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Use of radar data in modelling at the Met

Office (UK)

Bruce Macpherson

Mesoscale Assimilation, NWP

Met Office

EWGLAM / COST-717 Joint Session

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Outline Radar data for assimilation into:

– atmospheric models

– land surface models

Radar data for NWP model verification Radar data for model validation

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Rainfall Assimilation at the Met Office

1996 - Operational assimilation of 3-hourly rain rates from UK weather radar network into Mesoscale Model

1997 - NWP forecast impact studies on radar data 1997 - test assimilations of lightning data as proxy rainfall 1998 - Assimilation of hourly radar data 2000 - Radar Quality Estimate used in assimilation 2001/2 - French & German radars added to UK composite

2003 - Retuning for ‘New Dynamics’ model version

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Radar Data Impacts - objective scores

(v radar analyses)

Period 1 - significant benefit up to t+6/12

Period 2 - neutral signal

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Radar Data Impacts - subjective

OPER

t+15

NO radar

assimilation

t+15

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Radar Data Impacts: hourly v 3-hourly data

3-hourly

radar data

Hourlyradar data

T+3 T+3

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Radar Data Impacts: hourly v 3-hourly data

3-hourlyhourly

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Relative importance of radar assimilation for short-period rain

forecasts

Radar &

satellite

aircraft

surface

No of Cases

showing

benefit

sonde

Light rain

Heavy rain

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Radar Coverage and Quality

Estimate(Nimrod system)

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Mesoscale Model Rainfall Assimilation

Data: hourly surface rain rates, pure radar -no gauge/satellite

QC & processing (with help from NWP):– clutter & anaprop removal -- bright band correction

– range correction -- orographic enhancement

– weekly radar calibration v gauge Monthly

Totals

Raw radar

Corrected

radar

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Mesoscale Model Rainfall Assimilation (II)

Averaging: 5km raw data ==> 15km (model ~12km)

Assimilation: latent heat nudging (LHN)

– target rainfall analysis Ran = (Rmod + W Robs) / (1+W)

– Robs interpolated from hourly values to model timestep

– assimilation increments ( T) filtered on scale 2x

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Land Surface Assimilation For agricultural and hydrological products, soil

moisture input to mesoscale model Current system: “MORECS”

– rainfall data ~150 daily gauges over UK

– weekly analysis on 40km grid

– interpolated variable is % of average annual rainfall

New system: “Soil State Diagnosis Model (SSDM)”– rainfall data: Nimrod radar analysis

– hourly analysis on 5km grid (same as SSDM)

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UK Mes soil moisture

Relax to climatology

Radar

artefacts

MORECSNimrod SSDM

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Radar wind assimilation

VAD profile availability

(CWINDE project)

• operational since 2001

• monthly monitoring

• quarterly quality reports

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Radar data to verify NWP rainfall forecasts

on monthly timescale, gauges and ‘corrected’ radar tell roughly same overall story

Model skill

Month ==>

v gauge

v radar

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Global Model precipitation verification over U.K

Models 6 models, mostly 09/2000-10/2002 12Z runs up to 72h 24h accumulation up-/down-scaled to 96*96 km2 by box

averaging Observations corrected radar data upscaled to 96*96 km2 by box averaging

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Global Model precipitation verification over U.K., 0-24h

forecasts

Frequency bias

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LAM verification v UK radar

UK Mesoscale DWD LM Hirlam reference …any more?

Work in progress for:

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For short NWP trials and batches of case studies, radar provides – better spatial sampling than gauges

– clearer link with forecaster’s subjective assessment

v radar

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…..radar may allow study of model behaviour with higher resolution in time

Mesoscale Model trial verification

Frequency bias for

hourly totals > 0.17mm

(v Nimrod radar)

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and maps of verification v radar can begin to show land/sea differences

v radar

Rain/no-rain (>0.4 mm/6hrs)Frequency bias t+12-18 hr forecasts

autumn 2000

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Observations of Evaporation

02 Apr 2000 11 Dec 1999

94GHz Radar-Derived Ice Water Content (below 0ºC)

Radar data provided by Robin Hogan (Reading Univ.) and RCRU (RAL)

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Model/Obs Comparison

Average ice evaporative depth scale from the Chilbolton 94 GHz cloud radar and the operational UM for 20 separate days in Oct, Nov, Dec 1999.

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FASTEX IOP 16: ValidationComparison of the reference and modified model ice evaporative depth scales with

94GHz radar observation statistics

Average depth scale

Reference:1260 m

Modified: 780 m

Obs: 640 m (160m)

Modified model = higher vertical resolution, double ice evaporation rate and two thirds of ice fall speed

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Impact of including rain advection on rainfall distribution.

Rainfall rate (mm/hr) Orography (m)Rainfall rate difference (advection-no advection)

10hr model forecast.

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VerificationDartmoor River Catchment Rainfall

3 Hour Accumulations

Avon & Erme

Dart

Teign

Tamar

Exe

With Rain AdvectionNo Rain Advection

Radar 2km Model Forecasts

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VerificationCorrelation between model surface rainfall

and NIMROD radar-derived surface rainfall for Dartmoor

With Rain AdvectionNo Rain Advection

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Future Plans

Limited area 4D-Var operational 2005– with radar derived surface rainfall data in 2006

Experimental 4D-Var assimilation of radar radial winds

– project with Salford University Partial Dopplerisation of UK radar network

– 7 radars by 2006 Convective scale model by 2008

– develop radar verification techniques– establish viable radar assimilation method

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Questions?