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Motivation

Progress in Radar Assimilation at MeteoSwiss Daniel Leuenberger 1 , Marco Stoll 2 and Andrea Rossa 3 1 MeteoSwiss 2 Geographisches Institut, University of Bern 3 Centro meteorologico di Teolo, ARPA Veneto, Italy. Motivation. Convection often missed in the model model deficiencies

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Motivation

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  1. Progress in Radar Assimilation at MeteoSwissDaniel Leuenberger1, Marco Stoll2 and Andrea Rossa31 MeteoSwiss2 Geographisches Institut, University of Bern3 Centro meteorologico di Teolo, ARPA Veneto, Italy

  2. Motivation • Convection often missed in the model • model deficiencies • improper initial conditions • Prerequisites for convection • Prefrontal environment (instability,wind) • Trigger (frontal pressure disturbance,local low-level convergence) • Radar rainfall assimilation provides trigger at the right time and location

  3. z Rainrate Radar Model Diabatic Heating Latent Heat Nudging refresher • Simple, economic 4DDA scheme for radar rainfall • Forcing via buoyancy • Temperature adjustment given by ratio of radar and model precipitation • Vertical distribution given by model • Scale nearby or idealised profile if no suitable model profile is available

  4. LHN Experiments • aLMo with 7km grid size, diagnostic precipitation • 6 summer convection cases over Switzerland of airmass (2), prefrontal (2) and frontal (2) type • focus to role of low-level environment and response of model dynamics to radar forcing • mostly missed convection in CTRL runs, but one case was well captured • 3-6h assimilation duration • Best radar estimate of surface precipitation from 3 Swiss radar stations (clutter reduction, vertical profile correction), measurements 5min apart.

  5. Observation weight w(x,y,t) • Quality function based on visibility of radar • Extendable (e.g. clutter maps…)

  6. 22.7.2003 Case: Missed frontal convection CTRL LHN RADAR Assimilation 23 22 21 20 19 18 Free forecast

  7. Role of low-level Environment OBS CTRL from aLMo ANA 12UTC LHN from aLMo ANA 12UTC LHN from aLMo ANA 15UTC Free forecast

  8. Impact of improved low-level environment LHN from 12 UTC aLMo ANA 3h sums (+1 to +4 h free forecast) Additional three hours of conventional aLMo assimilation improve environment and thus precip forecast started from LHN! LHN from 15 UTC aLMo ANA

  9. Response of model dynamics to forcing OBS CTRL

  10. Findings • LHN is an effective convection trigger • Positive impact in QPF up to 5 hours • General improvement of postconvective environment (though sometimes locally too strong forcing during assimilation) • Weak overestimated precipitation is not sufficiently removed • Rapid loss of precipitation signals may be caused by wrong thermodynamical/dynamical PBL structure • Need to improve low-level atmosphere, particularly humidity

  11. 6h cumulated clear sky echo 6h cumulated model response Errors in Radar Data can be a Problem ! 6h Assimilation of Clear-Sky Echos (CAPE = 800 J/kg)

  12. Anaprop • Stable stratification (strong inversion) and no rain • assimilation of clear-sky echos (6h) • no model response (0% rain!) • updrafts of 6m/s (for PJC) and 12m/s (for OMC) are induced • no errorneous rain, but updrafts could possibly influence larger environment

  13. Findings • Non-meteorological echos can be drastically amplified by LHN in unstable, moist situations • Area of echo seems to be as important as amplitude • Wind can drift rain out of forcing area • Problem can be reduced by quality control of data and by filtering the input data in the model • Effect is reduced in drier or more stable situations

  14. Towards operational application • LHN promising for • very short-range forecasts (up to 12h) • rapid update cycle (aLMo/2, 18h forecasts per day, started every 3h) • use in concert with other observations, particularly surface observations • Extended tests • Long periods including different weather situations • aLMo/7km and aLMo/2.2km configurations • Sensitivity tests • Radar quality (ground clutter) • Composite size (Swiss Composite vs. Eurocomposit)

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