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Use of radar data in modelling at the Met Office (UK)

EWGLAM / COST-717 Joint Session. Use of radar data in modelling at the Met Office (UK). Bruce Macpherson Mesoscale Assimilation, NWP Met Office. Outline. Radar data for assimilation into: atmospheric models land surface models Radar data for NWP model verification

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Use of radar data in modelling at the Met Office (UK)

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  1. EWGLAM / COST-717 Joint Session Use of radar data in modelling at the Met Office (UK) Bruce Macpherson Mesoscale Assimilation, NWP Met Office

  2. Outline • Radar data for assimilation into: • atmospheric models • land surface models • Radar data for NWP model verification • Radar data for model validation

  3. 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

  4. Radar Data Impacts - objective scores (v radar analyses) Period 1 - significant benefit up to t+6/12 Period 2 - neutral signal

  5. Radar Data Impacts - subjective OPER t+15 NO radar assimilation t+15

  6. Radar Data Impacts: hourly v 3-hourly data 3-hourly radar data Hourly radar data T+3 T+3

  7. Radar Data Impacts: hourly v 3-hourly data 3-hourly hourly

  8. Relativeimportance of radar assimilation for short-period rain forecasts No of Cases showing benefit Light rain aircraft Radar & satellite sonde surface Heavy rain

  9. Radar Coverage and Quality Estimate(Nimrod system)

  10. 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 

  11. 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) • Robsinterpolated from hourly values to model timestep • assimilation increments ( T) filtered on scale 2x

  12. 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)

  13. UK Mes soil moisture MORECS Nimrod SSDM Radar artefacts Relax to climatology

  14. Radar wind assimilation VAD profile availability (CWINDE project) • operational since 2001 • monthly monitoring • quarterly quality reports

  15. Radar data to verify NWP rainfall forecasts • on monthly timescale, gauges and ‘corrected’ radar tell roughly same overall story v radar Model skill v gauge Month ==>

  16. 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

  17. Global Model precipitation verification over U.K., 0-24h forecasts Frequency bias

  18. LAM verification v UK radar Work in progress for: • UK Mesoscale • DWD LM • Hirlam reference • …any more?

  19. 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

  20. …..radar may allow study of model behaviour withhigher resolution in time • Mesoscale Model trial verification Frequency bias for hourly totals > 0.17mm (v Nimrod radar)

  21. and maps of verification v radar can begin to show land/sea differences Rain/no-rain (>0.4 mm/6hrs)Frequency biast+12-18 hr forecastsautumn 2000 v radar

  22. Observations of Evaporation 94GHz Radar-Derived Ice Water Content (below 0ºC) Radar data provided by Robin Hogan (Reading Univ.) and RCRU (RAL) 02 Apr 2000 11 Dec 1999

  23. 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.

  24. FASTEX IOP 16: Validation Comparison 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

  25. Impact of including rain advection on rainfall distribution. Rainfall rate difference (advection-no advection) Rainfall rate (mm/hr) Orography (m) 10hr model forecast.

  26. VerificationDartmoor River Catchment Rainfall 3 Hour Accumulations Exe Teign Dart Tamar Avon & Erme No Rain Advection With Rain Advection Radar 2km Model Forecasts

  27. VerificationCorrelation between model surface rainfall and NIMROD radar-derived surface rainfall for Dartmoor No Rain Advection With Rain Advection

  28. 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

  29. Questions?

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