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1October 26, 2009 8th COPS Workshop, Cambridge, UK
COPS (Convective and Orographically-induced Precipitation Study)
Goal: Advance the quality of forecasts of orographically-induced convective precipitation by 4D observations and modeling of its life cycle
Wulfmeyer et al., Bull. Amer. Meteor. Soc. 89, 1477-1486, 2008, DOI:10.1175/2008BAMS2367.1.
Volker Wulfmeyer
Institute of Physics and Meteorology (IPM)
University of Hohenheim, Stuttgart, Germany
and the COPS International Science Steering Committee
Research strategy Recent highlights Research desiderates Recommendations
Brandnew: Rotach et al., Bull. Amer. Meteor. Soc. 90, 1321-1336, 2009, DOI:10.1175/2009BAMS2776.1.
2October 26, 2009 8th COPS Workshop, Cambridge, UK
COPS Treasure ChestArea-wide and synergetic
observation of process chain
Impact studies and data assimilation methodology
Integrated verification of process chain
Predictive skill of probabilistic QPF (PrQPF), predictability of convection and precipitation
3October 26, 2009 8th COPS Workshop, Cambridge, UK
Achievements: European-wide JDC data set
Soil moisture and flux analyses
Detailed observations of ABL, clouds, and precipitation
Various process studies ongoing
Area-wide, synergetic observation of process chain
Soil moisture intercomparison with DWD GME model at site Simonswald, courtesy Christian Barthlott, KIT.
Frequency distribution of IPT-LWC with height at AMF site, April-December 2007. Courtesy Kerstin Ebell et al., B1.
4October 26, 2009 8th COPS Workshop, Cambridge, UK
10 s, 150 m
IPM Water-vapor Differential Absorption Lidar Measurement During IOP11b, July 26, 2007
Application of remote sensing data is a key challenge of this workshop.
10 s, 60 m
1 s, 15 m
New performance!
RHI scan
5October 26, 2009 8th COPS Workshop, Cambridge, UK
Challenges and strategy: Few integrations of different data sets
but 3D analyses missing, e.g., by 3DVAR.
Emerging picture: Severe problems of models to simulate dynamics and humidity distribution on meso-
scale,
but relative importance of deficiencies in process understanding with respect to PrQPF, e.g., role of aerosol-cloud-precipitation microphysics, unknown.
Area-wide, synergetic observation of process chain
Data overlay and COSMO2 output, Aoshima et al., A2.
IOP 14a, August 6, 2007, 16 UTC
COSMO2 output
Thorough analyses of process chain based on integrated data sets.
6October 26, 2009 8th COPS Workshop, Cambridge, UK
Achievements: D-PHASE model verification (precipitation only) over Switzerland
Superior performance of convection-permitting models demonstrated
goodbad
Threshold (mm/3h) Threshold (mm/3h)
Fra
ctio
n s
kill
sc
ore
-COSMO-7 (7km)COSMO-2 (2.2km)
Threshold (mm/3h)
Difference
Sp
ati
al
sc
ale
(k
m) 90
58
33
20
7
=COSMO-7 better COSMO-2 better
JJA 2007, Verification versus Swiss Radar Composite, 3-hourly acc. , rain events only
Courtesy Tanja Weusthoff, Marco Arpagaus, MeteoSwiss
Integrated verification of process chain
7October 26, 2009 8th COPS Workshop, Cambridge, UK
Challenges and strategy: D-PHASE ensemble available but data gaps
First results over COPS domain (see A3, C7, Dorninger et al.), however, strong inhomogeneity of European surface
data
Incorporation of new ensemble members, e.g., DWD reanalyses (B4)
Integrated verification of process chain
Agreement essential on: - data sources and variables, - verification approach and skill scores,- temporal resolution, e.g., diurnal cycle,- spatial resolution and domains,- deterministic models and ensembles.
AROME temperature corr. and rms during July 2007
T2M corr.
T2M rms
8October 26, 2009 8th COPS Workshop, Cambridge, UK
Achievements, challenges, and strategy: 3DVAR (Arome, Meteo France) and 3DVAR/4DVAR
(WRF, IPM) with GPS and radar data
Nudging (DWD reanalyses, ARPA SIMC)
Strong impact of the assimilation of humidity, Doppler wind, and radar reflectivity data
but no comparison of data assimilation methodology (e.g., VAR versus EnKF),
so far data assimilation efforts not coordinated.
Data assimilation methodology and impact studies
Data assimilation testbed required, as suggested by WWRP WG MWFR and JSC.
IOP9c, improvement of QPF by WRF 3DVAR using synop, sat, and GPS ZTD, Bauer et al., A3
3DVAR
Control
9October 26, 2009 8th COPS Workshop, Cambridge, UK
Achievements, challenges, and strategy: Analyses of ensemble simulations
(Barthlott et al., Keil et al., Hanley et al. C5)
First results of D-PHASE models (A3)
Calibration of multi-model ensembles
Comparison of predictive skill in dependence on forcing conditions, boundaries, model physics, and
initial conditions
Predictability Pr(F, B, I, P, PDF)
Predictive skill of PrQPF and predictability
10October 26, 2009 8th COPS Workshop, Cambridge, UK
Recommendations
Integrated data sets and verification tools
Joint multi-boundary, multi-model ensemble forecast system with different data assimilation techniques
Platform to link CSIP and COPS research activities (QPF in different regions)
The WWRP Integrated Mesoscale Research Environment (IMRE) according to the new WWRP Strategic Plan 2009-2017
