applications of nwp and radar-based qpf techniques for flash flood and landslip warnings in hong...
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![Page 1: Applications of NWP and Radar-based QPF Techniques for Flash Flood and Landslip Warnings in Hong Kong International Workshop on Flash Flood Forecasting](https://reader038.vdocuments.us/reader038/viewer/2022102622/56649d395503460f94a12f30/html5/thumbnails/1.jpg)
Applications of NWP and Radar-Applications of NWP and Radar-based QPF Techniques for Flash based QPF Techniques for Flash
Flood and Landslip Warnings in Hong Flood and Landslip Warnings in Hong KongKong
International Workshop on Flash Flood ForecastingInternational Workshop on Flash Flood ForecastingSan Jose, Costa RicaSan Jose, Costa Rica 13 - 17 March 200613 - 17 March 2006
Edwin S.T. Lai Edwin S.T. Lai Hong Kong ObservatoryHong Kong Observatory
134A Nathan Road, Kowloon, Hong Kong134A Nathan Road, Kowloon, Hong Kong
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Presentation OutlinePresentation Outline
• Rain-related Hazards in Hong KongRain-related Hazards in Hong Kong
• QPF in support of Warning SystemsQPF in support of Warning Systems
• Symbiotic Evolution of Forecast and Symbiotic Evolution of Forecast and Warning SystemsWarning Systems
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Presentation OutlinePresentation Outline
• Rain-related Hazards in Hong KongRain-related Hazards in Hong Kong
• QPF in support of Warning SystemsQPF in support of Warning Systems
• Symbiotic Evolution of Forecast and Symbiotic Evolution of Forecast and Warning SystemsWarning Systems
![Page 4: Applications of NWP and Radar-based QPF Techniques for Flash Flood and Landslip Warnings in Hong Kong International Workshop on Flash Flood Forecasting](https://reader038.vdocuments.us/reader038/viewer/2022102622/56649d395503460f94a12f30/html5/thumbnails/4.jpg)
Mechanisms leading to Mechanisms leading to Heavy rain over southern Heavy rain over southern ChinaChina• Rainstorms over southern China display Rainstorms over southern China display
full range of spatial and temporal full range of spatial and temporal characteristics characteristics – Monsoon trough – warm moist air from south Monsoon trough – warm moist air from south
merging with cool dry air from the north merging with cool dry air from the north (spring, summer, autumn)(spring, summer, autumn)
– Convergence between Indochina southwest Convergence between Indochina southwest monsoon and Pacific ridge (summer)monsoon and Pacific ridge (summer)
– Tropical cyclone nearbyTropical cyclone nearby– Land-sea coastal effectsLand-sea coastal effects
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Computer Drainage Models and FlComputer Drainage Models and Flood Hazard Mapsood Hazard Maps
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Sheung ShuiSheung Shui (Northern New Terri (Northern New Territories)tories), 2001, 2001
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Wing Kei Tsuen, 2001Wing Kei Tsuen, 2001
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Collection of Hydrological data By Collection of Hydrological data By DSD Wireless Flow Gauging StatioDSD Wireless Flow Gauging Stationn
Alert Level
Sensor
Warning to Local
Villagers
Telemetry
• Warnings will be issued when floodwater Warnings will be issued when floodwater reaches a predetermined alert level. reaches a predetermined alert level.
• Warning signals are disseminated automatically Warning signals are disseminated automatically through flood sirens or via automatic telephone through flood sirens or via automatic telephone calls to village representatives. calls to village representatives.
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Village Flood Pumping Scheme Village Flood Pumping Scheme –– Conceptual LayoutConceptual Layout
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Shenzhen River Regulation Shenzhen River Regulation ProjectProject
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Tsuen Wan, 2001Tsuen Wan, 2001
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Mongkok, 1997Mongkok, 1997
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Drainage TunnelsDrainage Tunnels
下游市區DownstreamUrban Area
中上游半山Upstream
Urban Area
填海區Reclaimed Area
Intercepting tunnel
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Tai Hang Tung Stormwater Storage Tai Hang Tung Stormwater Storage TankTank
Capacity = Capacity = 100,000 cu. m100,000 cu. m
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Presentation OutlinePresentation Outline
• Rain-related Hazards in Hong KongRain-related Hazards in Hong Kong
• QPF in support of Warning SystemsQPF in support of Warning Systems
• Symbiotic Evolution of Forecast and Symbiotic Evolution of Forecast and Warning SystemsWarning Systems
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Presentation OutlinePresentation Outline
• Rain-related Hazards in Hong KongRain-related Hazards in Hong Kong
• QPF in support of Warning SystemsQPF in support of Warning Systems
• Symbiotic Evolution of Forecast and Symbiotic Evolution of Forecast and Warning SystemsWarning Systems
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Rainstorm WarningsRainstorm Warnings
• floodingflooding in some low-lying and poorly in some low-lying and poorly drained areasdrained areas
• Key Key GovernmentGovernment departments and departments and major major transporttransport and and utilityutility operators operators are put on are put on alertalert. .
• publicpublic will be given clear will be given clear adviceadvice on on the appropriate actions to take.the appropriate actions to take.
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Special Announcement Special Announcement on Flooding in the on Flooding in the Northern New TerritoriesNorthern New Territories • criterioncriterion for issuance is based on heavy for issuance is based on heavy rainrain
having fallen in the northern New Territories. having fallen in the northern New Territories.
• Drainage Services DepartmentDrainage Services Department– clear blocked drains and watercourses in the clear blocked drains and watercourses in the
northern NTnorthern NT
• emergency response departmentsemergency response departments – evacuation and rescue evacuation and rescue – emergency treatmentemergency treatment– transport of casualties to hospitalstransport of casualties to hospitals
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Hong Kong Observatory’s Hong Kong Observatory’s Nowcasting System - SWIRLSNowcasting System - SWIRLS
• SShort-range (0 - 3 hort-range (0 - 3 hours)hours)
• WWarning ofarning of• IIntense ( > 30 mm per ntense ( > 30 mm per
hour) hour) • RRainstorms inainstorms in• LLocalized ( 10 - 100 km)ocalized ( 10 - 100 km)• SSystemsystems
• Operational since 1998, Operational since 1998, originally for rainstorm, originally for rainstorm, but has evolved into a but has evolved into a multi-function systemmulti-function system
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2/12
22
2
2
12
1
2121
- )( - )(
)()(1
- )()( R
kk
k k k
ZNkZZNkZ
kZkZN
kZkZ
TREC (Pattern Matching)TREC (Pattern Matching)
Searching radius
Pixel matrix
Maximum correlatedpixel matrix
TREC vector
T T – 6min
Searching radius
0.5, 1, 1.5, 2, … 5 km CAPPI
64, 128, 256 km range
where Z1 and Z2 are the reflectivity at T+0 and T+6min respectively
Searching radiusSearching radius :: 55 ,, 1010 ,, 20 20 km km ((64, 128 and 256 km CAPPI64, 128 and 256 km CAPPI))Pixel matrix sizePixel matrix size :: 5, 10, 20 km 5, 10, 20 km ((64, 128 and 256 km CAPPI64, 128 and 256 km CAPPI))Max resolvableMax resolvable :: 50, 100, 200 km/h50, 100, 200 km/h ( (64, 128 and 256 km CAPPI64, 128 and 256 km CAPPI))ResolutionResolution :: 1.3, 2.6, 5.2 km/h1.3, 2.6, 5.2 km/h ( (64, 128 and 256 km CAPPI64, 128 and 256 km CAPPI))
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TREC fields in Weather TREC fields in Weather SystemsSystems
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GEO + DSD + HKO rain gaugesGEO + DSD + HKO rain gauges
Total ~ 140, update frequency 5 minsMean distance x, y ~ 1.5 km
HKO rain gauge
HKO AWS
GEO rain gauge
DSD rain gauge
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Direct Matching – Direct Matching – Dynamic Dynamic Z-RZ-R relation relation Z = aRZ = aRbb
An adaptive Z-R relation (updated every 5 min.)
dBZ = 10*log(a) + 10*b*log(R)
1 km radar reflectivityZ: 00, 06, 12, … min
140 rain gaugesR: 05, 10, 15, … min
20
25
30
35
40
45
50
55
60
5 7 9 11 13 15 17 19 21
dBG
dBZ
Searching radius
Adjustable data assimilation window
140
1
2)(mini
ii dBRdBG bdBRadBZ log10
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Modified Semi-Lagrangian Modified Semi-Lagrangian Advection SchemeAdvection Scheme
• Robert scheme (3 iterations)Robert scheme (3 iterations)
• Bi-cubic Lagrangian interpolationBi-cubic Lagrangian interpolation
• Flux limiter (local max, min constraint)Flux limiter (local max, min constraint)
• One-way nestedOne-way nested– resolution 1.1km -> 0.5kmresolution 1.1km -> 0.5km
• Non-conservative, to allow:Non-conservative, to allow:– growth/decay (intensity profile easily to be added)growth/decay (intensity profile easily to be added)– echo entering, departing the domainecho entering, departing the domain
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Forecast reflectivityForecast reflectivity
TREC wind Forecast reflectivityUp to 6 hr (6-min interval)
FCT hour 0hr 1hr 2hr 3hr 4hr 5hr 6hr
Max. ratio 1.00 0.98 0.97 0.96 0.96 0.96 0.94
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Extrapolation of pure rotationExtrapolation of pure rotation
FCT hour 0hr 1hr 2hr 3hr 4hr 5hr 6hr
Max. ratio 1.00 0.98 0.98 0.97 0.97 0.97 0.96
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Quantitative Precipitation ForecastQuantitative Precipitation Forecast
4 steps:4 steps:• Storm Tracking (radarStorm Tracking (radar reflectivityreflectivity))
– TREC winds (Tracking Radar Echoes by Correlations) TREC winds (Tracking Radar Echoes by Correlations) • Adaptive Adaptive Z-RZ-R relation relation
– Dynamically calibrate radar reflectivity using rain gauge data Dynamically calibrate radar reflectivity using rain gauge data • EExtrapolationxtrapolation
– linear: upwind advection or semi-Lagrangian advectionlinear: upwind advection or semi-Lagrangian advection• IntegrationIntegration
– Forecast 1, 2, up to 3 hr accumulated rainfallForecast 1, 2, up to 3 hr accumulated rainfall
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TREC QPF (1 – 3 hours)TREC QPF (1 – 3 hours)
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SWIRLS rainfall forecast for a rainstormSWIRLS rainfall forecast for a rainstorm
SWIRLS 1-hr forecast Actual rainfall (rain-gauge)
TREC winds
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Actual rainfall (rain gauge) SWIRLS 1hr rainfall forecast
SWIRLS rainfall forecast for a TyphoonSWIRLS rainfall forecast for a Typhoon
20:00 HKT, 2 Sep 2003
20:12 HKT, 2 Sep 2003
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SWIRLS Landslip Warning Forecast
GEO Studies → factors contributing to landslip : 24-hr accumulated rainfall vulnerable area
Based on 1982-1997 data
• Each grid has 4Each grid has 4 slope slope types and percentagestypes and percentages ::– Soil-cut (Soil-cut ( 切削泥斜坡切削泥斜坡))– Fill (Fill ( 填土坡填土坡))– Rock-cut (Rock-cut ( 切削石斜坡切削石斜坡))– Wall (Wall ( 擋擋土墙土墙))
RF (min)RF (min) RF (max)RF (max) weightweight
00 0.10.1 00
0.50.5 5050 0.0000039750.000003975
5050 100100 0.0000107270.000010727
100100 150150 0.000028950.00002895
150150 200200 0.0000781290.000078129
200200 250250 0.0002108940.000210894
250250 300300 0.0005690250.000569025
300300 20002000 0.001535650.00153565
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SWIRLS Landslip ForecastSWIRLS Landslip Forecast
• If fIf forecastorecast >= 15 landslip to occur -> issue Landslip Warning >= 15 landslip to occur -> issue Landslip Warning
• 24 accumulated rainfall = 24 accumulated rainfall = past 21 hr accumulated rainfall (actual) + future 3-hr rainfall past 21 hr accumulated rainfall (actual) + future 3-hr rainfall (forecast)(forecast)
= 21hr (actual) + 3hr (forecast)
SWIRLS QPF
No. of landslip occurrence as function of 24 hr accumulated rainfall and total vulnerable area
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SWIRLS 3hr accumulated rainfall SWIRLS 3hr accumulated rainfall forecastforecast
Past 21hr rain gauge accumulated Past 21hr rain gauge accumulated rainfallrainfall
5 May 2003 – prolonged rainfall 5 May 2003 – prolonged rainfall brought by a low pressure troughbrought by a low pressure trough
Landslip Warning Criteria reached = 8:40 HKTSWIRLS forecast warning reached = 5:42 HKTLead time = 2:58 hr
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Verification of SWIRLS Verification of SWIRLS WarningsWarnings
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Verification of SWIRLS Verification of SWIRLS WarningsWarnings
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Presentation OutlinePresentation Outline
• Rain-related Hazards in Hong KongRain-related Hazards in Hong Kong
• QPF in support of Warning SystemsQPF in support of Warning Systems
• Symbiotic Evolution of Forecast and Symbiotic Evolution of Forecast and Warning SystemsWarning Systems
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Presentation OutlinePresentation Outline
• Rain-related Hazards in Hong KongRain-related Hazards in Hong Kong
• QPF in support of Warning SystemsQPF in support of Warning Systems
• Symbiotic Evolution of Forecast and Symbiotic Evolution of Forecast and Warning SystemsWarning Systems
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HazardsHazards
DisastersDisasters
HazardsHazards
DisastersDisasters
PoliticalPoliticalBacklashBacklash
PoliticalPoliticalBacklashBacklash
IdentificationIdentificationofof
StakeholdersStakeholders
IdentificationIdentificationofof
StakeholdersStakeholders
NMSNMS
Major Players(e.g. hydrologists)
Major Players(e.g. hydrologists)
Key Users(e.g. Disaster Managers)
Key Users(e.g. Disaster Managers)
Peripheral UsersPeripheral Users
Action PlanAction PlanAction PlanAction Plan
ResponseActions
ResponseActions
WarningSystem
WarningSystem
?
ForecastSystem
Development
ForecastSystem
Development
NMS Collaborationwith Major Players
and Key Users
NMS Collaborationwith Major Players
and Key Users
Something cannot be done and is not done.Disaster struck and something has to be done.Something was crudely done and remains crudely done.Until the next disaster struck when all were undone………
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A Good Warning SystemA Good Warning System
does not end with the warning bulletins leaving the does not end with the warning bulletins leaving the forecast officeforecast office
offers a platform with agreed terminology for ready offers a platform with agreed terminology for ready exchange of information on expected scenariosexchange of information on expected scenarios
manages expectations of stakeholders and users, manages expectations of stakeholders and users, “downscaling” problems into something more “downscaling” problems into something more manageablemanageable
prompts prompt actions from decision-makers, prompts prompt actions from decision-makers, vulnerable groups and those at riskvulnerable groups and those at risk
provides incentive for further development of provides incentive for further development of forecasting toolsforecasting tools
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From Action to Information EndFrom Action to Information End
Consolidate stakeholders’ requirementsConsolidate stakeholders’ requirements Design warning system that can address the Design warning system that can address the
key issueskey issues Assess technical feasibility and develop Assess technical feasibility and develop
necessary technical support for forecastingnecessary technical support for forecasting If technically not feasible, go back to If technically not feasible, go back to
stakeholders and re-work the process until a stakeholders and re-work the process until a level of balance and synergy is reached level of balance and synergy is reached between forecasting and warning systemsbetween forecasting and warning systems
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Three Most Popular DemandsThree Most Popular Demands
Extended QPFExtended QPF Forecast of “Warnings”Forecast of “Warnings” Location-specific/time-specific QPFLocation-specific/time-specific QPF
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Three Most Popular DemandsThree Most Popular Demands
Extended QPFExtended QPF Forecast of “Warnings”Forecast of “Warnings” Location-specific/time-specific QPFLocation-specific/time-specific QPF
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RAPIDSRAPIDS(Rainstorm Analysis and Prediction Integrated Data-processing System)(Rainstorm Analysis and Prediction Integrated Data-processing System)
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Three Most Popular DemandsThree Most Popular Demands
Extended QPFExtended QPF Forecast of “Warnings”Forecast of “Warnings” Location-specific/time-specific QPFLocation-specific/time-specific QPF
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SWIRLS Amber Verification SWIRLS Amber Verification (May)(May)
• CorrectCorrect (73%) (73%)Amber: Amber: 5/11 (46%)5/11 (46%)No amber:No amber:3/11 (27%)3/11 (27%)
• WrongWrong (27%) (27%)FAR:FAR:3/11 (27%)3/11 (27%)NAP:NAP:0/11 (0%)0/11 (0%)
• Lead timeLead time::35 minutes35 minutes
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SWIRLS Amber Verification SWIRLS Amber Verification (Jun)(Jun)• CorrectCorrect (55%) (55%)
Amber: Amber: 4/18 (22%)4/18 (22%)No amber:No amber:6/18 (33%)6/18 (33%)
• WrongWrong (45%) (45%)FAR:FAR:5/18 (28%)5/18 (28%)NAP:NAP:3/18 (17%)3/18 (17%)
• Lead timeLead time::20 minutes20 minutes
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SWIRLS Amber Verification SWIRLS Amber Verification (Jul)(Jul)• CorrectCorrect (86%) (86%)
Amber: Amber: 3/7 (43%)3/7 (43%)No amber:No amber:3/7 (43%)3/7 (43%)
• WrongWrong (14%) (14%)FAR:FAR:0/7 (0%)0/7 (0%)NAP:NAP:1/7 (14%)1/7 (14%)
• Lead timeLead time::45 minutes45 minutes
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SWIRLS Amber Verification SWIRLS Amber Verification (Aug)(Aug)
• CorrectCorrect (57%) (57%)Amber: Amber: 3/7 (43%)3/7 (43%)No amber:No amber:1/7 (14%)1/7 (14%)
• WrongWrong (43%) (43%)FAR:FAR:2/7 (29%)2/7 (29%)NAP:NAP:1/7 (14%)1/7 (14%)
• Lead timeLead time::37 minutes37 minutes
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7 types of rainstorm7 types of rainstorm
• Land-sea breeze/Weak Northerly Storms (LS)Land-sea breeze/Weak Northerly Storms (LS)• Quasi-stationary Southwesterly Rainbands (QU)Quasi-stationary Southwesterly Rainbands (QU)• Southesterly Rainbands (SE)Southesterly Rainbands (SE)• Squall-lines/Bow Echoes (SQ)Squall-lines/Bow Echoes (SQ)• Supercells (SU)Supercells (SU)• Tropical Cyclone Rainbands (TC)Tropical Cyclone Rainbands (TC)• X-type Rainbands (X)X-type Rainbands (X)
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7 Rainstorm Types7 Rainstorm Types
LS
QU
SE
SQ
SU TC X
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LSLS
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QUQU
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SESE
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SQSQ
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SUSU
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TCTC
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XX
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Data sourceData source
• 2001 – 2005 all rainstorms either triggered Amber, Red,2001 – 2005 all rainstorms either triggered Amber, Red, Black, Landslip or Flooding Warning Black, Landslip or Flooding Warning
• A total of 73 rainstorm casesA total of 73 rainstorm cases• 800 hours of radar images800 hours of radar images• 8000 TREC images; 8000 GTrack images8000 TREC images; 8000 GTrack images
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Distribution (Occurrence)Distribution (Occurrence)7 rainstorm types during 2001-7 rainstorm types during 2001-2005)2005)
0
5
10
15
20
25
30
35
40
LS QU SE SQ SU TC X
Occ
urre
nce
• QU – 43%QU – 43%
• X – 18%X – 18%
• LS – 14%LS – 14%
• SQ – 10%SQ – 10%
• TC – 8%TC – 8%
• SE – 6%SE – 6%
• SU – 3%SU – 3%
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GTrack Cell Features AnalysiGTrack Cell Features Analysiss
ellipse
AdbZI
ab
aEP
aba
abA
)/(tan
),2/(4
/
1
22
max dBZ <--> max rainfallave dBZ <--> ave rainfallmax50% rainfallmax25% rainfall (upper quartile)
x
ye.g. 128 km,3km CAPPI, 39dBZ threshold
a (major axis)
b (minor axis)
(orientation)
V
(TREC speed and direction)
Area
Eccentricity
Perimeter
Orientation
TotalIntensity
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Sample Feature MatrixSample Feature MatrixTable 1 - Frequency distribution of various radar parameters extracted from the 3-km CAPPI 128-km range 39-dBZ threshold TREC/GTrack analyses for
different rainstorm types. On each column, scales on the x-axes are the same. Scales on the y-axes are 0 to 100%.
Parameter
(unit)
x-axis
scale
Type of
Rainstorm
TREC
Speed
(km/hr)
0 100
TREC
Direction
(bearing)
0 360
Eccentricity
0 1.0
Orientation
(bearing)
0 180
Area
(km2)
0 1000
APR
(km)
0 20
Upper-quartile
rainfall
(mm/hr)
20 200
Total
Intensity
(km2-dBZ)
104 105
LS
QU
SE
SQ
SU
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Implications on Warning Implications on Warning StrategiesStrategies
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ConclusionsConclusions
• Not All Rainstorms Are Created Equal!Not All Rainstorms Are Created Equal!– Different rainstorm carries different impactDifferent rainstorm carries different impact– Different rainstorm shows different feature matrixDifferent rainstorm shows different feature matrix
• Rainstorm databank for more systematic Rainstorm databank for more systematic studiesstudies
• Classification process can be automated for Classification process can be automated for objective analysisobjective analysis– Feature space (matrices)Feature space (matrices)– Cluster analysisCluster analysis– Artificial Neural NetworkArtificial Neural Network
• Conceptual Framework for Warning DecisionConceptual Framework for Warning Decision
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Three Most Popular DemandsThree Most Popular Demands
Extended QPFExtended QPF Forecast of “Warnings”Forecast of “Warnings” Location-specific/time-specific QPFLocation-specific/time-specific QPF
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Three Most Popular DemandsThree Most Popular Demands
Extended QPFExtended QPF Forecast of “Warnings”Forecast of “Warnings” Location-specific/time-specific QPFLocation-specific/time-specific QPF
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Three Most Popular DemandsThree Most Popular Demands
Extended QPFExtended QPF Forecast of “Warnings”Forecast of “Warnings” Location-specific/time-specific QPFLocation-specific/time-specific QPF
– At this moment in time, we may consider such At this moment in time, we may consider such demands to be unrealistic. But then we re-wind demands to be unrealistic. But then we re-wind back to ten years ago when we thought it would back to ten years ago when we thought it would be impossible to do what we are routinely doing be impossible to do what we are routinely doing now, and we think again and say: “Maybe we now, and we think again and say: “Maybe we shall see …….”shall see …….”
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Presentation OutlinePresentation Outline
• Rain-related Hazards in Hong KongRain-related Hazards in Hong Kong
• QPF in support of Warning SystemsQPF in support of Warning Systems
• Symbiotic Evolution of Forecast and Symbiotic Evolution of Forecast and Warning SystemsWarning Systems
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Emerging Technology for Emerging Technology for FFFFFF
• Meteorologists’ angleMeteorologists’ angle– QPE (?)QPE (?)– QPF (??)QPF (??)– EPS (???)EPS (???)
• Hydrologists’ angle (????)Hydrologists’ angle (????)• IT angleIT angle
– Computer processing powerComputer processing power– Visualization and displayVisualization and display– IT methodology and AI algorithmsIT methodology and AI algorithms– Telecommunication and enhanced connectivityTelecommunication and enhanced connectivity
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Emerging Technology for Emerging Technology for FFFFFF
• Meteorologists’ angleMeteorologists’ angle– QPE (?)QPE (?)– QPF (??)QPF (??)– EPS (???)EPS (???)
• Hydrologists’ angle (????)Hydrologists’ angle (????)• IT angleIT angle
– Computer processing power Computer processing power – Visualization and displayVisualization and display– IT methodology and AI algorithmsIT methodology and AI algorithms– Telecommunication and enhanced connectivityTelecommunication and enhanced connectivity
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Emerging Technology for Emerging Technology for FFFFFF
• Meteorologists and hydrologists Meteorologists and hydrologists joining forces to attain 60-min joining forces to attain 60-min reliable warning lead time.reliable warning lead time.
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Emerging Technology for Emerging Technology for FFFFFF
• Meteorologists and hydrologists Meteorologists and hydrologists joining forces to attain 60-min joining forces to attain 60-min reliable warning lead time.reliable warning lead time.
• But only good IT utilization and But only good IT utilization and applications can make that 60 applications can make that 60 minutes productive and meaningful!minutes productive and meaningful!
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Thank YouThank You