Large‐Scale Extreme Rainfall‐Producing Synoptic Systems of the Indian Summer Monsoon

Nikumbh, Akshaya C; Chakraborty, Arindam; Bhat, G. S.; Frierson, Dargan M. W.

doi:10.1029/2020gl088403

Cited by 35 publications

(26 citation statements)

References 61 publications

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“…This vorticity strip is spread across nearly 4,000 km in the east‐west direction and is possibly linked with the enhanced monsoon trough associated with the ISO over the northern Bay of Bengal and central India region (Figure 1(a)), as well as with the northwest‐southeast tilted large‐scale structure of cyclonic ISO winds known to extend from the Arabian Sea to the West Pacific (Karmakar & Misra, 2020). This could be also linked to the development of a secondary cyclonic vortex to the west of LPS during large‐scale extreme rainfall events (Nikumbh et al., 2020). The vorticity anomaly is weaker and less elongated for lows forming during the active ISO phase (Figure 3(a)).…”

Section: Resultsmentioning

confidence: 99%

Influence of Intraseasonal Variability on the Development of Monsoon Depressions

Karmakar

Boos

Misra

2021

Geophysical Research Letters

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Intraseasonal oscillations (ISOs) in the Indian summer monsoon represent dominant modes of variability of that circulation (Sikka & Gadgil, 1980; Yasunari, 1979). One of the most prominent manifestations of these ISOs is characterized by northward propagation of rain bands from the equatorial Indian Ocean to the foothills of the Himalayas with a periodicity of 20-60 days (Ajaya Mohan & Goswami, 2003; Karmakar et al., 2017a; Krishnamurthy & Shukla, 2007). This ISO is often associated with an eastward-propagating planetary-scale circulation traveling at a speed of almost 8° longitude/day (Krishnamurti et al., 1985) that is commonly referred to as the Madden-Julian oscillation (Karmakar & Krishnamurti, 2019; Madden & Julian, 1972; Pai et al., 2011; Singh et al., 1992). Active-break cycles of rainfall over India during the monsoon season are often associated with the passage of this ISO (Karmakar et al., 2017a; Rajeevan et al., 2010). Here, we examine the association of this ISO with synoptic-scale precipitating vortices, also known as low-pressure systems (LPS). In South Asia, weaker LPS are typically called monsoon lows and stronger ones are called monsoon depressions. These lows and depressions together account for around half of the

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Section: Resultsmentioning

confidence: 99%

Influence of Intraseasonal Variability on the Development of Monsoon Depressions

Karmakar

Boos

Misra

2021

Geophysical Research Letters

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“…However, it is known that LPS over AS and BoB initiates rainfall over central India [49]. Over the Indian region, multiple low-pressure systems may play an essential role in influencing extreme rainfall events [50], and KFE was one such case. At present, the ultimate goal of weather forecasts should be dedicated to extreme rainfall events, which always pose a challenging task [5,14], because every new flood is unique.…”

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confidence: 99%

Interaction of a Low-Pressure System, an Offshore Trough, and Mid-Tropospheric Dry Air Intrusion: The Kerala Flood of August 2018

et al. 2020

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The present study examines the Kerala Flood Event (KFE, 15–16 August 2018, in India) that occurred along the west coast of India and resulted in ~400 mm of rainfall in one day. The KFE was unique in comparison to previous floods in India, not only due to the rainfall duration and amount, but also due to the fact that the dams failed to mitigate the flood, which made it the worst in history. The main goal of this study is to analyze and elucidate the KFE based on meteorological and hydrological parameters. A propagating low-pressure system (LPS) from the Bay of Bengal (BoB) caused the streak of plenty of rainfall over Kerala, the west coast, central India, and the BoB. Additionally, the upper-tropospheric anti-cyclonic system over the Middle East region inhibited a northward advancement of LPS. On the western coast of India, a non-propagating (with diurnal fluctuations) offshore trough was observed over the west coast (from Kerala to Gujarat state). Therefore, a synergic interaction between LPS, an intrusion of dry air in the middle-troposphere, and the offshore trough was the main reason for KFE. However, after around ten days, rainfall saturated the dam capacities; thus, the released water, along with the amount of precipitation on the day of the event, was one of the other possible reasons which worsened the flood over Kerala.

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“…Both TC (Lin et al ., 2015; Zhou and Li, 2015; Cheung et al ., 2017; Wang et al ., 2019) and monsoon (Nikumbh et al ., 2020; Sooraj et al ., 2020; Yuan et al ., 2020) play important roles on extreme precipitation in eastern China. In order to distinguish TCEP and nTCEP, the 6‐hr tropical cyclone best‐path dataset, acquired from the Tropical Cyclone Data Center of China Meteorological Administration (Ying et al ., 2014), is used to identify TCEP events.…”

Section: Datamentioning

confidence: 99%

Spatial effects on extreme precipitation in the coastal areas of southeastern China during the raining season

Qian

Sun

2022

Intl Journal of Climatology

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This study investigated the spatial effects of the extreme precipitation during the raining season in the perspective of tropical cyclone‐related (TCEP) and non‐TC‐related extreme precipitation (nTCEP). The seasonal maximum 1‐day precipitation (RX1day) data across 94 stations in the coastal areas of southeastern China from 1964 to 2013 were used and partitioned into different homogenous regions. Regional Bayesian models were developed for generalized extreme value (GEV) distribution to quantify the spatial effects on extreme precipitation in each homogeneous region. Four coastal and one inland homogeneous regions were identified, which were consistent with the TC tracks. The extreme precipitation was found to decrease as the distance from the coastline increases, whose sensitivity to the distance from the coastline differs from region to region. For TCEP, the distance from the coastline has effects on the location and the scale parameters of the regional GEV model in all regions. The 50‐year return level of TCEP in southern regions is five times more sensitive to the distance from the coastline than that in the northern regions. For nTCEP, the distance from the coastline has effects on the scale parameter in all regions, while the location parameter is affected only in two regions in the south. The sensitivity of 50‐year return levels of nTCEP to the distance from the coastline decreases gradually from south to north. Within 200 km from the coastline, the 50‐year return level of TCEP is 15.6–78.9% larger than that of nTCEP in the same region.

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Large‐Scale Extreme Rainfall‐Producing Synoptic Systems of the Indian Summer Monsoon

Cited by 35 publications

References 61 publications

Influence of Intraseasonal Variability on the Development of Monsoon Depressions

Influence of Intraseasonal Variability on the Development of Monsoon Depressions

Interaction of a Low-Pressure System, an Offshore Trough, and Mid-Tropospheric Dry Air Intrusion: The Kerala Flood of August 2018

Spatial effects on extreme precipitation in the coastal areas of southeastern China during the raining season

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