to current April-May 2007 conditions.  Table 3 lists our analog selections.

 

We select prior hurricane seasons since 1949 which have similar atmospheric-oceanic conditions to those currently being experienced.  For 2007, we searched for years that had transitioning warm to cool ENSO conditions and warm North Atlantic sea surface temperatures.

 

There were six hurricane seasons since 1949 with characteristics most similar to what we observe in April-May 2007 and characteristics that we expect to see in August-October 2007.  The best analog years that we could find for the 2007 hurricane season are 1952, 1954, 1964, 1966, 1995 and 2003.  We anticipate that 2007 seasonal hurricane activity will have activity slightly more than what was experienced in the average of these six years.  We continue to expect that the 2007 hurricane season will be very active. 

 

Table 3:  Best analog years for 2007 with the associated hurricane activity listed for each year.

 

Year

NS

NSD

H

HD

IH

IHD

ACE

NTC

1952

7

39.75

6

22.75

3

7.00

87

103

1954

11

51.75

8

31.50

2

9.50

95

127

1964

12

71.25

6

43.00

6

14.75

170

184

1966

11

64.00

7

41.75

3

7.75

145

137

1995

19

121.25

11

61.75

5

11.50

227

222

2003

16

79.25

7

32.75

3

16.75

175

174

Mean

12.7

71.20

7.5

38.90

3.7

11.40

150

158

 

2007 Forecast

17

85

9

40

5

11

170

185

 

4                   ENSO

 

ENSO conditions have continued to trend cooler over the past couple of months.  Currently observed SST anomalies in the various Nino regions range from approximately +0.1°C in the Nino 4 region (5°S-5°N, 160°E-150°W) to approximately -1.5°C in the Nino 1+2 regions (10°S-0°, 80-90°W), indicating that we currently have ENSO-neutral conditions in the tropical Pacific.  However, these current SST anomalies are now on the cool side of neutral, and we expect either cool neutral or La Niña conditions during this year’s hurricane season.  Table 4 shows the April-May SST anomalies compared with the February-March SST anomalies in various Nino regions.  A continued cooling trend is evident in all regions. 

 


Table 4:  April-May SST anomaly compared with February-March SST anomaly in various Nino regions.  

 

Year

February-March Anomaly (°C)

April-May Anomaly (°C)

(Apr-May) – (Feb-Mar)

Nino 1+2

-0.3

-1.2

-0.9

Nino 3

-0.1

-0.4

-0.3

Nino 3.4

0.1

-0.1

-0.2

Nino 4

0.5

0.2

-0.3

 

 

All ENSO forecast models indicate that neutral or cool ENSO conditions are likely for this upcoming summer/fall.  Based on the latest prediction plume figure from the International Research Institute (IRI) (Figure 2), no models are calling for El Niño conditions (SST anomaly greater than 0.5°C) in the Nino 3.4 region (5°S-5°N, 120-170°W) during the August-October period.  The forecast models are basically split between weakly cool and La Niña conditions (SST anomaly less than -0.5°C). 

 

Based on the latest ENSO predictions as well as currently observed conditions in the tropical Pacific, we expect fairly cool ENSO conditions to be in place in the tropical Pacific during the upcoming hurricane season.  Since SSTs in the tropical and northern Atlantic continue to be well above average, we expect a very active hurricane season in 2007.