A Revised Technique for Forecasting Hurricane Movement by Statistical Methods

Miller, Banner I.; Hill, Elbert C.; Chase, Peter P.

doi:10.1175/1520-0493(1968)096<0540:artffh>2.0.co;2

Cited by 17 publications

(6 citation statements)

References 4 publications

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“…The mean errors in the forecast for 1967 were considerably lower than those in 1966 for both areas B and c. length of the forecast period mas changed slightly beginning in 1967 which makes comparison of results with those of earlier years awkward, and 3) a new and improved objective technique, NHC-67 [8], was used for the first time as an aid by the forecasters, and it is believed that 1 yr. is too short a time to evaluate its impact on the official forecasts. One might argue that the storms were easier to forecast in the latter periods.…”

Section: Results Of the Forecast Experimentsmentioning

confidence: 96%

An Eight-Year Experiment in Improving Forecasts of Hurricane Motion

Dunn¹,

Gentry²,

Lewis³

1968

Mon. Wea. Rev.

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The National Hurricane Center and the National Hurricane Research Laboratory joined forces in a n effort t o improvc techniques for forecasting hurricanc motion in the spring of 1959 when the latter moved its headquarters from West Palm Beach to Miami into offices adjacent to those occupied by the principal hurricane forecast office in the United States. Results now available from verification of forecasts made during the period 1954 through 1966 show that there has been a significant improvement in the accuracy of hurricane forecasts during the period of increased cooperation between the research and operational forecasting groups. This improvement is indicated by B reduction in the mean error of hurricane forecasts of approximately 10 and 12 percent, respectively, for the two principal hurricane forecast areas near the eastern coasts of the United States.

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Section: Results Of the Forecast Experimentsmentioning

confidence: 96%

An Eight-Year Experiment in Improving Forecasts of Hurricane Motion

Dunn¹,

Gentry²,

Lewis³

1968

Mon. Wea. Rev.

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show abstract

“…Trough stratification, the forecast is adapted to the climatological differences of these two zones. Moreover predictors are selected in different order and/or different weights are assigned to the different predictors to forecast slow (between 13 and 24 km/h) and fast moving cyclones (more than 24 km/h) (Miller et al, 1968). In contrast the stratification methods used by NHC72 and EPHC77 split the predictor datasets with respect to the initial direction of motion of the cyclone.…”

Section: Chen-elsberrymentioning

confidence: 99%

“…Sub-system 2: Forecast from steering methods using 1000, 700, and 500 mbar geopotential heights as steering levels (Miller et al, 1968). Sub-system 3: Forecast from synoptic techniques, where 24, 36, and 48 hour geopotentialheight prognoses from the NMC primitive equation model are used (Shuman and Hovermale, 1968).…”

Section: National Hurricane Center Statistical-dynamical Technique Sementioning

confidence: 99%

Tropical cyclone track forecasting techniques ― A review

Roy

Kovordanyi

2012

Atmospheric Research

129

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Delivering accurate cyclone forecasts in time is of key importance when it comes to saving human lives and reducing economic loss. Difficulties arise because the geographical and climatological characteristics of the various cyclone formation basins are not similar, which entails that a single forecasting technique cannot yield reliable performance in all ocean basins. For this reason, global forecasting techniques need to be applied together with basin-specific techniques to increase the forecast accuracy. As cyclone track is governed by a range of factors variations in weather conditions, wind pressure, sea surface temperature, air temperature, ocean currents, and the earth' rotational force-the coriolis force, it is a formidable task to combine these parameters and produce reliable and accurate forecasts. In recent years, the availability of suitable data has increased and more advanced forecasting techniques have been developed, in addition to old techniques having been modified. In particular, artificial neural network based techniques are now being considered at meteorological offices. This new technique uses freely available satellite images as input, can be run on standard PCs, and can produce forecasts with good accuracy. For these reasons, artificial neural network based techniques seem especially suited for developing countries which have limited capacity to forecast cyclones and where human casualties are the highest.

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“…This model is the baseline by which model skill is evaluated. 3) NHC67, or A67E [run operationally 1967-87;Miller et al (1968)], was an update of the statistical-synoptic NHC64 model (Miller and Case 1966). The locations in which the geopotential heights in the current and 24-h-old 1000-, 700-, and 500-hPa analyses are most significantly correlated with future motion were found.…”

Section: The Modelsmentioning

confidence: 99%

The Ensemble of Tropical Cyclone Track Forecasting Models in the North Atlantic Basin (1976–2000)

Aberson¹

2001

Bull. Amer. Meteor. Soc.

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The suite of tropical cyclone track forecast models in the Atlantic basin from the 1976 to 2000 hurricane seasons are treated as a forecast ensemble. The 12-h ensemble mean forecast, adjusted for forecast difficulty, has improved at a rate of just under 1% per year, and the improvement rate increases to almost 2.4% per year for the 72-h forecasts. The average size of the 72-h (48-h) error in 1976 is less than the average size of the 48-h (36-h) error in 2000. The average 36-h forecast error in 2000 is comparable to the 24-h forecast error in 1976. The ensemble currently spans the true path of the tropical cyclone in the cross-track direction more than 90% of the time and in the alongtrack direction between 60% and 90% of the time depending on the forecast lead time. The ensemble spread is unable to provide estimates of individual forecast reliability, likely making probabilistic landfall forecasts from this ensemble unreliable. The reliability of the spread in the cross-track direction suggests the possibility of limiting hurricane watch and warning regions depending upon the ensemble spread at landfall.

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A Revised Technique for Forecasting Hurricane Movement by Statistical Methods

Cited by 17 publications

References 4 publications

An Eight-Year Experiment in Improving Forecasts of Hurricane Motion

An Eight-Year Experiment in Improving Forecasts of Hurricane Motion

Tropical cyclone track forecasting techniques ― A review

The Ensemble of Tropical Cyclone Track Forecasting Models in the North Atlantic Basin (1976–2000)

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