EXTENDED RANGE FORECAST OF ATLANTIC SEASONAL HURRICANE ACTIVITY AND
We foresee an
above-average Atlantic basin tropical cyclone season in 2007. We anticipate an above-average probability of
(as of 8 December 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, Colorado State University Media Representative, (970-491-6432) is
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) |
8 December 2006 Forecast for 2007 |
|
Named Storms (NS) (9.6) |
14 |
|
Named Storm Days (NSD) (49.1) |
70 |
|
Hurricanes (H) (5.9) |
7 |
|
Hurricane Days (HD) (24.5) |
35 |
|
Intense Hurricanes (IH) (2.3) |
3 |
|
Intense Hurricane Days (IHD) (5.0) |
8 |
|
Accumulated Cyclone Energy (ACE) (96.1) |
130 |
|
Net Tropical Cyclone Activity (NTC) (100%) |
140 |
In order to facilitate easier comparison with other seasonal forecasting groups (e.g., NOAA, Tropical Storm Risk, etc.), we have decided to start predicting an Accumulated Cyclone Energy (ACE) index as part of our seasonal forecasts. ACE is defined to be a measure of a named storm’s potential for wind and storm surge destruction defined as the sum of the square of a named storm’s maximum wind speed (in 104 knots2) for each 6-hour period of its existence. ACE is similar to the Hurricane Destruction Potential (HDP) index that we forecast for a number of years.
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
ABSTRACT
Information obtained through
November 2006 indicates that the 2007 Atlantic hurricane season will be more
active than the average 1950-2000 season.
We estimate that 2007 will have about 7 hurricanes (average is 5.9), 14
named storms (average is 9.6), 70 named storm days (average is 49.1), 35
hurricane days (average is 24.5), 3 intense (Category 3-4-5) hurricanes
(average is 2.3) and 8 intense hurricane days (average is 5.0). The probability of
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 six years and has been second author on these forecasts for the last five 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 six 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.
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
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 50-55 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 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 Early December
Forecast Methodology
Our initial 6-11 month early December seasonal hurricane forecast scheme (Gray et al. 1992) demonstrated hindcast skill for the period of 1950-1990 but did not give skillful results when utilized on a real-time basis for forecasts between 1995-2001. This was due to the discontinuation of the strong relationships we had earlier found between West African rainfall and the stratospheric quasi-biennial oscillation (QBO) with Atlantic basin major hurricane activity 6-11 months in the future. We did not expect these relationships that had worked so well for 41 years to stop working from 1995 onward. We do not yet have a good explanation as to why these relationships have failed. We have discontinued this earlier 1 December forecast scheme and have developed a new 1 December forecast scheme.
Beginning with the 2002 December forecast for the 2003 season, we have relied on a new early December forecast scheme (Klotzbach and Gray 2004) which does not utilize West African rainfall and gives less weight to the QBO. This newer extended range forecast scheme shows significantly improved hindcast skill compared with our earlier December forecast scheme. The location of each of these predictors is shown in Figure 1. The pool of six predictors for the extended range forecast is given in Table 1. Strong statistical relationships can be extracted via combinations of these predictors (which are available by 1 December) and the Atlantic basin hurricane activity occurring the following year.
Several of these predictors are
related to a positive Pacific-North American (PNA) pattern which is typically
correlated with warm ENSO conditions.
However, this year, the PNA was mostly negative through the fall, and
therefore, several of our predictors came in much less favorable for hurricane
activity than is typically expected when ENSO conditions are present. This year’s ENSO event came in 2-3 months
later than the typical warm event, and we believe that the atmosphere may not
have fully responded to the tropical oceanic forcing yet. In addition, years with warm Atlantic sea
surface temperatures in the North Atlantic tend to have weaker zonal winds
across the
We are inclined to put less stock in this early December statistical forecast this year due to the above-mentioned conditions. We have decided to develop a new scheme that uses even fewer predictors that we feel have stronger physical links with the following year’s hurricane activity. In addition, in an effort to design forecast schemes that will be more stable with time, we are now developing forecasts over a portion of the reliable record and testing it on the remainder of the record.
We have recently developed an even simpler, three-predictor model that we are consulting for the first time this year. This scheme shows comparable hindcast skill to the six-predictor scheme that we have been using over the past few years. We feel that the relationships between individual predictors and seasonal tropical cyclone activity occurring the following year are somewhat better understood using this new prediction scheme. Similar to our newly-developed August seasonal forecast scheme, this scheme only predicts Net Tropical Cyclone (NTC) activity, and the other predictors are then derived from this NTC prediction. For example, if a typical season has 10 named storms and the predicted NTC value is 120%, the predicted number of named storms for the season would be 12 (10 * 120%).
The location of the three predictors is shown in Figure 2, and a description of each of these predictors is given in Table 2. Predictors for this revised scheme were selected based on their hindcast skill over the 1950-1989 period, and the predictors were tested on independent data from 1990-2004. The combination of these three predictors explains 51 percent of the variance for Net Tropical Cyclone (NTC) activity on the dependent data (1950-1989), and using the equations developed over the 1950-1989 period, it explains 49 percent of the variance for NTC activity on the independent data (1990-2004).
Figure 1: Location of predictors for our early December extended range statistical prediction (developed in 2002) for the 2007 hurricane season.
Table 1: Listing of 1 December
2006 predictors for the 2007 hurricane season.
A plus (+) means that positive values of the parameter indicate
increased hurricane activity the following year, and a minus (-) means that
positive values of the parameter indicate decreased hurricane activity the
following year.
|
Predictor |
2006 Values for 2007 Forecast |
|
1) November 500 mb geopotential height (67.5-85°N,
10°E-50°W) (+) |
-1.1 SD |
|
2) October-November SLP (45-65°N, 120-160°W) (-) |
+1.4 SD |
|
3) September 500 mb geopotential height (35-55°N,
100-120°W) (+) |
+0.3 SD |
|
4) July 50 mb U (5°S-5°N, 0-360°) (-) |
+1.2 SD |
|
5) September-November SLP (15-35°N, 75-95°W) (-) |
-1.1 SD |
|
6) November SLP
(7.5-22.5°N, 125-175°W) (+) |
-0.6 SD |
Figure 2: Location of predictors for our experimental December extended range statistical prediction (developed in 2006) for the 2007 hurricane season.
Table 2: Listing of 1 December 2006 predictors using
the experimental forecast for the 2007 hurricane season. A plus (+) means that positive values of the
parameter indicate increased hurricane activity the following year, and a minus
(-) means that positive values of the parameter indicate decreased hurricane
activity the following year.
|
Predictor |
2006 Values for 2007 Forecast |
|
1) October-November SLP (10-60°N, 10-30°W) (-) |
-1.7 SD |
|
2) October-November SST (55-65°N, 10-60°W) (+) |
+1.6 SD |
|
3) October-November SLP
(5-25°N, 150-180°W) (+) |
-1.6 SD |
2.1
Physical
Associations among Predictors Listed in Table 1 for our Forecast Scheme Developed
in 2002
The locations and brief descriptions of our 6-11 month predictors follow:
Predictor
1. November 500 mb Geopotential Height
in the far
(67.5-85°N, 10°E-50°W)
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 a warm
Predictor
2. October-November SLP in the
(45-65°N, 120-160°W)
Negative values of this predictor are strongly correlated
with a positive “Alaskan pattern” (Renwick and Wallace 1996) as well as a
slightly eastward shifted positive “Pacific North American Pattern” (PNA) which
implies reduced ridging over the central Pacific with increased heights over
the western United States. The negative
mode of this predictor is typically associated with warm current eastern
Pacific equatorial SST conditions and a mature warm ENSO event. Low sea level pressure is observed to occur
in the
Predictor
3. September 500 MB Geopotential Height
in
(35-55°N, 100-120°W)
Positive values of this predictor correlate very strongly (r
= 0.8) with positive values of the PNA. PNA
values are usually positive in the final year of an El Niño event (Horel and
Wallace 1981). Therefore, cooler ENSO
conditions are likely during the following year. Significant lag correlations exist between
this predictor and enhanced 200 mb geopotential height anomalies in the
subtropics during the following summer. Higher
heights in the subtropics reduce the height gradient between the deep tropics
and subtropics resulting in easterly anomalies at 200 mb throughout the
tropical
Predictor
4. July 50 MB Equatorial U (-)
(5°S-5°N, 0-360°)
Easterly anomalies of the QBO during the previous July indicate that the QBO will likely be in the west phase during the following year’s hurricane season. The west phase of the QBO has been shown to provide favorable conditions for development of tropical cyclones in the deep tropics according to Gray et al. (1992, 1993, 1994) and Shapiro (1989). Hypothetical mechanisms for how the QBO effects hurricanes are as follows: a) Atlantic TC activity is inhibited during easterly phases of the QBO due to enhanced lower stratospheric wind ventilation and increased upper-troposphere-lower stratosphere wind shear, and b) for slow moving systems, the west phase of the QBO has a slower relative wind (advective wind relative to the moving system) than does the east phase. This allows for greater coupling between the lower stratosphere and the troposphere.
Predictor
5. September-November SLP in the Gulf –
(15-35°N, 75-95°W)
This feature is strongly related to the following year’s
August-September sea level pressure in the tropical and subtropical
Predictor
6. November SLP in the Subtropical NE
Pacific (+)
(7.5-22.5°N, 125-175°W)
According to Larkin and
2.2
Physical
Associations among Predictors Listed in Table 2 (Experimental Forecast Scheme)
The locations and brief descriptions of our 6-11 month predictors for our new experimental forecast are as follows:
Predictor
1. October-November SLP in the
(10-60°N, 10-30°W)
Low pressure in the North Atlantic in October-November SLP
is generally related to weaker trade winds during the late fall/early winter
which drives less evaporation and upwelling during the winter and spring in the
tropical and subtropical Atlantic.
Reduced upwelling and evaporation during the previous fall tends to
relate to a warmer tropical
Predictor
2. October-November SST in the
(55-65°N, 10-60°W)
Warm
Predictor
3. October-November SLP in the
Subtropical NE Pacific (+)
(35-55°N, 100-120°W)
According to Larkin and
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 2006/2007. These years also provide useful clues as to likely trends in activity that the forthcoming 2007 hurricane season may bring. For this early December extended range 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 October-November 2006 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. Analog years for 2007
were selected primarily on how similar they are to conditions that are
currently observed. We searched for
years that had warm ENSO conditions, warm North Atlantic sea surface
temperatures, and a weaker-than-normal
There were four hurricane seasons since 1949 with characteristics most similar to what we observe in October-November 2006. The best analog years that we could find for the 2007 hurricane season are 1952, 1958, 1966, and 2003. We anticipate that 2007 seasonal hurricane activity will have activity in line with what was experienced in the average of these four years. We believe that 2007 will be an active season in the Atlantic basin.
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 |
4.00 |
87 |
93 |
|
1958 |
10 |
55.50 |
7 |
30.25 |
4 |
8.50 |
121 |
134 |
|
1966 |
11 |
64.00 |
7 |
41.75 |
3 |
7.75 |
145 |
137 |
|
2003 |
16 |
79.25 |
7 |
32.75 |
3 |
16.75 |
175 |
174 |
|
Mean |
11.0 |
59.6 |
6.8 |
31.8 |
3.3 |
9.3 |
132 |
134.5 |
|
2007 Forecast |
14 |
70 |
7 |
35 |
3 |
8 |
130 |