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5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
QUEST
Quantitative Evaluation of Regional Precipitation Forecasts Using Multi-
Dimensional Remote Sensing Observations
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Quantitative evaluation of regional precipitation forecasts using
multi-dimensional remote sensing observations
Partnership Susanne Crewell, Thorsten Reinhardt, University of Cologne (IGM) Jürgen Fischer, Anja Hünerbein, FU Berlin (FUB) George Craig, Martin Hagen, Monika Pfeifer, (DLR) Michael Baldauf, Deutscher Wetterdienst (DWD) Nicole van Lipzig, Ingo Meirold-Mautner, Katholieke Universiteit Leuven
(KUL), Belgium (QUEST-B)
Contributes to PQP Goals Identification of physical and chemical processes responsible for the
deficiencies in quantitative precipitation forecast Determination and use of the potentials of existing and new data and
process descriptions to improve quantitative precipitation forecast
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
satellite
MSG ~ 5km; 15min Cloud Mask Cloud top pressureMODIS ~ 1km; 1day Cloud Mask Optical thickness
IPT / Micro-wave
1D vertical; Lindenberg (and Cabauw) temperature profile humidity profile LWC
GPS
~ 147 stations; Germany; 15min IWV
Ceilometer
17 stations;Germany; 1min; ranges up to 4km Cloud base height Cloud cover (<4km)
Radar
DWD radar composite; 1km; 5min Rain rate RANIE combined radar and gauge analysisPolarimetric radar (DLR)
Quantitative evaluation of regional precipitation forecasts using multi-dimensional remote sensing observations (QUEST)
Observations
Surface: rain gauges
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
QUEST: StrategyObservations- multi-frequency radiances- polarimetric radar quantities- ground-based and space-borne observations
Forward Operator Retrieval
Weather Forecasts- three-dimensional description of the forecasted atmospheric state - focus on Lokal-Modell Kürzestfrist (LMK)
- SynPolRad (polari. radar)- SynSat (MSG, MODIS)- SynSatMic (AMSU, SSM/I)
- water vapour- cloud properties- precipitation
MODIS LM MESO-NH MM5MODIS LM MESO-NH MM5
Schröder et al. [2006]
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
QUEST: ApproachCase Studies (ongoing)
Model Sensitivity Runs
Tool development SynPolRad SynSat (-Mic) MSG µ-phys. retrievals verification measures ..
Hypothesis formulation"What are the crucial variables/processes
to observe and to improve?"
Model Improvement (new) cloud microphysics land surface turbulence
comparison tools test of hypotheses
Identification of systematic model deficits
Long-Term EvaluationLokal-Modell Kürzestfrist test suites GOP duration 2007 benefits of high
resolution modelling
Conditional verification regionalization diurnal cycle weather situation dep.
Cross correlation of different variables
"How important is physical consistency?"
case study selection for
process studies
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Case studies versus long-term evaluationC
ase
Stud
ies
Long
-Ter
m E
valu
atio
n
+ Detailed analysis
+ Formulation of hypothesis
+ Tool development
- Low significance
- Subjectively chosen cases
+ Sensitivity runs feasible /physical explanation
+ High significance
- Difficult to identify physical mechanism
- Automated analysis
+ Objective selection of cases
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
• Mesh size: x = 2.8 km • direct simulation of deep convection• convection parameterization for shallow part
only• assimilation of radar data by latent heat
nudging method
• timestep T=25 s• 421 x 461 x 50 gridpoints,
lowest model level in 10 m above surface
• Centre of domain: 10 °E, 50 °N• Forecast time: 21 h, started every 3 h• Boundary conditions from
Lokal-Modell Europa (“COSMO-LME”) with x = 7 km
Deutscher Wetterdienst‘sLokal-Modell Kürzestfrist (“COSMO-LMK”)
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
LMKRadar LM
Case study 26-08-2004 (M. Baldauf DWD)
3.9 mm/day 5.2 mm/day 3.4 mm/daymm/day
Accumulated precipitation over 24 hr
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
General Observation Period (GOP)Year 2007
http://gop.meteo.uni-koeln.de
Central activity of QUEST in second phase of PP.
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
gather as many data about the atmospheric state as possible within an area covering Germany and it neighboring states.
to provide information of all kinds of precipitation types
to identify systematic model deficits
to select case studies for specific problems
to relate the COPS results to a broader perspective (longer time series and larger spatial domain)
GOP Organization and PerformanceThe General Observation Period ─ January to December 2007 ─ encompasses COPS in time and space
http://gop.meteo.uni-koeln.de
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
GOP
Partnership Karl Bumke (IFM-Geomar) Disdrometer observations (WP 3) Susanne Crewell (IGM) Overall GOP organisation Galina Dick (GFZ) GPS observations (WP 5) Jürgen Fischer (FUB) Satellite observations (WP 7) Martin Hagen (DLR) GOP weather radar data (WP 2) Thomas Hauf (UHan) Lightning networks (WP 6) Christian Koziar (Thomas Hanisch) (DWD) Access to DWD observations (all WPs) Armin Mathes (Univ. Bonn) Coordination/QC rain gauges (WP 1) Mario Mech (IGM) GOP data management Gerhard Peters (UHH) Micro Rain Radar (WP 3) Matthias Wiegner (LMU) EARLINET Observations (WP 4) and many more
+ DKRZ (Claudia Wunram, Hannes Thiermann)+ COPS
General Observation Period 2007
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Rain gauge
GOP Ingredients: Precipitation
Weather Radar
Drop Size Distribution
WP-GOP-1 Rain gauges; DWD precip analyses (RANIE, REGNIE)
WP-GOP-2 Weather Radar
WP-GOP-3 Drop Size Distribution DSD
several hundred independent observations by DWD, water authorities, environmental agencies etcDWD analyses: RANIE, REGNIE
DWD radar network and research radars, 3D volume scans, PI, RY, QY, RADOLAN
vertical structure at about 15 locations with Micro Rain Radar (MRR)
Continuous precipitation observation with high temporal resolution
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Lindenberg
Zingst
Helgoland
Lichtenau
WienIMKMPI_4/IG4DWD_2
UKO
DLR
MPI_1/IG2DWD_1
MPI_2MPI_3/IG1UHH_1/IG3
MPI
UHH_2
UBO_1UBO_2
LAMP
LAMP
Micro Rain Radar MRR-2
Optical Distrometer ODM470_1
Optical Distrometer FD12P
Optical Distrometer PARSIVEL
Distrometer JOSS/WALDVOGEL
Scanning X-Band Radar (LAWR)
DLR Inst. Phys. Atmos., OberpfaffenhofenDWD_1 R. Assmann Obs., LindenbergDWD_2 Met.. Obs. HohenpeissenbergIG_1-4 IfM Geomar, KielIMK Inst. Met. Klim., KarlsruheLAMP Laboratoire de Météorologie PhysiqueMPI_1-4 MPI Hamburg UBO_1-2 Uni BonnUHH_1-2 Uni HamburgUKÖ Uni KölnWien Uni Wien
GOP-3
Gerhard Peters
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
WP-GOP-4 Lidar (aerosol, cloud base, mixing layer height)
WP-GOP-5 GPS water vapour column
WP-GOP-6 Lightning networks
WP-GOP-7 Satellite observations (cloud properties, water vapor, aerosol)
WP-GOP-8 Meteorological stations
Lidar
GOP Ingredients: Auxillary Information
GPS
AMF
EARLINET stations (4), about 100 lidar ceilometer stations in Germany
DWD: ca 147 stations in LMK area, ca 200 in LME area + GPS COPS + Switzerland
European and national networks VLF and VHF
MSG, MODIS, MERIS, AMSU, CLOUDSAT, CALIPSO
ARM Mobile Facility (AMF), Lindenberg, diverse universities and research institutes
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
GOP-7: SatellitesMSG:- cloud mask- cloud top pressure (+temperature?), - optical depth - IR brightness temperature
MODIS:- cloud mask- cloud optical thickness τ - liquid water path LWP- effective radius reff
- geometric cloud thickness H - IWV - aerosol?
MERIS:- cloud mask- cloud optical thickness τ - cloud top pressure (+temperature?)
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Evaluation Areas Northsea Baltic Sea Alps North western German lowland North eastern German lowland Low mountain ranges COPS area Countries (D, B, A, CH, NL, F) River catchments (in Germany)
LMK domain
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Diurnal comparisons / plots, processed near real-time (“Quicklooks”) Radiosoundings: Plots for each sounding in Germany and neigbouring countries
- Stüve diagramm together with corresponding +12h LMK forecast- differences of temperature, specific humidity and wind speed forecasts (+0,+3,+6,+9,+12,+15,+18,+21 h) at each model level
GPS, Ceilometer: Daily colour coded maps of BIAS/RMSE of cloud base height (ceilometer) and IWV (GPS); LMK vs. observation
GOP - First order model evaluation
Monthly comparisons / plots.
Radiosoundings: Bias and RMSE profiles for temperature, humidity and wind for all stations
Ceilometer / GPS: Monthly time series of Bias/RMSE for each station or region (depending on number of stations within regions)
Ceilometer / GPS: Monthly analysis of mean diurnal cycle and comparison to differnet model runs (lagged ensemble)
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Example for GPS Quicklook
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Example for Radiosonding Quicklooks
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Task: Archiving model outputTotal LMK output too large for permanent storage!
=> Therefore: Extracting model output relevant for model evaluation :
3 types of data extraction:
1.) statistics over (sub-) areas, timeseries at stations (1-d in time)
2.) column output at individual gridpoints (2-d in height and time)
3.) field output (3-d in x,y,t)
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
1d output (time series)
-- statistics of individual quantities (precip, wind, …) in (sub-)domains for direct evaluation & classification für weather-type dependent evaluation
-- time series of near-surface variables Werte at Synop stations
-- time series of integrated water vapour (IWV) at GPS stations
-- time series of cloud base height at ceilometer stations
-- time series of precipitation at precipitation stations
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
2d output (column output)All available variables at certain gridpoints with vertically sounding instruments:
-- Radiosonding stations
-- Micro rain radars (ca 15)
-- ARM Mobile Facility
-- Earlinet stations
-- Cloudnet stations
-- COPS Supersites
-- Meteorological Observatories
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Field Output
-- brightness temperature of synthetic MSG channels-- radar reflectivity in 850 hPa, max. radar reflectivity in column-- Integrated condensate (TQC,TQR,TQS,TQG)-- height of cloud top and cloud base-- cloud cover (CLCT, CLCL, CLCM, CLCH)-- optical thickness-- precipitation (R, S, G), rates and sums-- radiation balances-- CAPE-- HZERO; 850-hPA temperature, wind; 500-hPa geopotential-- albedo, ground temperature
For AMSU: all prognostic variables at overpass times
for comparison with area covering instruments (radar, satellite)
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Cloud top MSGCloud base Ceilometer
Cloud cover MSG
Examples of LTE (I): cloud parameters
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Example of LTE (II): cloud cover Cloud cover (%) LMK00 / LMK12 BIAS (%) STD (%) Korrelation
LMK total 8 / 5 9 / 9 0.80 / 0.80
North Sea 9 / 8 17 / 17 0.72 / 0.70
Alpes 6 / 2 14 / 15 0.78 / 0.81
Lowlands 9 / 7 17 / 17 0.68 / 0.70
Low mountains 7 / 5 15 / 16 0.68 / 0.67
Poldirad area 5 / 2 17 / 17 0.72 / 0.75
COPS area 4 / 0 22 / 20 0.49 / 0.61
Meteosat Second Generation comparison: July 2004
CabauwLindenberg
AMF
run 00UTC run 12UTC
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
MSG data – Cloud top pressure
• Overestimation of cloud top height by model• Model simulates realistically no great variation
throughout a day.
OBSmodel
Daily cycle Daily cycle of RSME
(run started at 00UTC)
Example of LTE (III): cloud cover
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Summary LMK LTE
LE
Boundary layer too thin and too wet IWV generally well
predicted IWV Bias of
-0.85 kg/m2 for runs started at 12 UTC
Clouds too thick Cloud cover in good
agreement with MSG
Precipitation underestimated by 20%
(problem addressed in the maintime by several model changes)
Daily cycle not well forecast
Case studies to look into more detail in the problems
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Observation
LMK,
Thompson,
Rain, snow, graupel
LMK, 2 comp.
Rain, snow
LMK, 3 comp.
Rain, snow, graupel
Reflectivity
Case study example: pol.radar
By Monika Pfeifer,DLR
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Observation
LMK :3 comp.
Rain, snow, graupel
Hydrometeor Classification
LMK :
2 comp.
Rain, snow
LMK:
Thompson
Rain, snow,
graupel
Case study example: pol.radar
By Monika Pfeifer,DLR
5.-9. März 2007, Bad Herrenalb
Thorsten Reinhardt, Institut für Geophysik und Meteorologie, Universität zu Köln
Summary QUEST Goals
• Optimization and refinement of existing evaluation tools• Identification of systematic errors in precipitation and cloud fields
forecasts• Exploitation of the complementary information of the different remote
sensing observations; model consistency; cross-correlation of model performance for different variables
• Evaluate model using long-term observations collected during the GOP
• Provide an independent test bed for model improvements• Improve LMK performance by changes in the treatment of cloud
microphysics, turbulence, land surface,… (motivated by results of model evaluation)