1. Introduction
This study concerns identifying the synoptic to local-scale precursors responsible for extreme rainfall events over the coastal city of Mumbai, India, that has become a poster case of heavy rains and urban flooding. The rise in the frequency of extreme rain events has become a global feature (Lehmann et al. 2015). Over the Indian monsoon region, the complex interplay of extreme rains and the growth in urbanization has become increasingly interlinked (Kishtawal et al. 2010). The heavy rain events and resulting urban flooding in cities such as Chennai and Mumbai have been of interest to both the scientific and the operational disaster mitigation community (Kumar et al. 2008). Studies such as Kumar et al. (2008), Krishnamurti et al. (2017a,b), and Baisya and Pattnaik (2019) have sought to diagnose the dynamical and thermodynamical aspects of such events in the context of multiscale interactions focusing on specific events in Indian cities such as Mumbai, Chennai, and Kerala. Globally, such event-based analysis is of interest (e.g., Viterbo et al. 2020; Li et al. 2020). The prediction of these extreme rain events has been a challenging task for operational meteorologists (Yussouf and Knopfmeier 2019; Routray et al. 2010).
Examples of multiscale studies on extreme heavy rainfall (ERF) urban events across the globe, telescoping onto India and Mumbai, are shown in Figs. 1a–c. Champion et al. (2019) studied U.K. summer ERF events showing the evidence of linkage to surface pressure fields, localized high relative humidity, the position of 200-hPa geopotential height, intense westerly jet, and orographic influence. Similarly, Archer and Fowler (2018) identified specific features of flash floods across the United Kingdom. With the analysis of radar data, Lochbihler et al. (2017) showed that extreme events over the Netherlands are associated with the convergence of moist air. For the United States, floods related to extreme rain events have been linked to jet stream position and midlatitude disturbances as the primary drivers along with landfalling tropical cyclones. Climate model simulation for the U.S. region by Chan et al. (2018) shows that mean sea level pressure and relative vorticity influence localized ERF occurrences. Over Atlanta, Georgia, the possible role of urbanization on ERF patterns is studied in McLeod et al. (2017). Doswell et al. (1996) reported that the extreme rain events over the central United States are associated with a high amount of vertical moisture flux, heavy updraft, high specific humidity, and precipitation efficiency, which is a function of the relative humidity of the environment. In China, rainfall extremes over the Yangtze River basin have been linked primarily to the water vapor advection (Cao et al. 2019). Considering the prevailing atmospheric conditions during extreme and nonextreme rain events over Sweden, Hellström (2005) found that low-level westerly flow and strong southerly winds are conducive to ERF. A study over Nepal suggests that the extreme precipitation is related to the local physiogeographical regions (Karki et al. 2017). These are examples provided only to highlight the wide interest in studying the multiscale interactions for ERF, especially with the renewed interest in pattern detection/machine learning approaches (Schultz et al. 2021; Espeholt et al. 2022; Sasanka et al. 2023).
Some of the literature that has attempted to analyze the specific features that are associated with extreme precipitation over a region: The literature available (a) worldwide and (b) for India with the location where the events occurred. (c) Mumbai, which is the area of interest for the study.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
Indian region has witnessed several notable ERF disasters in recent decades (Kumar et al. 2008). Some of the major events include the heavy rainfall and associated flooding in Uttarakhand (16 June 2013), Chennai (10 December 2015), Kerala (August 2018), and Mumbai (26 July 2005). Krishnamurti et al. (2017a) showed that the horizontal convergence of moisture-laden monsoon air present within the moist boundary layer over the Bay of Bengal (BoB) actuated streams of buoyancy toward the region of extreme orographic lifting, causing heavy rain in base Himalayan regions. Medina et al. (2010) and Dimri and Niyogi (2013) explain that the occurrence of intense convective systems near the Himalayan orographic region and land cover heterogeneity are often associated with BoB depressions. The depression carrying conditionally unstable air upon reaching the foothills of the mountainous region with orographic lift releases the instability in the form of narrow, vertically oriented convective cells (Houston and Niyogi 2007). Studies also showed linkage of the extreme event to midlatitude westerlies, Rossby wave breaking and eddy shedding of the Tibetan anticyclone, and orographic lifting with the presence of semiperennial quasi-stationary atmospheric rivers (Ranalkar et al. 2016; Vellore et al. 2016; Gimeno et al. 2014; Guan and Waliser 2015; Jackson et al. 2016). The role of vorticity stretching during the occurrence of heavy precipitation is also highlighted as a mechanism (Chakraborty 2016). The sea surface temperature (SST) increase in the Indian Ocean can climatologically increase the extreme events over the Indian subcontinent (Rajeevan et al. 2008). A detailed diagnostic study for Kerala floods by Viswanadhapalli et al. (2019) suggests that the two spells (7–10 and 14–18 August) responsible for the catastrophic events were associated with an offshore trough, a depression over the BoB along with high convective instability due to strong westerly jet. ERFs occurring over India’s northeast region are due to thermal instability of the atmosphere and orographic effect (Mahanta et al. 2013). Atmospheric instability due to mesoscale events is another important reason behind producing ERFs (Fuentes et al. 2008; Gómez et al. 2011; Luo et al. 2016; Wang et al. 2014; Lepore et al. 2015).
Thus, various atmospheric conditions are responsible for extreme events. Because a single parameter cannot be considered as the driving force for heavy rainfall events, different possible atmospheric and oceanic conditions that bring about ERF events should be analyzed concurrently to understand the causes.
Mumbai (19.07°N, 72.87°E) is one of the most populated metropolitan cities globally and is India’s business capital, with a population of 18 million. Mumbai receives an average of 2422 mm of annual rainfall, of which 77% is received during the June–September period alone. The city experiences ERF events (>204.5 mm day−1) approximately once every other year during the summer monsoon season. ERF events such as the 944 mm on 26 July 2005 have been well studied both from observational and numerical modeling aspects. The megacity’s geographical location on the coast of the Arabian Sea (AS) at the leeward side of the Western Ghats likely sets a conducive meteorological environment. Jenamani et al. (2006) and Kumar et al. (2008) showed that mesoscale systems embedded in favorable synoptic-scale flow patterns and intense thunderstorm activity with high CAPE value could cause heavy rains. Evidence for the possible role of land use and urbanization in Mumbai’s intense convective activity has also been presented (Lei et al. 2008).
Mumbai facing continued stress on urban services and a geographical propensity for intense rainfall events is the focus of this study. A survey to establish the cause of the ERF events over Mumbai is undertaken to help delineate the processes. An advanced interpretation of the conducive atmospheric situations responsible for ERF events will likely support the forecaster community to disseminate early warnings that can save many lives and minimize damage to the economy. Until now, limited studies discuss the precursors that significantly impact extreme urban rain events. Therefore, the study with the goal to analyze the atmospheric and oceanic conditions that impact the extreme rain events for the coastal city of Mumbai is carried out.
2. Data and method
For rainfall analysis, the India Meteorological Department (IMD) gridded daily rainfall dataset at 0.25° × 0.25° latitude/longitude horizontal resolution is considered in this study. A large number of automated weather station data are used to generate the gridded rainfall analysis and the data are quality controlled as per the World Meteorological Organization standard procedure. There are a total of 6955 rain gauge stations over India, of which 494 are hydrometeorology observatories, 74 are Agromet observatories, 547 are IMD observatory stations, and the remaining ones are maintained by the state governments (Pai et al. 2014). In this study, the analysis period is confined to the recent era of 39 years (1981–2019).
IMD has classified the rainfall intensity into seven different categories, which vary from “very light rain” to “exceptionally heavy” depending on the amount of rainfall (IMD 2015), and the study follows this IMD classification. The details of the classification are shown in Table 1. ERF events are defined as the days having precipitation intensity ≥ 204.5 mm according to the above mentioned IMD classification. To analyze the meteorological parameters associated with the ERFs over Mumbai city, the top 15 ERF days with the heaviest precipitation (>270 mm day−1) in the last 40 years are considered in the present study. To examine the large-scale meteorological parameters leading to the ERF events, the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) (ERA5) at a horizontal resolution of 0.25° and 3-hourly intervals datasets have been used (Hersbach et al. 2018, 2020). It uses four-dimensional variational data assimilation (4D-Var) of satellite and in situ observations. ERA5 is a more recent and improved version of the ECMWF Integrated Forecast System, which includes higher spatial and temporal resolution, new data assimilation techniques, improved convection and microphysics parameterizations, and improved observational and forcing datasets. The evolution of hydroclimatic conditions is investigated using specific humidity and zonal (u wind), meridional (υ wind), and vertical winds from the surface and 1000–100 hPa pressure levels, along with SST from this dataset. Optimum Interpolation SST (OISST) at 25-km spatial and daily temporal resolution provided by National Oceanic and Atmospheric Administration (NOAA) has also been used for SST analysis. These data include observations from different resources including satellite, ships, buoys, and Argo floats and the information is interpolated onto a global grid.
To analyze some of the contrasting features, respective “dry” days (taken as the days having no rainfall within ±10 days of the respective ERF days) are also considered. The list of the events is presented in Table 2. There are no two consecutive ERF days taken here, as we have considered only single-day maxima in rainfall intensity of the respective ERF event. Thus, each ERF day represents an independent sample. The large-scale atmospheric and oceanic features are analyzed to identify the dominating factors responsible for contrasting rainfall events over Mumbai. Multivariate regression analyses of all suggested events are carried out to get the order of contribution of the meteorological parameters to the ERF (Gao and Xie 2014).
All extreme rainfall days and all dry days over Mumbai.
3. Results
The following section describes the multiscale meteorological processes associated with ERF events over Mumbai considered in this study.
a. Environmental setups responsible for ERF events over Mumbai
Different synoptic and mesoscale features occurring prior to the ERF events over Mumbai are discussed below.
1) Rain-bearing systems
(i) Offshore trough
Frequently occurring heavy rainfall events over India’s west coast are mainly associated with the convective systems embedded in large scale and associated with offshore troughs along the west coast (Rao 1976; Rao 2005). Interestingly, all the identified ERF cases are associated with the offshore trough along the latitude of 15°–21°N. Trough positions for individual cases are provided in Fig. 2, indicated by the pressure gradient. All the ERF events are associated with the active offshore trough that lasts up to 72 h. The temporal extension of these troughs lasts from 48 h prior to the ERF event to 24 h after the event. The position of the trough lines influences the moisture advection and moisture flux convergence in the lower level of atmosphere over the AS. This moisture advection has been identified as the dynamic proxy of the moisture source by Konduru and Mrudula (2021). This essentially contributes to an increased equivalent potential temperature with an amount greater than 402 K for all the cases taken in the study over the active offshore trough region. Warmer equivalent potential temperature triggers high relative humidity, thus causing heavy precipitation over the active offshore region. These offshore troughs are also responsible for the eastward movement of the rainbands that accumulate over the western coastal India with the presence of Western Ghats and ultimately cause ERF over a local area like the Mumbai urban region with the influence of various other environmental conditions (Konduru and Mrudula 2021). The correlation between the offshore trough with the rainfall over Mumbai is 0.52. The occurrence of the transient offshore troughs is thus one of the vital indicators of ERF events over Mumbai.
Offshore trough (contours; hPa) for each ERF case taken with SST 48 h prior (color shading) to the ERF that occurred over the Mumbai region. Two 2017 plots are shown for the (bottom left) August and (bottom center) September cases, respectively.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
SST during 24 h prior to the event for each case is reviewed along with the trough lines in Fig. 2. There is an increasing gradient of SST from west to east in the AS. Near Mumbai, there is a warmer SST gradient present along the coast from in northward direction. This may be a major influence for local convection because over the eastern AS, the local air–sea interaction plays a dominant role on a shorter intraseasonal time scale (Izumo et al. 2008). A detailed analysis of the role of SST in bringing on ERF events is discussed in section 3a(2).
(ii) Midtropospheric cyclone
The midtropospheric level plays a pivotal role in modulating India’s monsoonal flow during boreal summer (Hunt et al. 2018). The cyclonic circulation in the midtropospheric region, generally known as midtropospheric cyclones (MTCs), sets a conducive environment for ERF. These quasi-stationary systems with a horizontal stretch of about 1000 km and vertical elongation of about 6–8 km can persist up to 10 days. These MTCs are well studied in the association of heavy rain events (Krishnamurti and Hawkins 1970). In the present study, the midlevel circulation pattern stretching from 700 to 500 hPa for each of 15 ERF cases is shown in Fig. 3. Most of the ERF cases (August 1981, 1991, 1993, 1997, 2000, 2005, 2009, and 2017) are found to have well-organized prominent MTCs over central India, persisting more than 12 h before the rainfall. For the cases in 1984 and 2007 the circulation is present toward the west, and for 1990 and 2019 the circulation is toward east. For 1985, the circulation is present over the western coast; however, it is not prominent enough. For cases in September 2015 and 2017, two cyclonic gyres are present in the east and west directions. The figure also shows that the midlevel averaged wind has a strong veering tendency over the peninsula region and is positioned over the central India region. This amplified cyclonic circulation triggers strong interaction of moist westerly winds from the AS with the steep orography along the Western Ghats region, causing convergence and localized convection. MTCs are associated with latent heat release from the cumulus convections (Miller and Keshavamurthy 1968). Most of the MTCs persisting for longer period (≥5 days) brings heavy precipitation over the northern AS region (Choudhury et al. 2018).
Similar to Fig. 2, but for horizontal wind circulation streamlines from 700 to 500 hPa, with shaded wind magnitude.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
(iii) BoB depressions
During the southwest monsoon season, the surface wind from the AS veers toward the warmer mainland of the Indian subcontinent bringing moisture-laden winds to the land. The cross-equatorial flow and the Somali jet stream carry a large amount of moisture, contributing mainly to the summer monsoon rainfall over India (Krishnamurti et al. 1989). During this period, the northern and northwestern part of the BoB receives low pressure systems that develop into depressions and deep depressions, typically moving toward westward and north-westward (Bhat et al. 2001). These mesoscale systems from the BoB moving toward the Gujarat and Maharashtra coast accrue large moisture to the west coast, thus becoming one of the major sources of rains over the region. Most of the cases presented in the study are associated with BoB or land depressions. The intensity of the land depressions is generally weaker than the BoB depressions (Jadhav 2002). Rainfall with the depression track for each extreme rainfall case has been provided in Fig. 4. It is found that the depressions are mostly westward and northwestward moving. Many cases such as 1981, 1993, 2000, 2009, 2017 (September), and 2019 are not associated with any kind of depression. August 1991 and 2017 rainfall cases are associated with land depressions rather than BoB depressions. In the 1985 case, although a depression has formed in the BoB during the rainfall period, the system moves in a northward direction and not toward the west coast of India. ERF events over the western coast of India have higher intensity and greater spatial distribution when associated with BoB depressions. However, cases without BoB depressions, including 1981, 1993, 2000, and 2019, do not have southward spread of the precipitation distribution. These low pressure systems, when present during the period of extreme rainfall, remotely supply a copious amount of moisture to the systems developing over the west coast inland. The spatial distribution of rainfall for each ERF event over Mumbai is shown in Fig. 4. Quantitative analysis including correlation between the intensity of the depressions with the associated ERF over Mumbai shows a positive correlation of 0.16. Therefore, we may consider the BoB depressions moving toward the west coast can have contribution toward the ERF events occurring over Mumbai.
Rainfall (color shading) of each ERF day considered, with the tracks of depression from the Bay of Bengal and land where present. The insets show the rainfall over Mumbai for each respective case. The arrow provides the direction of movement of the low pressure system.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
2) Sea surface temperature
Analysis of the synoptic environment during the ERF events shows a consistent warming in the SST along with a strong gradient in the proximity of the Mumbai coast. Each case shows a localized higher SST zone along the same latitude as Mumbai, about 100 km offshore. The SST pattern obtained from averaging the 15 cases is shown in Fig. 5a. Interestingly, this localized region of high SST gradient appears to be present about 72 h before the event and erodes slowly after the event. This can be a good indicator of the model setup required for simulating such an event in terms of the initial conditions. The presence of the local SST regime can also be an indicator of the ERF forecast. The SST pattern shows a west-to-east and south-to-north increasing gradient toward Mumbai concentrated off the coast. This relatively small locale of warmer SST along Mumbai appears to be contributing to the ERF events. The analysis also shows that the maximum variability is due to the zonal temperature gradient present off the coast. Once again, this feature associated with the localized SST gradient is absent for the dry days of the same years relative to the ERF days shown in Fig. 5b. A strong southward gradient is observed for the dry days. The SST anomaly averaged over all cases of ERF days and dry days and shown in Figs. 5c and 5d. The composite SST of ERF and dry days from OISST is presented in Fig. 6. From both the sources of SST, all ERF days show warmer SST anomaly near a small region in the AS at the same latitude as Mumbai. However, a warmer anomaly for dry days is absent, which shows a clear indicator for consideration. In the analysis of the record-breaking 2005 Mumbai heavy rain event, Kumar et al. (2008) also identified an offshore high SST filament that had a similar setup as shown in Fig. 5a. A 99% significance of the SST anomalies is observed over the warmer SST region shown in Figs. 5c and 5d. Positive correlation of SST during wet days with the ERF over Mumbai is found, with a value 0.34. Interestingly, the SST of dry days are negatively correlated with the ERF over Mumbai. Thus, the surface thermal gradients help to create a local convergence zone with moisture convergence greater than 0.45 g kg−1 s−1 (shown in Fig. 9a) that can block the moisture advection toward the west coast. This can be supported by local high intensity updrafts near Mumbai presented for each individual case in Fig. 7. Strong negative values with magnitude 2.5 cm s−1 for vertical velocity is present near Mumbai 24 h prior to the event occurred. The convection is highly concentrated near the warmer SST zone. This local convergence zone offshore, the Western Ghats and the urban region along the coast help create a blocking pattern that allows the moisture and convection to build up and eventually precipitate over a relatively small region.
Composite SST for (a) extreme rainfall days and (b) dry days,, and daily SST anomaly taking 30 years of data for (c) extreme rainfall days and (d) dry days. A significance level of 99% for SST anomalies for both extreme rainfall days and dry days is shown with stippling in (c) and (d), respectively.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
As in Fig. 5, but with OISST data without significant level.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
Vertical velocity 24 h prior to the event for each ERF case, with negative values showing updrafts. Two 2017 plots are shown for the (bottom left) August and (bottom center) September cases, respectively.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
b. Additional synoptic and local conducive environments
1) Vorticity
Low-level vorticity for each case along with the geopotential height at 850 mb is represented in Fig. 8. It shows there is highly concentrated positive vorticity present over the Mumbai region. These small-scale cyclonic vortices are often embedded in an offshore trough near the surface, causing wind shear and strengthening the monsoonal rainfall (Rao 1976). Such a setup is persistent for several days before the ERF, driving the upper midlevel (700–500 hPa) winds to height and bringing intense precipitation over the coastal region (Mukherjee et al. 1978). The average correlation between the vorticity with the rainfall over Mumbai is calculated to be 0.38. The geopotential height is another major indicator of heavy rainfall events. These synoptic atmospheric patterns are strongly connected to dynamically induced heavy rainfall events (Tymvios et al. 2010). The 1981 and 2007 cases show the presence of low pressure over Mumbai region. However, for the rest of the cases, a trough-like low formed a little north of Mumbai. For cases 1990, 1991, 1993, 1997, and 2000, the low pressure is toward east of Mumbai over central India. This pattern of geopotential lines impacts convection over the region and causes rainfall south of the trough. Thus, with the presence of such synoptic patterns, Mumbai becomes susceptible to ERF events.
Similar to Fig. 2, but for low-level vorticity (color shading) and 850-hPa geopotential height (contours; gpm).
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
2) Moisture source and transport
Composite mean of vertically integrated moisture convergence (color shading) from 1000 to 500 hPa with horizontal wind at 850 hPa (vectors) for (a) extreme rainfall days and (b) dry days. Also shown is moisture transport for (c) extreme rainfall days and (d) dry days over Mumbai. For (a) and (b), the vector legend is 5 m s−1; for (c) and (d), the vector legend is 500 kg m−1 s−1.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
3) Frontogenesis and temperature advection
(a) Composite temperature advection (color shades) and geostrophic wind vectors. Geostrophic wind direction change is represented inside the outlined box. (b) Composite Q vectors represented as arrows, with frontogenesis (color shades); Q vector convergence over Mumbai and high positive frontogenesis value is highlighted inside the outlined box. The location of Mumbai is represented with a triangle mark.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
4) Vertical distribution of wind circulation
Intense local moisture convergence near Mumbai may be a result of Western Ghat orography. The Western Ghats have an average height of 1200 m, which can substantially impact rainfall on the hill’s leeward side. Therefore, the zonal and meridional wind patterns are analyzed during the ERF days and dry days, as shown in Fig. 11. The location for Mumbai is shown as a dashed black line in the figure. The zonal and meridional winds are shown as vectors (vertical velocity is magnified by an order of 10). Lower-level meridional (shaded; Fig. 11a) with vectors of zonal wind from the northern part shows a strong veering force converging over Mumbai. Also, the meridional wind vectors with midlevel zonal winds (shaded, Fig. 11c) converge over Mumbai. The convergence with course change of the zonal and meridional vertical winds is visible over Mumbai due to orographic interaction (Rajesh et al. 2016). This is a strong indication of the inflow of intense moist westerlies converging over Mumbai. These atmospheric features are absent on dry days shown in Figs. 11b and 11d. These support the localized effect due to enhanced buoyancy through orographic lifting, setting the conducive environment for ERF events to occur.
Variation of zonal wind (color shading) and meridional wind (vectors) with latitude–height and constant longitude for (a) extreme rainfall days, (b) dry days; also shown is the variation of meridional wind (color shading) and zonal wind (vectors) with longitude–height and constant latitude for (c) extreme rainfall days and (d) dry days.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
The above discussion shows the climatology of the antecedent settings for the ERF events over Mumbai in the last 30 years with particular cases. MTCs, offshore troughs, and the anomalous SST gradient are evident for almost all of the ERF days. The occurrence of moisture convergence over the Mumbai region is equally important and present for all the ERF events. The additional meteorological features present 6 h before the ERF events are moisture transport, vertical velocity at 500 hPa temperature advection, and total column integrated precipitable water. The threshold values of these meteorological precursors over the Mumbai region at the beginning of the ERF events have been calculated considering all the 15 cases and are provided in Table 3. It shows at least 333 kg m−1 s−1 moisture transport along with temperature advection of 2.33 K h−1over an SST of 300.7 K is sufficient to bring about the ERF events over Mumbai. Vertical velocity (w) with the value of 0.024 m s−1 (positive value shows updrafts) and the accumulation of total precipitable water to an amount of ∼60 mm over Mumbai set the thresholds for ERF to happen. The contribution of the abovementioned environmental conditions is calculated from regression analysis of multivariate for the respective parameters for each case. It shows the maximum contribution comes from offshore trough followed by MTC and then BoB depression. In addition to this, orographic lifting also plays a vital role. The last but the most significant contribution for arresting a large amount of moisture over Mumbai in bringing about anomalous events is the increasing SST gradient off the coast at the same latitude as Mumbai. The occurrence of the environmental conditions responsible for each of the ERF events are tabulated in Table 4. It shows at least two of the environmental setups are present for the ERF events over Mumbai.
Threshold values of the precursor parameters.
Presence of environmental conditions for an individual extreme day event.
4. Summary
A comprehensive analysis of the environmental conditions responsible for extreme rain episodes that occur over the coastal city of Mumbai is presented in the study. A total of 15 cases of ERF days from 1981 to 2019, have been identified and considered in the analysis. In addition, diagnostics of various meteorological parameters that set the stage for the heavy rain hazard over Mumbai is undertaken.
The study shows that the ERF events over Mumbai occur due to the concurrent existence of at least two of the rain bearing systems; MTC circulation over central India, a strong offshore trough and BoB depression moving toward the Gujrat coast. The highly anomalous SST and an increasing SST gradient toward the coast along Mumbai concentrated over a small region set up a precursor that advects warm air with moisture from the AS toward the Mumbai coast. A large amount of moisture convergence near Mumbai with the presence of the Western Ghats orography sets another precursor condition to the ERF events allowing moist advected air mass to lift, condense, and rain in the leeward side. Additionally, the moisture source is enriched with the moisture transport along with a prominent low-level westerly jet from the latitudinal extension of 10°–15°N in the presence of midlevel cyclonic circulation. This meteorological feature is responsible for supplying abundant moisture remotely over the local region. Therefore, the latitude of the meteorological precursors occurring might play a pivotal role in setting up the precursors for catastrophic events. The graphical representation of the meteorological conditions set up in the climatological context is demonstrated in Fig. 12. The processes can be well understood from the flowchart presenting the precursors and their interactions in Fig. 13. The environmental conditions are found to exist with at least 48 h of lead time, and therefore, with close verification of these meteorological conditions can be helpful in predicting these hazardous events. Because each ERF event represented here has some distinguishable features, the prediction of these kinds of weather extremes becomes challenging. With the limitation of the operational model forecast to capture these extreme events in advance, additional verified meteorological setups such as those presented in this study can be considered. If the environment shows conducive signs as discussed in the present study, between the latitudinal extents of 15°–20°N, a warning may be announced over the city.
Schematic representation of understanding the meteorological features from synoptic to local scales that are responsible for extreme rainfall over Mumbai.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
Flowchart showing different environmental conditions and their interactions to bring about extreme rainfall events over Mumbai. The dashed border shows primary rain-bearing systems that contribute to ERF events. The solid-outlined boxes show various atmospheric processes that cause ERF.
Citation: Journal of Applied Meteorology and Climatology 62, 2; 10.1175/JAMC-D-21-0223.1
Acknowledgments.
This work is partly funded by the Center for the Development of Computing Applications (CDAC), Ministry of Electronics and Information Technology, GoI (CORP: DG:3170) and Indo-U.S. Science and Technology Forum (IUSSTF) New Delhi (IUSSTF/JC/012/2012-2014-15). The authors acknowledge the ECMWF for making the data freely available in the public domain. Author S. Mohanty acknowledges the DST-INSPIRE (IF150814). Author Niyogi acknowledges the William Stamps Farish Chair through the Jackson School of Geosciences at University of Texas and funding from the NASA Interdisciplinary Sciences (IDS) Program (NNH19ZDA001N-IDS and 80NSSC20K1268), NASA CyGNSS 80NSSC21K1008, and NSF AGS 1902642. Niyogi conceived the problem of the study. Authors S. Mohanty and Swain carried out data acquisition, analysis, and plots. Author S. Mohanty prepared the initial draft with input from authors Niyogi, Nadimpalli, and Swain. Nadimpalli helped with improving visualization. Nadimpalli and author Osuri helped in analysis and provided scientific input. All authors, including U. C. Mohanty and Patel, reviewed the paper and helped to improve readability. Niyogi and U. C. Mohanty provided the funding for the study. There are no conflicts of interest.
Data availability statement.
The data used in this study are available from the ECMWF ERA5 data repository.
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