Some Inferences From Satellite Pictures of Tropical Disturbances

Fritz, Sigmund; Hubert, L. F.; Timchalk, Andrew

doi:10.1175/1520-0493(1966)094<0231:sifspo>2.3.co;2

Cited by 33 publications

(17 citation statements)

References 9 publications

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“…At this time there were no enhancement or animation capabilities. Early work by Fett (1966), Fritz et al (1966), and Hubert and Timchalk (1969) was generally unsuccessful in inferring TC intensity from this type of imagery.…”

Section: 1 I • R I Vernon Dvorak (Circa: Late 1970s) Timationmentioning

confidence: 99%

The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years

Velden¹,

Harper²,

Wells³

et al. 2006

Bull. Amer. Meteor. Soc.

328

200

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Section: 1 I • R I Vernon Dvorak (Circa: Late 1970s) Timationmentioning

confidence: 99%

The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years

Velden¹,

Harper²,

Wells³

et al. 2006

Bull. Amer. Meteor. Soc.

328

200

View full text Add to dashboard Cite

“…(Fritz et al, 1966;Timchalk et al, 1965;Dvorak, 1975 and others) In the course of these investigations, satellite imagery has also revealed the various kinds of organized patterns of convective clouds in the tropics other than typhoons and hurricanes.…”

mentioning

confidence: 91%

Analysis of the Deep Convective Activity Over the Western Pacific and Southeast Asia

Murakami¹

1983

Journal of the Meteorological Society of Japan

176

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Using the infrared (IR) irradiance data observed by GMS-1 geostationary satellite, it was tried to quantitize the deep convective activity in a manner which is physically more interpretable than the conventional areal average. This was partly accomplished by defining the intensity index of the deep convective clouds within the 1* longitude-latitude square mesh in the manner which takes the horizontal variation of the observed temperature and the vertical distribution of the atmospheric temperature into account.Diurnal variation of the deep convective activity was investigated by using the abovementioned intensity index for the period during northern hemispheric winter (December 1978-January 1979) and summer (July-August 1979). During northern winter, the amplitude of the diurnal variation is large over the Indonesian region and the northern Australia. Within this area it was found that there exist a distinct contrast in the phase of diurnal cycle between the land and the adjacent ocean. Composite analysis has revealed that the land shows the suppressed convective activity in the morning hours with the minimum around 9 o'clock local time. The convective activity is rapidly enhanced in the afternoon and reaches the maximum at around 18 o'clock local time. In contrast, the adjacent ocean clearly shows the enhancement of the convective clouds in the local morning and the suppressed convective activity in the afternoon and night.During northern summer the intense diurnal variation was observed over the southern part of Tibetan Plateau. The amplitude is also large over the western Pacific to the east of Philippines.Composited diurnal cycle shows that there exists a contrast between the continent and the ocean, being similar to the one observed during northern winter. The continent and the large islands generally show the minimum convective activity around 9 o'clock in the local morning and the maximum enhancement aound 18 o'clock in the evening. In contrast the oceanic area like western Pacific shows the maximum enhancement of the deep convective clouds around 6-to 9 o'clock local time in the morning and the suppressed activity in the afternoon.In addition to this land-ocean contrast, the evidences which suggest the regional effect on the diurnal variation are also discussed.

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“…When the satellite era began, the intensity of tropical cyclones was estimated using satellite images [21], where methods involving cloud features with conventional estimates of cyclone strengths were devised for estimating the intensity [22], [23]. Dvorak (1975) used a technique to combine meteorological analysis of satellite imagery with a model consisting a set of curves that depicted cyclone intensity change with time and cloud feature descriptions of the cyclone at intervals along the curves [24].…”

Section: B Related Work In Cyclone Wind-intensity Predictionmentioning

confidence: 99%

Cooperative neuro-evolution of Elman recurrent networks for tropical cyclone wind-intensity prediction in the South Pacific region

Chandra

Dayal

2015

2015 IEEE Congress on Evolutionary Computation (CEC)

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Climate change issues are continuously on the rise and the need to build models and software systems for management of natural disasters such as cyclones is increasing. Cyclone wind-intensity prediction looks into efficient models to forecast the wind-intensification in tropical cyclones which can be used as a means of taking precautionary measures. If the windintensity is determined with high precision a few hours prior, evacuation and further precautionary measures can take place. Neural networks have become popular as efficient tools for forecasting. Recent work in neuro-evolution of Elman recurrent neural network showed promising performance for benchmark problems. This paper employs Cooperative Coevolution method for training Elman recurrent neural networks for Cyclone windintensity prediction in the South Pacific region. The results show very promising performance in terms of prediction using different parameters in time series data reconstruction.

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Some Inferences From Satellite Pictures of Tropical Disturbances

Cited by 33 publications

References 9 publications

The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years

The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years

Analysis of the Deep Convective Activity Over the Western Pacific and Southeast Asia

Cooperative neuro-evolution of Elman recurrent networks for tropical cyclone wind-intensity prediction in the South Pacific region

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