DAGDU: center location of tropical cyclones using Deviation Angle Gradient Distribution Uniformity from infrared satellite images

2021 ◽  
Vol 42 (24) ◽  
pp. 9222-9240
Author(s):  
Chang-Jiang Zhang ◽  
Xiao-Jie Wang ◽  
Li-Cheng Xue
Keyword(s):  
Tropical Cyclones ◽  
Satellite Images ◽  
Deviation Angle ◽  
Gradient Distribution ◽  
Center Location ◽  
Distribution Uniformity

scholarly journals Meteorological Education and Training Using A-Train Profilers

2012 ◽  
Vol 93 (5) ◽  
pp. 687-696 ◽  
Author(s):  
Thomas F. Lee ◽  
Richard L. Bankert ◽  
Cristian Mitrescu
Keyword(s):  
Tropical Cyclones ◽  
Satellite Data ◽  
Satellite Images ◽  
Satellite Observations ◽  
Two Dimensional ◽  
Marine Stratocumulus ◽  
Severe Thunderstorm ◽  
Fundamental Information ◽  
Frontal Systems ◽  
And Training

NASA A-Train vertical profilers provide detailed observations of atmospheric features not seen in traditional imagery from other weather satellite data. CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) profiles vividly depict the vertical dimension of otherwise two-dimensional features shown in mapped products. However, most forecasters have never seen these profiles and do not appreciate their capacity to convey fundamental information about cloud and precipitation systems. Here, these profiles are accompanied by weather satellite images and explained in the context of various meteorological regimes. Profile examples are shown over frontal systems, marine stratocumulus, orographic barriers, tropical cyclones, and a severe thunderstorm.

scholarly journals Genesis and maintenance of "Mediterranean hurricanes"

2005 ◽  
Vol 2 ◽  
pp. 217-220 ◽  
Author(s):  
K. Emanuel
Keyword(s):  
Numerical Simulations ◽  
Mediterranean Sea ◽  
Tropical Cyclones ◽  
Satellite Images ◽  
Baroclinic Instability ◽  
Small Areas ◽  
Warm Core ◽  
Surface Enthalpy ◽  
The Mediterranean ◽  
Cyclonic Storms

Abstract. Cyclonic storms that closely resemble tropical cyclones in satellite images occasionally form over the Mediterranean Sea. Synoptic and mesoscale analyses of such storms show small, warm-core structure and surface winds sometimes exceeding 25ms-1 over small areas. These analyses, together with numerical simulations, reveal that in their mature stages, such storms intensify and are maintained by a feedback between surface enthalpy fluxes and wind, and as such are isomorphic with tropical cyclones. In this paper, I demonstrate that a cold, upper low over the Mediterranean can produce strong cyclogenesis in an axisymmetric model, thereby showing that baroclinic instability is not necessary during the mature stages of Mediterranean hurricanes.

A Deep Learning Framework for the Detection of Tropical Cyclones from Satellite Images

2021 ◽  
pp. 1-1
Author(s):  
Aravind Nair ◽  
K S S Sai Srujan ◽  
Sayali R. Kulkarni ◽  
Kshitij Alwadhi ◽  
Navya Jain ◽  
...  
Keyword(s):  
Deep Learning ◽  
Tropical Cyclones ◽  
Satellite Images ◽  
Learning Framework

scholarly journals The Benefits of Using Short-Interval Satellite Images to Derive Winds for Tropical Cyclones

1979 ◽  
Vol 107 (5) ◽  
pp. 575-584 ◽  
Author(s):  
Edward Rodgers ◽  
R. Cecil Gentry ◽  
William Shenk ◽  
Vincent Oliver
Keyword(s):  
Tropical Cyclones ◽  
Satellite Images ◽  
Short Interval

scholarly journals Estimation of the Upper-Layer Rotation and Maximum Wind Speed of Tropical Cyclones via Satellite Imagery

2011 ◽  
Vol 50 (3) ◽  
pp. 750-766 ◽  
Author(s):  
Chun-Chieh Chao ◽  
Gin-Rong Liu ◽  
Chung-Chih Liu
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Satellite Imagery ◽  
Satellite Images ◽  
Rotation Speed ◽  
Maximum Wind Speed ◽  
Maximum Wind ◽  
The Mean ◽  
Wind Intensity ◽  
The Relationship

Abstract The movement of convective rainbands embedded in a tropical cyclone (TC) is usually derived from satellite images via the atmospheric motion vector (AMV) method or through the calculation of a radar’s echo track. In estimating the rotation speed of a TC rainband, however, the land-based radar can only detect approaching tropical cyclones within the vicinity. The AMV method is unable to fully account for the TC eyewall movement, thus making it difficult to estimate the TC intensity. The widely used method in estimating the TC maximum wind speed is the Dvorak technique in which the cloud pattern is extracted from only one image. In this study, the rainband rotation speeds are computed via satellite imagery and further applied in estimating the TC maximum wind speed. In contrast to previous research, this study adopts an innovative method by using two subsequent geostationary satellite images. The TC spin rates observed by weather satellites could often be seen to be positively related to the TC intensity. Analyses of the relationship between the typhoon wind intensity and estimated rotation speed at the 130–260-km ring via infrared channels are conducted for major typhoon cases that occurred during 2000–05 in the northwestern Pacific Ocean. Results show that the correlation between the wind intensity and estimated rotation speeds is strong for most of the cases. The highest R2 value from the individual cases could reach 0.93, and on an annual basis it could attain a value of 0.67. The mean R2 value for the 2000–05 dataset was roughly 0.53. The correlation between the wind intensity and estimated rotation speeds is further improved by factoring in the previous 6-h average rotation speeds. A regression equation is derived from the chosen typhoon cases between 2000 and 2005, which is utilized in verifying the major typhoon occurrences during 2006–08. The mean absolute error (MAE) of the hourly and 6-h average intensity estimates during 2000–08 was 20 and 18.7 kt, respectively (1 kt ≃ 0.5 m s−1). The best verification result occurred during 2008, for which the R2 value and MAE could reach 0.7 and 15.6, respectively. These research results demonstrate the suitability of using geostationary satellite image data in estimating the maximum wind speed. Nevertheless, the drawback of this study is that sometimes the rotation speeds will become slower when tropical cyclones mature because of the strong outflow of the secondary circulation. It is assumed that the relationship between the estimated rotation speeds and wind intensity can be further improved if the outflow speed of the tropical cyclones is also considered.

scholarly journals An Algorithm for Tracking Eyes of Tropical Cyclones

2009 ◽  
Vol 24 (1) ◽  
pp. 245-261 ◽  
Author(s):  
Pao-Liang Chang ◽  
Ben Jong-Dao Jou ◽  
Jian Zhang
Keyword(s):  
Standard Deviation ◽  
Tropical Cyclone ◽  
Eye Tracking ◽  
Tropical Cyclones ◽  
Satellite Images ◽  
Initial Guess ◽  
Computationally Efficient ◽  
Tracking Time ◽  
Reflectivity Data ◽  
Previous Volume

Abstract A tropical cyclone (TC) eye tracking (TCET) algorithm is presented in this study to objectively identify and track the eye and center of a tropical cyclone using radar reflectivity data. Twelve typhoon cases were studied for evaluating the TCET algorithm. Results show that the TCET can track TC centers for several hours. The longest tracking time is about 35 h. Eye locations estimated from different radars showed consistency with a mean distance bias of about 3.5 km and a standard deviation of about 1.5 km. The TCET analysis shows decreasing eye radius as TCs approach land, especially within 50 km of the coastline. The TCET algorithm is computationally efficient and can be automated by using the TC center in the previous volume or the estimated center from satellite images as an initial guess. The TCET may not accurately find the TC center when a TC is weak or does not have an enclosed eyewall or when it does have highly noncircular eyes. However, the algorithm is still suitable for operational implementation and provides high spatial and temporal resolution information for TC centers and eye radii, especially for intense TCs.

scholarly journals Tropical Cyclogenesis Detection in the North Pacific Using the Deviation Angle Variance Technique

2015 ◽  
Vol 30 (6) ◽  
pp. 1663-1672 ◽  
Author(s):  
Kimberly M. Wood ◽  
Oscar G. Rodríguez-Herrera ◽  
Elizabeth A. Ritchie ◽  
Miguel F. Piñeros ◽  
Ivan Arias Hernández ◽  
...  
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Tropical Cyclones ◽  
Median Time ◽  
North Pacific ◽  
Western North Pacific ◽  
Tropical Cyclogenesis ◽  
Deviation Angle ◽  
Variance Technique ◽  
Cloud Clusters

Abstract The deviation angle variance technique (DAV-T) for genesis detection is applied in the western and eastern North Pacific basins. The DAV-T quantifies the axisymmetric organization of cloud clusters using infrared brightness temperature. Since axisymmetry is typically correlated with intensity, the technique can be used to identify relatively high levels of organization at early stages of storm life cycles associated with tropical cyclogenesis. In addition, the technique can be used to automatically track cloud clusters that exhibit signs of organization. In the western North Pacific, automated tracking results for the 2009–11 typhoon seasons show that for a false alarm rate of 25.6%, 96.8% of developing tropical cyclones are detected with a median time of 18.5 h before the cluster reaches an intensity of 30 knots (kt; 1 kt = 0.51 m s−1) in the Joint Typhoon Warning Center best track at a DAV threshold of 1750°2. In the eastern North Pacific, for a false alarm rate of 38.0%, the system detects 92.9% of developing tropical cyclones with a median time of 1.25 h before the cluster reaches an intensity of 30 kt in the National Hurricane Center best track during the 2009–11 hurricane seasons at a DAV threshold of 1650°2. A significant decrease in tracked nondeveloping clusters occurs when a second organization threshold is introduced, particularly in the western North Pacific.

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