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Numerical simulations of the 26 July 2005 Extreme Heavy Rainfall Event over Mumbai using the Weather Research and Forecast (WRF) model.

1. Introduction

Mumbai City, located on the west coast of India (72.8[degrees]E, 19.1[degrees]N), has an area extent of 437.71 [km.sup.2] and is a habitat for 16 million populations. The city, with an average elevation in the range of 10-15 m, is vulnerable to flooding during the occurrence of heavy precipitation. Due to its location, on the westward side of the western ghats of the Indian west coast, Mumbai receives an average annual precipitation of 245 cm and heavy precipitation occurrences are not uncommon. On 26 July 2005 Santa Cruz in north-central Mumbai recorded an unprecedented 94.4 cm of rainfall. Another nearby weather station at Vihar lake was reported to have received as high a precipitation as 104.5 cm. But, interestingly, Colaba in south Mumbai received merely 7.3 cm. Rainfall (rounded-off to the nearest cm) recorded in different areas of Mumbai over the 24 h period is: Santa Cruz: 94 cm, Bhandup: 81 cm, Dharavi: 49 cm, Vihar lake: 104 cm, Malabar Hill: 7 cm and Colaba: 7 cm (Figure 1) (Lal et al., 2006). Life in Mumbai was totally disrupted on 26 July due to torrential rains. This extraordinary rainfall event was localized over a region 20-30 km. The heavy precipitation on July 26 is a historical record for Mumbai as the previous highest was 57.5 cm for Santa Cruz on 5 July 1974. This unprecedented precipitation produced widespread, massive flooding in and around Mumbai City that was responsible for the deaths of over 1800 people and estimated economic losses in terms of business and commerce were about 5000 crores in Indian rupees (1billion US Dollars). These Extreme Heavy Rainfall Event (EHRE) are different from the heavy precipitation associated with tropical cyclone systems. According to India Meteorological Department (IMD), HPE and EHRE are noted to occur when the precipitation during the preceding 24 h exceeds 12 cm and 20 cm respectively. Normally these EHRE are due to the occurrence of the precipitation within the duration of a few hours.

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Over the Indian subcontinent, HPE are generally known to occur over the west coast of India and northeast parts of India (Assam, Meghalaya and Mizoram) due to orographic features. However, heavy precipitation occurrences are also noted over isolated locations during the southwest monsoon season (Kumar et al., 2008; Deb et al., 2008). The HPE along the west coast and northeast India are known to be associated with mesoscale convective systems with a life cycle of a few hours to one day which give rise to heavy or extreme heavy precipitation over isolated locations (Routray et al., 2005; Hatwar et al., 2005). Mumbai, influenced by the Western Ghats mountains that run parallel to the Indian coast, normally receives heavy rainfall during the summer monsoon; however, several features make the 26 July 2005 event unique. First, the rainfall amount of 944 mm is thus far a record amount for a single day rain event for a mega city (population over 10 million) such as Mumbai . Second, it exceeds some of the heaviest single day rainfall amounts over the Western Ghats region and Mumbai (Santacruz) such as 375 mm on 5 July 1975, 318 mm on 23 September 1981, 399 mm on 10 June 1991 and 346 mm on 23 August 1997 (Jenamani et al., 2006). Third, the rainfall was highly northern Mumbai with no comparable amounts occurring in the surrounding region.

Many attempts have been made to assess and evaluate the performance of numerical weather predictions from model configurations for the region because on the basis of flood forecasting, even rainfall forecasting as well as safety evaluation model for Mumbai, the early warning could be avoiding disaster. During the last two decades, weather forecasting all over the world has greatly benefitted from the guidance provided by Numerical Weather Prediction (NWP). Significant improvement in accuracy and reliability of NWP products has been driven by advances in numerical techniques, explosive growth in computer power and by the phenomenal increase in satellite-based soundings. The prediction of these systems is subject to the limitations of synoptic forecasting methods, which only indicate probable occurrence of heavy precipitation but not the quantity. Although numerical models provide quantitative prediction of precipitation, they are subject to the limitations of initial data, model dynamics and physics which can lead to uncertainties model output. Uncertainties are "data uncertainties", "modeling uncertainties", "completeness uncertainties." Data uncertainties arise from the quality or appropriateness of the data used as inputs to models. Modeling uncertainties arise from an incomplete understanding of the modeled phenomena, or from approximations that are used in formal representation of the processes. Completeness uncertainties refer to all omissions due to lack of knowledge. They are, in principle, non-quantifiable and irreducible. The prediction of the mesoscale systems requires the use of high resolution atmospheric mesoscale models and observations with a mesoscale network. Some studies of the numerical prediction of EHRE over India using high resolution mesoscale models show the predictability of events with precipitation less than 20 cm/day (Rao and Prasad, 2005; Routray et al., 2005; Hatwar et al., 2005).

A number of modeling studies have been recently performed for the 26 July 2005 Mumbai heavy rain case (Bohra et al., 2006; Sikka and Rao, 2008; Kumar et al., 2008; Vaid and Mehta, 2009). However, the simulation of heavy rains over Mumbai is highly sensitive to the model resolution (grid size), as the amount and location of the rainfall is modulated by land surface feedbacks which affected the formation and intensity of rain producing convection cells. The National Centre for Medium Range Weather Forecasting (NCMRWF) high resolution global model (T170L28) could predict 8 cm over south of Mumbai and that the high resolution Eta and MM5 models simulated 4 cm and 2 cm respectively Bohra et al. (2006). United Kingdom Meteorological Office (UKMO) model with 20-24 cm near Mumbai and 16-20 cm, 12-16 cm by Japan Meteorological Association (JMA) and National Centers for Environmental Prediction (NCEP) global models respectively (Bohra et al. (2006). Vaidya and Kulkarni (2007) simulated the EHRE using Advanced Regional Prediction System (ARPS) model with 40 km resolution and indicated that the model with the use of larger domain and NCEP 1 degree data could give the best prediction of 35 cm precipitation to the east of Mumbai. Shyamala and Bhadram (2006) examined the analyses of synoptic, thermodynamic, radar and satellite data associated with the Mumbai EHRE and suggested that the interaction between the low pressure system over central India and the active southwest monsoon flow from the Arabian Sea could be responsible for the MCS that produced the observed heavy precipitation. The performance analysis of different dynamical models in predicting the high impact events was carried out by Sikka and Rao (2008) and based on their study they concluded that operational models were unable to simulate the magnitude, location and extent of this unprecedented heavy precipitation event over Santa Cruz (Mumbai) in real time attributing the reasons to the uncertainties in numerical weather prediction arising due to inadequate initial and boundary conditions and the model structure. Special emphasizes has been given to the need to configure and test the mesoscale models for application to specific atmospheric phenomena [Sikka and Rao (2008)]. It is essential to examine the short range predictability of an EHRE, for example with the predictability of the occurrence of the precipitation greater than 30 to 40 cm in a day ahead of at least 12-24 h, which will be useful for the public and the administrators to effectively plan mitigation measures. In our case we used WRF version released on 31 July 2009 (a new state of art) model and got simulated localized precipitation at Mumbai more than 55cm (best from previous studies).

Though a few reported studies are available at the moment, in view of their deficiencies in the simulation of the event, the present study is an attempt to assess the predictability of the intensity and location of this event using mesoscale models and to understand the dynamic and thermodynamic mesoscale characteristics that lead to the reported unusual EHRE within a short duration of a few hours and over a localized region of a few kilometers radius. The details of the model are given in Section 3. Many different numerical experiments were performed to study the model capability to predict the heavy precipitation event. Numerical experiments were designed with one way nesting and two way nesting with three domains to study the possible boundary interactions in forecast of the event. Model diagnostics were performed and an attempt is made to explain the occurrence of event by studying the characteristics of the MCS which contributed for this event. Moreover we attempted to identify and understand the various mesoscale to synoptic scale system and their interaction for the formation of convective cells which lead to EHRE.

Section 2 describes observed synoptic conditions leading up to the Mumbai EHRE on 26 July 2005, Section 3 describes the WRF model experiments we conducted to simulate and understand this EHRE, Section 4 provides model results, and Section 5 provides a summary of the present study.

2. Synoptic conditions and mesoscale features

In this section we attempted to present synoptic condition prevailing prior and during the formation of the event. Apart from this, the mesoscale characteristics favorable during the event have also been presented. A MAJOR meteorological puzzle is what kind of atmospheric system it was that off-loaded an unprecedented amount of rain-nearly a meter of water column-over the city of Mumbai in about 24 hours beginning 8-30 a.m. on July 26. The meteorological station at Santacruz in North Mumbai recorded 94.4 cm of rainfall, the highest ever in the history of the city, of which 88.5 cm (nearly 94 per cent) was received in 12 hours from 11-30 a.m. In fact, the first four hours itself saw 13 to 15 cm/hr of rain. During the period, monsoon features all over India was active and there was revival of monsoon from a break/weak monsoon phase during 19-22 July. A well marked low pressure area was present over northwest Bay of Bengal off West Bengal--Orissa coast on 24th and 25th July 2005,which moved over to northern parts of Orissa and adjoining Jharkhand and Chattisgarh on 26th July with the associated cyclonic circulation extending up to 9.5 km above sea level and tilting southwestwards with height. There was strong cross-equatorial flow. As the system moved westward, the low-level jet gained strength and strong westerly winds lashed the north Konkan and Goa coasts. A western disturbance existing as an upper air circulation up to mid-tropospheric levels was over north Pakistan and adjoining Jammu and Kashmir during 23-25 July moved away east northeastwards on 26th July. The rainfall band moved north and large parts of Maharashtra started receiving heavy rainfall. Mahabaleshwar, Kolhapur and Pune received 43, 17 and 8 cm of rainfall respectively, on 26 July. Subsequently, the rainfall belt moved further north towards Gujarat, but in its wake it had devastated Mumbai and many other parts of Maharashtra. The monsoon trough at sea level passed through Rajasthan, Haryana, north Madhya Pradesh, Chattishgarh, northwest Bay and to north Andaman Sea during 24th to 26th July. An off-shore trough at sea level extended from Maharashtra to Kerala coast was active during these days. In association with the movement of the low pressure system, the precipitation along the west coast increased from south to north during 23-25 July.

On 26 July 2005, IMD's the cyclone detection radar at Colaba reported clouds with heights of 5-6 km around Mumbai at 03 UTC and clouds extending up to 15 km covering the Mumbai City area at 08 UTC. The cloud height decreased to 9-10 km between 12 to 18 UTC and to 5-8 km between 21UTC of 26 July and 03 UTC of 27 July. The maximum recorded wind speed at Santa Cruz was 78 km/h at 11 UTC with a sustained wind speed of 50 km/h and the wind direction was predominately from the northwest direction. Above synoptic features speak about the overall strong monsoon conditions and due to this heavy rainfall was expected (and predicted) over Mumbai, but not the intensity and the localized nature (Figure 2). An attempt has also been carried out with available sources of data to analysis mesoscale characteristics at Mumbai (centered at 72.8[degrees]E, 19.1[degrees]N) favorable for the formation of the event during 26th July 2005. Here we used Finite Global Analysis (FNL) and ERA 40 6hr. available data for the analysis. Figure 3 shows wind speed (shaded) and wind vector at lat 19.1N w. r. to vertical level using FNL data. Strong westerly winds at lower level and easterlies at upper level are seen with downpour of winds from 200mb level upto surface at Mumbai longitude centered at 72.8[degrees]E. Strong easterlies at lower level indicate the moisture flow from Arabian sea during 00UTC of 26 July 2005. Sudden increase in the potential vorticity at surface level during the event was also observed and can be seen in Figure 4. Figure 4 shows the potential vorticity at surface level during 18UTC 25Jul2005 and 00UTC 26Jul2005. A significant increase in potential vorticity from 18UTC 25Jul2005 to 00UTC 26Jul2005 is clearly evident. Potential vorticity is a quantity which is proportional to the dot product of vorticity and stratification that, following a parcel of air or water, can only be changed by diabatic or frictional processes. It indicates the generation of vorticity in cyclogenesis (the birth and development of a cyclone). Hence present case we may say the tendency of sudden formation of system responsible for the EHRE. Total column water using ERA 6hr. data has been plotted and given in Figure 5 and it shows heavy amount of total water column in the atmosphere during the period 00UTC 26Jul2005 to 06UTC 26Jul2005 ERA 40 daily data which is consistent with results of Relative Humidity in % at Mumbai (Lat 19.1N) using FNL data (Figure 6). Sudden increase in total water column at 00UC 26Jul 2005 and 06UTC 26 Jul can be clearly evident from figure 5. Figure 6 shows Relative Humidity in % at Mumbai (Lat 19.1N) w. r. to vertical level using FNL data. Relative humidity (describe the amount of water vapor that exists in a gaseous mixture of air and water vapor) more than 90% can be clearly observed over the Mumbai longitude from 500 mb level to 200mb level during 00UTC 26Jul 2005. Sudden increase in potential vorticity during 00UTC 26Jul 2005 support the lift the moist flow Arabian Sea to make increase in water column in the atmosphere required for heavy rainfall event and this has been investigated more in detail using model study. For more detailed study we simulated the event near to observation using recent WRF model and carried out diagnostic analysis of the model to characterize MCS during the event.

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3. WRF Model Experiments

The Weather Research and Forecast model (WRF) is the next generation forecast model and data assimilation system that has advance both the understanding and prediction of weather. It has been designed to support operational forecasting and atmospheric research needs. Moreover, it is suitable for scales ranging from several 100 meters to thousands of kilometers. The WRF model is a fully compressible, nonhydrostatic model. The grid staggering is the Arakawa Cgrid. The model uses higher order numerics. These numerics include the RungeKutta 2nd and 3rd order time integration schemes, and 2nd to 6th order advection schemes in both horizontal and vertical directions. The dynamics solver conserves scalar variables. The WRF model code contains an initialization programs (metgrid.exe, ungrib.exe, geogrid.exe, real.exe, ndown.exe) and a numerical integration program (wrf.exe). The equation set for ARW is fully compressible, Eulerian and nonhydrostatic with a run-time hydrostatic option. It is conservative for scalar variables. The model uses terrain-following, hydrostatic-pressure vertical coordinate with the top of the model being a constant pressure surface. The model supports both idealized and real-data applications with various lateral boundary condition options. The model also supports one-way, two-way and moving nest options. It runs on single-processor, shared- and distributed-memory computers. WRF Model (a new state of art) has potential for disaster monitoring and assessment, so in the present study it is adopted to simulate EHRE over Mumbai, India on 26 July 2005. Flow chat for WRF model is given in figure 7.

WRF ARW modeling system consists of three main components. First is the preprocessing system and its function renovate the input data to the model grid acceptable form. Second component which is the main component of the WRF model system which does all computation based on the physics options used. Third component is the post processing system which converts the model output into the required format. The WRF model version which we used in the present study is WRFV3.1.1 Model, released on 31 July 2009. Physics option and schemes used in the model are given below in the table
Model Type       Fully compressible, Euler non-hydrostatic

Domain           Mother Domain: 53E-96E; 5S:43N
Integration      Nested Domain: 63E-83E;7N-30N, 69E-78E;11N-23N

Horizontal       Mother Domain 45km
Resolution       Nested Domain 15km, 5km

Time step        Mother Domain: 270 Sec
                 Nested Domain: 90 Sec, 30sec

Microphysics     WSM 6-class graupel

LW Radiation     RRTM Scheme

SW Radiation     Dudhia Scheme

PBL              YSU Scheme

Surface scheme   Monin-Obukhov similarity theory

CU Physics       Grell-Devenyi (GD) ensemble, Kain Fritsch (KF)
                 schemes using 1 and 2 way nesting technique


In the present study, model is forced with initial and boundary condition form NCEP Final global analysis (FNL)and model integrated 48hr with initial and boundary condition started from 25July 0000UTC. Forcing variables are:
Air Temperature       Cloud Amount/Frequency
Geopotential Height   Humidity
Land Cover            Maximum/Minimum Temperature

Precipitable Water    Sea Surface Temperature
Soil Moisture/Water   Surface Air Temperature
  Content
Tropospheric Ozone    Upper Level Winds
Wind Shear

Air Temperature       Cloud Liquid Water/Ice
Geopotential Height   Hydrostatic Pressure
Land Cover            Planetary Boundary
                      Layer Height
Precipitable Water    Skin Temperature
Soil Moisture/Water   Surface Pressure
  Content
Tropospheric Ozone    Vertical Wind Motion
Wind Shear

Air Temperature       Convection
Geopotential Height   Ice Extent
Land Cover            Potential Temperature

Precipitable Water    Snow Water Equivalent
Soil Moisture/Water   Surface Winds
  Content
Tropospheric Ozone    Vorticity
Wind Shear


We carried out number of experiment with the latest released version of WRF ARW model using one way nesting and two way nesting schemes with three domains (Figure 8). The implementation and proper use of grid nesting requires attention to inter-grid communication, which can be split into two different problems. The first part is communication from the coarse grid to the nested grid, typically through the specification of the boundary conditions of the nested grid. The conditions at the nested grid boundary must satisfy the radiation condition that outgoing disturbances should leave the nested grid without causing reflections back into the domain, but also allow disturbances on the coarse grid to propagate onto the nested grid without distortion. Several such boundary conditions are reviewed in Zhang et al. (1986) and Staniforth (1997). The second part of the grid communication problem is that from the nested to the coarse grid, also referred to as coarse-grid updating. Many mesoscale models give the choice of either one-way (parasitic) nesting or two-way (interactive) nesting. One-way nesting performs no nested-to-coarse grid communication; the solution on the coarse grid is simply independent of that on the nested grid. On the other hand, in two-way nesting the solution on the coarse grid is continually replaced (or \updated") by that on the nested grid wherever the two grids coincide. Details of the model experiments are given below

(1) One way nesting with three domain (information is communicated only from successive outer to inner grid)

(a) First two domain no cu physics and third domain GD scheme used.

(b) First two domain no cu physics and third domain KF scheme used.

(c) All domain GD scheme.

(d) All domain KF scheme.

(2) Two way nesting with three domain (bi-directional information exchange among all three grids)

(a) First two domain no cu physics and third domain GD scheme used.

(b) First two domain no cu physics and third domain KF scheme used.

(c) All domain GD scheme.

(d) All domain KF scheme.

We explore that out of all the above cases, one way nesting case 1(a) gave best result near to approximation w. r to observation. [It is found that one-way nesting can produce significantly more spurious reflection than two-way nesting in the present case. The increased reflection in the one-way case is due to the difference in the phase speeds of the numerical solutions on the coarse and fine meshes, which can lead to accumulating phase differences between those solutions at the nested-grid boundary.] The detailed description is given in section 4. Figure 9 shows the (a) TRMM 3B42(V6) 24 hrs. accumulated Rainfall (mm) for 26th Jul, (b) accumulated precipitation (mm) for past 24hr. from 00UTC 26 July 2005 for Domain 3 (grid resolution 5km, case 1(a)) and (c) IMD rainfall on 26 Jul 2005. It is encouraging to note that over Mumbai the WRF-simulated, accumulated rainfall on July 26th agrees well with that measured by the TRMM and India Meteorological Department (IMD). Model simulated rainfall is found to be 55 cm (Figure 9b). Note that the model simulation in Figure 9b has a much higher resolution than the TRMM rainfall shown in Figure 9a. Therefore, a more detailed structure of rainfall is visible in the model simulation, particularly over the Western Ghats. Since the model simulated the extreme heavy precipitation isolated over Mumbai City with a maximum of 55 cm, within the limitations of the model resolution, and the location coinciding with the observations, the model derived dynamical and thermodynamic fields were analyzed to understand the characteristics of the MCS responsible for the EHRE and same has been presented in section 4 (Model diagnostics).

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4. Results of the WRF Simulations

Rainfall is an important parameter in many operational and research activities, ranging from weather forecasting to climate research. WRF simulated rainfall is observed to be consistent show fairly good agreement with TRMM. Simulation of Rainfall pattern during EHRE at Mumbai gives insights into the dynamics and thermodynamics of the underlying processes. Since the model simulated the extreme heavy precipitation isolated over Mumbai City with a maximum of 55 cm over the localized domain coinciding with the observations. We carried out detailed study of model derived fields to explore the mesocale characters and their possible interaction with synoptic scale features during the event. The model derived dynamical and thermodynamic fields were analyzed to understand the characteristics of the convective system which was responsible for the EHRE. Upper level atmosphere behavior is studied carefully as it is crucial in understanding its system leads to EHRE. The upper level flow and dynamics and thermodynamics can give key insights development of the system and how long it might have persisted.

Figure 10 shows the model derived relative humidity (RH), (a) RH at Mumbai latitude longitude (19.1N, 72.8E) w. r. to vertical level on 00UTC 26Jul 2005(b) RH at Mumbai (Lat fixed) w. r. to vertical levels on 00UTC 26Jul 2005 (c) time series (from 00UTC25Jul 2005 to 00UTC 27Jul 2005) of RH on Mumbai latitude longitude in percentage at 500mb level. Over Mumbai model predicts more than 90% RH above the vertical level of 500mb (typically is at 18,000 feet or ~5-6 kilometers). Since examining all heights of the atmosphere at any given time is not feasible, it is logical to choose a particular height that best represents the atmosphere at any given time. A higher than normal height pattern at the 500-mb level typically represents regions at the surface in which higher pressure and warmer temperatures tend to occur. Likewise, a lower than normal height pattern at 500-mb level typically represents regions at the surface in which lower pressure and cooler temperatures tend to occur. Strong values of RH are observed over the 500 mb level. The time series of RH over Mumbai at 500mb level clearly shows the time at which RH was prominent. Interestingly RH values were seen to be sudden rise during 00UTC 26Jul 2006 to 18UTC 26Jul 2005 which shows model predictability of the event in agreement with the formation of system. Model derived Potential temperature (in degrees), temperature, Perturbation Potential Temperature, and Potential Temperature at 2m are analysised and are shown in the figure 11 a) Potential temperature (in degrees) at 500mb, b) temperature at 500mb, c) Perturbation Potential Temperature at 500mb, d) Potential Temperature at 2m. The creditable signature in potential temperature during 00UTC26Jul 2005 were observed which indicates that capability for the formation of sudden system over Mumbai which leads to EHRE. Model derived potential temperature shows sudden increase during 00UTC 26th Jul to 18UTC 26 Jul 2005. We did detailed analysis of model derived winds. Model derived Wind direction in degrees w. r. vertical levels at Mumbai 00UTC26 Jul 2005, Wind direction at 500mb level in degrees 00UTC26 Jul 2005 are shown in Figure 12 a and b respectively. Clear indication in the circulation of winds at 500mb level is notified hence indicator for mesoscale system over Mumbai at 00UTC 26Jul 2005. The horizontal circulation features over Mumbai at 500mb level is seen to be extended one from 70E to 73E (Figure 12b). A detailed study of the vertical distribution of the kinetic energy is given in figure 12c. Kinetic energy reaches a maximum at about the 500-mb level and infact evident from figure 12d that kinetic energy values peak observed at 00UTC 26 Jul 2005. Wind vectors at 500mb levels during 21UTC 25Jul 2005 to 12UTC 26Jul 2005 are shown in Figure 13a. Anticlockwise circulation over Mumbai during the heavy rainfall event is clearly evident in the Model wind vector and it is in agreement with the circulation shown in Figure 13b (NCEP winds (m/s) during 26 July 2005 500mb level). Model shows strong westerly winds at lower level and easterlies at upper level are seen with downpour of winds from 200mb level up to surface at Mumbai lon. centered at 72.8[degrees]E. Strong easterlies at lower level indicate the moisture flow from Arabian Sea during 00UTC of 26July 2005 (Figure 14) and this is in consistent with observation (Figure 3).

The differential model fields, (a) Wind speed w. r. to levels over Mumbai 00UTC at 26JUL2005 (b) z component of wind w. r. to levels at mum., 00UTC 26JUL2005 [C] Z-component of wind at 250mb Minus Z-component of wind at 850mb at Mumbai Latitude on 00UTC of 26 JULY 2005 are shown in Figure 15. In meteorology the vertical wind shear perspective is superior to other meteorological parameters, because it establishes the kind of physical cause and effect link between storm structure and the pre-storm environment that forecasters can readily apply when attempting to assess storm potential on any given day. To the degree that the pre-storm environment is known and that convection is going to occur, a forecaster can simply look at the hodograph and determine to a good approximation whether there is sufficient shear over a sufficient depth to promote supercell development (e.g. 20 ms-1 of wind variation over the lowest 4-6 km above ground level). From figure 15a and 15b, strong vertical levels of winds from surface to upper level has been evident at location centered at 72.8[degrees]E where Mumbai is located. It shows the dominance of strong vertical component of wind. Figure 15c gives the qualitative change in the z component of wind and clears that z component of wind at 250mb level was higher than that 850 mb level, which speaks of shear presented during the time for the formation of EHRE. We speculate that this strong vertical z component of wind cause the cloud burst during the time which leads to heavy rainfall. Figure 16 shows model derived high cloud fraction in % the Mumbai region. On 26 July 2005, IMD, the cyclone detection radar at Colaba reported clouds with heights of 5-6 km around Mumbai at 06 UTC and clouds extending up to 15 km covering the Mumbai City area at 12 UTC. It is encouraging that model derived cloud fraction at Mumbai found to be agrees well with IMD observation. Model produced dynamical structure show veering of wind with height, with westerlies at lower levels turning clockwise with height (Figure 17) to become easterly at 400 hPa level indicating warm air advection triggering the convection and these features agree with the observations (Jenamani et al., 2006). Figure 18 shows potential temperature (in degrees) at Mumbai on 00UTC 26Jul 2005. The model predicted a decrease of Potential temperature from surface to 700 mb level and increase above up to 400 mb during 00 UTC of 25 to 00 UTC of 26 July, indicating that potential instability increased at lower levels due to dry air capping at middle levels that caused suppression of convection during this period and all this gave rise to sudden explosive deep convection with super cell structure introducing a heavy precipitation spell. Results show WRF's feasibility for predicting EHRE-relevant meteorological data (precipitation, air temperature, relative humidity, wind, potential temperature, and cloud fraction).

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5. Summary

The model produced maximum precipitation of 55 cm (predicted rainfall 55cm is best from previous studies) over Mumbai. The simulated location of the maximum precipitation and the precipitation distribution significantly coincided with the observations (TRMM 3B42-V6). Model diagnostics of the wind speed w. r to vertical level, temperature, vorticity shows the mesoscale characteristics of the convective system. The model simulated circulation features indicate the sudden initiation of deep convection and cloud burst with heavy precipitation. The model simulated dynamic and thermodynamic features at 00 UTC of 26 July lead to understand the structure of the MCS that caused the extreme precipitation over Mumbai. At 500 hPa level, north and northeastwind flow towards Mumbai City is depicted clearly moreover cyclonic circulation over the Mumbai is observed. Simulation of this feature is significant, as dry air incursion at this level was crucial for development of a deep convective system. These results show the mesoscale characteristics of the convective system which produced the model simulated heavy precipitation over isolated small areas of the Mumbai City region. The model produced thermodynamic structure show veering of wind with height, with westerlies at lower levels turning clockwise with height to become easterly at 400 hPa level indicating warm air advection and the strength of veering increases from 06 to 21 UTC of 25 July indicating the triggering of convection and these features agree with the observations (Jenamani et al., 2006). The presence of the dry air at middle levels was also observed in the thermodynamic analysis corresponding to 00 UTC of 26 July. This simulation of the thermodynamic features coinciding with observations is significant to understand the development of the convective system that caused the EHRE. The model predicted a decrease of potential temperature from surface to 700 hPa level and increase above up to 400 hPa during 00 UTC of 25 to 00 UTC of 26 July, indicating that potential instability increased at lower levels due to dry air capping at middle levels that caused suppression of convection during this period and all this gave rise to sudden explosive deep convection with super cell structure producing a heavy precipitation spell. From model derived results we can conclude that the highly localized, heavy rain was the result of an interaction of synoptic-scale weather systems with the mesoscale features. High-resolution WRF model analysis captured the formation mesoscale features over Mumbai that appears to have enhanced the conditions for localized, heavy rainfall over Mumbai. Both thermodynamic and dynamical characteristics associated with Mumbai extreme heavy rainfall has been analysised. Based on the analysis, it can be hypothesized that the moisture flow from Arabian Sea at lower levels, dry air incursion at middle levels and strong vertical wind shear along with orographic features supporting vertical lift of low level moist flow could be the causation of the heavy rainfall over Mumbai. It is to be noted that model simulations are always sensitive to the initial conditions, domain size and location, model dynamics, physics and hence research is still continuing to improve the prediction.

6. Acknowledgement

Author thanks Director, ICCSIR, Ahmedabad for kind support and Mr. K. Seshu for technical help.

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B. H. Vaid *

Indian Centre for Climate and Societal Impacts Research (ICCSIR), Ahmedabad, India

* Email: hardeep_vaid@yahoo.co.in
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Author:Vaid, B.H.
Publication:International Journal of Computational and Applied Mathematics
Article Type:Report
Geographic Code:9INDI
Date:May 1, 2010
Words:5936
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