The Working Group No. 7 (WG7) on Predictability and Ensemble Methods collects and coordinates the activities on ensemble forecasting, including predictability studies, which are carried out in the COSMO Consortium.
The WG7
activities
The main areas for cooperation are:
- Maintenance and improvements of the ensemble systems, considering different methodologies for e.g. providing initial and boundary perturbations, model error description, products interpretation and verification, post-processing
- Development of methodologies for ensemble forecasting with the COSMO and ICON model at the different spatial scales
- Predictability studies with the COSMO and ICON model
- Feed-back on the use of the ensemble products by people involved in verification and forecasting
- Organisation of dedicated meetings
- Participation to international activities
ensembles
The COSMO members develop and maintain several ensemble systems at the convection-permitting scale:
- ICON-D2-EPS, by DWD, operational, 2.1 km
- COSMO-2E and COSMO-1E, by MCH, operational, 2.2 km and 1.1 km, resp.
- TLE-MVE, by IMGW, operational, 2.8 km
- COSMO-IT-EPS, by CNMCA, operational, 2.2 km
- COSMO-2I-EPS, by Arpae, pre-operational, 2.2 km
- COSMO-Ru2-EPS, by RHM, for reserach, 2.8 km
- COSMO-IL-ENS, by IMS, under development, 2.5 km
CNMCA operates also an ensemble at 7 km, COSMO-ME-EPS.
the COSMO ensenble systems
The Consortium has also a common operational mesoscale ensemble, COSMO-LEPS, developed and maintained by Arpae-SIMC, running at ECMWF thanks to a collection of COSMO computational resources. The system covers 5 days forecast range and the current spatial resolution is 7 km (more).
For more information about the set-up of the ensembles, see the operational (Table3) page.
ICON-D2-EPS, COSMO-2E, COSMO-1E, COSMO-2I-EPS and COSMO-IT-EPS use as Initial Condition the analyses provided by a KENDA data assimilation cycle. See the WG1 and KENDA-O pages about this topic.
The transition to ICON-LAM in ensemble mode is carried out within the WG7 Priority Projects APSU and PROPHECY, establishing a coordination with the Priority Project C2I.
A list of ICON parameters suitable for tuning and model perturbations is available.
On 5-7 February 2024, a Workshop on hectometric scale model physics and predictability took place at DWD.
The aim of the Workshop was to bring together scientists currently working on the model physics and predictability aspects of hectometric scale (O(100m)) forecasts.
The final programme can be found here.
The group photo! photo.
The presentations are available here:
Opening
- Aim of the workshop (Chiara Marsigli, DWD, Arpae) pdf
- Review of last 100m workshop (Natalie Theeuwes, KNMI, and Humphrey Lean, Met Office) pdf
Session: observations
- FESSTVaL: The Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (Cathy Hohenegger, MPI) pdf
- Evaluating ICON-LEM simulations with observations from the FESSTVaL campaign (Maike Ahlgrimm, DWD) pdf
- High resolution observations and modelling during a heatwave: urbisphere-Berlin (Russell Glazer, University of Reading) pdf
- Using doppler lidar measurements to evaluate the representation of the boundary layer in high-resolution numerical models (Natalie Theuwees, KNMI) pdf
- A short summary of the WesCon campaign (Humphrey Lean and Kirsty Hanley, Met Office) pdf
- Discussion on observations (Cathy Hohenegger, MPI) pdf
Session: ensemble
- Evaluation and analysis of Meteorological Service for Beijing Winter Olympic Games supported by RMAPS-LES Prediction System (Yujue Liu, CMA) pdf
- An urban-scale ensemble for WesCon (Kirsty Hanley, Met Office) pdf
- Impact of horizontal resolution and model uncertainty scheme in ensemble prediction of extreme weather events ( Aristofanis Tsiringakis, ECMWF) pdf
- Predictability limits of short-range high precipitation events (Francois Bouttier, Meteo-France) pdf
- Predictability and hectometric scale activities in RC LACE: A-LAEF and TOUCANS (Martina Tudor, LACE) pdf
- Studies of Convection-Permitting Ensemble Forecasting for ICON-D2 with a 1km Nest over the Alps (Zahra Parsakhoo, DWD) pdf
- Discussion on ensemble (Inger-Lise Frogner, Met Norway; Anne Mccabe, Met Office) pdf
Session: turbulence
- High-fidelity weather forecasts in the grey-zone of convective turbulence (George Efstathiou, University of Exeter) pdf
- Boundary Layer and Convection issues with the 100m scale UM (Humphrey Lean, Met Office) pdf
- Prognostic TKE scheme in the IFS model (Ivan Bastak Duran, ECMWF) pdf
- Still uncertainties in the physics at very high resolutions? (Eric Bazile, Meteo-France) pdf
- ICON at high resolution (Günther Zängl, DWD) pdf
- Modelling the mountain boundary layer: Does higher resolution improve model performance? (Brigitta Goger, ETH) pdf
- High-Resolution Modelling of Storm Events over the complex Alpine Terrain (Daniela Littmann, DWD) pdf
- Discussion on turbulence (Eric Bazile, Meteo-France; Natalie Theuween, KNMI)
Session: surface
- Facing heterogeneities with increasing resolution (Anurag Dipankar, ETH) pdf
- Resolving cities in a global model (Jacopo Canton, ETH) pdf
- Optimising orography for global high-resolution simulations (Birgit Sützl, ECMWF) pdf
- ICON-LEPS simulation over southern-Italy region at 600m grid resolution (Davide Cinquegrana, CIRA) pdf
- Discussion on surface (Anurag Dipankar, ETH; Jan-Peter Schulz, DWD)
Session: convection
- The ParaChute programme: overview and focus on the development of a scale-aware convection scheme (Alison Stirling, Met Office) pdf
- Convection parameterization at high resolution (Wim de Rooy, KNMI) pdf
- Using ICON-LES to understand convective anvil processes (Martin Köhler, DWD) pdf
- Towards AROME-500m operational configurations at Météo-France in 2024: strengths and weaknesses (Yann Seity, Meteo-France) pdf
- Added Value of higher resolution for forecasts of severe convection? (Alberto de Lozar, DWD) pdf
- Ensemble forecasts in hectometric scale – comparison of results for 7, 2.8 and 0.7 km resolution model runs – case study (Andrzej Mazur, IMGW) pdf
Closing
- Summary of key points and final discussion (all; Chiara Marsigli, DWD; Humphery Lean, Met Office; Rapporteur: Russell Glazer, University of Reading) pdf
On the 2nd and 3rd of March 2021, a Stochastic Workshop took place online.
The aim of the Workshop was to present and discuss the activities on-going in the COSMO Consortium and in the other European Consortia in the field of "stochastic physics", in particular intrinsically stochastic parametrisations, in view of their usage in ensembles.
The final programme can be found here.
The presentations are available here:
- Introductory talk about instrinsically stochastic parametrisations (George Craig, LMU) pdf
- Stochastic parametrisation of processes leading to convective initiation in kilometer-scale models (Mirjam Hirt, LMU) pdf
- Meteo-France (Axelle Fleury and Francois Bouttier, Meteo-France) pdf
- Plans for a stochastic version of the comorph convection scheme (Michael Whitall, Met Office) pdf
- Stochastic microphysics at convection resolving scales (Judith Berner, NCAR)
- Stochastic representation of model uncertainties at ECMWF (Martin Leutbecher, ECMWF) pdf
- Local impact of stochastic shallow convection on clouds and precipitation in the tropical Atlantic (Mirijana Sakradzija, MPI) pdf
- An update about the stochastic shallow convection scheme in ICON at DWD (Maike Ahlgrimm, DWD) pdf
- Uncertainties, stochastic and deterministic components in radiation modelling (Sophia Schäfer, DWD) pdf
- Attempts to objectively identify a stochastic model for model errors (Mikhail Tsyrulnikov and Dmitriy Gayfulin, RHM) pdf
- Characterization of the model error in ICON-D2-EPS using a flow-dependent partial SDE (Martin Sprengel and Christoph Gebhardt, DWD)
- A process-oriented perspective on stochastic physics, with a focus of SPPT on warm conveyor belts in the IFS (Moritz Pickl, KIT) pdf
- Presentation of the open issues (Anne McCabe, Met Office; Marco Arpagaus, MCH) pdf
The minutes of the discussion are available here.
Priority Projects
The main research activities about the development of the convection-permitting ensembles are carried out mainly within Priority Projects.
The PP SPRED has ended in February 2018, please have a look at the project page for the main developments. Its final report is available as a COSMO TechReport No39.
From the 1st of March 2018 to the 30th of August 2020 the PP APSU was running, please see the APSU page. The final report will be provided as COSMO Technical Report by the end of 2021.
A new PP PROPHECY (more) has started in September 2020.
Ensemble activities were formerly coordinated in the framework of the WG4, a dedicated WG has been established in Sep 2010, hence the workplan starts from this date.
Stochastic physics
The most widely used model perturbation methodologies and the methods developed in the COSMO Consortium are here listed and shortly described:
PP:
Perturbed Parameters:
each member has a different value of one or several parameters, fixed during the integration.
RPP:
Random Perturbed Parameters:
each member has a different value of one or several parameters, fixed during the integration, but the value of the parameter is randomly chosen for each cycle and member.
RP:
Random Parameters:
each member has a different value of one or several parameters, fixed in space during the integration but varying in time; the value of the parameter is randomly chosen for each cycle and member.
SPPT:
Stochastically Perturbed Parametrization Tendency:
stochastically perturbed physical tendency, with spatial and temporal correlation. (Buizza et al., 1999; Palmer et al., 2009)
iSPPT:
independent SPPT:
as SPPT but the tendency from each parametrization scheme is perturbed using an independent stochastic pattern. (Christensen et al., 2017)
SPP:
Stochastically Perturbed Parametrisations:
physics parameters are stochastically perturbed with spatial and temporal correlation. (Ollinaho et al., 2017)
PSP:
Physically Based Stochastic Perturbations:
Boundary Layer stochastic perturbations with amplitude based on information obtained from turbulence parameterization, with spatial and temporal correlation. (Kober and Craig, 2016)
PSP2:
Physically Based Stochastic Perturbations, revised:
The scheme has been further developed improving its realism. (Hirt et al., 2019)
Multi-physics:
different members use different physics schemes, fixed
Multi-model:
different members use different models, fixed
Stochastic parametrisation:
a scheme for parametrising a physical process in the model which is intrinsically stochastic. (Craig and Cohen, 2006; Plant and Craig, 2008)
Stochastic Shallow Convection:
stochastic version of the shallow convection scheme. (Sakradzija et al., 2015, 2016)
SMME:
Stochastic Model of the Model Error:
aims at modeling the model error by integrating a stochastic partial differential equation, which solution has spatial and temporal correlations corresponding to the model error in the training data set. These solutions of the SPDE (different in each member of the ensemble) are added to the tendencies in the slow physics scheme.
AMPT:
Additive Model-error perturbations scaled by Physical Tendency:
AMPT produces model-error perturbation fields by scaling the unit-variance Stochastic Pattern Generator (SPG; Tsyrulnikov and Gayfulin, 2017) fields with an area averaged physical tendency. SPG computes Gaussian pseudo-random fields with tunable variance and spatial/temporal scales.
Summary scheme of the methods to represent model error in ensembles:
model perturbation methods
References
Buizza, R., M. Miller and T. N. Palmer, 1999:
Stochastic simulation of model uncertainties.
Q. J. R. Meteorol. Soc., 125, 2887-2908.
Christensen H. M., S.-J. Lock, I. M. Moroz and T. N., Palmer, 2017.
Introducing independent patterns into the Stochastically Perturbed Parametrization Tendencies (SPPT) scheme.
Q. J. R. Meteorol. Soc., 143, 2168-2181. doi:10.1002/qj.3075.
Craig G. C. and B. G. Cohen, 2006.
Fluctuations in an equilibrium convective ensemble. Part I: Theoretical formulation.
J. Atmos. Sci., 63, 1996-2004. DOI:10.1175/JAS3709.1.
Hirt M., Rasp S., Blahak U and Craig G. C., 2019.
Stochastic Parameterization of Processes Leading to Convective Initiation in Kilometer-Scale Models.
Monthly Weather Review, 147, 3917-3934. DOI:10.1175/MWR-D-19-0060.1.
Kober K and Craig G. C., 2016.
Physically based stochastic perturbations (PSP) in the boundary layer to represent uncertainty in convective initiation.
J. Atmos. Sci., 73, 2893-2911. DOI:10.1175/JAS-D-15-0144.1.
Ollinaho P., Lock S.J., Leutbecher M., Bechtold P., Beljaars A., Bozzo A., Forbes R. M., Haiden T., Hogan R. J. and Sandu I., 2017.
Towards process-level representation of model uncertainties: stochastically perturbed parametrizations in the ECMWF ensemble.
Q. J. R. Meteorol. Soc., 143, 702, 408-422, doi: 10.1002/qj.2931.
Plant R. S. and G. C. Craig, 2008.
A stochastic parameterization for deep convection based on equilibrium statistics.
J. Atmos.Sci., 65, 87-105. DOI: 10.1175/2007JAS2263.1.
Sakradzija M., A. Seifert and T. Heus, 2015.
Fluctuations in a quasi-stationary shallow cumulus cloud ensemble.
Nonlinear Proc. Geophys., 22, 65-85. DOI:10.5194/npg-22-65-2015
Sakradzija M., A. Seifert and A. Dipankar, 2016.
A stochastic scale-aware parameterization of shallow cumulus convection across the convective gray zone.
J. Adv. Model. Earth Syst., 8, 786-812. DOI:10.1002/2016MS000634
Tsyrulnikov M. and D. Gayfulin, 2017.
A limited-area spatio-temporal stochastic pattern generator for simulation of uncertainties in ensemble applications.
Meteorologische Zeitschrift, 26(5), 549-566. DOI: 10.1127/metz/2017/0815