Predicting Atlantic Basin Seasonal Tropical Cyclone Activity by 1 August

William M. Gray Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Search for other papers by William M. Gray in
Current site
Google Scholar
PubMed
Close
,
Christopher W. Landsea Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Search for other papers by Christopher W. Landsea in
Current site
Google Scholar
PubMed
Close
,
Paul W. Mielke Jr. Department of Statistics, Colorado State University, Fort Collins, Colorado

Search for other papers by Paul W. Mielke Jr. in
Current site
Google Scholar
PubMed
Close
, and
Kenneth J. Berry Department of Sociology, Colorado State University, Fort Collins, Colorado

Search for other papers by Kenneth J. Berry in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

More than 90% of all seasonal Atlantic tropical cyclone activity typically occurs after 1 August. A strong predictive potential exists that allows seasonal forecasts of Atlantic basin tropical cyclone activity to be issued by 1 August, prior to the start of the active portion of the hurricane season. Predictors include June-July meteorological information of the stratospheric quasi-biennial oscillation (QBO), West African rainfall, the El Niño-Southern Oscillation (ENSO) as well as sea level pressure anomalies (SLPA), and the upper-tropospheric zonal-wind anomalies (ZWA) in the Caribbean basin.

Use of a combination of these global and regional predictors provides a basis for making cross-validated (jackknifed) 1 August hindcasts of subsequent Atlantic seasonal tropical cyclone activity that show substantial skill over climatology. This relationship is demonstrated in 41 years of hindcasts of the 1950-90 seasons. It is possible to independently explain more than 60% of the year-to-year variability associated with intense (category 3–4–5) hurricane activity. This is significant because over 70% of all United States tropical cyclone damage comes from intense hurricanes, and over 98% of intense hurricane activity occurs after 1 August.

Empirical evidence suggests that least sum of absolute deviations (LAD) regression yields substantially more improved cross-validated results than an analogous procedure based on ordinary least sum of squared deviations (OLS) regression. This improvement surprisingly occurs even with the squared Pearson product-moment correlation coefficient for which one might anticipate OLS regression to yield better cross-validated results than LAD regression.

Abstract

More than 90% of all seasonal Atlantic tropical cyclone activity typically occurs after 1 August. A strong predictive potential exists that allows seasonal forecasts of Atlantic basin tropical cyclone activity to be issued by 1 August, prior to the start of the active portion of the hurricane season. Predictors include June-July meteorological information of the stratospheric quasi-biennial oscillation (QBO), West African rainfall, the El Niño-Southern Oscillation (ENSO) as well as sea level pressure anomalies (SLPA), and the upper-tropospheric zonal-wind anomalies (ZWA) in the Caribbean basin.

Use of a combination of these global and regional predictors provides a basis for making cross-validated (jackknifed) 1 August hindcasts of subsequent Atlantic seasonal tropical cyclone activity that show substantial skill over climatology. This relationship is demonstrated in 41 years of hindcasts of the 1950-90 seasons. It is possible to independently explain more than 60% of the year-to-year variability associated with intense (category 3–4–5) hurricane activity. This is significant because over 70% of all United States tropical cyclone damage comes from intense hurricanes, and over 98% of intense hurricane activity occurs after 1 August.

Empirical evidence suggests that least sum of absolute deviations (LAD) regression yields substantially more improved cross-validated results than an analogous procedure based on ordinary least sum of squared deviations (OLS) regression. This improvement surprisingly occurs even with the squared Pearson product-moment correlation coefficient for which one might anticipate OLS regression to yield better cross-validated results than LAD regression.

Save