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- Author or Editor: JOSEPH M. PELISSIER x
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Abstract
This study provides an operational evaluation of the seven prediction models-five statistical and two dynamical-used at the National Hurricane Center. Following a brief description of the rationale for each model, various performance characteristics, including forecast error, skill. bias. dispersion, timeliness and availability are evaluated.
The conclusion of the study is that none of the models can be singled out as clearly superior or inferior, each having at least one temporal, spatial, economic or utilitarian advantage. In practice, it is difficult to combine these advantages into one all-purpose model. Accordingly. for some time to come, operational guidance will be obtained from a number of different models, both statistical and dynamical. Tropical cyclone forecasters will need to be kept aware of model attributes so that potential conflicts in the guidance can be rationally resolved.
Abstract
This study provides an operational evaluation of the seven prediction models-five statistical and two dynamical-used at the National Hurricane Center. Following a brief description of the rationale for each model, various performance characteristics, including forecast error, skill. bias. dispersion, timeliness and availability are evaluated.
The conclusion of the study is that none of the models can be singled out as clearly superior or inferior, each having at least one temporal, spatial, economic or utilitarian advantage. In practice, it is difficult to combine these advantages into one all-purpose model. Accordingly. for some time to come, operational guidance will be obtained from a number of different models, both statistical and dynamical. Tropical cyclone forecasters will need to be kept aware of model attributes so that potential conflicts in the guidance can be rationally resolved.
Abstract
Official Atlantic tropical cyclone track forecasts issued by the National Hurricane Center over the decade of the 1970's are examined in this study. The purpose is to isolate any significant biases, trends or other statistical properties of the forecast errors. In this analysis, we consider (i) storms Initially located in the easterlies and (ii) storms initially in the westerlies. Latitude 24.5°N approximately delimits the two zones. The mean forecast error (MFE) on group (i) storms is shown to be substantially less than group (ii). However, it also is shown that “skill,” defined as the ability to improve on a forecast based only on climatology and persistence, is greater for storms embedded in the westerlies.
An examination of the year-to-year variation in MFE, after these errors have been adjusted according to attendant year-to-year variation in average storm latitude and translational speed, fails to disclose any upward or downward trend in the ability to forecast tropical cyclone motion over the decade of the 1970's. This finding is evaluated in relation to an earlier study, which describes a 10–12% decline in MFE over the 8-year period 1959–66.
To examine biases and dispersion patterns of the errors, probability ellipses associated with the bivariate normal distribution were fitted to the classes of forecast errors described above. Two coordinate systems were used: one system was oriented in the conventional zonal/meridional sense and the other was rotated in accordance with storm emotion. Small right-of-track and slow biases were identified. Overall, these biases were found to be small, although a number of sizable regional biases were identified. The study concludes with an evaluation of temporal and spatial aspects of landfall error, i.e., the distance between forecast and observed point of tropical cyclone landfall measured along the coast.
Abstract
Official Atlantic tropical cyclone track forecasts issued by the National Hurricane Center over the decade of the 1970's are examined in this study. The purpose is to isolate any significant biases, trends or other statistical properties of the forecast errors. In this analysis, we consider (i) storms Initially located in the easterlies and (ii) storms initially in the westerlies. Latitude 24.5°N approximately delimits the two zones. The mean forecast error (MFE) on group (i) storms is shown to be substantially less than group (ii). However, it also is shown that “skill,” defined as the ability to improve on a forecast based only on climatology and persistence, is greater for storms embedded in the westerlies.
An examination of the year-to-year variation in MFE, after these errors have been adjusted according to attendant year-to-year variation in average storm latitude and translational speed, fails to disclose any upward or downward trend in the ability to forecast tropical cyclone motion over the decade of the 1970's. This finding is evaluated in relation to an earlier study, which describes a 10–12% decline in MFE over the 8-year period 1959–66.
To examine biases and dispersion patterns of the errors, probability ellipses associated with the bivariate normal distribution were fitted to the classes of forecast errors described above. Two coordinate systems were used: one system was oriented in the conventional zonal/meridional sense and the other was rotated in accordance with storm emotion. Small right-of-track and slow biases were identified. Overall, these biases were found to be small, although a number of sizable regional biases were identified. The study concludes with an evaluation of temporal and spatial aspects of landfall error, i.e., the distance between forecast and observed point of tropical cyclone landfall measured along the coast.
Abstract
A general overview of the 1970 hurricane season in the North Atlantic is presented together with detailed accounts of all named tropical cyclones and certain subtropical or hybrid storms.
Abstract
A general overview of the 1970 hurricane season in the North Atlantic is presented together with detailed accounts of all named tropical cyclones and certain subtropical or hybrid storms.
Abstract
No Abstract Available.
Abstract
No Abstract Available.
Abstract
A summary of the 1980 hurricane season is presented. Eleven named tropical cyclones were tracked, of which nine reached hurricane force. Allen, an intense storm, affected a number of Caribbean countries before making landfall on the Texas coast.
Abstract
A summary of the 1980 hurricane season is presented. Eleven named tropical cyclones were tracked, of which nine reached hurricane force. Allen, an intense storm, affected a number of Caribbean countries before making landfall on the Texas coast.
Abstract
Eleven named tropical cyclones and one subtropical cyclone were tracked during 1981 in the Atlantic-Caribbean region. There were no landfalling hurricanes.
Abstract
Eleven named tropical cyclones and one subtropical cyclone were tracked during 1981 in the Atlantic-Caribbean region. There were no landfalling hurricanes.
Abstract
This study focuses on the use of the bivariate normal distribution model to describe spatial distributions of tropical cyclone forecast errors. In this connection, it is found that forecast errors from the entire Atlantic tropical cyclone basin (Gulf of Mexico, Caribbean and North Atlantic) are multimodal and the fitting of these collective data to the usual unimodal bivariate normal distribution will be judged invalid by the usual statistical goodness-of-fit tests. While this is a recognized pitfall in classical statistics, it is often overlooked in meteorological application. The isolation of the clusters (components) and their statistical characteristics permit the issuance of forecast positions accompanied by more representative error ellipses.
The study continues with a bivariate clustering analysis of a set of 979 tropical cyclone 24 h forecast errors for the Gulf of Mexico, Caribbean and North Atlantic. These errors were collected from the entire tropical cyclone basin without regard to season or geography. The analysis shows that these errors could be drawn from two or possibly three parent bivariate normal distributions. A further analysis of the two clusters was made and it is shown that group membership is essentially a function of forecast “difficulty.” One group (essentially storms located in the Caribbean and Gulf of Mexico) has about one-half the component standard errors of the other group (the more northerly storms). A physical interpretation of the more complex three-mode clustering was not accomplished.
The study has application with regard to the future development of statistical prediction models and in connection with a recently inaugurated tropical cyclone “strike” probability concept.
Abstract
This study focuses on the use of the bivariate normal distribution model to describe spatial distributions of tropical cyclone forecast errors. In this connection, it is found that forecast errors from the entire Atlantic tropical cyclone basin (Gulf of Mexico, Caribbean and North Atlantic) are multimodal and the fitting of these collective data to the usual unimodal bivariate normal distribution will be judged invalid by the usual statistical goodness-of-fit tests. While this is a recognized pitfall in classical statistics, it is often overlooked in meteorological application. The isolation of the clusters (components) and their statistical characteristics permit the issuance of forecast positions accompanied by more representative error ellipses.
The study continues with a bivariate clustering analysis of a set of 979 tropical cyclone 24 h forecast errors for the Gulf of Mexico, Caribbean and North Atlantic. These errors were collected from the entire tropical cyclone basin without regard to season or geography. The analysis shows that these errors could be drawn from two or possibly three parent bivariate normal distributions. A further analysis of the two clusters was made and it is shown that group membership is essentially a function of forecast “difficulty.” One group (essentially storms located in the Caribbean and Gulf of Mexico) has about one-half the component standard errors of the other group (the more northerly storms). A physical interpretation of the more complex three-mode clustering was not accomplished.
The study has application with regard to the future development of statistical prediction models and in connection with a recently inaugurated tropical cyclone “strike” probability concept.
