The 26 July 2005 heavy rainfall event over Mumbai: numerical modeling aspects

Sahany, Sandeep; Venugopal, Vengatesan; Nanjundiah, Ravi S.

doi:10.1007/s00703-010-0099-3

Cited by 28 publications

(12 citation statements)

References 18 publications

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“…This was the case for direct model forecasts leading up to the disastrous 2011 Brisbane River and Lockyer Valley floods, which were a third of the amount actually received (van den Honert and McAneney 2011). A similar situation occurred in the disastrous 2005 Mumbai Floods (Sahany et al 2010), and in 2006 associated with one of the worst floods to affect China since 1983 (Gao et al 2009). …”

Section: Summary and Discussionmentioning

confidence: 74%

“…van den Honert and Mc Aneney (2011), for example, showed that the rainfall forecasts prior to the disastrous 2011 Brisbane River and Lockyer Valley floods in Queensland forecasted rainfall that was approximately one third of that actually received. An underestimation of extremely heavy rainfall also occurred for the disastrous 2005 Mumbai Floods (Sahany et al 2010), and the severe floods in China in 2006 (Gao et al 2009). Indeed, often the most intense rainfall in a major flood event is not sampled by even a relatively dense rain gauge network.…”

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confidence: 99%

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A vertical wind structure that leads to extreme rainfall and major flooding in southeast Australia

Callaghan¹,

Power²

2017

JSHESS

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Here we examine winds associated with extreme rainfall and major flooding in coastal catchments and more broadly over southeastern Australia. Both radiosonde and re-analysis data are examined. In every case (i) atmospheric moisture content is high and (ii) the low-level winds are onshore, and in almost every case (iii) the wind-direction turns anti-cyclonically with increasing height up to 500 hPa. Data from Brisbane extending back more than 50 years is consistent with this behavior: winds turn anti-cyclonically with increasing height on days with heavy rainfall, whereas winds turn cyclonically with increasing height on days with light or no rainfall. In the coastal zone, extreme rainfall rarely occurs without (i), (ii) and (iii). In eastern Australia beyond the coastal zone, conditions (i) and (iii) are also associated with extreme rainfall. We found very few cases where such conditions were not associated with extreme rainfall in this broader region. This study extends previous work by showing that the link between turning winds and rainfall exists in both the tropics and subtropics, and the link applies in cases of extreme rainfall and associated major flooding.

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Section: Summary and Discussionmentioning

confidence: 74%

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confidence: 99%

A vertical wind structure that leads to extreme rainfall and major flooding in southeast Australia

Callaghan¹,

Power²

2017

JSHESS

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“…The breaking of the MCS with a part going north-westward and another part moving towards Mumbai has not been documented in the previous study of Sahaney et al [41]. They used conventional methods of manually tracking low pressure systems (Figure 1 in their paper).…”

Section: Mumbai Rainfallmentioning

confidence: 91%

“…If we examine the large-scale features we note that prior to this event, monsoon was in an inactive phase from 19-22 July 2005. On 23 July a low pressure area formed over Northern Bay of Bengal, intensified into a well-marked low, and moved westward [41]. Figure 10(a) shows the set of clouds during the start of the rainfall phenomenon over Mumbai.…”

Section: Mumbai Rainfallmentioning

confidence: 99%

An Exploration Framework to Identify and Track Movement of Cloud Systems

Doraiswamy

Natarajan

Nanjundiah

2013

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. Studying cloud systems at different scales. Our framework is used to study the movement of the equatorial Madden Julian Oscillation (MJO) over the Indian Ocean. Given the IR brightness temperatures over the island of Borneo, we first identify the set of clouds. Users can select clouds of interest and track their movement. Smaller scale cloud systems embedded in a MJO move in a westward direction. The manifestation of a convectively coupled kelvin wave results in a temporary eastward movement of parts of the cloud cluster. Such movement can be easily obtained using the querying ability of our framework. The rightmost figure shows a subset of the clouds that move eastward for at least 90 minutes. The temporary movement is indicated by the fact that the movement reverts to its original westward direction after a short duration. Our framework also helps quantify the overall eastward propagation of the MJO.Abstract-We describe a framework to explore and visualize the movement of cloud systems. Using techniques from computational topology and computer vision, our framework allows the user to study this movement at various scales in space and time. Such movements could have large temporal and spatial scales such as the Madden Julian Oscillation (MJO), which has a spatial scale ranging from 1000 km to 10000 km and time of oscillation of around 40 days. Embedded within these larger scale oscillations are a hierarchy of cloud clusters which could have smaller spatial and temporal scales such as the Nakazawa cloud clusters. These smaller cloud clusters, while being part of the equatorial MJO, sometimes move at speeds different from the larger scale and in a direction opposite to that of the MJO envelope. Hitherto, one could only speculate about such movements by selectively analysing data and a priori knowledge of such systems. Our framework automatically delineates such cloud clusters and does not depend on the prior experience of the user to define cloud clusters. Analysis using our framework also shows that most tropical systems such as cyclones also contain multi-scale interactions between clouds and cloud systems. We show the effectiveness of our framework to track organized cloud system during one such rainfall event which happened at Mumbai, India in July 2005 and for cyclone Aila which occurred in Bay of Bengal during May 2009. Index Terms-Cloud clusters, tracking, computational topology, split tree, weather and climate simulations.

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“…• N for the July 2005 Mumbai rainfall event [12]. The period of simulation was from July 24, 2005 18:00 hours -July 27, 2005 18:00 hours.…”

Section: B Domain Configurationsmentioning

confidence: 99%

A Diffusion-Based Processor Reallocation Strategy for Tracking Multiple Dynamically Varying Weather Phenomena

Malakar

Natarajan

Vadhiyar

et al. 2013

2013 42nd International Conference on Parallel Processing

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Abstract-Many meteorological phenomena occur at different locations simultaneously. These phenomena vary temporally and spatially. It is essential to track these multiple phenomena for accurate weather prediction. Efficient analysis require highresolution simulations which can be conducted by introducing finer resolution nested simulations, nests at the locations of these phenomena. Simultaneous tracking of these multiple weather phenomena requires simultaneous execution of the nests on different subsets of the maximum number of processors for the main weather simulation. Dynamic variation in the number of these nests require efficient processor reallocation strategies. In this paper, we have developed strategies for efficient partitioning and repartitioning of the nests among the processors. As a case study, we consider an application of tracking multiple organized cloud clusters in tropical weather systems. We first present a parallel data analysis algorithm to detect such clouds. We have developed a tree-based hierarchical diffusion method which reallocates processors for the nests such that the redistribution cost is less. We achieve this by a novel tree reorganization approach. We show that our approach exhibits up to 25% lower redistribution cost and 53% lesser hop-bytes than the processor reallocation strategy that does not consider the existing processor allocation.

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The 26 July 2005 heavy rainfall event over Mumbai: numerical modeling aspects

Cited by 28 publications

References 18 publications

A vertical wind structure that leads to extreme rainfall and major flooding in southeast Australia

A vertical wind structure that leads to extreme rainfall and major flooding in southeast Australia

An Exploration Framework to Identify and Track Movement of Cloud Systems

A Diffusion-Based Processor Reallocation Strategy for Tracking Multiple Dynamically Varying Weather Phenomena

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