Satellite Observations on Cyclone-Induced Upper Ocean Cooling and Modulation of Surface Winds—A Study on Tropical Ocean Region

Badarinath, K. V. S.; Kharol, Shailesh Kumar; Dileep, P. K.; Prasad, Vikram

doi:10.1109/lgrs.2009.2018487

Cited by 9 publications

(7 citation statements)

References 25 publications

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“…From the results obtained it can be summarized that deepening of MLD of ∼30 m, decaying of BL, deeper 26 • C isotherm level of ∼90 m, near surface cooling of 1 • C, and increase of near surface salinity by 1 psu were observed in the southern quadrant (both along left and right side of the track). These observations are consistent with the report of Badarinath et al (2009) based on satellite measurements. Maximum precipitation accumulated in the left side of the storm.…”

Section: Discussionsupporting

confidence: 93%

“…In this present study three ARGO floats are located in the latitudinal zone of 14-15 • N. Appreciable changes in TCHP are not observed before, during, and after the MALA passage. Badarinath et al (2009) reported surface cooling of 4-5 • C in the same latitudinal belt during MALA passage. The present study reveals that this significant cooling could be accountable due to turbulent and diapycnal mixing.…”

Section: Uppermentioning

confidence: 91%

“…More details of MALA event can be found in the published work of Rajesh Kumar et al (2009) and Dube et al (2009). In a very recent work Badarinath et al (2009) evaluated the relationship between the SST and meteorological parameters over BoB region during the passage of this MALA cyclone using satellite data. Along the trail of the cyclone a cold patch, weakening of wind speeds, and associated cooling of 4-5 • C SST was reported.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Response of Upper Ocean during passage of MALA cyclone utilizing ARGO data

Vissa

Satyanarayana

Kumar

2012

International Journal of Applied Earth Observation and Geoinfor

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Section: Discussionsupporting

confidence: 93%

Section: Uppermentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Response of Upper Ocean during passage of MALA cyclone utilizing ARGO data

Vissa

Satyanarayana

Kumar

2012

International Journal of Applied Earth Observation and Geoinfor

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“…On the other hand, the aerosols, both natural and anthropogenic, play an important role in the local monsoon system (onset of the monsoon, intensity, rainfall amounts and distribution), as numerous studies over South Asia have shown [e.g., Menon et al , 2002; Lau et al , 2006; Gautam et al , 2009; Prasad et al , 2009; Zhang et al , 2010]. Furthermore, the presence of intense tropical cyclones over the Bay of Bengal [ Badarinath et al , 2008, 2009a] affects strongly the cloud cover over the region as well as the SST [ Badarinath et al , 2009b]. In late 1980s, the COD over Hyderabad is low, while in the beginning and the middle of 1990s it was high.…”

Section: Resultsmentioning

confidence: 99%

Solar dimming over the tropical urban region of Hyderabad, India: Effect of increased cloudiness and increased anthropogenic aerosols

et al. 2010

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[1] The present work examines the multidecadal changes in the net downward shortwave radiation (NDSWR) over the urban region of Hyderabad, India, during the period . The trends in NDSWR and in cloud optical depth (COD) are analyzed over the region using the Modern Era Retrospective-Analysis for Research and Applications (MERRA 2D), which is a newly available data set. The NDSWR exhibits a significant reduction of ∼−20.25 W m −2 for the period 1993-2005; however, it declined at a slower rate (0.468 W m −2 ) during the period 1979-1992. This reduction translates to −1.56 W m −2 yr −1 in the first period and to −0.04 W m −2 yr −1 in the second. The large difference in the NDSWR trends between the two periods is mainly attributed to the dramatic increase in high COD and in aerosol optical depth (AOD) during the last decade. The total COD over the region suggests an increase of 6.85% during the study period, with the larger increase to be depicted in the high-level clouds (70.86%). Furthermore, retrievals of AOD 550 from Microtops-II Sun photometer and Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) show a significant increase of ∼34% and ∼20% during the period 2002-2008 over Hyderabad, respectively. It is demonstrated that aerosols and clouds contribute to the remarkable reduction in NDSWR over Hyderabad in the recent years, thus resulting in a continuous solar dimming over the area. The main role in the decline of NDSWR has been the increase in COD of the high clouds, mainly in monsoon and premonsoon. On the other hand, the dramatic increase in the AOD 550 plays an important role in the decrease of NDSWR, mainly in winter. Furthermore, the indirect aerosol effect can modify the cloud formation, albedo, and lifetime, also playing a key role in the aerosol-cloud-radiation interactions.

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“…In recent years, machine learning (ML) does not need any linear statistical technique to classify the tropical cyclone formation (Park et al 2016;Zhang et al 2015). The approaches used in these ML classifiers are random forest (RF), decision tree (DT) and support vector machine (SVM) as they predict the TC formation earlier than the linear discriminated analysis (LDA) (Kim et al 2019).Moreover, the microwave sensors such as wind scatterometer and TMI may effectively identify the intensity and position of TC (Badarinath et al 2009;Hawkins et al 2008) due to the infrared image gathered from the fixed satellite. The aforementioned information acquired sensor provides a high temporal sampling and more area coverage capability to predict more reliable result of intensity as well as the position of TC.…”

Section: Introductionmentioning

confidence: 99%

A novel approach for predicting the tc center of remotely sensed images using pso based density matrix

Mubeen¹,

Priya²,

Vijayaraj³

2021

Earth Sci Inform

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In the present work,an image extraction technique has been designed to fix the center spot of the tropical cyclone. The cyclone prediction is processed within the CBIR system and hence it established a well-effective output. A raw cyclone image is being processed under the image processing techniques such as Adaptive Gaussian Notch Filter (Pre-processing), Adaptive Thresholding (segmentation) and Feature-extraction. The extracted features are collectively used as an input to the CNN-HMO classifier which produces a relevant classified output. Relevance feedback is a key factor which passes these corresponding outputs to the user. User selects the required cyclone image after then, the image extraction process of PSO based density matrix takes place. The extractor has variance, gradient and density matrix (DM) to predit the center spot. So that the brightness temperature is computed for each pixel coordinates in both zonal and meridional axial direction. After then DM point converges over every pixel in an image and a PSO is followed towards the pixel orientation of each convergence line to determine the best optimal solution (i.e.,) the center of the Tropical Cyclone. With this optimizing criterion, the center of the Tropical Cyclone is generated.

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Satellite Observations on Cyclone-Induced Upper Ocean Cooling and Modulation of Surface Winds—A Study on Tropical Ocean Region

Cited by 9 publications

References 25 publications

Response of Upper Ocean during passage of MALA cyclone utilizing ARGO data

Response of Upper Ocean during passage of MALA cyclone utilizing ARGO data

Solar dimming over the tropical urban region of Hyderabad, India: Effect of increased cloudiness and increased anthropogenic aerosols

A novel approach for predicting the tc center of remotely sensed images using pso based density matrix

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