WEATHER RADAR FOR URBAN PLUVIAL FLOOD FORECASTINGProfessor Chris CollierNational Centre for Atmospheric Science, Head of Strategic PartnershipsUniversity of Leeds, UK

Impact of Flash Floods in Cities

Commercial district of Istanbul, September 2009At least 20 people died in Istanbul

7 drowned in a minibus going to work

Urban drainage• In many urban areas of England

the UDS is complex, and in parts old and in need of refurbishment.

• Sewage discharges to natural water courses

• Accurate high resolution (1km x 1km) rainfall measurements and forecasts needed.

• Changes in rainfall patterns and amounts may cause problems in UDS management.

Flood protection and forecasting

Why radar?• Wide area measurements of precipitation from a single location.• High resolution.

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High resolution (1 km) radar imagery 7 May 2000

Courtesy Met OfficeGreen on this map of Hull UK indicates areas that are prone to flooding

Rainfall totals measured at Ruislip, London and discharge from Yeading Brook West Branch on 8 May 1988

Bank full

1 in 100 yrs 1 in 25 yrs63.5 mm in 2.5 h 34.2 mm in 75 min

How radar works

Courtesy Met Office

The passage of line convection over London as observed by the Chenies C-band radar 7 December 2006, 1053UTC

Chenies

tornado

Courtesy Met Office

X-band radar

• Ease of siting

• Cost

• Mobility

• Less ground clutter provided one degree beamwidth used.

• Can detect smaller particles including the detection of light precipitation such as snow.

Advantages Disadvantages• Attenuation through rain,

snow and ice (hail) but can correct if polarisation capability exists.

• Very limited clear air measurements.

Polarization techniques offer increased accuracy for measuring heavy rain

60 dBZ core could be torrential rain or hail

Conventional Radar Reflectivity

Differential Phase Shift

Phase shift indicates torrential rain

Rain gauge confirmed 250mm/hour

Examples of mobile Doppler dual polarisation X-band radar

Selex Gematronik University of Auckland, NZ, Ardmore

Why do (some) hydrologists still distrust radar estimates of rainfall? Comparison with raingauges

Rainfall rate (mm h-1) on 21 June 2004, around 9:48 UTC, given by the Hameldon Hill C-band radar located some 24 km north

of the centre of Manchester, North West England.

Study domainStudy domain

Wind

Study domainStudy domain

Wind

Study domainStudy domain

WindWind

The red and white dot indicates Manchester city centre. This image is an example of the radar product used in this work (10 m in image, with 2 x 2 km2 spatial resolution).

Why we need to merge rainfall data?

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Rain

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Cumulative Rain Depth (23/08/2010 event)@Beal RG

Beal_RG Radar 1km

Amplification of radar errorsDischarge bias using radar data input to a stochastic model of the urban River Croal,

UK catchment compared to a model of the Baron Fork River USA catchment

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Croal August-September

January frontal

October squall line

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Fundamental Limitation of Widely Spaced Long Range Radars

High resolution numerical forecasts• 1-2 km grid lengths now beginning to be used

operationally.• Realistic forecasts now being produced, but problems

remain e.g. Representing sub-grid scale processes, although grid lengths of less than 1 km are also possible.

• These forecasts are expected to replace radar-based nowcasts for lead times beyond two hours or so.

• However the assimilation of radar data is likely to become an essential part of operational procedures.

Illustrating Cobbacombe radar 5 hour total rainfall (mm) (left panel) and 1 km UM forecast rainfall (mm) for 12-17 UTC 16 August 2004 (from Golding et al, 2005) [performance due in part to the dynamic impact of the sea breeze with orography which introduced a level of stationarity to the convection]

The problem of issuing an alert under flood forecasting uncertainty

Expected value= ForecastProbability of overflowLevelCostsCross section

(courtesy E. Todini)

Expected value= Forecast

Probability of overflow

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Costs

Cross section

(a) (b) (c)

Example of the exploitation of new data sources, data assimilation and ensemble techniques for storm and flood forecasting Boscastle storm

Case study: Boscastle storm (a) a ‘pseudo-ensemble’ of high-resolution 1 km NWP rainfall, (b) an ensemble of distributed hydrological model

simulations of river flow using the Grid-to-Grid (G2G) model, (c) comparison of G2G ensembles with observations for the River Tamar at Gunnislake (location and 1 km catchment boundary is given in (a) and (b)). (courtesy R. Moore and S.

Cole)

Concluding remarks• Radar data are likely to be the basis of forecasts for 1-2

hours ahead. However for longer lead times high resolution NWP forecasts assimilating radar data, offer the best hope of improvement to hydraulic and hydrological forecasts.

• It will be necessary to constrain uncertainty using both rainfall and hydrological model ensembles with statistical procedures.

• Rain Gain will produce a significant step forward in using X-band radar data within the context of operational radar networks.