Assimilation of MODE-S EHS observations in HARMONIE

Assimilation of MODE-S EHS observations in HARMONIE

Cisco de Bruijn and Siebren de Haan

KNMI The Netherlands

15th EMS / 12th ECAM Sofia

Table of contents 1. Mode-S EHS observations 2. Data assimilation in HARMONIE 3. Case study 28 May 2013, optimal thinning 4. IMPACT experiment 2013111800 – 2013123118 5. Conclusions/Outlook

15th EMS / 12th ECAM Sofia 2

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Dutch Air Traffic Control (ATC) Projection on latitude-flight level plane 1.5 million observations per day Heading correction and quality control are applied

Reference De Haan, JGR 2011


Wind derived from tracking information

4 15th EMS / 12th ECAM Sofia

Data assimilation

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TTbb xHyxHyxxxxxJ ))(((R))(()(B)()( -1-1 −−+−−=

Pre-processing Quality control / screening Variational analysis / 3D VAR Minimalisation of the COST-function


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1. Preliminary check of observations (completeness of the reports) 2. Black listing (suspicious observations are rejected) 3. Background check against First Guess 4. Vertical consistency check (duplicated levels in multi-level reports are

removed) 5. Redundancy check (reports that are co-located and originate from

the same station are removed) 6. Thinning


Quality control / screening

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• Thinning along the flight track • The reports closest to the analysis date are selected • Radius sizes (Conventional:25km, Mode-S EHS:15km,5km)


Thinning of AIREPS


MUAC data, also radars from Belgium, Luxemburg, Germany (and Denmark) Wind data as function of pressure Frequency minimal 4 sec


MODE-S EHS 15 KM

MODE-S EHS 05 KM

CONVENTIONAL

Thinning Minimalization of the COST-function RFIND=15 km, 20% of the available Mode-S EHS data is used

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Meteorological impact, 28 May 2013 Convergence line and occlusion front

De Bilt

Cabauw




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-HARMONIE cy38h1.2 800 x 800 3h cycling 24 h forecast at 00 06 12 18 03 h forecast at 03 09 15 21 Dedicated B-matrix -Observations Mode-S EHS Thinned in time 15 min window around analysis time Thinned in space 15km -Verification against unused Mode-S EHS for different forecast times


Impact experiment 18.11.2013 – 31.12.2013


Wind 875 hPa

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Wind 400 hPa


Temperature 225 hPa


Conclusions • Assimilation of Mode-S EHS observations has a positive impact • Case-study shows that wind shift timing errors can be reduced • Better verification scores in wind and temperature on short-range forecast

Outlook: • 4D VAR data assimilation

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Research performed within SESAR WP 11.2 Further information: http://mode-s.knmi.nl


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Assimilation of MODE-S EHS observations in HARMONIE