Performance Analysis of the HURRAN Tropical Cyclone Forecast System

Neumann, Charles J.; Hope, John R.

doi:10.1175/1520-0493(1972)100<0245:paotht>2.3.co;2

Cited by 48 publications

(52 citation statements)

References 9 publications

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“…Table 4 shows that the average track errors in 1997 are comparable to the 10-yr average at periods through 36 h, and smaller at longer periods. In comparison, most errors of the forecast model based on climatology and persistence (CLIPER) (Neumann 1972) for the same periods were larger than normal. The higher than average CLIPER errors are consistent with most of the 1997 tropical storms and hurricanes occurring at high latitude, where CLIPER performs most poorly.…”

Section: Verificationmentioning

confidence: 88%

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Atlantic Hurricane Season of 1997

Rappaport¹

1999

Mon. Wea. Rev.

143

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The 1997 Atlantic hurricane season is summarized and the year's tropical storms, hurricanes, and one subtropical storm are described. The tropical cyclones were relatively few in number, short lived, and weak compared to long-term climatology. Most systems originated outside the deep Tropics. Hurricane Danny was the only system to make landfall. It produced rainfall totals to near 1 m in southern Alabama and is blamed for five deaths. Hurricane Erika was responsible for the season's two other fatalities, in the coastal waters of Puerto Rico.

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Section: Verificationmentioning

confidence: 88%

“…The months of August and September were particularly quiet. On average, about six tropical storms develop during that two-month period (Neumann et al 1993). There was just one in 1997, an occurrence last noted in 1929.…”

Section: Introductionmentioning

confidence: 99%

Atlantic Hurricane Season of 1997

Rappaport¹

1999

Mon. Wea. Rev.

143

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“…TC forecasts are produced in the final step, where meteorologists take advantages of three different techniques separately: (a) steering airflow determination (Keenan, 1982), (b) averaging across historical TCs , and (c) climatology and persistence (Neumann, 1972). Though these techniques are separately used for producing TC forecasts, meteorologists ultimately rely on their expert knowledge to forecast TC track and intensity for the next 12 hours on the basis of the movement direction and speed of the analogous past TCs and the extrapolated movement of the current TC.…”

Section: Tc Forecastingmentioning

confidence: 99%

An Informed System Development Approach to Tropical Cyclone Track and Intensity Forecasting

Roy

2016

Linköping Studies in Science and Technology. Dissertations

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Introduction: Tropical Cyclones (TCs) inflict considerable damage to life and property every year. A major problem is that residents often hesitate to follow evacuation orders when the early warning messages are perceived as inaccurate or uninformative. The root problem is that providing accurate early forecasts can be difficult, especially in countries with less economic and technical means. Aim:The aim of the thesis is to investigate how cyclone early warning systems can be technically improved. This means, first, identifying problems associated with the current cyclone early warning systems, and second, investigating if biologically based Artificial Neural Networks (ANNs) are feasible to solve some of the identified problems.Method: First, for evaluating the efficiency of cyclone early warning systems, Bangladesh was selected as study area, where a questionnaire survey and an in-depth interview were administered. Second, a review of currently operational TC track forecasting techniques was conducted to gain a better understanding of various techniques' prediction performance, data requirements, and computational resource requirements. Third, a technique using biologically based ANNs was developed to produce TC track and intensity forecasts. Systematic testing was used to find optimal values for simulation parameters, such as feature-detector receptive field size, the mixture of unsupervised and supervised learning, and learning rate schedule. Five types of 2D data were used for training. The networks were tested on two types of novel data, to assess their generalization performance. Results:A major problem that is identified in the thesis is that the meteorologists at the Bangladesh Meteorological Department are currently not capable of providing accurate TC forecasts. This is an important contributing factor to residents' reluctance to evacuate. To address this issue, an ANN-based TC track and intensity forecasting technique was developed that can produce early and accurate forecasts, uses freely available satellite images, and does not require extensive computational resources to run. Bidirectional connections, combined supervised and unsupervised learning, and a deep hierarchical structure assists the parallel extraction of useful features from five types of 2D data. The trained networks were tested on two types of novel data: First, tests were performed with novel data covering the end of the lifecycle of trained cyclones; for these test data, the forecasts produced by the networks were correct in 91-100% of the cases. Second, the networks were tested with data of a novel TC; in this case, the networks performed with between 30% and 45% accuracy (for intensity forecasts). Conclusions:The ANN technique developed in this thesis could, with further extensions and up-scaling, using additional types of input images of a greater number of TCs, improve the efficiency of cyclone early warning systems in countries with less economic and technical means. The thesis work also creates opportunities for furthe...

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“…The TC forecasting technique that the meteorologists are currently using is a combination of three TC forecasting techniques: (a) steering airflow determination [59], (b) averaging across historical TCs [60], and (c) climatology and persistence [61]. Instead of combining the outputs from these three techniques (hybrid forecasting technique 1 ), the meteorologists take advantage of each technique separately.…”

Section: Tc Forecasting At Bmdmentioning

confidence: 99%

The current cyclone early warning system in Bangladesh: Providers' and receivers' views

Roy

Sarkar

Åberg

et al. 2015

International Journal of Disaster Risk Reduction

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Bangladesh has experienced several catastrophic Tropical Cyclones (TCs) during the last decades. Despite the efforts of disaster management organizations, as well as the Bangladesh Meteorological Department (BMD), there were lapses in the residents' evacuation behavior. To examine the processes of TC forecasting and warning at BMD and to understand the reasons for residents' reluctance to evacuate after a cyclone warning, we conducted an individual in-depth interview among the meteorologists at BMD, as well as a questionnaire survey among the residents living in the coastal areas. The results reveal that the forecasts produced by BMD are not reliable for longer than 12-hour. Therefore, longer-term warnings have to be based on gross estimates of TC intensity and motion, which renders the disseminated warning messages unreliable. Our results indicate that residents in the coastal areas studied, do not follow the evacuation orders due to mistrust of the warning messageswhich can deter from early evacuation; and insufficient number of shelters and poor transportation possibilities-which discourages late evacuation. Suggestions made by the residents highlight the necessity of improved warning messages in the future. These findings indicate the need for improved forecasting, and more reliable and more informative warning messages for ensuring a timely evacuation response from residents.

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Performance Analysis of the HURRAN Tropical Cyclone Forecast System

Cited by 48 publications

References 9 publications

Atlantic Hurricane Season of 1997

Atlantic Hurricane Season of 1997

An Informed System Development Approach to Tropical Cyclone Track and Intensity Forecasting

The current cyclone early warning system in Bangladesh: Providers' and receivers' views

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