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Category 6 has moved! See the latest from Dr. Jeff Masters and Bob Henson here.Active 2009 hurricane season predicted by Colorado State scientists
It's going to be a moderately more active than average Atlantic hurricane season in 2009, according to the latest seasonal forecast issued by Dr. Bill Gray and Phil Klotzbach of Colorado State University (CSU) today. The CSU team is calling for 14 named storms, 7 hurricanes, 3 intense hurricanes, and an ACE index 30% above average (Accumulated Cyclone Energy (ACE) is a measure of the total destructive power of a hurricane season, based on the number of days strong winds are observed). An average season has 10 named storms, 6 hurricanes, and 2 intense hurricanes. The CSU forecast calls for a 63% chance of a major hurricane hitting the U.S., which is 11% above average. The odds for a major East Coast hurricane are put at 39% (a 31% chance is average), and odds for the Gulf Coast are put at 38% (30% chance is average). The CSU team's prediction of an above average hurricane season hinges on two main factors:
1) An El Niño event is not expected in 2009. The current pressure pattern in the Northeast Pacific is one frequently associated with the development of a La Niña event. A number of the computer models used to forecast El Niño are now calling for development of a La Niña event in 2009. Lack of an El Niño event in 2009 will lead to average to below average values of wind shear over the Atlantic, enhancing hurricane activity.
2) Sea Surface Temperatures (SSTs) in the North Atlantic have been anomalously warm in October and November. This implies we are still in the active phase of the Atlantic Multidecadal Oscillation (AMO), the active period of hurricane activity that began in 1995.
Figure 1. Accuracy of long-range forecasts of Atlantic hurricane season activity performed by Bill Gray and Phil Klotzbach of Colorado State University (colored squares) and TSR (colored lines). The skill is measured by the Mean Square Skill Score (MSSS), which looks at the error and squares it, then compares the percent improvement the forecast has over a climatological forecast of 10 named storms, 6 hurricanes, and 2 intense hurricanes. TS=Tropical Storms, H=Hurricanes, IH=Intense Hurricanes, ACE=Accumulated Cyclone Energy, NTC=Net Tropical Cyclone Activity. Image credit: TSR.
How good are these December hurricane season forecasts?
Keep in mind that these December forecasts are a research project, and as yet have shown no skill in predicting the activity of upcoming hurricane seasons. They make this clear in the introduction to the December forecast, stating, "our real-time forecasts issued in early December from 1992-2007 did not show skill in real time". The CSU team talks extensively about their "hindcast" skill with these December forecasts, which means they can successfully predict the behavior of past hurricane seasons using their methodology. In their words, "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." The problem is that the atmosphere often does not continue to behave in the future as it has in the past, and a technique that is successful in a hindcast will often fail in a forecast. In their 2007 December forecast, they showed that the correlation coefficient (r squared), a standard mathematical measure of skill, was near zero for their real-time December forecasts between 1992-2007. They made a successful December 2007 forecast which was not included in that analysis, and their December skill is probably slightly positive now.
Another way to measure skill is using the Mean Square Skill Score (MSSS), which looks at the forecast error and squares it, then compares the percent improvement the forecast has over a climatological forecast of 10 named storms, 6 hurricanes, and 2 intense hurricanes (Figure 1). The skill of the December forecasts issued by both CSU and Tropical Storm Risk, Inc. (TSR) have averaged near zero since 1992. Not surprisingly, the forecasts get better the closer they get to hurricane season. The TSR forecasts show more skill than the CSU forecasts, but it is unclear how much of this superiority is due to the fact that TSR issues forecasts of fractional storms (for example, TSR may forecast 14.7 named storms, while CSU uses only whole numbers like 14 or 15). TSR does an excellent job communicating their seasonal forecast skill. Each forecast is accompanied by a "Forecast Skill at this Lead" number, and they clearly define this quantity as "Percentage Improvement in Mean Square Error over Running 10-year Prior Climate Norm from Replicated Real Time Forecasts 1987-2006."
The June and August forecasts from CSU, TSR, and NOAA show some modest skill, and are valuable tools for insurance companies and emergency planners to help estimate their risks. The key problem with forecasts done in April or earlier is that the El Niño/La Niña atmospheric cycle that can dominate the activity of an Atlantic hurricane season is generally not predictable more than 3-6 months in advance. For example, none of the El Niño forecast models foresaw the September 2006 El Niño event until May of 2006. Until we can forecast the evolution of El Niño more than six months in advance, December forecasts of Atlantic hurricane activity are merely interesting mental exercises that don't deserve the media attention they get. There is hope for the December forecasts, since Klotzbach and Gray (2004) showed that their statistical scheme could make a skillful forecast in December, when applied to 50 years of historical data. However, these "hindcasts" are much easier to make than a real-time forecast. For example, before 1995, it was observed that high rainfall in the Sahel region of Africa was correlated with increased Atlantic hurricane activity. This correlation was used as part of the CSU forecast scheme. However, when the current active hurricane period began in 1995, the correlation stopped working. Drought conditions occurred in the Sahel, but Atlantic hurricane activity showed a major increase. The CSU team was forced to drop African rainfall as a predictor of Atlantic hurricane activity.
References
Klotzbach, P.J., and W.M. Gray, "Updated 6-11 Month Prediction of Atlantic Basin Seasonal Hurricane Activity," Weather and Forecasting 19, Issue 5, October 2004, pp. 917-934.
Jeff Masters
1) An El Niño event is not expected in 2009. The current pressure pattern in the Northeast Pacific is one frequently associated with the development of a La Niña event. A number of the computer models used to forecast El Niño are now calling for development of a La Niña event in 2009. Lack of an El Niño event in 2009 will lead to average to below average values of wind shear over the Atlantic, enhancing hurricane activity.
2) Sea Surface Temperatures (SSTs) in the North Atlantic have been anomalously warm in October and November. This implies we are still in the active phase of the Atlantic Multidecadal Oscillation (AMO), the active period of hurricane activity that began in 1995.
Figure 1. Accuracy of long-range forecasts of Atlantic hurricane season activity performed by Bill Gray and Phil Klotzbach of Colorado State University (colored squares) and TSR (colored lines). The skill is measured by the Mean Square Skill Score (MSSS), which looks at the error and squares it, then compares the percent improvement the forecast has over a climatological forecast of 10 named storms, 6 hurricanes, and 2 intense hurricanes. TS=Tropical Storms, H=Hurricanes, IH=Intense Hurricanes, ACE=Accumulated Cyclone Energy, NTC=Net Tropical Cyclone Activity. Image credit: TSR.
How good are these December hurricane season forecasts?
Keep in mind that these December forecasts are a research project, and as yet have shown no skill in predicting the activity of upcoming hurricane seasons. They make this clear in the introduction to the December forecast, stating, "our real-time forecasts issued in early December from 1992-2007 did not show skill in real time". The CSU team talks extensively about their "hindcast" skill with these December forecasts, which means they can successfully predict the behavior of past hurricane seasons using their methodology. In their words, "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." The problem is that the atmosphere often does not continue to behave in the future as it has in the past, and a technique that is successful in a hindcast will often fail in a forecast. In their 2007 December forecast, they showed that the correlation coefficient (r squared), a standard mathematical measure of skill, was near zero for their real-time December forecasts between 1992-2007. They made a successful December 2007 forecast which was not included in that analysis, and their December skill is probably slightly positive now.
Another way to measure skill is using the Mean Square Skill Score (MSSS), which looks at the forecast error and squares it, then compares the percent improvement the forecast has over a climatological forecast of 10 named storms, 6 hurricanes, and 2 intense hurricanes (Figure 1). The skill of the December forecasts issued by both CSU and Tropical Storm Risk, Inc. (TSR) have averaged near zero since 1992. Not surprisingly, the forecasts get better the closer they get to hurricane season. The TSR forecasts show more skill than the CSU forecasts, but it is unclear how much of this superiority is due to the fact that TSR issues forecasts of fractional storms (for example, TSR may forecast 14.7 named storms, while CSU uses only whole numbers like 14 or 15). TSR does an excellent job communicating their seasonal forecast skill. Each forecast is accompanied by a "Forecast Skill at this Lead" number, and they clearly define this quantity as "Percentage Improvement in Mean Square Error over Running 10-year Prior Climate Norm from Replicated Real Time Forecasts 1987-2006."
The June and August forecasts from CSU, TSR, and NOAA show some modest skill, and are valuable tools for insurance companies and emergency planners to help estimate their risks. The key problem with forecasts done in April or earlier is that the El Niño/La Niña atmospheric cycle that can dominate the activity of an Atlantic hurricane season is generally not predictable more than 3-6 months in advance. For example, none of the El Niño forecast models foresaw the September 2006 El Niño event until May of 2006. Until we can forecast the evolution of El Niño more than six months in advance, December forecasts of Atlantic hurricane activity are merely interesting mental exercises that don't deserve the media attention they get. There is hope for the December forecasts, since Klotzbach and Gray (2004) showed that their statistical scheme could make a skillful forecast in December, when applied to 50 years of historical data. However, these "hindcasts" are much easier to make than a real-time forecast. For example, before 1995, it was observed that high rainfall in the Sahel region of Africa was correlated with increased Atlantic hurricane activity. This correlation was used as part of the CSU forecast scheme. However, when the current active hurricane period began in 1995, the correlation stopped working. Drought conditions occurred in the Sahel, but Atlantic hurricane activity showed a major increase. The CSU team was forced to drop African rainfall as a predictor of Atlantic hurricane activity.
References
Klotzbach, P.J., and W.M. Gray, "Updated 6-11 Month Prediction of Atlantic Basin Seasonal Hurricane Activity," Weather and Forecasting 19, Issue 5, October 2004, pp. 917-934.
Jeff Masters
The views of the author are his/her own and do not necessarily represent the position of The Weather Company or its parent, IBM.