Observations and PolarimetricSignatures of Flash Flood Storms in 

Taipei

BEN JONG‐DAO JOUDepartment of Atmospheric Science, National Taiwan University

24‐25 November 2015 APTS at Manila

Introduction  • In recent years, flash floods over mega cities are becoming frequent, 

especially in the monsoon region. These urban flash floods sometimes cause un‐expected disasters due to lack of in‐time warning and poor emergency response.

• The urban flash floods are sometimes associated with complex feature of thunderstorm development. Merging several individual convective cells into one gigantic “thunderstorm complex” entity is frequently observed.

• The newly upgraded WSR‐88D polarimetric radar system combining with dense mesoscale network can provide important information for the formation and development of these flash‐flood producing thunderstorm complex. 

• In this presentation, a case occurred in Taipei city (14 June 2015) is examined. Polarimetric signatures from the flash flood storm are particularly emphasized.

Taipei basin viewed from south/Hot spots for storm occurrence

Taipei

Tanshui

Keelong

WFS

CKS

Flash flood in Taipei

Rank Date (May-Sep,1992-2013)

3-h rainfall in mm (Taipei)

Weather systems

1 2004/9/11 275.5 TD/Monsoon trough (Haima)

2 2001/9/17 236.0 TC, Nari

3 2004/8/24 233.5 TC, Aere

4 2001/9/5 227.5 TD/monsoon trough

5 1999/6/19 198.0 Meiyu front/MCS

6 2000/11/1 175.5 TC, Xangshan

7 1998/10/15 166.0 TC, Zeb

8 1997/8/18 163.0 TC, Winnie

9 2007/10/6 162.0 TC, Krosa

10 2012/8/2 160.5 TC, Saola

11 2009/9/28 157.5 TC/NE monsoon (Ketsana)

12 2006/6/10 157.0 Meiyu front/MCS

13 2008/9/13 155.5 TC, Sinlaku

14 2004/5/31 153.5 Meiyu front/MCS

15 2012/6/16 152.0 Meiyu front/MCS

2015/6/14193mm/3 hourAfternoon thunderstorm complex

Proto-type Taipei afternoon thunderstorm prediction system using fuzzy logic has been developed (Lin et al. 2012 WaF)

Currently, only storm or non-storm occurrence is predicted. No information for potential flash flood is given.

Flash flood/heavy rain cases in TaipeiCase studied Publications Case description

21 June 1991 Jou (1994) Flash flood was over SE and central districts of Taipei, 140mm/3 hour rain was recorded by Taipei station;The importance of sea breeze on enhancing storm development was recognized by using single Doppler wind analysis.

29 August 1999 Lin, Jou and Yu (2003)

Heavy rain and hail storm(dual-Doppler wind synthesized);Outflows from the pre-existing cell produced enhanced convergence favored for storm development were identified.

14 June 2015 Jou et al. (2015)

193mm/3 hour rain was recorded; Cell merge is observed; Polarimetricsignatures are identified

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Keelung/135mm, Taipei/140mm, within 3 hours.

Late afternoon organized thunderstorm and flash flood in Taipei (1991/6/21) (Jou 1994)

Ps

T

Td

Rain rates in mm/15min

95mm/60min

CKS

SW NE

SENWNW SE

SW NE

NW SE

Jou (1994)

Storm merge and intensification

Interaction of sea breeze and outflows: single Doppler wind analysis (Jou 1994)

NW SE

Signature of sea breeze, precipitating outflows, enhanced convergence, upward transport of westerly momentum by convective updraft, and intensified precipitation.

Doppler radar synthesized horizontal winds at 1 km height

Dual-Doppler wind analysis of a hailstorm in the Taipei basin (1999/8/29), interaction among local circulation, storm circulation and complex terrain effect. (Lin et al. 2001)

1454 1500 1506 1512 1518 1524 1530 1536 1542 1548 1554 1600

1

3

5

7

9

11

Time (LST)

Height in km

AB

Cell merge

Hail storm in Taipei, 29 August 1999

Hail storm signature from Doppler radar observation (embryo curtain, weak echo vault, and hail cascade)

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Embryo curtain

Weak echo vault

Hail cascade

Enhanced convergence between the sea breeze from NW and the outflows from the precipitating storm in SE

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SENW 1500LST

WFS

Urban flash flood in Taipei in the monsoon season

1504 LST 14 June 2015

A

B C

(c) 1428 LST (d) 1452 LST

AB C

Storm evolution

A BA+B+C

SW NECell merge

1417 1428 1440

1452 1503 1521

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Enhanced surface convergence over the leading edge of the previous rainfall is observed, outflows from the precipitating storm

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Zhh1435

Zhh1452

Vr 1452Vr 1435

Enhanced low-level convergence observed by WFS radial velocity

Westcott and Kennedy (1989): Cell merge associated with enhanced convergence on the order of 10 [-3] per sec and much larger than the mesoscaleconvergence calculated from surface station observations on the order of 10 [-4] per sec

Westcott and Kennedy (1989): Cell merge associated with enhanced convergence

Polarimetric Parameters：Zh , Zdr , and Kdp

●Radar Reflectivity: Zh

(=10x log10Zh*) (dBZ)

Zh*：reflectivity factor of horizontalwave

D：Diameter N(D)：Particle size distribution

・Proportional to sixth power of diameter・Proportional to particle Size distribution

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Small（e.g. drizzle）

Large（e.g. heavy rain, hail）

●Differential Reflectivity: Zdr

Zh*：reflectivity factor of horizontalwave

Zv*：reflectivity factor of verticalwave

・oblate shape → Zdr > 0・spherical shape → 0・prolate shape → Zdr < 0

graupel, hail

drizzle

large rain drop

ice crystal

Z*v reflectivity factor：small

Z*h reflectivity factor：large

(dB)

(mm6m-3)

●Specific differential Phase Kdp

Φdp： differential phase r ：range

For a large rain drop, horizontal phase shift is larger than vertical phase shift, Φdpis largeOblate particle → Kdp is large.Large water content → Kdpis large.

(deg./km)

drizzle Heavy rain

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Zdr1435

Kdp1435

Zdr1504

Kdp1452

Zdr layer by size sorting (before merge 1354 LST)

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Zdr

Kdp

Zhh

Appearance of Zdr and Kdp column (after merge 1441 LST)

23

Zdr

Kdp

Zhh

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Enhanced and deepening of low-level convergence directly observed by Vr1355 vs 1441 LST

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Differential phase and specific differential phase (1355 vs 1441 LST)

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=1/2 d(Φdp)/dr

Kdp column

Specific differential phase Kdp is good for rainfall amount estimation (QPE)

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Conclusions Observations and polarimetric signatures of a flash flood storm in

Taipei basin is discussed. Cell merge caused by the interaction between sea breeze and outflow of pre-existing storm produces gigantic storm complex and enlarges the horizontal extend and enhances the intensity of rainfall.

Polarimetric signatures of Zdr can be used to infer the state of storm development. Zdr layer is a result of size sorting indicating a weaker storm. Zdr column is closely related to strong convergence and intense upward vertical velocity intensity (strong enough to hold larger drops in the higher layer) indicating an intensifying state of the storm.

Rainfall intensity can be inferred by Kdp distribution which is calculated from differential phase (Φdp) observed by the polarimetricradar. When estimating rainfall amount, Kdp (Kdp-R relation) is more accurate than using Zhh (Z-R relation).

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• CWB, 4 S-band Doppler radars and only RCWF is upgraded to polarimetricthis spring;

• Air-Force, 3 C-band Doppler radars with two of them are polarimetric;

• QPESUMS (10min, 1.3km)• TTFRI, C-band polarimetric

radar; (windprofiler etc.)• WRA+CWB, 5 more C-

band polarimetric radars (under deployment) (2min, 150m)

Developing algorithms suitable for local area are needed. QPE at mountain regions are important!

282015/11/24

Taiwan Weather Radar Network Update (2017)

THANK YOU!jouben@ntu.edu.tw

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Snyder, J.C., A. V. Ryzhkov, M. R. Kumjian, A. P. Khain, and J. Picca, 2015: A ZDR Column Detection Algorithm to Examine Convective Storm Updrafts. (WaF)

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Observations and recent high-resolution numerical model simulations indicate that liquid water and partially-frozen hydrometeors can be lofted considerably above the environmental 0 °C level in the updrafts of convective storms owing to the warm thermal perturbation from latent heating within the updraft and to the non-instantaneous nature of drop freezing. Consequently, upward extensions of positive differential reflectivity (i.e., ZDR ≥ 1 dB) – called ZDR columns – may be a useful proxy for detecting the initiation of new convective storms and examining the evolution of convective storm updrafts. High-resolution numerical simulations with spectral bin microphysics and a polarimetric forward operator reveal a strong spatial association between updrafts and ZDR columns and show the utility of examining the structure and evolution of ZDR columns for assessing updraft evolution. This paper introduces an automated ZDR column algorithm designed to provide additional diagnostic and prognostic information pertinent to convective storm nowcasting. Although suboptimal vertical resolution above the 0 °C level and limitations imposed by commonly-used scanning strategies in the operational WSR-88D network can complicate ZDR column detection, examples provided herein show that the algorithm can provide operational and research-focused meteorologists with valuable information about the evolution of convective storms.

Kumjian, M. R., and A. V. Ryzhkov, 2008: Polarimetric Signatures in SupercellThunderstorms. J. Appl. Meteor. Climatol., 47, 1940–1961.

Data from polarimetric radars offer remarkable insight into the microphysics of convective storms. Numerous tornadic and nontornadic supercell thunderstorms have been observed by the research polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN); additional storm data come from the Enterprise Electronics Corporation “Sidpol” C-band polarimetric radar in Enterprise, Alabama, as well as the King City C-band polarimetric radar in Ontario, Canada. A number of distinctive polarimetricsignatures are repeatedly found in each of these storms. The forward-flank downdraft (FFD) is characterized by a signature of hail observed as near-zero ZDR and high ZHH. In addition, a shallow region of very high ZDR is found consistently on the southern edge of the FFD, called the ZDR “arc.” The ZDR and KDP columns and midlevel “rings” of enhanced ZDR and depressed ρHV are usually observed in the vicinity of the main rotating updraft and in the rear-flank downdraft (RFD). Tornado touchdown is associated with a well-pronounced polarimetric debris signature. Similar polarimetric features in supercell thunderstorms have been reported in other studies. The data considered here are taken from both S- and C-band radars from different geographic locations and during different seasons. The consistent presence of these features may be indicative of fundamental processes intrinsic to supercell storms. Hypotheses on the origins, as well as microphysical and dynamical interpretations of these signatures, are presented. Implications about storm morphology for operational applications are suggested.

2015/11/24 31Zdr column, Kdp column, Zdr arc, Zdr ring, Rhv hole

Tanamachi, R. L., P. L. Heinselman, and L. J. Wicker, 2015: Impacts of a Storm Merger on the 24 May 2011 El Reno, Oklahoma, Tornadic Supercell. Wea. Forecasting, 30, 501–524.

On 24 May 2011, a tornadic supercell (the El Reno, Oklahoma, storm) produced tornadoes rated as category 3 and 5 events on the enhanced Fujita scale (EF3 and EF5, respectively) during a severe weather outbreak. The transition (“handoff”) between the two tornadoes occurred as the El Reno storm merged with a weaker, ancillary storm. To examine the impacts of the merger on the dynamics of these storms, a series of three-dimensional cloud-scale analyses are created by assimilating 1-min volumetric observations from the National Weather Radar Testbed’s phased array radar into a numerical cloud model using the local ensemble transform Kalman filter technique. The El Reno storm, its updrafts, and vortices in the analyzed fields are objectively identified, and the changes in these objects before, during, and after the merger are examined. It is found that the merger did not cause the tornado handoff, which preceded the updraft merger by about 5 min. Instead, the handoff likely resulted from midlevel mesocycloneocclusion, in which the midlevel mesocyclone split and a portion is shed rearward with respect to storm motion. During the merger process, the midlevel mesocyclone and updraft structure in the El Reno storm became relatively disorganized. New updraft pulses that formed above colliding outflow boundaries between the two storms tilted environmental vorticity from low levels to generate an additional midlevel vortex that later merged with the El Reno storm’s midlevel mesocyclone. Once the ~10-min merger process was complete, the El Reno storm and its mesocyclone rapidly reintensified, as access to buoyant inflow sector air was restored.

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Kennedy, P. C., S. A. Rutledge, B. Dolan, and E. Thaler, 2014: Observations of the 14 July 2011 Fort Collins Hailstorm: Implications for WSR-88D-Based Hail Detection and Warnings. Wea. Forecasting, 29, 623–638.The issuance of timely warnings for the occurrence of severe-class hail (hailstone diameters of 2.5 cm or larger) remains an ongoing challenge for operational forecasters. This study examines the application of two remotely sensed data sources between 0100 and 0400 UTC 14 July 2011 when pulse-type severe thunderstorms occurred in the jurisdiction of the Denver/Boulder National Weather Service (NWS) Forecast Office in Colorado. First, a developing hailstorm was jointly observed by the dual-polarization Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) research radar and by the operational, single-polarization NWS radar at Denver/Front Range (KFTG). During the time period leading up to the issuance of the initial severe thunderstorm warning, the dual-polarization radar data near the 0 °C altitude contained a positive differential reflectivity ZDR column (indicating a strong updraft lofting supercooled raindrops above the freezing level). Correlation coefficient ρHVreductions to ~0.93, probably due to the presence of growing hailstones, were observed above the freezing level in portions of the developing >55-dBZ echo core. Second, data from the National Lightning Detection Network (NLDN), including the locations and polarity of cloud-to-ground (CG) discharges produced by several of the evening’s storms, were processed. Some association was found between the prevalence of positive CGs and storms that produced severe hail. The analyses indicate that the use of the dual-polarization data provided by the upgraded Weather Surveillance Radar-1988 Doppler (WSR-88D), in combination with the NLDN data stream, can assist operational forecasters in the real-time identification of thunderstorms that pose a severe hail threat.2015/11/24 33