Analysis of a genesis potential parameter during pre-cyclone watch period over the Bay of Bengal

Nath, Sankar; Kotal, S. D.; Kundu, Prabir Kumar

doi:10.1007/s11069-012-0473-1

Cited by 12 publications

(3 citation statements)

References 14 publications

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“…Given the lack of consensus surrounding the TC genesis features in the BoB, Kotal et al (2009a,b) proposed a genesis potential parameter (GPP), which includes both dynamic and thermodynamic variables, for differentiating between developing and nondeveloping TC systems over the northern Indian Ocean. Nath et al (2013) used the GPP to analyze the precyclone status of approximately 30 tropical disturbances over the BoB from 2001 to 2010, enabling them to provide a possible 2-day lead prediction for depression systems in the region. The study examined precyclone genesis conditions during the pre-and postmonsoon transition periods and determined the applicability of the GPP in the BoB basin.…”

Section: Introductionmentioning

confidence: 99%

Environmental Conditions Modulating Tropical Cyclone Formation over the Bay of Bengal during the Pre-Monsoon Transition Period

et al. 2019

Journal of Climate

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Globally, the highest formation rate of super tropical cyclones (TCs) occurs over the Bay of Bengal (BoB) during the premonsoon transition period (PMT), but TC genesis has a low frequency here. TCs have occurred over the BoB in only 20 of the past 36 years of PMTs (1981–2016). This study investigates which environmental conditions modulate TC formation during the PMT over the BoB by conducting a quantitative analysis based on the genesis potential parameter, vorticity tendency equation, and specific humidity budget equation. The results show that there is a cyclonic anomaly in the TC genesis group compared to the non-TC genesis group, which is mainly due to the divergence term. A significant difference in vorticity contributes to TC formation over the BoB during the PMT. Furthermore, anomalous cyclonic flow enhances ascending motion, transporting moisture to the midlevel atmosphere. A change in specific humidity (SH) causes an increase in relative humidity, which contributes positively to TC formation. The vertical wind shear also makes a small positive contribution. In contrast to the previous three terms, the contribution from the instability term associated with 500- and 850-hPa air temperatures is negative and almost negligible. In addition, the synoptic-scale disturbance energy is more powerful in the TC genesis group than in the non-TC genesis group, which is favorable for TC breeding. Together, these conditions determine whether TCs are generated over the BoB during the PMT.

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Section: Introductionmentioning

confidence: 99%

Environmental Conditions Modulating Tropical Cyclone Formation over the Bay of Bengal during the Pre-Monsoon Transition Period

et al. 2019

Journal of Climate

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“…There have been extensive studies on the tropical cyclone genesis (Kotal et al 2009;Nath et al 2013) and intensity prediction (Kotal et al 2008) over BOB. The studies on the long-term variability of tropical cyclone frequency, in comparison, has received relatively less attention, particularly, for post-monsoon season although several studies have documented the variation of TC activity with sea surface temperature and atmospheric circulation for monsoon periods.…”

Section: Introductionmentioning

confidence: 99%

Decadal variation of ocean heat content and tropical cyclone activity over the Bay of Bengal

Nath¹,

Kotal²,

Kundu

2016

J Earth Syst Sci

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The upper ocean heat content up to 700 m depth (OHC 700) is an important climatic parameter required for atmospheric and oceanographic studies like a cyclone. In this study, therefore, an attempt has been made to examine the inter-decadal variations of tropical cyclone (TC) activity and OHC 700 over the Bay of Bengal (BOB) for the post-monsoon season (October-December) during 1955-2013 periods. The sea-surface temperature (SST), geopotential height at 500 hPa, low-level vorticity at 850 hPa, vertical wind shear between 200 and 850 hPa, middle tropospheric humidity at 500 hPa and outgoing long-wave radiation are also being studied using seasonal mean data. The results show a significant inter-decadal variation during 1955-2013, with two distinct decadal periods: active decadal period (ADP) (1955-1988) and inactive decadal period (IDP) (1989-2013). The anomalies of these parameters are opposite in phase for two periods. It is found that the large scale atmospheric features and oceanic parameters have significant inter-decadal variability, but frequency of the tropical cyclone is attributed to the variation in the atmospheric dynamic and thermodynamic conditions rather than the variation of oceanic parameters OHC 700 and SSTs during the post-monsoon season.

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“…There are several studies on the genesis (Roy Bhowmik, 2003;Kotal et al, 2009;Nath et al, 2013) and intensity prediction (Dvorak, 1975;Roy Bhowmik et al, 2007;Kotal et al, 2008) of cyclones over the Indian Sea. However, in comparison the Indian Sea has received relatively limited attention, given that several studies have documented the seasonal prediction (including the NN method approach) of cyclones in other ocean basins of the world.…”

Section: Introductionmentioning

confidence: 99%

Seasonal prediction of tropical cyclone activity over the North Indian Ocean using the neural network model

Nath

Kotal

Kundu

2015

Atm

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Se desarrolla un modelo de red neuronal para predecir el número estacional de ciclones tropicales (CT) que se desarrollan en el Océano Índico septentrional después de la estación del monzón (octubre a diciembre). Se analizan la frecuencia de los CT y las variables climáticas de gran escala derivadas de la base de datos de reanálisis del NCEP/NCAR con resolución de 2.5 × 2.5º para el periodo 1971-2013. Se utilizaron datos del periodo 1971-2002 para desarrollar el modelo, y éste se probó con datos de muestreo independientes del periodo 2003-2013. Se eligieron cinco variables climáticas de gran escala (altura geopotencial a 500 hPa, [septiembre]) como predictores para aplicar un análisis de correlación. Con base en algunos parámetros ran con el modelo lineal de regresión múltiple. Los resultados indican que el número de ciclones tropicales calculado por medio de ambos modelos es muy similar al número real de ciclones ocurridos en cada año. Sin embargo, los resultados del modelo de redes neuronales fueron superiores a los del modelo linear de regresión múltiple, de modo que esta técnica de predicción de ciclones tropicales puede ser muy útil para propósitos operativos de predicción.

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Analysis of a genesis potential parameter during pre-cyclone watch period over the Bay of Bengal

Cited by 12 publications

References 14 publications

Environmental Conditions Modulating Tropical Cyclone Formation over the Bay of Bengal during the Pre-Monsoon Transition Period

Environmental Conditions Modulating Tropical Cyclone Formation over the Bay of Bengal during the Pre-Monsoon Transition Period

Decadal variation of ocean heat content and tropical cyclone activity over the Bay of Bengal

Seasonal prediction of tropical cyclone activity over the North Indian Ocean using the neural network model

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