Study of hail storm features in mesoscale convective systems over south east Asia by TRMM precipitation radar and TRMM - microwave imager

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1 Study of hail storm features in mesoscale convective systems over south east Asia by TRMM precipitation radar and TRMM - microwave imager Sanjay Sharma 1, Devajyoti Dutta 1, 1 Department of Physics, Kohima Science College, Jotsoma, Kohima, , India. Sanjay Sharma sanjay_sharma11@hotmail.com (Dated: 02 June 2012) 1. Introduction Hail is a meteorological hazard, which cause significant loss to property. Significant work has been carried out in the past to characterize convective environments with an explicit reference to the hail phenomena (Frisby and Sansom, 1967; Morgan, 1970; Modahl, 1979; Chaudhaury and Mazumdar, 1983; Chowdhury and Banerjee, 1983; Chakravorty and Bhomik, 1993; Tudurı and Ramis 1997; Lo pez et al. 2001; Groenemeijer and van Delden, 2007; Manzato 2012). The tropical region lacks good network of hail detecting device. Conventionally hail storm studies over the region are based on ground reporting of the events by staffers and volunteers. Therefore satellite based detection of hail features is an alternative option. Recently Ceil (2009) has utilized the passive microwave brightness temperature as a proxies for the detection of hail storms.. Motivated by encouraging results of Cecil (2009), a study is carried out over a part of south east Asia to study the hail features in MCSs by using simultaneous observations by TRMM Microwave Imager (TMI) and TRMM- Precipitation Radar (PR) and Lightening Imaging Sensor (LIS). The main objective of the present work is to study the spatial and temporal variability of the occurrence of Mesoscale Convective Systems (MCSs) with hail features over a part of the south east Asia. For this purpose brightness temperatures of 85 (V, H) GHz and 37 (V, H) GHz channels of TMI along with reflectivity measurements from TRMM-PR and lightening flash rate by LIS are utilized. 2. Study Area: The gridded map of the study region is shown in Figure 1. The domain range is E and N. The study region is divided into 24 grids. Each grid is of a size of x The study region has a complex topography, where height of the terrain is changing from mean Sea Level (MSL) to mountains of average height of 5000 meters Figure 1: Topographical map of the study region, 1

2 3. Methodology Hail features during MCSs events are identified by a 85 GHz (V,H) and 37 GHz (V, H) channels of the TMI. For this purpose, Polarization Corrected Temperature (PCT) at 85 GHz (PCT 85 ) and 37 GHz ( PCT 37 ) are utilized. PCT 85 and PCT 37 are an indicator of ice scattering (Spencer et al. 1989, Kummerow 1993). Lower the value of these parameters, stronger is convection. Precipitating systems are considered as MCSs when they are characterized by an area of at least 2000 km 2 bounded by PCT 85 value of 250 K, with a minimum value of PCT 85 in it 225 K (Mohr and Zipser, 1996). For the detection of hail, the threshold values for these two parameters i.e. PCT K and PCT K are considered (Cecil 2009). Corresponds to these two parameters following parameters are also considered to develop new indices for hail features. (i). Echo Top Height (ETH): ETH is a measurement of the vertical extent of the precipitating systems. It is an proxy for rain height. ETH is estimated for three different threshold values namely 20 dbz, 30 dbz and 40 dbz (ii). Near Surface Z (NSZ): The TRMM-PR works at Ku band (14.8 GHz), which is attenuated by rain. For present study attenuation corrected NSZ is utilized. The parameter is proxy for rain intensity (iii). Lightening Flash Rate ( LFR): LFR are observed from LIS optical sensors of TRMM. LFR is represented by No. of lightening flash detected per minute. Further, intensity and occurrence of MCSs are associate with atmospheric convective parameters such as Convective Available Potential Energy (CAPE) and Vertical velocity (ω). The details of these atmospheric convective parameters are as follows (i). CAPE: Atmospheric convective parameter CAPE describe potential buoyancy available to idealised rising air parcels and thus denote the instability of the troposphere and also the strength of the convection. (ii). Vertical Velocity ( ω): It is defined as the rate of change of pressure with time. The vertical velocity is computed by making use of the continuity equation in isobaric coordinate systems. The upward motion (ascent) is a NEGATIVE value, and downward motion (subsidence) is a POSITIVE value 4. Results: At the outset count of MCSs in each grid during is found out along with the average values of Max. ETH 40 dbz, The values of these parameters over each grid is provided in Table I. It is observed that the regions with complex topography (5, 9, 10, 11, 12, 18, 21, 24) are associated with significant count of MCSs ( count > 400), with average values of Max. ETH 40 dbz, is varying in the range of 4-6 km. The western part of the study area ( 7, 13,14,15, 19, 20) consist of plain topography with relatively less no. of MCSs, where average values of Max. ETH 40 dbz is varying in the range of 6-7 km. The characteristics of higher altitude region of Tibetan plateau ( 1, 2, 3, 4) is different compared to these two types of topographic regions. It is associated with small count of MCSs shallow MCSs particularly in terms of ETH 40 dbz., where its value is varying in the range of 2-4 km. Further MCSs with hail features are identified with a criteria of PCT K and PCT K. With this criteria, hail features are mostly detected over a region between N and E. as indicated by the black colour box in Figure 1. This region is of Gangetic West Bengal (India) and Bangladesh. In this domain, total 42 numbers of MCS with hail features are detected by the TRMM. For these detected hail features, seasonal and diurnal variation is shown in figure 2 (a, b) respectively. It is observed that seasonally MCS with hail features occurs only during the pre-monsoon months with the maximum events in the month of May. Diurnally the maximum occurrence is found to be during late evening with a peak during hrs. These results are consistent with the previously reported work on hail storm occurrence (Chaudhary and Mazumdar 1983; Chowdhuiry and Banerjee 1983; Ramamurthy 1983). To understand the seasonal variation of the occurrence of MCSs with hail features, the spatial variation of the climatological mean of CAPE at 12 GMT ( Indian Standard Time: GMT hrs) during pre-monsoon (MAM) and Monsoon (JJA) months are shown in figure 3 (a, b) respectively. It is observed that 2

3 Count Count ERAD THE SEVENTH EUROPEAN CONFERENCE ON RADAR IN METEOROLOGY AND HYDROLOGY Table 1 (Average value of the satellite derived convective parameters for MCSs) Region MCS Count Max.. ETH 40dBZ Months Time (IST) Figure 2 : (a) Seasonal and (b). Diurnal variation of the occurrence of MCSs with hail features over the study regions maximum value of CAPE is observed during monsoon months with the values varying in the range of J/Kg. Then it is followed by pre-monsoon months (MAM) with the values varying in the range from J/Kg. It is evident from Table -1 and the figure that climatologically, the region of relatively large count are associated with shallow MCSs, higher values of CAPE, whereas region of relatively less count are associated with deep MCSs and lower values of CAPE. Spatial variation of the climatological mean value of ω at 12 GMT during pre-monsoon (MAM) and Monsson (JJA) months at 12 GMT, are shown in figure 4 (a, b) respectively. It is observed that over the study regions maximum ω is observed during pre-monsoon months (MAM) with its values varying in the range of to Pa/sec ( upward ω ) and it is followed by the monsoon months ( JJA). It is evident from the Table -1 and the figures that climatologically, the region of large count MCSs are associated with shallow and relatively lower values of upward vertical velocity, whereas region of relatively less count are associated with deep MCSs and higher values of upward ω. It is also observed that climatologically during the pre monsoon months, the region with max. hail features ( red box) is associated with lower values of CAPE and higher values of upward ω. 3

4 Figure 3 Seasonal variation of spatial plots of the climatological mean of CAPE during (a) pre-monsoon (b) monsoon months Figure 4 Seasonal variation of spatial plots of the climatological mean of ω during (a) pre-monsoon and (b) monsoon months The estimated mean (standard deviation) values of PCT 85 and PCT 37, for MCS with hail features are found to be 61.0 (7.0 ) K and (14.0) K respectively. With a view to develop a new indices for detecting the hail features, the mean and standard deviation (std. dev.) values of various parameter are estimated and provided in Table -2. As it is pointed out by Cecil (2009), that PCT 37 is better parameter for the identification of large hail, therefore the Correlation Coefficient (CC) is found out for these parameters with the PCT 37. The CC values are also provided in Table - 2. It is observed that NSZ and ETH 40 dbz are most closely related with PCT 37. The mean (standard deviation ) value of ETH 40 dbz and NSZ are 15 ( 2) km and 55 (2) dbz respectively. It is suggested that together these values may also be considered as a proxies for the detection of hail features in MCSs. 4

5 Table 2 (Mean (Std. dev.) values of the parameters corresponds to PCT 85 < 70K and PCT 37 <180 K) Statistics Max. ETH 20 dbz Max.ETH 30 dbz Max.ETH 40 dbz Max. NSZ Max. LFR /Minute (dbz) Mean Std, dev CC with PCT Summary and conclusion The results of the present work are summarized as follows (i). Climatologically, there is a spatial variability in the no. of count and vertical extent of MCSs over the study region. Within the study region the region of complex topography is associated with large count of shallow MCSs, higher values of CAPE and lower values of upward ω, whereas region of plain topography is associated with relatively less counts of MCSs but with deep systems, lower values of CAPE and higher values of upward ω. (iii). The patterns of seasonal and diurnal occurrence of MCS with hail features as detected by satellite derived parameters are consistent with the previously reported work over the region. (iv). Climatologically, the regions of maximum hail features (during pre monsoon months) are associated with lower values of CAPE and higher values of upward ω. (v). In terms of radar observable parameters, together, ETH 40dBZ and NSZ dbz with a mean (Std. Dev.) value of 15 km (2 km) and 55.0 dbz (2 dbz), are found to be most suitable parameters for detecting the hail features. The present work is still in a developing stage. The process to procure the data of ground reporting of hail is in progress. Further analysis with the reported hail data will enhance the utility and objectivity of the present work. Acknowledgement The financial support from Indian Space Research Organization (ISRO) to carry out the work is thankfully acknowledged. The TRMM data, downloaded from the web site ( of University of Utah, PMM science, is thankfully acknowledged. The downloaded 20 th Century Reanalyzed data products of NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their web site at is thankfully acknowledged. References Chakabarty, K.K., and S.K. Bhowmik, 1993: Study of unusual hailstorm over Bombay, Mausam,44, Chaudhary, A.K., and A.B. Mazumdar, 1983 : Nor westers and the synoptic climatology of hot weather season in northeast India. Vayu Mandal, 13, Chowdhury. A. and A.K. Banerjee, 1983: A study of hailstorms over northeast India. Vayu Mandal,13, Frisby, E.M., and H.W. Sansom, 1967: Hail incidence in the tropics. J.Appl. Meteor.,6, Groenemeijer, P. H., and A. van Delden, 2007: Sounding-derived parameters associated with large hail and tornadoes in the Netherlands. Atmos. Res., 83, Kummerow, C., 1993: On the Eddington approximation for raditative transfer in microwave frequencies, J. Geophys Res. 98, Lopez, L., J.L. Marcos, J.L. Sanchez, A. Castro and R. Fraile, 2001: CAPE values and hail storms on north western Spain, Atmos. Res , Manzato, A., 2012: Hail in north east Italy: Climatology and bivariate analysis with the sounding derived indices, J. Appl. Meteor. Clim., 51, Modahl, A. C., 1979: Synoptic parameters as discriminators between hail fall and less significant convective activity in northeast Colorado. J. Appl. Meteor., 18,

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