EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND U.S. LANDFALL STRIKE PROBABILITY FOR 2006

EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND U.S. LANDFALL STRIKE PROBABILITY FOR 2006

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

Colorado State University

Fort Collins, CO 80523

Email: amie@atmos.colostate.edu

ATLANTIC BASIN SEASONAL HURRICANE FORECAST FOR 2006

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 U.S. coastline - 82% (average for last century is 52%)

2) U.S. East Coast Including Peninsula Florida - 69% (average for last century is 31%)

3) Gulf Coast from the Florida Panhandle westward to Brownsville - 38% (average for last century is 30%)

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

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 U.S. major hurricane landfall is estimated to be about 60 percent above the long-period average. Landfall probabilities are based upon our expectation for another very active season as well as analysis of our new steering current predictors for the East Coast and Gulf Coast of the United States.

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 Atlantic Ocean have become somewhat more favorable for an active hurricane season. Weaker trade winds have led to anomalous warming of the tropical Atlantic since the early part of April. We therefore continue to expect that another very active hurricane season is likely for the Atlantic basin.

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 Colorado State University for much statistical analysis and advice over many years.

DEFINITIONS

1 Introduction

This is the 23^rd 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 Atlantic (Gray 1984a, Goldenberg and Shapiro 1996). These increased westerlies increase vertical wind shear across the area where Atlantic tropical cyclones develop.

Predictor 2. April-May SST off the Northwestern European Coast (+)

(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 Atlantic are also weaker than normal, and there is less cold water advection. These anomalies in April-May correlate strongly with a generally warm Atlantic Ocean as well as with low sea level pressure throughout the tropical Atlantic during the main part of the hurricane season from August-October. Weaker trade winds and easterly anomalies at upper levels (i.e., reduced vertical wind shear) during the summer/fall throughout the tropical Atlantic are also associated with this feature.

Predictor 3. March-April SLP in the Tropical Atlantic (-)

(0-20°N, 0-40°W)

Low sea level pressure in the tropical Atlantic during March-April implies increased instability, reduced trade wind strength and warm sea surface temperatures during the spring. In general, these are favorable conditions for tropical cyclone activity. Such conditions tend to persist through the summer and fall, as evidenced by strong lag correlations (r > 0.4) between this feature and warm sea surface temperatures in the tropical Atlantic during the late summer/early fall. Also, reduced vertical wind shear and continued low sea level pressure in the tropical Atlantic during the late summer/early fall are associated with low pressure in this area during March-April.

Predictor 4. Previous November 500 MB Geopotential Height in the far North Atlantic (+)

(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 North Atlantic Ocean (50-60°N, 10-50°W). Also, on decadal timescales, weaker zonal winds in the sub-polar areas are indicative of a relatively strong thermohaline circulation which is favorable for hurricane activity. Positive values of this November index are negatively correlated with both 200 mb zonal winds and trade winds the following August-October in the tropical Atlantic. The associated reduced tropospheric vertical wind shear enhances conditions for TC development. Other features that are directly correlated with this predictor are low sea level pressure in the Caribbean and a warm North and tropical Atlantic the following summer. Both of the latter are also hurricane-enhancing factors.

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).

Variable	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 North Atlantic sea surface temperatures and neutral ENSO conditions. In addition, we look for analogs with similar conditions to what we project for August-October 2006 including warm Atlantic sea surface temperatures, neutral ENSO conditions and west phase QBO conditions.

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 Atlantic is warm and neutral ENSO conditions are present, Atlantic basin hurricane activity is enhanced.