motivation
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
Progress in Radar Assimilation at MeteoSwiss
Daniel Leuenberger1, Marco Stoll2 and Andrea Rossa3
1 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
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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
RadarModel
Rain
rate
Diabatic Heating
z
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.
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Observation weight w(x,y,t)
Quality function based on visibility of radar
Extendable (e.g. clutter maps…)
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22.7.2003 Case: Missed frontal convection
Free forecast
Assimilation
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2
2
2
1
2
0
1
9
1
8CTRL LHN RADAR
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Role of low-level Environment
OBS
CTRL from aLMo ANA 12UTC
LHN from aLMo ANA 12UTC
LHN from aLMo ANA 15UTC
Free forecast
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Impact of improved low-level environment
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 from12 UTCaLMo ANA
LHN from15 UTC aLMo ANA
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Response of model dynamics to forcing
OBS CTRL
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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
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Errors in Radar Data can be a Problem !
6h cumulated clear sky echo6h cumulated model response
6h Assimilation of Clear-Sky Echos (CAPE = 800 J/kg)
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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
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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
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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 testsLong periods including different weather situationsaLMo/7km and aLMo/2.2km configurations
Sensitivity tests Radar quality (ground clutter)Composite size (Swiss Composite vs. Eurocomposit)