A study on raindrop size distribution variability in ...

Author’s Accepted Manuscript A study on raindrop size distribution variability in before and after landfall precipitations of tropical cyclones observed over southern India Jayalakshmi Janapati, Balaji Kumar seela, M. Venkatrami Reddy, K. Krishna Reddy, Pay-Liam Lin, T. Narayana Rao, Chian-Yi Liu www.elsevier.com/locate/jastp

PII: DOI: Reference:

S1364-6826(16)30274-7 http://dx.doi.org/10.1016/j.jastp.2017.04.011 ATP4583

To appear in: Journal of Atmospheric and Solar-Terrestrial Physics Received date: 20 September 2016 Revised date: 23 April 2017 Accepted date: 25 April 2017 Cite this article as: Jayalakshmi Janapati, Balaji Kumar seela, M. Venkatrami Reddy, K. Krishna Reddy, Pay-Liam Lin, T. Narayana Rao and Chian-Yi Liu, A study on raindrop size distribution variability in before and after landfall precipitations of tropical cyclones observed over southern India, Journal of Atmospheric and Solar-Terrestrial Physics, http://dx.doi.org/10.1016/j.jastp.2017.04.011 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

A study on raindrop size distribution variability in before and after landfall precipitations of tropical cyclones observed over southern India

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Jayalakshmi Janapati1 Institute of Atmospheric Science, College of Earth Science, National Central University, Zhongli City-32001, Taiwan. Email: [email protected]

Balaji Kumar seela1, 2 Institute of Atmospheric Science, College of Earth Science, National Central University, Zhongli City-32001, Taiwan. 2 Taiwan International Graduate Program (TIGP), Earth System Science (ESS) Program, Research Center for Environmental Changes, Academia Sinica-115, Taiwan. Email: [email protected]

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M. Venkatrami Reddy3, National Centre for Medium Range Weather Forecasting (NCMRWF), Ministry of Earth Sciences, Government of India, A-50, Sector-62, Noida- 201 309 Email: [email protected] 3

K. Krishna Reddy4 4 Semi-arid zonal Atmospheric Research Centre, Department of Physics, Yogi Vemana University, Kadapa-516 003, Andhra Pradesh, India. Email: [email protected] Pay-Liam Lin1 1

Institute of Atmospheric Science, College of Earth Science, National Central University, Zhongli City-32001, Taiwan. Email: [email protected]

T. Narayana Rao5 5 Clouds and Convective Systems Group, National Atmospheric Research Laboratory, Gadanki517 112, Andhra Pradesh, India. Email: [email protected] 6

Chian-Yi Liu6 Center for Space and Remote Sensing Research, College of Earth Science, National Central University, Zhongli City-32001, Taiwan. Email: [email protected]

*Corresponding Author and address: Prof. K. Krishna Reddy Coordinator, Semi-arid-zonal Atmospheric Research Centre (SARC) Department of Physics, Yogi Vemana University, Vemanapuram, Kadapa – 516003, Andhra Pradesh, India, Ph: +91-8562-225455; Fax: +91-8562-225419 E-mail: [email protected]

Abstract Raindrop size distribution (RSD) characteristics in before landfall (BLF) and after landfall (ALF) of three tropical cyclones (JAL, THANE, and NILAM) induced precipitations are investigated by using a laser-based (PARticleSIze and VELocity - PARSIVEL) disdrometer at two different locations [Kadapa (14.47°N, 78.82°E) and Gadanki (13.5oN, 79.2oE)] in semi-arid region of southern India.

In both BLF and ALF precipitations of these three cyclones,

convective precipitations have higher mass weighted mean diameter (Dm) and lower normalized intercept parameter (log10Nw) values than stratiform precipitations. The radar reflectivity (Z) and rain rate (R) relations (Z=A*Rb) showed distinct variations in BLF and ALF precipitations of three cyclones. BLF precipitation of JAL cyclone has a higher Dm than ALF precipitation. Whereas, for THANE and NILAM cyclones ALF precipitations have higher Dm than BLF. The Dm values of three cyclones (both in BLF and ALF) are smaller than the Dm values of the other (Atlantic and Pacific) oceanic cyclones.

Interaction of different regions (eyewall, inner

rainbands, and outer rainbands) of cyclones with the environment and underlying surface led to RSD variations between BLF and ALF precipitations through different microphysical (collisioncoalescence, breakup, evaporation, and riming) processes. The immediate significance of the present work is that (i) it contributes to our understanding of cyclone RSD in BLF and ALF precipitations, and (ii) it provides the useful information for quantitative estimation of rainfall from Doppler weather radar observations.

Keywords: Tropical cyclones, Raindrop size distribution, Mass-weighted mean diameter (Dm), and Rain rate

1. Introduction Tropical cyclones are one of the most severe natural hazards that cause huge damage, loss of property and human lives once they reach the inland region with torrential rainfall (Rappaport, 2000; Zhang et al., 2009; Mohleji and Pielke, 2014; Fischer et al., 2015). Tropical cyclones originating from the Bay of Bengal (BOB) influence the life and economy of the southeastern part of India (Raghavan and Rajesh, 2003; Rao et al., 2007; Revadekar et al., 2016). Once the cyclone makes landfall with torrential rainfall, its main threat is flooding, which is a function of rain rate as well as total surface rain accumulation (Villarini et al., 2014). This implies that it is 1

essential to monitor the rainfall characteristics associated with tropical cyclones.

Rain

microphysical parameters [rain rate, radar reflectivity, and raindrop size distribution (RSD) etc.,] play a key role in the apprehension of precipitation features of tropical cyclones. Rainfall erosivity and its association with tropical cyclones can be conceived with the aid of RSD information (Nanko et al., 2016). Prediction of cyclone track and its rainfall is necessary to reduce the cyclone vulnerability (Wijesundera et al., 2013; Saha et al., 2015). Knowledge about the RSD is useful in realizing precipitation microphysics (Rosenfeld and Ulbrich, 2003), establishing quantitative precipitation estimation (QPE) algorithms (Boodoo et al., 2015) for radar measurements, and improving microphysical parameterizations in modelling studies (Gilmore et al., 2004b; Cohen and Mc Caul, 2006; Fadnavis et al., 2014; Wainwright et al., 2014; McFarquhar et al., 2015).

The RSD characteristics of hurricane Ginger over the Atlantic Ocean were studied by Merceret (1974) and noticed no differences in RSD between rainbands and the eyewall region. Radar reflectivity – rain rate (Z-R) relations of hurricanes deduced by Jorgensen and Willis (1982) showed no difference between eyewall and outer eyewall regions as well as at or below 3 km from the surface. A later study of Marks et al. (1993) on hurricanes by using airborne radar and disdrometer showed a significant difference in the eyewall and outer rainband Z-R relations (eyewall: Z=253R1.3; outer rainband Z=341R1.25; total Z=311R1.27).

By using aircraft

observations, Houze et al. (1992) noticed a higher concentration of small ice particles aloft the tropical cyclone center (Hallett and Mossop, 1974).

With the aid of ground-based Joss-

Waldvogel disdrometer, Ulbrich and Lee (2002) recorded the RSD differences in prior and during the passage of hurricane Helene (2000) over the inland region. They suggested to adopt different Z-R relations (Z=118R1.48) in deriving rainfall amounts of tropical storms instead of using tropical Z-R relations (Z=250R1.2) or default relations (Z=300R1.4).

By using two-

dimensional video disdrometer, RSD characteristics of tropical storm Jeanne (2004) were analyzed by Maeso et al. (2005). Tokay et al. (2008) noticed more small and midsize drops and few large drops with the maximum diameter seldom exceeding 4 mm. Chang et al. (2009) studied RSD and drop shape relation characteristics of northwest Pacific typhoon systems over Taiwan during their landfall. They found a maritime convective type of RSD in typhoon systems over the ocean. They persuaded that terrain influenced deep convective systems of typhoons 2

resulted with RSD characteristics intermediate to maritime and continental clusters. Chen et al. (2012) studied the microphysical characteristics of Morakot (2009) typhoon by using PARSIVEL disdrometer. They found significant differences in eyewall precipitation to that of the outer rainband precipitation. Kim et al. (2013) analyzed microphysical characteristics of Kompasu typhoon using ground-based wind profiler and disdrometer. They observed a weak bright band in the eyewall region and a strong bright band in the rainband regions of the typhoon. Even they noticed large mass-weighted mean diameter (Dm) in the inner and outer rainbands, and particularly higher in outer rainband than eyewall region. Over Korea, Suh et al. (2016) noticed smaller values of Dm and Nw in typhoon rainfall than other rainfall categories. They observed a lower (higher) Dm (Nw) in typhoon convective rainfall than stratiform and their results are opposite to that of the Chang et al. (2009). Deo and Walsh (2016) observed higher concentration of small drops near the tropical cyclone center and larger drops in the outer regions of the tropical cyclone. Recently, over the southern coast of Korea, Kim and Lee (2017) investigated the rainband characteristics of a hurricane Bolaven and they found different microphysical characteristics between stratiform and mixed stratiform-convective regimes of the rainband. In India, even though an adequate research was carried out on RSD characteristics of different seasons and types of precipitations (Reddy and Kozu, 2003; Reddy et al., 2005; Kozu et al., 2006; Konwar et al., 2006; Narayana Rao et al., 2009; Sharma et al., 2009; Harikumar et al., 2010; Konwar et al., 2012; Chakravarty and Raj, 2013; Jayalakshmi and Reddy, 2014; Konwar et al., 2014; Sarma et al., 2016; Das et al., 2017), few studies on RSD characteristics of cyclones were documented. Radhakrishna and Narayana Rao (2010) studied the seasonal variation of cyclonic and non-cyclonic precipitation, and they found a large number of small and medium drops with the almost absence of big drops. Kumar and Reddy (2013) illustrated the differences in RSD of cyclonic precipitation to that of a northeast monsoon thunderstorm. Kumari et al. (2014) detailed about the RSD differences between two tropical cyclones occurred over southern India. Bhattacharya et al. (2013) established the existence of stratiform features during pre and post-phase of AILA cyclone formed over BOB. Nevertheless, there were no studies on RSD of cyclones in terms of before and after landfall over India. Therefore, in the present work, an attempt has been made to analyze the RSD characteristics of before landfall (BLF) and after landfall (ALF) precipitations of three cyclones formed over BOB. The rest of the paper is

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organized as follows: Section 2 outlines the data and methodology. A brief description of three cyclones is provided in Section 3.

Modelling and observational results of three cyclones

(variability of RSD in stratiform and convective precipitations, their radar reflectivity- rain rate relations, and gamma parameters) are detailed in Section 4. Possible reasons for the variations in RSD of three cyclones are discussed in Section 5 followed by the summary and conclusions in Section 6.

2. Data and methodology 2.1 PARSIVEL disdrometer The PARticleSIze and VELocity (PARSIVEL) disdrometer is a laser based instrument designed to count and measure simultaneously the size and fall speed of precipitation particles. Detailed explanation about the PARSIVEL disdrometer along with the assumptions used to determine the size and velocity of hydrometeors can be found in Löffler-Mang and Joss (2000), Battaglia et al. (2010), Jaffrain and Berne (2011), Friedrich et al. (2013a, 2013b), Tokay et al. (2014), Raupach and Berne (2015) and reference within. The core element of the instrument is an optical sensor that produces a horizontal sheet of light (180 mm long, 30 mm wide, 1 mm high and wavelength of 650 nm with an output power of 3 mW). A decrease in the signal occurs due to the passage of precipitating particles through the light sheet. The amplitude of the signal deviation is a measure of particle size, and the duration of the signal allows an estimate of particle fall velocity. PARSIVEL measures the precipitating particles with diameters ranging from 0.2 to 25 mm and fall velocities from 0.2 to 20 m/s and is sorted into 32 classes. The lowest two size classes are not used because of their low signal-to-noise ratio (Tokay et al., 2013).

The measurement of this instrument is done by assuming hydrometeors as oblate

spheroids with a pre-assumed relationship (Ar=1.075-0.075Deq) between drop axis ratio (Ar defined as the ratio of height to width) and equivalent drop diameter (Deq) from Andsager et al. (1999). Particles with drop diameter (D) < 1 mm are assumed to be spherical (axis ratio = 1). For particles with D > 5 mm, an axis ratio of 1.3 is used. For particles with D between 1 and 5 mm, the assumed axis ratio varies linearly from 1 to 1.3. PARSIVEL has been known to suffer from some instrumental errors in strong wind, marginal, and splashing effect conditions. If particles fall through the edges of the sample area, they appear as small particles that move faster 4

than the empirical fall velocity–diameter relation (known as the marginal effect). The raindrops hit by the PARSIVEL surface will break apart and bounce back into the sampling area (splashing effect). In the present study, the above mentioned instrumental errors are minimized by adopting the quality control procedures of Friedrich et al. (2013a). Further, the status flag check is considered for high-quality measurements as suggested by Raupach and Berene (2015). The raindrop concentration N(Di) (m–3 mm–1) at an instant of time from the PARSIVEL disdrometer counts (Jaffrain and Berne, 2011; Raupach and Berne, 2015) can be obtained from the following equation ( )

∑

( )

Where nij is the number of drops reckoned in the size bin i and velocity bin j, Δt (s) is the sampling time, and ΔDi (mm) is the width of the ith class diameter, Vj (m/s) is the jth class mean (

velocity and Aeff (m2) is the effective sampling area given by

) in

which Di (mm) is the ith bin size drop diameter, L is the length of the PARSIVEL beam (180 mm) and B is the width of the beam (30 mm). From the raindrop concentration N(Di), drop diameter (Di) and terminal fall velocity V (Dj) (Beard, 1976), the radar reflectivity factor Z (mm6 /m3), rain rate R (mm/h), and liquid water content W (g/m3) are derived (Friedrich et al., 2013b) by the following expressions. (

(

∑ ( )

)

)

(

∑ ( )

)

( )

( )

∑ ( )

( )

( )

For the validation of PARSIVEL disdrometer during the rainy periods of three cyclones, hourly accumulated rainfall amounts of PARSIVEL disdrometer are compared with a tipping bucket rain gauge of collocated automatic weather station (AWS).

A scatterplot of the hourly

accumulated rainfall amounts measured from PARSIVEL and the collocated rain gauge for the three cyclones is shown in Fig. 1. A linear fit performed to the scatterplot showed a reasonably good correlation coefficient between these two measurements.

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The nth order moment of the drop size distribution is expressed as ( )

∫

( )

Where n=3 for the 3rd moment, 4 for the 4th moment, and 6 for the 6th moment of the size distribution. The mass-weighted mean diameter (Dm, mm), shape parameter (µ,-) and slope parameter (Λ, mm-1) are obtained (Ulbrich, 1983; Tokay and Short, 1996; Bringi et al., 2003) from the 3rd, 4th, and 6th moments of the size distribution as ( ) The slope parameter Λ (mm-1) is given by (

)

( )

Where µ is the shape parameter (no dimensions) and is given by (

) (

√ ( )

)

( )

Where G is

The normalized intercept parameter, Nw (m-3 mm-1) is defined by Bringi et al. (2003) as (

)

( )

Where ρw (106 g/m3) represents the density of water and W (g/m3) represents the liquid water content for the corresponding size distribution.

One minute RSDs of three cyclones are

classified into stratiform and convective rainfall by adopting the classification scheme proposed by Bringi et al. (2003).

2.2. Tropical cyclone track data The track, intensity, and landfall information of three cyclones (JAL, THANE, and NILAM) occurred over BOB are obtained from the Regional Specialized Meteorological Centre (RSMC), India Meteorological Department (IMD) (http://www.rsmcnewdelhi.imd.gov.in). The 6

best track data provides longitude, latitude, maximum sustained surface wind speed, minimum central pressure, and category type of tropical cyclones. According to RSMC-IMD, the tropical cyclones are categorized into seven types: low pressure area (less than 17 knots), depression (1727 knots), deep depression (28-33 knots), cyclonic storm (34-47 knots), severe cyclonic storm (48-63 knots), very severe cyclonic storm (64-119 knots), and super cyclonic storm (more than or equal to 120 knots). The landfall of a tropical cyclone is defined as the time when the center of the storm first crosses the coastal area. According to RSMC-IMD, JAL cyclone made landfall with deep depression intensity on 7th November 2010 near north Tamil Nadu and south Andhra Pradesh coast (13.3oN and 80.2oE) around 16:00 UTC.

With very severe cyclonic storm

intensity, THANE cyclone crossed the Tamil Nadu coast close to the south of the Cuddalore (11.6o N and 79.7o E) between 01:00 and 02:00 UTC on 30th December 2011. The NILAM cyclone crossed north Tamil Nadu coast near Mahabalipuram, south of Chennai (12.6 oN and 80.2o E) on 31st October 2012 between 10:30 to 11:30 UTC with cyclonic storm intensity.

2.3 Satellite Images Microwave satellite images obtained from the Naval Research Laboratory (NRL) Marine Meteorology Division in Monterey, California (Hawkins et al., 2001) are used to examine the relative position between the disdrometer site and the cyclone center. The NRL website provides imagery from the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSM/I; F-8, -10, -11, -12, -13, -14, and -15) and the Special Sensor Microwave Imager/ Sounder (SSMIS; F-16, -17, and 18) (Hawkins and Velden, 2011). In addition to above imagery, NRL website offers the passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data from the polar-orbiting TRMM satellite (Kummerow et al., 1998), and the Advanced Microwave Sounding Unit humidity sensor (AMSU-B) imagery (Vangasse et al., 1995). The swath width of SSM/I data (1394 km) is larger than the TMI data (759 km) however, the resolution (12.5-50 km) is smaller than the TMI data (5-37 km). The AMSU-B includes 89 GHz channel with a spatial resolution of 16-km at nadir. Further details on the multi-satellite imagery of NRL can be found in Hawkins et al. (2001) and Hawkins and Velden (2011).

2.4 Model description

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In the present study, non-hydrostatic, fully compressible Advanced Research Weather Research Forecast (WRF-ARW) model version 3.4, developed by the National Centre for Atmospheric Research (NCAR) (Skamarock et al., 2008) is used to get vertical profile information (radar reflectivity and vertical wind) of three cyclones over Kadapa (JAL and NILAM) and Gadanki (THANE).

WRF model uses terrain-following hydrostatic pressure

coordinates with 27 vertical levels. Model domain and the resolution used in the present analysis are provided in Table 1. The National Centre for Environmental Prediction Final Analysis (NCEP-FNL) data from Global Data Assimilation System (GDAS, Kanamitsu, 1989) available at 6 hour intervals and at 1o ×1o resolution are used for initial and boundary conditions for the three cyclones. In the present study, microphysical scheme of Thompson et al. (2004), Yonsei University (YSU) planetary boundary layer (PBL) scheme (Hong et al., 2006), Kain-Fritsch Cumulus parameterization scheme (Kain, 2004), Dudhia shortwave scheme (Dudhia, 1989) for shortwave radiation and Radiative Transfer Model (RTM) (Mlawer et al., 1997) for the longwave radiation have been used at 27 km resolution by following Osuri et al. (2012), Srinivas et al. (2013), and Reddy et al. (2014). 3. Overview of three (JAL, THANE, and NILAM ) cyclones The tracks of three cyclones along with their date, time, and intensity are shown in Fig. 2. The JAL and NILAM cyclones induced precipitations were measured at Kadapa (14.47°N, 78.82°E) (denoted with the black triangle in Fig. 2), and the THANE cyclone precipitation was measured at Gadanki (13.5oN, 79.2oE) (denoted by a black square in Fig. 2). Among three cyclones, one (JAL) passed through the observational site, and the remaining two (THANE and NILAM) passed outside of the observational sites. The JAL cyclone was formed as a depression over southeast BOB near 8o N and 92o E at 00:00 UTC on 4th November 2010. The depression was intensified to deep depression on 5th November 2010 at 00:00 UTC and developed into a cyclonic storm, JAL, at 06:00 UTC with its center near 9o N and 87.5o E, at about 900 km southeast of Chennai. The cyclonic storm JAL moved ahead in the direction of west-northwestwards over southeast BOB and then enhanced to severe cyclonic storm during the early hours of 6th November 2010. The severe cyclonic storm intensity persisted up to 03:00 UTC on 7th November 2010 and then weakened to cyclonic storm with its center near 12.5o N and 82.5o E over southwest BOB at 06:00 UTC on 7th November at 8

about 250 km east-southwest of Chennai. With further weakened intensity to deep depression, it crossed near north Tamil Nadu-south Andhra Pradesh coast, close to the north of Chennai near 13.3o N and 80.3o E around 16:00 UTC on 7th November 2010. Over the inland region, it continued to move west-northwestwards as a depression at 03:00 UTC, and to a well-marked low-pressure area over Rayalaseema and adjoining south interior Karnataka at 06:00 UTC on 8th November 2010. JAL cyclone microwave satellite images (85-91 GHz) from SSM/I, SSMIS, TMI, and NOAA-16 obtained from the NRL website are depicted in Fig. 3. Location of the disdrometer (Kadapa) is marked with a black colored triangle on each satellite image. Color contour on the satellite images of Fig. 3 represents blackbody brightness temperature (TB) caused by scattering from precipitation-size ice hydrometeors. TB is used as a proxy for strong (TB < 230 K) or weak convection (230 < TB 1) (Atlas et al., 1999; Atlas and Williams, 2003; Steiner et al., 2004). The radar reflectivity and rain rate (Z-R) relations of BLF and ALF rainfall of the three cyclones and their precipitation type (stratiform and convective) are obtained by applying linear regression to logarithmic values of rain rate (R) and radar reflectivity (Z). The Z-R relations of present cyclones and tropical cyclones of other oceanic regions are given in Table 2. Marks et al. (1993) analyzed the Z-R relations of different regions of Atlantic hurricane Anita, and they found a higher coefficient and lower exponent for outer rainband when compared to eyewall region (Table 2). A recent study of tropical cyclones Z-R relations over Australia by Deo and Walsh (2016) found similar characteristics. The coefficient (exponent) of Z-R relations was higher (lower) for outer rainbands (> 200 km from 14

the tropical cyclone center) than eyewall region (< 60 from cyclone center) [Fig. 9(c) of Deo and Walsh, 2016]. The Z-R relations of BLF and ALF precipitation of JAL cyclone also showed higher A and lower b value in BLF than ALF precipitation. Previous researchers (Baeck and Smith, 1998; Ulbrich and Lee, 2002; Tokay et al., 2008) found that the tropical cyclone rainfall is underestimated by default Z-R relation (Z=300R1.4) and overestimated by tropical Z-R relation (Z=250R1.2). Present results (in Table 2) reconfirm their opinion, leading to adaptation of different coefficient and exponent values in estimating the rainfall from the Doppler radar observations. From the table, it is clear that the Z-R relations of other oceanic (Pacific and Atlantic) cyclones are different from that of the current cyclones (Indian Ocean). This gives a clue to adopt modified Z-R relations in modelling the tropical cyclones (Franklin et al., 2005) of BOB. However, there is a need to study more cyclones to obtain generalized Z-R relations for the tropical cyclones of BOB.

4.5 Variation of RSD and gamma parameters in BLF and ALF precipitations Variations of mean raindrop concentrations in BLF and ALF precipitations of three cyclones (JAL, THANE, and NILAM) with drop diameter are depicted in Fig. 14. By following the drop diameter classification into small, mid, and large drops from Tokay et al. (2008), it is apparent that the concentration of small drops is higher in ALF than BLF precipitation of JAL cyclone. However, mid and large size drops are associated with slightly higher concentration in BLF than ALF precipitation [Fig. 14(a)]. On the other hand, the number density of mid and large size drops are higher in ALF compared to BLF in both THANE and NILAM cyclones [Fig. 14(b) and Fig. 14(c)]. In spite of that, small drop concentration is lower (slightly lower) in ALF precipitation of THANE (NILAM) than BLF precipitation [Fig. 14(b) and Fig. 14(c)]. In both BLF and ALF precipitation of three cyclones, maximum raindrop diameter rarely overreaches by 4 mm. This characteristic is, unsurprisingly,

similar to the observations noticed by previous

researchers (Tokay et al., 2008; Chang et al., 2009; Radhakrishna and Narayana Rao, 2010).

Parameterization of RSD to modified gamma distribution is worthwhile for the modelling studies (Kozu et al., 2009b; Carollo and Ferro, 2014; Ekerete et al., 2015). The three-parameter gamma function is often employed to parameterize the disdrometer observed RSD measurements in various applications including precipitation retrieval algorithms from Tropical Rainfall 15

Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) radar measurements (Iguchi et al., 2000; Kozu et al., 2009a, 2009b; Nakamura and Iguchi, 2007). As a consequence, RSDs of three cyclones are fitted to modified gamma distribution. Variations in mass-weighted mean diameter (Dm, mm), normalized intercept parameter (log10Nw, m-3 mm-1), slope parameter (Λ, mm-1), and shape parameter (μ, no units) as a function of rain rate in BLF and ALF precipitations of three cyclones are depicted in Fig. 15. The normalized intercept parameter Nw represents N(D) when raindrops diameter approaches to its minimum value.

The slope

parameter (Λ) designates the truncation of RSD tail with drop diameter. The smaller value of Λ indicates the extension of the RSD tail to a larger diameter and larger Λ to a smaller diameter. The shape (μ) parameter represents the breadth of the RSD. If μ is greater (lower) than zero, then RSD is concave downward (upward) and is exponential if it is equal to zero (Ulbrich, 1983). In both BLF and ALF precipitations of three cyclones, with the increase in rain rate, distributions of Dm get narrowed [Fig. 15(a)-(c)] at higher rain rates (R > 10 mm/h). The distribution of Dm is widespread at lower rain rates (below 10 mm/h) for three cyclones. The distribution of Dm is wider in BLF than the ALF precipitation of JAL cyclone, and is wider in ALF than BLF precipitations of THANE and NILAM cyclones. However, in all the three cyclones Dm increases with the increase in rain rate (Rosenfeld and Ulbrich, 2003) and its maximum value is less than 2.5 mm. This clearly indicates that the three cyclones are predominantly associated with small and midsize drops rather than large drops.

Similar observations were documented in the

literature (Tokay et al., 2008; Chang et al., 2009; Radhakrishna and Narayana Rao, 2010). In BLF and ALF precipitations of three cyclones, normalized intercept parameter increases with the increase in rain rate and attains stable values at higher rain rates (R > 10 mm/h) [Fig. 15(d)-(f)]. The shape (µ) and slope (Λ) parameters decrease with an increase in rain rate for BLF and ALF precipitations of three cyclones [Fig. 15(g)-(l)]. The μ and Λ values are found to be larger at lower rain rates (< 5 mm/h) when compared to moderate and heavy rain rates (rain rate > 5 mm/h). Similar characteristics were observed by Chang et al. (2009) for western Pacific typhoon systems. Large values of μ and Λ could be due to the statistical errors arising in the estimation of moments as described by Zhang et al. (2003). A detailed study on possible reasons for the large values of μ and Λ at lower rain rates can be found in Zhang et al. (2003), Brandes et al. (2003), and Cao et al. (2008). Probability distributions of mass-weighted mean diameter (Dm), normalized intercept parameter (log10Nw), shape (µ), and slope (Λ) parameters of three cyclones 16

are depicted in Fig. 16. In all of the above parameters (Dm, log10Nw, µ, and Λ), an apparent segregation between BLF and ALF precipitations of JAL and THANE cyclones with slight variation in NILAM cyclone can be noticed. Statistical values of all the above parameters (Dm, log10Nw, μ, and Λ) in BLF and ALF precipitations are provided in Table 3. Variations of normalized intercept parameter against mass-weighted mean diameter in BLF and ALF precipitations of three cyclones are depicted in Fig. 17. Mean Dm in BLF of JAL cyclone is higher than ALF precipitation. Whereas, mean Dm in BLF precipitations of THANE and NILAM are less than ALF precipitations. For both BLF and ALF precipitations of three cyclones, mean Dm is varying from 0.7 to 1.35 mm. Mass-weighted mean diameter (Dm) values calculated by Tokay et al. (2008) for Atlantic and central Pacific are varying in the range of 1.64 to 1.98 mm and 1.59 to 1.68 mm respectively. By following the Tokay et al. (2008) radar reflectivity criteria, mean Dm values estimated by Radhakrishna and Narayana Rao (2010) were found in the range of 1.85 to 1.9 mm and 1.7 to 1.75 mm for southwest and northeast monsoon cyclonic precipitations respectively. Mean Dm values of present cyclones are smaller than the cyclonic precipitations of Radhakrishna and Narayana Rao (2010). This might be due to their consideration of low-pressure systems as cyclonic precipitation instead of choosing only tropical cyclone category. For western Pacific typhoon systems, an average Dm of about 2 mm was noticed by Chang et al. (2009). For typhoon Morakot (2009) an average Dm of 1.3 mm was observed by Chen et al. (2012). Kim et al. (2013) noticed an increase in mean Dm value from eyewall to outer rainbands for typhoon Kompasu (2010) and their Dm ranges from 1.16 to 1.35 mm. Suh et al. (2016) measured mean Dm of around 1.4 mm and 1.3 mm for stratiform and convective precipitations, respectively, for nine typhoon systems observed over Korea. The mass-weighed mean diameters of present cyclones are smaller than the Pacific and Atlantic tropical cyclones [except Kim et al. (2013) case study]. The decrease of log10Nw with the increase of Dm in BLF than ALF precipitation of JAL cyclone is due to the lower number of small drops in BLF than the ALF precipitation [Fig. 14(a)].

In THANE cyclone, lower

concentration of smaller drops in ALF than BLF result in lower log10Nw and higher Dm in ALF than BLF precipitation [Fig. 14(b)]. Whereas in the case of NILAM cyclone, higher log10Nw and Dm in ALF than BLF is due to the presence of higher concentration of mid and large size drops and slightly lower concentration of small drops in ALF than BLF precipitation [Fig. 14(c)]. In

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BLF and ALF precipitations of JAL and THANE cyclones, a negative relation between Dm and log10Nw was found and similar features were observed by Kim et al. (2013) at different locations (outer/inner rainbands and eyewall) of typhoon Kompasu.

The RSD variations in BLF and ALF precipitations of three cyclones at three different radar reflectivity (Z, dBZ) classes (C1: 20 < Z < 25, C2: 25 < Z < 30, and C3: 30 < Z < 40 dBZ) are shown in Fig. 18. The RSDs of three cyclones are stratified into three radar reflectivity classes in such a way that the mean radar reflectivity in each class is nearly equal in BLF and ALF precipitations. The mean and standard deviations of each radar reflectivity class of three cyclones are given in Table 4. For the first radar reflectivity class of JAL cyclone, mean RSD distribution has a higher concentration of mid drops and lower concentration of small drops in BLF than ALF precipitation [Fig. 18(a)]. Second radar reflectivity class [Fig. 18(b)] of JAL cyclone has a lower concentration of raindrops below 1.3 mm diameter and a higher concentration of raindrops above 1.3 mm diameter in BLF than ALF precipitation. In the case of third radar reflectivity class [Fig. 18(c)], raindrops up to (above) 1.7 mm diameter have a lower (higher) concentration in BLF than ALF precipitation. In the case of THANE cyclone, raindrops of diameter up to (above) 1.1 mm, 1.3 mm, and 1.6 mm have the lower (higher) concentration in ALF than BLF for first [Fig. 18(d)], second [Fig. 18(e)], and third [Fig. 18(f)] radar reflectivity classes respectively. The first radar reflectivity class of NILAM cyclone [Fig. 18(g)] has a lower concentration of raindrops below 0.6 mm and 1.1 mm - 1.8 mm, and a higher concentration of raindrops ranging from 0.6 mm -1.1 mm and above 1.8 mm in ALF as compared to BLF precipitation. The second radar reflectivity class [Fig. 18(h)] of NILAM cyclone showed a slight variation between small and mid drops in BLF compared to ALF precipitation. The third radar reflectivity class [Fig. 18(i)] of NILAM cyclone has a higher concentrations of small, mid, and large drops in ALF than BLF precipitation except at raindrops below 0.5 mm diameter.

Mean values of normalized intercept parameter (log10Nw) (with

standard deviation) and mass-weighted mean diameter (Dm) for the above mentioned radar reflectivity classes are shown in Fig. 19. In three radar reflectivity classes, BLF precipitation of JAL cyclone has higher Dm and lower log10Nw values than ALF precipitation [Fig. 19(a)]. Whereas, THANE cyclone has higher Dm and lower log10Nw values in ALF than BLF precipitation [Fig. 19(b)] in three reflectivity classes. These characteristics are due to lower 18

concentration of small drops and a higher concentration of mid or large drops in BLF (ALF) precipitation of JAL (THANE) cyclone [Fig. 18(a)-(c) and Fig. 18(d)-(f)].

In three radar

reflectivity classes, NILAM cyclone has higher Dm in ALF as compared to BLF precipitation [Fig. 19(c)].

5

Discussion During the landfall time of a tropical cyclone, an enhancement in the frictional

convergence in the outer region occurs due to the interaction of spiral rainbands with the environment and its underlying surface (Molinari et al., 1994). This causes the collision of ice particles in the mixed phase region associated with strong updrafts in the outer region (Houze, 1993). Over south China coast, Liu et al. (2007) found an enhancement in convection on the western side of the tropical cyclones during their landfall. If we look into different regions of a tropical cyclone, outer rainbands are more predominant with pronounced updraft, downdraft, and lightning activity as compared to eyewalls and inner rainbands (Molinari et al., 1999; Cecil et al., 2002; Zhang et al., 2013; Houze, 2010). The outer rainband region typically begins at 150 -200 km radius from the cyclone center and includes any rain features associated with the cyclone located beyond this distance (Cecil et al., 2002). The outer rainband reflectivity was found to be 1.35 times higher than the eyewall for the same rain rate (Marks et al., 1993). Zhang et al. (2013) noticed large lightning frequency, high positive cloud to ground lightning ratio, and the heights of 40 and 50 dBZ reflectivity reaching maximum values in the outer rainbands than inner rainbands. The outer rainbands of tropical cyclones have supercooled water and the largest graupel particles extending to greater heights (Cecil and Zipser, 2002). Inner rainbands are dominated by stratiform rain and rather weak convection (Szoke et al., 1986; Black et al., 1996; Molinari et al., 1999; Jorgensen et al., 1985). Inner rainbands are characterized by a low flash rate compared to eyewall and outer rainbands (Cecil and Zipser, 2002; Cecil et al., 2002). Raghavan (2003) reported higher values of storm heights in the outer rainbands (outside 100 km from storm center) than inner rainbands (inside 100 km from the storm center) of BOB tropical cyclones when they are over the ocean and also while crossing the coast. The eyewall is marked by a radar reflectivity signature that slopes radially outward with height (Marks and Houze, 1987). Frozen particles ejected from eyewall region sediment in inner rainbands resulting in minimum lightning density. This mechanism aid to remove supercooled water, and the cooling 19

caused by both melting and evaporation below zero degree isotherm strongly subdues convective updrafts in the inner rainbands (Molinari et al., 1994).

The radial distances between the observational site and the track of each cyclone are calculated by using haversine formula and are given in Table 5. From the table, it is clear that BLF precipitation of JAL cyclone emerges from outer rainbands and the ALF precipitation from regions ranging from eyewall to outer rainbands (Fig. 2 and Fig. 3). Because of deep depression strength of JAL cyclone, there is no clear appearance of the eyewall structure in ALF precipitation (middle right, bottom left and bottom right figures of Fig. 3). However, from Fig. 2, it is clear that the center of the cyclone passed over the disdrometer site during ALF period. In the case of the remaining two cyclones (THANE and NILAM) both BLF and ALF precipitations occurred due to their outer rainbands (Fig. 2, Fig. 4, and Fig. 5). From Fig. 3, it is apparent that the BLF (top left, top right, and middle left figures in Fig. 3) precipitation of JAL cyclone is relatively more convective than ALF (middle right, bottom left, and bottom right figures in Fig. 3) precipitation. The convective activity in the outer rainbands of THANE and NILAM cyclones further increases due to their interaction with the environment and its underlying surface after their landfall (Liu et al., 2007). Hence, ALF precipitations of THANE and NILAM cyclones are relatively more convective than their BLF precipitations. Intense convective activity modifies the drop size through drop sorting and enhancing the collision-coalescence process. The drop sorting keep out the smaller drops to fall under the influence of gravity and the large updrafts could suspend the drops aloft, resulting in sufficient time for collision and coalescence process. The collision-coalescence process consumes smaller drops for the growth of medium drops (Atlas and Ulbrich, 2000; Kollias et al., 2001). THANE cyclone ALF precipitation is associated with collision-coalescence and evaporation processes, resulting in higher concentration of large drops with reduced number of small drops (Rosenfeld and Ulbrich, 2003) than BLF precipitation [Fig. 14(b)]. Higher concentration of mid and large drops with a slightly lower concentration of small drops in ALF than BLF precipitation of NILAM cyclone is due to enhanced accretion, collision-coalescence, and collision induced breakup processes.

Consequently, ALF

precipitation of NILAM is associated with higher Dm and log10Nw values (Fig. 15) compared to BLF precipitation. Higher concentration of small ice particles in the inner regions of JAL

20

cyclone is the possible reason for the occurrence of a higher number of small drops in ALF than BLF precipitation, which results in smaller (larger) Dm (log10Nw) in ALF than BLF precipitation.

6

Summary and conclusions In the present work, an attempt has been made to study the raindrop size distribution

characteristics of three tropical cyclones (JAL, THANE, and NILAM) observed over two locations (Kadapa and Gadanki) of southeast India. These cyclonic precipitations are classified into before landfall (BLF) if the cyclone center is present over the ocean and as after landfall (ALF) if a cyclone crosses the inland region. WRF model results of the three cyclones showed that BLF precipitation of JAL cyclone is relatively more convective than ALF precipitation. Whereas, ALF precipitations of THANE and NILAM cyclones are relatively more convective than BLF precipitations. These model results are consistent with the satellite observations. Stratiform and convective classification of the three cyclones showed that both BLF and ALF precipitations have higher drop concentrations in convective than stratiform regimes. BLF (ALF) precipitation of JAL (THANE and NILAM) has higher Dm values in both stratiform and convective regimes. The radar reflectivity and rain rate (Z-R) relations of present cyclones are different from that of the default (Z=300R1.4), tropical (Z=250R1.2) Z-R relations, and also to that of the other oceanic tropical cyclones Z-R relations. BLF precipitation of JAL cyclone has a slightly higher concentration of mid and large drops compared to ALF. Remaining two cyclones have a higher concentration of mid and large drops in ALF than BLF precipitation. Mean Dm value in BLF precipitation of JAL cyclone is higher than ALF precipitation. Whereas, BLF precipitations of NILAM and THANE cyclones have smaller Dm values than ALF. The above features are clearly seen even after stratifying the RSD into different radar reflectivity classes. Mean Dm values in BLF and ALF precipitations of three cyclones are smaller than the Pacific and Atlantic tropical cyclones. Relatively higher convection (caused by cyclone interaction with the environment and land surface) in ALF precipitations of THANE and NILAM cyclones lead to higher Dm values than BLF precipitation by collision-coalescence and the evaporation process. A higher number of small ice particles in the inner regions of JAL cyclone resulted in smaller raindrops causing lower Dm in ALF than BLF precipitation. Even though there is no consistent pattern in BLF and ALF precipitation of three cyclones RSD, present analysis shows that the RSD of tropical cyclones differs in BLF and ALF precipitation. The present work reveals that 21

the RSD characteristics of present cyclones are distinct to that of the other oceanic tropical cyclones. The results presented here are limited to the three cyclones, and in the future work, we plan to study more tropical cyclones to obtain comprehensive Z-R relations for different regions (outer bands, inner band, and eyewall).

Acknowledgments We acknowledge the India Meteorological Department (IMD), Govt. of India, for providing the three cyclone track information.

We also gratefully acknowledge the Naval

Research Laboratory, Monterey, California for providing the multi-satellite images. The first author, J. Jayalakshmi greatly acknowledges the Ministry of Science and Technology (MOST), Taiwan, R.O.C for providing post-doctoral fellowship under the grant no. MOST 104-2811-M008-064. The second author, Balaji Kumar Seela, acknowledges Academia Sinica, Taiwan for providing graduate fellowship under Taiwan International Graduate Program (TIGP). BKS is partially supported from the MOST research grants no. MOST 105-2119-M-008-011 and MOST 105-2625-M-008-010. The corresponding author, K. Krishna Reddy is thankful to Indian Space Research Organization (ISRO), Govt. of India for supporting Semi-arid zonal Atmospheric Research Centre (SARC) at the Yogi Vemana University, Kadapa, India. The authors are thankful to the two anonymous reviewers and the editor for their valuable suggestions and comments for the great improvement of the manuscript.

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Figure captions Fig. 1 Scatterplot between hourly accumulated rainfall of PARSIVEL disdrometer and the collocated tipping bucket rain gauge for three (JAL, THANE, and NILAM) cyclones. Fig. 2 Six hourly track of JAL (black line), THANE (magenta line), and NILAM (blue line) cyclones along with initiation and before dissipation date and time. Different colored circle on the tracks indicates different intensities. Two observational sites Kadapa and Gadanki are represented with black color filled triangle and square respectively. Fig. 3 Color composite microwave satellite imagery of JAL cyclone. Lines of latitude and longitude are marked at 1o intervals. Location of the disdrometer (Kadapa) is overlaid on the satellite images with a black colored triangle. (Images provided courtesy of the Naval Research Laboratory in Monterey, CA.). Fig. 4 As in Fig. 3, but for THANE cyclone. The black colored square overlaid on the satellite images represents the location of the disdrometer (Gadanki). Fig. 5 As in Fig. 3, but for NILAM cyclone. The black colored triangle on the satellite images represents the location of the disdrometer (Kadapa). .

Fig. 6 The model simulated vertical profile of (a) radar reflectivity (Z, dBZ) and (b) vertical wind (W, m/s) of JAL cyclone (7th and 8th November 2010) over Kadapa. Fig. 7 The model simulated vertical profile of (a) radar reflectivity (Z, dBZ) and (b) vertical wind (W, m/s) of THANE cyclone (29th to 30th December 2011) over Gadanki. Fig. 8 The model simulated vertical profile of (a) radar reflectivity (Z, dBZ) and (b) vertical wind (W, m/s) of NILAM cyclone (31st October 2012) over Kadapa. Fig. 9 Time series of (a) raindrop concentration [N (D), m-3 mm-1] as a function of drop diameter (D, mm), (b) mass-weighted mean diameter (Dm, mm), rain rate (R, mm/h), radar reflectivity (Z, dBZ) measured with PARSIVEL disdrometer (every 60 seconds), hourly (c) surface temperature (T, oC), pressure (P, hPa), and (d) wind direction (WD, degrees), wind speed ( WS, m/s) from collocated automatic weather station during the passage of JAL cyclone (7th and 8th November 2010) measured at Kadapa. The vertical black line represents the landfall time. Fig. 10 Same as Fig. 3, but for THANE cyclone (29th to 30th December 2011) induced precipitation measured at Gadanki. Fig. 11 Same as Fig.3, but for NILAM cyclone (31st October 2012) induced precipitation measured at Kadapa.

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Fig. 12 Mean of raindrop concentration against drop diameter for stratiform (STF) and convective (CON) regimes of JAL, THANE, and NILAM cyclone’s before landfall (BLF) [(a), (e), and (i) respectively] and after landfall (ALF) [(b), (f), and (j) respectively] precipitations, and BLF and ALF precipitations of JAL, THANE, and NILAM cyclone’s stratiform [(c),(g), and (k) respectively] and convective [(d), (h), and (l) respectively] regimes. Fig. 13 Mean values of normalized intercept parameter (log10Nw with ±1σ standard deviation) versus mean values of the mass-weighted mean diameter (Dm) of stratiform (STF) and convective (CON) regimes of (a) JAL, (b) THANE, and (c) NILAM cyclone’s before landfall (BLF) and after landfall (ALF) precipitations. Fig. 14 Mean of raindrop concentration against drop diameter for before landfall (BLF) and after landfall (ALF) precipitations of (a) JAL, (b) THANE, and (c) NILAM cyclones. Fig. 15 Scatterplots of the mass-weighted mean diameter (Dm, mm) [(a), (b), and (c)], logarithmic values of normalized intercept parameter (log10Nw, m-3 mm-1) [(d), (e), and (f)], slope parameter (Λ, mm-1) [(g), (h), and (i)], and shape parameter (µ,-) [(j), (k), and (l)] as a function of rain rate for before landfall (BLF) and after landfall (ALF) precipitations of JAL, THANE, and NILAM cyclones. Fig. 16 Probability distribution functions (PDF) of mass-weighted mean drop diameter ( Dm, mm), normalized intercept parameter (log10Nw, m-3 mm-1), shape parameter (μ, -), and slope parameter (Λ, mm-1) in before landfall (BLF) and after landfall (ALF) precipitations of JAL [(a) - (d)], THANE [(e ) - (h)], and NILAM [(i) - (l)] cyclones. Fig. 17. Mean values of normalized intercept parameter (log10 Nw with ±1σ standard deviation) against mean values of mass-weighted mean diameter (Dm) for before landfall (BLF) and after landfall (ALF) precipitations of three cyclones. Fig. 18 Mean raindrop concentration variation with drop diameter in before landfall (BLF) and after landfall (ALF) precipitations of three cyclones (JAL, THANE, and NILAM ) for three radar reflectivity (Z, dBZ) classes. The continuous blue line represents the BLF and dotted red line represents the ALF. Fig. 19 Mean values of normalized intercept parameter (log10Nw with ±1σ standard deviation) versus mean values of mass-weighted mean diameter (Dm) at three radar reflectivity classes (C1: 20 < Z < 25, C2: 25 < Z < 30, and C3:30 < Z < 40 dBZ) as provided in Fig. 18 for (a) JAL, (b) THANE, and (c) NILAM cyclone’s before landfall (BLF) and after landfall (ALF) precipitations. BLF precipitation is represented by filled blue color markers and ALF with red color markers without color filling.

33

Table 1: Model configuration and parameterisation schemes used in the WRF model Model

NCAR Mesoscale model WRF

Dynamics Horizontal grid resolution

Non-hydrostatic with 3-D Coriolis force 27 km

Domain Size

Latitude: 4.670 W to 30.720N Longitude: 57.10 E to 101.590E 27 NCEP GFS data Arakawa-C grid Thompson Rapid Radiative Transport Model (RRTM) scheme Dudhia scheme Noah land surface model Yonsei University scheme (YSU)

Number of vertical levels Data Horizontal grid system Micro physics Long wave radiation scheme Short wave radiation scheme Land surface scheme Planetary Boundary Layer (PBL) scheme Surface layer scheme Cumulus parameterization scheme

MM5 similarity scheme Kain- Fritsch (KF)

Diffusion option

Simple diffusion

34

Table 2. Radar reflectivity (Z) –rain rate (R) relations for tropical storms of present study and different oceanic regions. Oceanic

Z-R relations

Cyclone

Region Indian Ocean

name Reference

/number of cyclones Z= 102.49 R1.39 (BLF)

JAL cyclone

Present study

THANE cyclone

Present study

NILAM cyclone

Present study

Z= 101.36 R1.28 (BLFstratiform) Z= 71.67 R1.6 (BLFconvective) Z= 57.9 R1.49

(ALF)

Z= R52.36 R1.35(ALFstratiform) Z= 71.95 R1.5 (ALFconvective) Indian Ocean

Z = 77.16 R1.36 (BLF) Z= 72.15 R

1.29

(BLF-

stratiform) Z= 83.35 R1.41 (BLFconvective) Z= 180.05 R1.44 (ALF) Z= 184.46 R1.41 (ALFstratiform) Z= 170.93 R1.47 (ALFconvective) Indian Ocean

Z = 202.19 R1.35 (BLF) Z= 207.54 R1.4 (BLF-

35

stratiform) Z= 187.08 R1.09 (BLFconvective) Z= 192.66 R1.39 (ALF) Z= 186.3 R1.38 (ALFstratiform) Z= 207.48 R1.36 (ALFconvective) Indian Ocean

Z

=

275.25

R1.39 Five cyclonic storms

(southwest monsoon) Indian Ocean

Z

=

142.04

R1.55 Six cyclonic storms

Z=235 R1.3 (total) Z=308 R

Pacific Ocean

1.32

and

Narayana Rao (2010)

(northeast monsoon) Pacific Ocean

Radhakrishna

Radhakrishna

and

Narayana Rao (2010) Typhoon Morakot

Chen et al., (2012)

(Eyewall)

Z = 206.83 R1.45

Thirteen

typhoon Chang et al., (2009)

systems Atlantic Ocean

Z=118 R1.48

Remnants of tropical Ulbrich and Lee (2002) storm Helene

Atlantic Ocean

Z = 253 R1.3 (Eyewall) Z= 341R

1.25

Hurricane Anita

Marks et al., (1993)

(outerband)

Z=311R1.27 (total) Atlantic Ocean

Z=276.7 R1.29

Hurricane Anita and Willis (1984) Frederic

Atlantic Ocean

Z=300 R1.35

Three hurricanes

Jorgensen

and

Willis

(1982) Atlantic Ocean

Z= 350 R

1.35

Hurricane Agnes

Wilson

and

(1974) Atlantic Ocean

Z= 300 R1.24

Tropical storm Felice

Z=260 R1.35

Hurricane Debbie

36

Scott (1974)

Pollack

Table 3. Statistical measure [ number of minutes/values (n), mean, standard deviation (Std), skewness (Skew.) and kurtosis (Kurt.)] of mass weighted mean diameter (Dm), normalized intercept parameter (log10Nw), shape (µ), and slope parameter (Λ) in BLF and ALF precipitations of JAL, THANE, and NILAM cyclones. Cyclon

Paramete

e

r

Before Landfall (BLF)

n

Mea

Std

n JAL

Dm (mm)

54

0.92

Skew

After Landfall (ALF)

Kurt.

. 0.29

1.02

-1

4.99

0.54

0

µ (-)

54

13.2

14.1

0

0

8

54

21.1

17.4

0

2

8

48

0.79

0.18

Dm (mm)

4.09

-1.17

3.87

NILAM

48

mm-1)

0

µ (-)

48

14.4

0

1

48

24.3

10.0

0

9

4

18

1.05

0.26

Dm (mm)

7.55

-1

18

mm )

7

µ (-)

18

.

0.75

0.23

1.54

5.59

46

5.41

0.29

-1.26

6.31

5.74

0.79

4.46

5.03

0.43

3.01

1.02

99.9

46

11.7

6

0

0

55.9

46

22.9

10.3

7

0

9

3

5.13

91

1.1

0.18

-0.01

3.41

5.16

0.34

-1.28

4.62

0.28

0.34

3.95

7.35

6.34

6.73

93.5

5.33

91 0

7.27

1.25

6.55

91 0

0.70

0.14

3.60

2.42

7 Nw(m-3

Kurt.

0

Nw(m-3

Λ (mm )

46

Skew

0

0

-1

Std

0

mm )

Λ (mm-1)

THANE

54

Mea n

0 Nw(m-3

n

3

91

10.6

7.90

6.67

90.4

0

6

26

1.29

0.33

-0.49

2.53

4.66

0.53

-1.43

5.24

7.34

6.59

3.14

21.5

8

1 4.47

0.58

-0.55

3.94

26 1

8.48

7.54

1.77 37

7.69

26

7 Λ (mm-1)

1

18

13.3

7

1

9.46

1.55

6.36

5

26

10.7

10.1

1

4

4

3.04

17.0 0

Table 4. Mean and standard deviations (std) of three radar reflectivity classes in before landfall (BLF) and after landfall (ALF) precipitations of three cyclones (JAL, THANE, and NILAM) Radar

JAL

THANE

NILAM

reflectivity (Z)

Before

After

Before

After

Before

After

classes

landfall

landfall

landfall

landfall

landfall

landfall

(BLF)

(ALF)

(BLF)

(ALF)

(BLF)

(ALF)

Mean (std) Mean (std) Mean (std) Mean (std) Mean (std) Mean (std) dBZ 20 < Z