stefan klink data assimilation section [email protected]

08.10.2003 - 1 -Joint SRNWP/COST-717 WG-3 session, Lisbon

Stefan Klink

Data Assimilation Section

[email protected]

Early results with rainfall assimilation at DWD

RADVOR-OP, supported by LAWA


Early results with rainfall assimilation at DWD

Radar data

Real case study– Humidity adjustment– Filtering of vertical profiles– Influence of convective parameterisation scheme– Influence of mesh size

Summary


Radar data

Input data currently used

• radar reflectivity at the ground (int. Composite: Germany and surrounding countries)

• pixel size: 4km 4km

• time resolution: 15 minutes (data from volume scan)

• conversion: reflectivity to precipitation rate by simple Z-R-relation

• problems: clutter, only 7 reflectivity classes


Radar data

„new“ radar data

• input data: reflectivities from precipitation scan, mesh: 1km 1°, time resolution: 5 minutes

• correction of orographic attenuation

• variable Z-R-relation

• compositing

• still incomplete clutter correction


Real case study: experimental setup

• Convective event on 28. Aug. 2002 over western Germany

• LM runs on the operational domain:– mesh size 7 km

• LM runs on an experimental domain:– covering almost Germany– mesh size 2.8 km

• convective parameterisation scheme switched off

• laterally driven by GME

• 6h Nudging + LHN starting at 6 UTC– adjustment of humidity during LHN

• 6h free forecast starting at 12 UTC

operational domain (7 km)

experimental domain (2.8 km)

evaluation domain


Real case study: humidity adjustment

• Increased heating increase q to reach f=100% over nudging timescale

• Reduced heating decrease q (maintain f)



LM runs on the experimental domain: – mesh size 2.8 km

• without humidity adjustment during LHN

• with humidity adjustment during LHN



Hourly sums of modeled and radar-observed precipitation in mm/h

• Nudging 08-09 UTC

• Nudging11-12 UTC



• free forecast14-15 UTC


Real case study: filtering of vertical profiles

vertical cross section W-E, t = 11 UTC, with humidity adjustment specific cloud liquid water content in g/kg

no filtering filtering


Real case study: influence of convective parameterisation scheme

LM runs on the operational domain: – mesh size 7 km– no adjustment of humidity during LHN

• without convective parameterisation scheme

• with convective parameterisation scheme



• Nudging

11-12 UTC

• free forecast

12-13 UTC



• free forecast

14-15 UTC


Case Studies: comparison: mesh sizes 7 km and 2.8 km

LM runs:

• CTRL 7 km:– mesh size 7km (operational domain)

• LHN 7 km: – mesh size 7 km (operational domain)

• LHN 2.8 km:– mesh size 2.8 km (smaller model domain)




• Nudging06- 07 UTC




• Nudging

11-12 UTC

• free forecast

12-13 UTC



• free forecast

14-15 UTC

• free forecast

17-18 UTC


Summary

• Results:

– adjustment of humidity supports the assimilation of precipitation and leads to more exact free forecasts

– explicit simulation of convection produces more realistic patterns and amounts of precipitation than the corresponding model run with a parameterisation scheme

– model with 2.8 km mesh size shows potential for further improvements of precipitation forecast

– sporadical occurrence of spurious precipitation

– influence of the assimilation lasts for several hours


Summary

• Future work:

– numerical problems with noisy profiles of latent heat (2 z-structures)

– quality of radar data

– improvements to extend the influence of assimilation during free model run

– prognostic precipitation

stefan klink data assimilation section [email protected]

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