EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND
We continue to foresee another very active Atlantic basin tropical cyclone season in 2006. Landfall probabilities for the 2006 hurricane season are well above their long-period averages.
(as of 31 May 2006)
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 and Brad Bohlander, Colorado State University Media
Representatives, (970-491-6432) are available to answer various questions about
this forecast
Department of Atmospheric Science
Email: amie@atmos.colostate.edu
|
Forecast Parameter and 1950-2000 Climatology (in parentheses) |
Issue Date 6 December 2005 |
Issue Date 4 April 2006 |
Issue Date 31 May 2006 |
|
Named Storms (NS) (9.6) |
17 |
17 |
17 |
|
Named Storm Days (NSD) (49.1) |
85 |
85 |
85 |
|
Hurricanes (H) (5.9) |
9 |
9 |
9 |
|
Hurricane Days (HD) (24.5) |
45 |
45 |
45 |
|
Intense Hurricanes (IH) (2.3) |
5 |
5 |
5 |
|
Intense Hurricane Days (IHD) (5.0) |
13 |
13 |
13 |
|
Net Tropical Cyclone Activity (NTC) (100%) |
195 |
195 |
195 |
PROBABILITIES FOR AT LEAST ONE MAJOR (CATEGORY 3-4-5) HURRICANE LANDFALL ON EACH OF THE FOLLOWING COASTAL AREAS:
1) Entire
2) U.S.
East Coast Including Peninsula
3)
4) Above-average
major hurricane landfall risk in the
Notice of Author Changes
By William Gray
The order of the authorship of these forecasts has been reversed 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 five years and has been second author on these forecasts for the last four 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 five years ago. 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. I plan to continue to be closely involved in the issuing of these forecasts for the next few years.
ABSTRACT
Information obtained through May
2006 continues to indicate that the 2006 Atlantic hurricane season will be much
more active than the average 1950-2000 season.
We estimate that 2006 will have about 9 hurricanes (average is 5.9), 17
named storms (average is 9.6), 85 named storm days (average is 49.1), 45
hurricane days (average is 24.5), 5 intense (Category 3-4-5) hurricanes
(average is 2.3) and 13 intense hurricane days (average is 5.0). The probability of
We expect Atlantic basin Net
Tropical Cyclone (NTC) activity in 2006 to be about 195 percent of the
long-term average. This late May
forecast is based on a newly devised extended range statistical forecast
procedure which utilizes 52 years of past global reanalysis data. Analog
predictors are also utilized. This 31 May forecast maintains our forecast from
our early December 2005 and early April 2006 predictions as, although weak La
Niña conditions have mostly returned to near neutral sea surface temperatures,
conditions in the tropical
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 Landfalling Hurricane Probability Webpage (available online at http://www.e-transit.org/hurricane).
The second author gratefully
acknowledges valuable input to his CSU research project over many years by
former graduate students and now colleagues Chris Landsea, John Knaff and Eric
Blake. We also thank Professors Paul
Mielke and Ken Berry of
This is the 23rd 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 a statistical methodology derived from 56 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 associated with 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 4-5 semi-independent atmospheric-oceanic parameters together. The best predictors (out of a group of 4-5) 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 4-5 other predictors.
In a five-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 five 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 4-5 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 Earlier
1 June Statistical Hurricane Forecast Scheme
Our original early June seasonal hurricane forecast scheme was developed in the early 1990s and demonstrated significant hindcast skill for the period of 1950-1991 (Gray et al. 1994). This scheme included measurements of West African rainfall as an important forecast input.
Since the observed shift of Atlantic Ocean SST patterns in 1995 [and the implied increase in the strength of the Atlantic Thermohaline Circulation (THC)], our original 1 June forecast scheme (1994) has consistently under-predicted Atlantic basin hurricane activity. Our earlier 1 June statistical scheme used West African rainfall data as an important predictor. We do not understand why, but the previously observed (1950-1994) strong association between West African rainfall and Atlantic hurricanes has not been reliable since 1994. We have lost confidence in the previous 1 June statistical forecast scheme compared to our newly developed one. We have thus decided to discontinue our earlier 1 June forecast scheme.
Over the past couple of years, we have been using an updated statistical scheme that utilized NOAA/NCEP reanalysis data. However, this scheme used mostly data from the previous fall and winter, and therefore we have recently developed a new early June (issued on 31 May) scheme that makes use of mostly spring data.
2.1 Newly-Developed
1 June Forecast Scheme
Our newly-developed early June forecast scheme also utilizes NOAA/NCEP reanalysis data and was developed on data from 1949-1989. It was then tested on independent data from 1990-2004 to insure that the forecast shows similar skill in this later forecast period.
The pool of four predictors for this new extended range forecast is given and defined in Table 1. The location of each of these new predictors is shown in Fig. 1. Strong statistical relationships can be extracted via combinations of these predictive parameters (which are available by the end of May), and quite skillful Atlantic basin hurricane forecasts for the following summer and fall can be made if the atmosphere and ocean continue to behave in the future as they have during the hindcast period of 1949-2004.

Figure 1: Location of predictors for the 31 May forecast for the 2006 hurricane season.
Table 1: Listing of 31 May 2006
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 four predictors
calls for an above-average hurricane season.
|
Predictor |
Values for 2006 Forecast |
|
1) May SST (5°S-5°N, 90-150°W) (-) |
+0.2 SD |
|
2) April-May SST (30-45°N, 10-30°W) (+) |
+0.5 SD |
|
3) March-April SLP (0-20°N, 0-40°W) (-) |
+0.2 SD |
|
4) Previous November 500 MB Ht. (67.5-85°N, 50°W
-10°E) (+) |
+0.6 SD |
Table 2 shows our statistical forecast for the 2006 hurricane season and the comparison of this forecast with climatology (average season between 1950-2000). Our statistical forecast is calling for above-average activity this year.
Table 2: 1 June statistical forecast for 2006.
|
Predictands and Climatology |
Statistical Forecast Numbers |
|
Named Storms (NS) – 9.6 |
11.0 |
|
Named Storm Days (NSD) – 49.1 |
57.4 |
|
Hurricanes (H) – 5.9 |
6.7 |
|
Hurricane Days (HD) – 24.5 |
28.8 |
|
Intense Hurricanes (IH) – 2.3 |
3.0 |
|
Intense Hurricane Days (IHD) – 5.0 |
7.7 |
|
Net Tropical Cyclone Activity (NTC) – 100 |
124 |
2.2 Physical Associations among Predictors Listed in Table 1
Brief descriptions of our 1 June predictors follow:
Predictor
1. May SST in the Eastern Equatorial
Pacific (-)
(5°S-5°N, 90-150°W)
Sea surface temperatures in this area are taken to be a
measure of ENSO conditions, as defined by the Nino 3 index. When sea surface
temperatures are much cooler than normal, La Niña conditions are present, and
when sea surface temperatures are much warmer than normal, El Niño conditions
are occurring. Although there is some changeover during the summer and fall, in
general, anomalies in this area tend to persist from the late spring through
the summer and fall. El Niño conditions during the summer and fall tend to
decrease Atlantic hurricane activity by increasing westerlies at upper levels
across the
Predictor
2. April-May SST off the
(30-45°N, 10-30°W)
Warm sea surface temperatures in this area indicate that the
Atlantic subtropical ridge is weaker than normal, and therefore northeasterly trade
winds across the
Predictor
3. March-April SLP in the Tropical
(0-20°N, 0-40°W)
Low sea level pressure in the tropical
Predictor
4. Previous November 500 MB Geopotential
Height in the far
(67.5-85°N, 50°W-10°E)
Positive values of this predictor correlate very strongly (r
= -0.7) with negative values of the Arctic Oscillation (AO) and the North
Atlantic Oscillation (NAO). Negative AO and NAO values imply more ridging in
the central Atlantic and likely also a warm
2.3 Hindcast Skill
Table 3 shows the degree of hindcast variance (r2) explained by our new 1 June forecast scheme based on our 41-year developmental dataset (1949-1989), our skill on the independent dataset (1990-2004), and our skill over the entire dataset (1949-2004). Note that the scheme generally shows comparable or improved skill in the independent dataset, which lends increased confidence in its use.
Table 3: Variance (r2) explained for our new 1 June forecast scheme in the developmental dataset (1949-1989), in the independent dataset (1990-2004), and over the entire dataset (1949-2004).
|
|
Variance (r2)
Explained Developmental Dataset (1949-1989) |
Variance (r2)
Explained Independent Dataset (1990-2004) |
Variance (r2)
Explained Entire Dataset (1949-2004) |
|
NS |
0.27 |
0.49 |
0.29 |
|
NSD |
0.40 |
0.65 |
0.37 |
|
H |
0.31 |
0.67 |
0.36 |
|
HD |
0.51 |
0.63 |
0.49 |
|
IH |
0.45 |
0.67 |
0.49 |
|
IHD |
0.54 |
0.38 |
0.48 |
|
NTC |
0.54 |
0.70 |
0.52 |
3 Analog-Based
Predictors for 2006 Hurricane Activity
Certain years in the historical record have global oceanic and atmospheric trends which are substantially similar to 2006. These years also provide useful clues as to trends in activity that the upcoming 2006 hurricane season may bring. For this late May extended range forecast, we project atmospheric and oceanic conditions for August through October 2006 and determine which of the prior years in our database have distinct trends in key environmental conditions which are similar to current April-May 2006 conditions. Table 4 lists our analog selections.
We select prior hurricane seasons
since 1949 which have similar atmospheric-oceanic conditions to those currently
being experienced. Analog years for 2006
were selected primarily on how similar they are to conditions that are
currently observed such as warm tropical and
There were four hurricane seasons since 1949 with characteristics similar to what we observed in April-May and what we project for August-October. The best analog years that we could find for the 2006 hurricane season are 1961, 1996, 2001 and 2004. We anticipate that 2006 will have comparable seasonal hurricane activity to what was experienced in the average of these four years. We believe that 2006 will be a very active season in the Atlantic basin.
Table 4: Best analog years for 2006 with the associated hurricane activity listed for each year.
|
Year |
NS |
NSD |
H |
HD |
IH |
IHD |
NTC |
|
1961 |
11 |
70.75 |
8 |
47.50 |
6 |
21.50 |
213 |
|
1996 |
13 |
79.00 |
9 |
45.00 |
6 |
13.00 |
192 |
|
2001 |
15 |
64.25 |
9 |
25.50 |
4 |
4.25 |
134 |
|
2004 |
14 |
90.25 |
9 |
45.50 |
6 |
22.25 |
229 |
|
Mean |
13.3 |
76.1 |
8.8 |
40.9 |
5.5 |
15.3 |
192.0 |
|
2006
Forecast |
17 |
85 |
9 |
45 |
5 |
13 |
195 |
4 ENSO
We believe that neutral ENSO
conditions are likely to be present during August-October 2006. A weakening La Niña event was observed in
the eastern and central tropical Pacific over the past few months. Sea surface temperatures have warmed somewhat
over the past couple of months, and according to the Climate Prediction Center
(CPC), neutral ENSO conditions are currently observed. However, Southern Oscillation Index (SOI)
values remain positive, trade winds in the central Pacific have remained fairly
strong, and oceanic heat content in the western and central Pacific is not
particularly warm. We therefore do not
expect El Niño conditions to develop this summer. In addition, most forecast models call for
neutral ENSO conditions to persist for the next 4-6 months. When the tropical
5 Adjusted
2006 Forecast
Table 5 shows our final adjusted late May forecast for the 2006 season which is a combination of our derived full 52-year statistical forecast, our analog forecast and qualitative adjustments for other factors not explicitly contained in either scheme. We foresee another very active Atlantic basin hurricane season. We anticipate that ENSO conditions will likely be neutral this summer and fall. Warm sea surface temperatures are likely in the tropical and North Atlantic during 2006, due to the fact that we are in a positive phase of the Atlantic Multidecadal Oscillation (AMO) (i.e., a strong phase of the Atlantic thermohaline circulation), and tropical Atlantic trade winds have been anomalously weak in April and May.
Table 5: Summary of our new late May statistical forecast, our analog forecast and our adjusted final forecast for the 2006 hurricane season.
|
Forecast Parameter and
1950-2000 Climatology (in parentheses) |
New Statistical Scheme |
Analog Scheme |
Adjusted Final Forecast |
|
Named Storms (9.6) |
11.0 |
13.3 |
17 |
|
Named Storm Days
(49.1) |
57.4 |
76.1 |
85 |
|
Hurricanes (5.9) |
6.7 |
8.8 |
9 |
|
Hurricane Days (24.5) |
28.8 |
40.9 |
45 |
|
Intense Hurricanes
(2.3) |
3.0 |
5.5 |
5 |
|
Intense Hurricane Days
(5.0) |
7.7 |
15.3 |
13 |
|
Net Tropical Cyclone Activity (100%) |
124.0 |
192.0 |
195 |
6 Skill
and Verification of 1 June Forecasts
We define forecast skill as the degree to which we are able to predict the variation of seasonal hurricane activity parameters above that specified by a long-term climatology. The latter is expressed as the ratio of our forecast error to the observed difference from climatology or:
Forecast Error / Seasonal Difference from Climatology
For example, if there were a year with five more tropical storms than average and we had predicted two more storms than average, we would give ourselves a skill score of 2 over 5 or 40 percent. By this measure, each of the seven parameters of our seasonal forecasts has shown some degree of skill from 1 June. Table 6 shows our skill based on 52 years of hindcasts from 1950-2001, and Table 7 displays our skill score in real-time forecasting for the last seven years. All parameters of our real-time forecasts have shown skill from 1 June.
Table 6: Average percent of variation explained of 1 June (or 31 May) hindcasts above that of climatology (in percent) for the 52-year period 1950-2001. A value of 30 means that we hindcast 30 percent of the variability from climatology or that we were unable to explain 70 percent of the variability from climatology.
|
Tropical Cyclone Parameter |
Early June Hindcast Skill |
|
NS |
22 |
|
NSD |
26 |
|
H |
26 |
|
HD |
32 |
|
IH |
27 |
|
IHD |
28 |
|
NTC |
33 |
Table 7: Last seven years’ (1999-2005) average percent of variation explained of our ‘real-time’ forecasts issued on 1 June (or 31 May) above that of climatology (in percent). A value of 40 means that we hindcast 40 percent of the variability from+ climatology or that we were unable to explain 60 percent of the variability from climatology.
|
Tropical Cyclone Parameter |
Early June Forecast Skill |
|
NS |
49 |
|
NSD |
53 |
|
H |
38 |
|
HD |
58 |
|
IH |
38 |
|
IHD |
27 |
|
NTC |
47 |
Another way to consider the skill of our forecasts is to evaluate whether the forecast for each parameter successfully forecast above- or below-average activity. Table 8 displays how frequently our forecasts have been on the right side of climatology in hindcasts from 1950-2001 and in real-time forecasts for the past seven years (1999-2005). Note that our early June scheme has been successful at determining whether various hurricane parameters will be above- or below-average about 75% of the time at the extended lead time of 1 June (or 31 May) in hindcasts and over 90% of the time in real-time forecasts.
Table 8: The number of years that our tropical cyclone forecasts issued on 1 June (or 31 May) has correctly predicted above- or below-average activity for each predictand in (A) hindcast mode (1950-2001) and in (B) real-time forecast mode (1999-2005).
|
Tropical Cyclone Parameter |
(A) Hindcast |
(B) Forecast |
|
NS |
39/52 |
7/7 |
|
NSD |
39/52 |
7/7 |
|
H |
37/52 |
6/7 |
|
HD |
35/52 |
6/7 |
|
IH |
41/52 |
7/7 |
|
IHD |
37/52 |
6/7 |
|
NTC |
42/52 |
7/7 |
|
Total |
270/364 |
46/49 |
|
Correct Prediction of Above or Below Climatology |
74% |
94% |
Of course, there are significant amounts of unexplained variance in a number of the individual parameter forecasts. Even though the skill for some of these parameter forecasts is somewhat low, there is a great curiosity in having some objective measure as to how active the coming hurricane season is likely to be. Therefore, even a forecast that has shown only modest skill in past years should be considered worthwhile when the only other information available is climatology.
7 Landfall
Probability
7.1 Introduction
A significant focus of our recent
research involves efforts to develop forecasts of the probability of hurricane
landfall along the
As shown in Table 9, NTC is a
combined measure of the year-to-year mean of six indices of hurricane activity,
each expressed as a percentage difference from the long-term average. Long-term statistics show that, on average,
the more active the overall Atlantic basin hurricane season is, the greater the
probability of
Table 9: NTC activity in any year consists of the seasonal total of the following six parameters expressed in terms of their long-term averages. A season with 10 NS, 50 NSD, 6 H, 25 HD, 3 IH, and 5 IHD would then be the sum of the following ratios: 10/9.6 = 104, 50/49.1 = 102, 6/5.9 = 102, 25/24.5 = 102, 3/2.3 = 130, 5/5.0 = 100, divided by six, yielding an NTC of 107.
|
1950-2000 Average |
||
|
1) |
Named Storms (NS) |
9.6 |
|
2) |
Named Storm Days (NSD) |
49.1 |
|
3) |
Hurricanes (H) |
5.9 |
|
4) |
Hurricane Days (HD) |
24.5 |
|
5) |
Intense Hurricanes (IH) |
2.3 |
|
6) |
Intense Hurricane Days (IHD) |
5.0 |
7.2 Steering Current Prediction
As mentioned in our early April forecast, we have considerably improved the statistical skill of our landfall probability forecasts through the inclusion of three predictors of mid-latitude steering flow for the Florida Peninsula and the East Coast and two predictors of mid-latitude steering flow for the Gulf Coast. Based on data from the NCEP/NCAR reanalysis, using a combination of our NTC forecast and the predictors listed in Tables 10 and 11 and displayed in Figures 2 and 3, we are able to hindcast approximately 30 percent of the variance in hurricane landfall for the Gulf Coast and approximately 50 percent of the variance in hurricane landfall for the Florida Peninsula and the East Coast over the period 1950-2004. As evidenced by hurricane landfall activity in 2004 and 2005 compared with the earlier period of 1995-2003, the strength of midlatitude westerly winds related to the position of the Bermuda High, is vitally important in determining how likely storms are to make landfall along either the East Coast or the Gulf Coast. The predictors listed in Tables 10 and 11 give us some degree of skill in predicting the mid-level steering flow during the hurricane season, and therefore add skill to our landfall probabilities beyond that specified by the combination of NTC and SSTA*. New research is finding that SSTA* does not add much additional skill beyond NTC and the steering current predictors, and therefore we have now discontinued the inclusion of SSTA* in our landfall probability calculations.
Table 10: Listing of 1
June steering current predictors for the East Coast and
|
Predictor |
Values for 2006 Forecast |
|
1) April-May 500 MB Ht. (35-50°N, 60-80°W) (+) |
+0.1 SD |
|
2) April-May SLP (20-40°S, 70-110°W) (+) |
+0.2 SD |
|
3) April-May 500 MB Ht. (70-85°N, 20°W-100°E) (+) |
+1.9 SD |
Table 11: Listing of 1 June
steering current predictors for the
|
Predictor |
Values for 2006 Forecast |
|
1) May 500 MB Ht. (10-25°S, 20-60°W) (+) |
-0.8 SD |
|
2) April-May 500 MB Ht. (40-55°S, 120°E-170°W) (+) |
+0.1 SD |

Figure 2: Listing of 1 June steering current
predictors for the East Coast and

Figure 3: Listing of 1
June steering current predictors for the
7.3 Steering Current Predictor Physical
Relationships
Brief descriptions of how we believe our April-May predictors relate to the steering currents likely to be present during the hurricane season are as follows:
East Coast
Predictors:
Predictor
1. April-May 500 MB Geopotential Height
in the Northeast United States and
(35-50°N, 60-80°W)
Anomalously high heights in the northeast
Predictor
2. April-May 500 MB Geopotential Height
off the West Coast of
(20-40°S, 70-110°W)
Anomalous ridging off the west coast of South America during
April-May is commonly associated with strong equatorial east winds over the
eastern Pacific and cold water upwelling.
Such cold water upwelling is associated with a positive Southern
Oscillation Index (SOI) and hence a La Niña event. La Niña events tend to persist from late May
through the summer/fall period. In
general,
Predictor
3. April-May 500 MB Geopotential Height
in the
(70-85°N, 20°W-100°E)
Anomalously high heights in the
Predictor
1. May 500 MB Geopotential Height off
the East Coast of
(10-25°S, 20-60°W)
Anomalously high heights off the east coast of
Predictor
2. April-May 500 MB Geopotential Height
off the
(40-55°S, 120°E-170°W)
Anomalous ridging off the south coast of
7.4 2006 Landfall Probabilities
Landfall
probabilities for the 2006 season are calculated based upon values of the
steering current predictors listed in the previous section and NTC. Landfall probabilities for the East Coast are
quite high this year, due to a combination of both a very high predicted NTC
value and favorable steering currents for East Coast landfall. In general, a negative North Atlantic Oscillation
(NAO) and Arctic Oscillation (AO) increases the likelihood of East Coast
landfall, and both of these indices have been predominately negative so far
this spring (Xie et al. 2005). Two of the
three predictors utilized in our East Coast steering current model relate to
the NAO and AO, especially Predictor 3, which as can be seen in Table 10, has
very high values this year. The odds of
a major hurricane making landfall along the East Coast are more than twice the
climatological average value this year.
For the
Table 12
displays the landfall probabilities for the 2006 season.
Please visit our website at http://www.e-transit.org/hurricane
for landfall probabilities for 11
Table 12: Estimated probability (expressed in percent) of one or more U.S. landfalling tropical storms (TS), category 1-2 hurricanes (HUR), category 3-4-5 hurricanes, and total hurricanes and named storms along the entire U.S. coastline, along the Gulf Coast (Regions 1-4), and along the Florida Peninsula and the East Coast (Regions 5-11) for 2006. The long-term mean annual probability of one or more landfalling systems during the 20th century is given in parentheses.
|
Coastal Region |
TS |
Category 1-2 HUR |
Category 3-4-5 HUR |
All HUR |
Named Storms |
|
Entire |
94% (80%) |
90% (68%) |
82% (52%) |
95% (84%) |
99% (97%) |
|
|
66% (59%) |
44% (42%) |
38% (30%) |
62% (61%) |
86% (83%) |
|
|
85% (51%) |
83% (45%) |
69% (31%) |
87% (62%) |
94% (81%) |
8 Is Global Warming Responsible for the
Large Upswing in 2004-2005 US Hurricane Landfalls?
8.1 Background
The
The global warming arguments have been given much attention by many media references to recent papers claiming to show such a linkage. Despite the global warming of the sea surface of about 0.4°C that has taken place over the last two decades, global numbers of hurricanes and their intensity have not shown increases over the past twenty years (Klotzbach 2006). In addition, we have no valid physical theory as to why small changes of global average sea surface temperature (SST) should bring about increases in Atlantic basin hurricane activity. In the past century, Atlantic basin hurricane activity has been above-average both when global SST has been increasing (from the middle 1920s through the middle 1940s) and when global SST has been decreasing (from the middle 1940s through the middle 1960s).
The Atlantic has seen a very large
increase in major hurricanes during the last 11-year period of 1995-2005
(average 4.0 per year) in comparison to the prior 25-year period of 1970-1994
(average 1.5 per year). This large
increase in Atlantic major hurricanes is primarily a result of a multi-decadal
increase in strength in the
There have been similar past
periods (1940s-1950s) when the
8.2 Discussion
There is no physical basis for assuming that global hurricane intensity or frequency is necessarily related to global mean surface temperature changes of less than ± 0.5oC. As the ocean surface warms, global upper air temperatures warm as well to maintain conditionally unstable lapse-rates and global rainfall rates at their climatological values. Seasonal and monthly variations of sea surface temperature (SST) within individual storm basins show only very low correlations with monthly, seasonal, and yearly variations of hurricane activity (Shapiro and Goldenberg 1998, Klotzbach 2006). Other factors such as tropospheric vertical wind shear, surface pressure, low level vorticity, mid-level moisture, etc. play more dominant roles in explaining hurricane variability than do surface temperatures. Although there has been a general global warming over the last 30 years and particularly over the last 10 years, the SST increases in the individual tropical cyclone basins have been smaller than the overall global warming (about half) and, according to the observations, have not brought about any significant increases in global major tropical cyclones except for the Atlantic which, as has been discussed, has multi-decadal oscillations driven primarily by changes in Atlantic salinity. No credible observational evidence is currently available that directly associates global surface temperature change with changes in global hurricane frequency and intensity.
Most Southeast coastal residents
probably do not know how fortunate they had been in the prior 38-year period
(1966-2003) leading up to 2004-2005 when there were only 17 major hurricanes
(0.45/year) that crossed the
We should interpret the last two
years of unusually large numbers of
It is rare to have two consecutive years with such a strong simultaneous combination of high amounts of major hurricane activity together with especially favorable steering flow currents. The historical records and the laws of statistics indicate that the probability of seeing another two consecutive hurricane seasons like 2004-2005 is very low. Even though we expect to see the current active period of Atlantic major hurricane activity continue for another 15-20 years, it is statistically unlikely that the coming 2006 and 2007 hurricane seasons, or the seasons which follow, will have the number of U.S. landfalling major hurricane events that we have seen in 2004-2005.
9 Forecast
Theory and Cautionary Note
Our forecasts are based on the
premise that those global oceanic and atmospheric conditions which preceded
comparatively active or inactive hurricane seasons in the past provide
meaningful information about similar trends in future seasons. It is important that the reader appreciate
that these seasonal forecasts are based on statistical schemes which, owing to
their intrinsically probabilistic nature, will fail in some years. Moreover, these forecasts do not specifically
predict where within the Atlantic basin these storms will strike. The probability of landfall for any one
location along the coast is very low and reflects the fact that, in any one
season, most
10 Forthcoming
Updated Forecasts of 2006 Hurricane Activity
We will be issuing seasonal updates of our 2006 Atlantic basin hurricane forecasts on Thursday 3 August, Friday 1 September and Tuesday 3 October 2006. The 3 August, 1 September and 3 October forecasts will include separate forecasts and updates of August-only, September-only and October-only Atlantic basin tropical cyclone activity. A verification and discussion of all 2006 forecasts will be issued in late November 2006. Table 13 displays our forecast schedule for the remainder of the 2006 hurricane season. Our first seasonal hurricane forecast for the 2007 hurricane season will be issued in early December 2006. All of these forecasts will be made available on the web at: http://hurricane.atmos.colostate.edu/Forecasts.
Table 13: Timetable of upcoming forecasts and updates for the 2006 hurricane season.
|
Forecast Date |
Based on Data Through |
Upcoming Forecasts and Updates |
|||
|
3 August 2006 |
July 2006 |
August Forecast |
September Forecast |
October Forecast |
Updated
Seasonal Forecast |
|
1 September 2006 |
August 2006 |
August Verification |
Updated September Forecast |
Updated October Forecast |
Updated Seasonal Forecast |
|
3 October 2006 |
September 2006 |
|
September Verification |
Updated October Forecast |
Updated Seasonal Forecast |
|
Late November 2006 |
Verification of all Forecasts |
||||
11 Acknowledgments
Besides the individuals named on page 4, there have been a number of other meteorologists that have furnished us with data and given valuable assessments of the current state of global atmospheric and oceanic conditions. These include Brian McNoldy, Arthur Douglas, Richard Larsen, Todd Kimberlain, Ray Zehr, and Mark DeMaria. In addition, Barbara Brumit and Amie Hedstrom have provided excellent manuscript, graphical and data analysis and assistance over a number of years. We have profited over the years from many in-depth discussions with most of the current and past NHC hurricane forecasters. The second author would further like to acknowledge the encouragement he has received for this type of forecasting research application from Neil Frank, Robert Sheets, Robert Burpee, Jerry Jarrell, former directors of the National Hurricane Center (NHC), and from the current director, Max Mayfield and their forecast staffs. Uma Shama and Larry Harman of Bridgewater State College, MA have provided assistance and technical support in the development of the Landfalling Hurricane Probability Webpage. We also thank Bill Bailey of the Insurance Information Institute for his sage advice and encouragement.
The financial backing for the issuing and verification of these forecasts has in part been supported by the National Science Foundation and by the Research Foundation of Lexington Insurance Company (a member of the American International Group). We also thank the GeoGraphics Laboratory at Bridgewater State College for their assistance in developing the Landfalling Hurricane Probability Webpage.
12 Citations
and Additional
13 Verification
of Previous Forecasts
Table 14: Summary verification of the authors’ six
previous years of seasonal forecasts for Atlantic TC activity between
2000-2005.
|
2000 |
8 Dec. 1999 |
Update 7 April |
Update 7 June |
Update 4 August |
Obs. |
|
No. of Hurricanes |
7 |
7 |
8 |
7 |
8 |
|
No. of Named Storms |
11 |
11 |
12 |
11 |
14 |
|
No. of Hurricane Days |
25 |
25 |
35 |
30 |
32 |
|
No. of Named Storm Days |
55 |
55 |
65 |
55 |
66 |
|
Hurr. Destruction Potential |
85 |
85 |
100 |
90 |
85 |
|
Intense Hurricanes |
3 |
3 |
4 |
3 |
3 |
|
Intense Hurricane Days |
6 |
6 |
8 |
6 |
5.25 |
|
Net Tropical Cyclone
Activity |
125 |
125 |
160 |
130 |
134 |
|
2001 |
7 Dec. 2000 |
Update 6 April |
Update 7 June |
Update 7 August |
Obs. |
|
No. of Hurricanes |
5 |
6 |
7 |
7 |
9 |
|
No. of Named Storms |
9 |
10 |
12 |
12 |
15 |
|
No. of Hurricane Days |
20 |
25 |
30 |
30 |
27 |
|
No. of Named Storm Days |
45 |
50 |
60 |
60 |
63 |
|
Hurr. Destruction Potential |
65 |
65 |
75 |
75 |
71 |
|
Intense Hurricanes |
2 |
2 |
3 |
3 |
4 |
|
Intense Hurricane Days |
4 |
4 |
5 |
5 |
5 |
|
Net Tropical Cyclone
Activity |
90 |
100 |
120 |
120 |
142 |
|
2002 |
7 Dec. 2001 |
Update 5 April |
Update 31 May |
Update 7 August |
Update 2 Sept. |
Obs. |
|
No. of Hurricanes |
8 |
7 |
6 |
4 |
3 |
4 |
|
No. of Named Storms |
13 |
12 |
11 |
9 |
8 |
12 |
|
No. of Hurricane Days |
35 |
30 |
25 |
12 |
10 |
11 |
|
No. of Named Storm Days |
70 |
65 |
55 |
35 |
25 |
54 |
|
Hurr. Destruction Potential |
90 |
85 |
75 |
35 |
25 |
31 |
|
Intense Hurricanes |
4 |
3 |
2 |
1 |
1 |
2 |
|
Intense Hurricane Days |
7 |
6 |
5 |
2 |
2 |
2.5 |
|
Net Tropical Cyclone
Activity |
140 |
125 |
100 |
60 |
45 |
80 |
|
2003 |
6 Dec. 2002 |
Update 4 April |
Update 30 May |
Update 6 August |
Update 3 Sept. |
Update 2 Oct. |
Obs. |
|
No. of Hurricanes |
8 |
8 |
8 |
8 |
7 |
8 |
7 |
|
No. of Named Storms |
12 |
12 |
14 |
14 |
14 |
14 |
14 |
|
No. of Hurricane Days |
35 |
35 |
35 |
25 |
25 |
35 |
32 |
|
No. of Named Storm Days |
65 |
65 |
70 |
60 |
55 |
70 |
71 |
|
Hurr. Destruction Potential |
100 |
100 |
100 |
80 |
80 |
125 |
129 |
|
Intense Hurricanes |
3 |
3 |
3 |
3 |
3 |
2 |
3 |
|
Intense Hurricane Days |
8 |
8 |
8 |
5 |
9 |
15 |
17 |
|
Net Tropical Cyclone
Activity |
140 |
140 |
145 |
120 |
130 |
155 |
173 |
|
2004 |
5 Dec. 2003 |
Update 2 April |
Update 28 May |
Update 6 August |
Update 3 Sept. |
Update 1 Oct. |
Obs. |
|
No. of Hurricanes |
7 |
8 |
8 |
7 |
8 |
9 |
9 |
|
No. of Named Storms |
13 |
14 |
14 |
13 |
16 |
15 |
14 |
|
No. of Hurricane Days |
30 |
35 |
35 |
30 |
40 |
52 |
46 |
|
No. of Named Storm Days |
55 |
60 |
60 |
55 |
70 |
96 |
90 |
|
Intense Hurricanes |
3 |
3 |
3 |
3 |
5 |
6 |
6 |
|
Intense Hurricane Days |
6 |
8 |
8 |
6 |
15 |
23 |
22 |
|
Net Tropical Cyclone
Activity |
125 |
145 |
145 |
125 |
185 |
240 |
229 |
|
2005 |
3 Dec. 2004 |
Update 1 April |
Update 31 May |
Update 5 August |
Update 2 Sept. |
Update 3 Oct. |
Obs. |
|
No. of Hurricanes |
6 |
7 |
8 |
10 |
10 |
11 |
15 |
|
No. of Named Storms |
11 |
13 |
15 |
20 |
20 |
20 |
27 |
|
No. of Hurricane Days |
25 |
35 |
45 |
55 |
45 |
40 |
51 |
|
No. of Named Storm Days |
55 |
65 |
75 |
95 |
95 |
100 |
125 |
|
Intense Hurricanes |
3 |
3 |
4 |
6 |
6 |
6 |
7 |
|
Intense Hurricane Days |
6 |
7 |
11 |
18 |
15 |
13 |
16.75 |
|
Net Tropical Cyclone
Activity |
115 |
135 |
170 |
235 |
220 |
215 |
275 |