The Royal Meteorological Institute of Belgium
Report 2008
1. Summary of highlights
A new version version of the ALADIN model with the ALARO physics parameterization package has been installed operationally since December 2008. This includes a specific organization of prognostic moist parameterizations allowing a consistent treatment of deep convection at resolutions finer than 7km (so-called gray zone). The model is currently run operationally at a resolution of 4 km.
2. Equipment in use at the Centre
SGI Altix 4700 with Itanium II processors with 192 cpu’s.
3. Data and Products from GTS in use
4. Forecasting system
4.1 System run schedule and forecast ranges
Medium and extended range forecasting are based on external NWP sources, but the RMI of Belgium runs its own short-range forecasting system.
Table 1 describe the timeline of computing
Grid / Arrival of coupling files (TU) / “forecast”(TU) / “post-processing”
(TU) / Products creation
(TU)
midnight / 3H15 to 3H40 / 3H15 to3H55 / 3H15 to 4H00 / 4H00
morning / 9H55 to 10H20 / 9H55 to10H35 / 9H55 to 10H40 / 10H40
midday / 14H45 to 15H10 / 14H45 to15H25 / 14H45 to 15H30 / 15H30
evening / 21H55 to 22H20 / 21H55 to 22H35 / 21H55 to 22H40 / 22H40
Table 1
4.2 MediumRange forecasting system (4-10 days)
No systems locally implemented. The IFS model output of ECMWF is operationally used. ECMWF Ensemble Prediction System (EPS) are operationally used to make probabilistic medium range forecasts up to 10 days
4.3 Short-range forecasting system (0-72 hrs)
The RMI uses a version of the ALADIN model, developed by the ALADIN cooperation and adapted to its local needs, called ALADIN Belgium.
ALADIN Belgium is Aladin 29, run 4 times a day with a forecast range of 60 hours each. Coupling files are coming from Météo-France and are made with Aladin France (from range 0 to 48) and Arpege (from range 48 to 60). The model runs at 7-km resolution on the Lambert domain (red). The RMI started to run ALADIN with ALARO physics on this domain at 7 km resolution and also runs with this model on a 4-km resolution smaller domain.
Fig 1 describe the Lambert computational domain and the two latitude-longitude domains used for products.
Lambert domain
latitude-longitude domain
latitude-longitude domain
4.3.1. Data assimilation, objective initialization
4.3.1.1. In operation
ALADIN Belgium is initialization by a digital-filtering initialization (DFI), proposed by Lynch (1990).
4.3.1.2 Research performed in data assimilation and initialization
It has been observed by Termonia (2008) that in case of fast propagating storms, the frequencies of the rotationally relevant part of the model may be shifted into the frequency domain that believed to belong exclusively to the gravity-wave part of the dynamics. It proposed in that paper to solve this by applying a scale-selective digital filter.
Model error is a central concern in present advanced data assimilation systems. This question has been investigated extensively in low-order chaotic systems in the light of results obtained on the dynamics of deterministic model errors (Nicolis, 2004; Nicolis et al, 2009). A new formulation for the treatment of the model error in sequential, Kalman filter type, algorithm has been proposed (Carrassi et al., 2008a), and work is presently under progress to extend this approach to variational schemes.
In parallel the investigation on data assimilation has been brought out with a focus on the development of advanced schemes for the treatment of the system instabilities (Carrassi et al., 2008b; Carrassi et al., 2008c). The institute has furthermore contributed to full comparative analysis of some recent data assimilation algorithms used at operational level in most of the numerical weather prediction centers in the world (Yang et al., 2009)
4.3.2 Model
4.3.2.1. In operation
See above.
4.3.2.2 Research performed in this field
A research effort is going on (in an international framework) around the consistent treatment of precipitation and clouds at meso-gamma scale resolutions (Gerard, 2007), using prognostic schemes and accounting a number of interactions between moist parameterizations. Current focus is on the convergence of the scheme towards explicit convection at resolutions finer than 2-km, as well as some specific aspects of the deep convection scheme, such as mixed prognostic closure, prognostic mixing and the relations with boundary layer and shallow convection.
A formulation proposed in Hamdi and Masson (2008) to include prognostic atmospheric layers in offline surface schemes is derived from atmospheric equations. This new formulation allows to retrieve the standard meteorological variables (2m temperature, 10m wind speed) without any use of analytical interpolation. This new SBL scheme has been validated coupled to a 3D atmospheric model (Masson and Seity 2009). The inclusion of the SBL into the urban Town Energy Balance (TEB) scheme is presented in Hamdi and Masson (2008), where the ability of the method to simulate the profiles of both mean and turbulent quantities from above the building down to the road surface is shown using the BUBBLE experiment data.
We are participating with this new scheme in a project to compare urban surface energy balance schemes, led by Sue GRIMMOND (Kings’s College London), Martin BEST (UK Met Office), and Janet BARLOW (University of Reading). The purpose of this project is to evaluate the ability of urban models to simulate heat fluxes by performing a multi-step model comparison of urban surface energy balance schemes with observational datasets (Grimmond et al. 2009).
Research has been carried out to find improved formulations for the lateral-boundary conditions, see Termonia and Voitus (2008) and Voitus et al. (2009). Additionally research has been done on the so-called lateral-boundary temporal resolution problem. In practice the ALADIN Belgium uses temporally interpolated coupling data with update intervals of 3 hours. It has been shown (Termonia 2003) that this is insufficient in case of extreme storms, although in normal meteorological situations this is sufficient. Termonia (2004) has shown that it can be anticipated when 3-h updates will turn out to be insufficient before the coupling data is used by the LAM. In a recent study carried out by Termonia et al. (2009) this method has been elaborated to provide an operational solution to deal with this problem. Research has also been carried on the problem of the physics-dynamics coupling, in particular on the numerical properties related to the choices in spectral models, see Termonia and Hamdi (2007).
An extensive investigation of the role of model domain size has been investigated in the context of the Eta regional model. This investigation suggests a complex dependence of the quality of the forecasts and climate on the choice of domain size, the smallest one being not necessarily the best (Vannitsem and Chomé, 2005).
4.3.3 Operatonal techniques for application of NWP products
4.3.3.1 In operation
-A suite of post processing modules are available
-The HAWK visualization software developed at the Hungarian Meteorological Service is used
-A trajectory model providing guidance on transport route (pollutants)
-A particle dispersion model to calculate dispersion and deposition of radioactive or chemical materials, having also a backward model to calculate the origin of pollutants
Based on these modules, a standard set of products is provided to the RMI Belgian forecasters and used for short and medium range forecasts. In case of necessity, the two last modules can be run by the on-duty forecasters at any time on demand mode.
A large quantity of tailor made products, based on direct model output, are disseminated to internal and external clients
4.3.3.2 Research performed in this field
Research has been carried out concerning MOS, see Termonia and Deckmyn (2007), Vannitsem and Nicolis (2008) and Vannitsem (2008) In the first work the choice of the predictors has been investigated. In the second, the origin and the dynamical properties of the correction which can be expected from MOS has been investigated.
The newly developed surface scheme of Météo-France SURFEX (SURFace Externalisée) is used offline, coupled to the output of the ALADIN model in order to remove the positive feedbacks between the surface and the atmosphere in stable situations. Results show a cyclic dependence of the ALADIN errors on the forecast range with large systematic error during cold winter night. This underestimation of the winter minimum screen temperature is largely reduced by SURFEX except for January 2008 which is an exceptionally warm month. However, SURFEX seems to overestimate the screen temperature in very stable situations but the occurrence of these situations is marginal.
5. Verification of prognostic products
5.1 Annual verification summary
Standard scores (RMSE, MAE, ME) are computed on a monthly basis of the variable 2-m temperature, 10-m wind, mean sea level pressure and radiation and clouds are monitored.
- Plans for the future (next 4 years)
6.1Development of the Global Data-processing and Forecasting System (GDPFS)
6.1.1Major changes in the operational DFPS which are expected in the next year
We expect to introduce an EPS system in the context of the GLAMEPS project within the next years. This is currently under development, see below. The current plans are to run about 10 members on the commonly agreed GLAMEPS domain.
6.1.2Major changes in the operational DFPS which are envisaged within the next 4 years
6.2Planned Research Activities in NWP, Nowcasting, Long-range Forecasting and Specialized Numerical Predictions
6.2.1. Planned Research Activites in NWP
The RMI is now taking part in the international GLAMEPS project ( to develop a European Limited-Area Model Ensemble Prediction System, and will continue during the next years to contribute to this.
6.2.2. Planned Research Activities in Nowcasting
In 2008, the RMI started with the implementation of an operational Quantitative Precipitation Forecast (QPF) system. This system will be used for short-term forecasting ("nowcasting") of precipitation and the generation of detailed warnings in case of severe events. It will primarily rely on radar data, but in a future stage it will also be extended to other data, like NWP, lightning
and satellite data. The actual development of an operational QPF system at the RMI is preceded by two dedicated studies. The first one is a detailed systematic study of convective precipitation in Belgium, primarily based on archived radar images, complemented by other sources (e.g. satellite products, GPS water vapor, lightning detection, etc...). This study will contribute to a better understanding of the initiation and evolution of convection over Belgium, and will provide important clues for the design of the future QPF system. A second study is a detailed overview of (i) the existing QPF systems in literature developed by other institutes and meteorological services, and (ii) an overview of the requirements that the future QPF system should have, requirements provided by the potential future users (forecasters, hydrological services, civil protection authorities, broad public, etc...).
In the context of the first study (a climatology of convective precipitation over Belgium), a software package developed by NCAR, the "Thunderstorm Identification Tracking Analysis and Nowcasting" (TITAN) tool, has been installed on the computer infrastructure of the RMI, and a first analysis of some prototypical convective events is ongoing. The first results of this study will be presented on the upcoming WMO Symposium on Nowcasting in Whistler (Canada) in August 2009. In the context of the second study, a comprehensive overview was made of the existing QPF systems that are documented in literature (Reyniers, 2008). The main result of the latter study is that a remarkable variety exists in the complexity of the existing QPF or nowcasting systems: some systems are built upon a simple tracker, while other systems ingest a variety of observations (ground and satellite) and pass them into sophisticated algorithms. The final design of the future QPF system at the RMI will ultimately rely on both the results of the characterization of the convective precipitation events, and a detailed formulation of the user requirements.
6.2.3. Planned Research Activities in Long-Range Forecasting
6.2.4. Panned Research Activities in Specialized Numerical Predictions
7. References
Carrassi, A., S. Vannitsem and C. Nicolis, 2008a: Model error and sequential data assimilation: A deterministic formulation. Quart. J. Royal Meteorol. Soc., 134, 1297-1313.
Carrassi, A., M. Ghil, A. Trevisan and F. Uboldi 2008b: Data assimilation as a nonlinear dynamical system problem: Stability and convergence of the prediction-assimilation system. Chaos, 18, 023112.
Carrassi, A., A. Trevisan, L. Descamps, O. Talagrand and F. Uboldi 2008c: Controlling instabilities along a 3D-Var analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF. Nonlin. Proc. in Geoph., 15, 503-521.
Gerard, L. 2007: An integrated package for subgrid convection, clouds and precipitation compatible with the meso-gamma scales. Q. J. R. Meteorol. Soc., 133, 711-730.
C.S.B. Grimmond, M. Blackett, M. Best, J. Barlowand, J.-J. Baik, S. Belcher, S. Bohnenstengel, I. Calmet, F. Chen, A. Dandou, K. Fortuniak, M. Gouvea, R. Hamdi, M. Hendry, H. Kondo, S. Krayenhoff, S. H. Lee, T. Loridan, A. Martilli, S. Miao, K. Oleson, G. Pigeon, A. Porson, F. Salamanca, L. Shashua-Bar, G.-J. Steeneveld, M. Tombrou, J. Voogt, N. Zhang, 2009: The International Urban Energy Balance Models Comparison Project: First results. Bulletin of the American Meteorological Society (submitted).
Hamdi, R., and V. Masson, 2008: Inclusion of a drag approach in the Town Energy Balance (TEB) scheme: offline 1-D evaluation in a street canyon. J. Appl. Meteor. Clim., 47, 2627-2644.
Hamdi, R, 2009: The offline version of SURFEX coupled to the operational ALADIN forecast over Belgium: A tool to improve winter screen temperature. Internal note, RMI, Uccle, Belgium.
Lynch, P., 1990: Initialization using a digital filter. In Research Activities in Atmospheric and Ocean Modeling, CAS/JSC Working Group on Experimentation. Report No. 14, WMO Secretariat, Geneva. 1.5-1.6.
Lynch, P., and X.-Y. Huang, 1992: Initialization of the HIRLAM Model Using a Digital Filter. Mon. Wea. Rev.,120, 1019-1034.
Nicolis, C. 2004. Dynamics of model error : the role of unresolved scales revisited, J. Atmos. Sci., 61, 1740-1753.
Reyniers, 2008: Quantitative Precipitation Forecasts based on radar observations: principles, algorithms and operational systems. RMI Scientific and Technical Publication. No 52.
Termonia, P., 2003: Monitoring and Improving the Temporal Interpolation of Lateral-Boundary Coupling Data for Limited-Area Models. Mon. Wea. Rev., 131, 2450-2463.
Termonia, P., 2004: Monitoring the Coupling-Update Frequency of a Limited-Area Model by means of a Recursive Digital Filter. Mon. Wea. Rev., 132, 2130-2141.
Termonia, P., and R. Hamdi, 2007: Stability and accuracy of the physics-dynamics coupling in spectral models, Q. J. R. Meteorol. Soc., 133, 1589-1604.
Termonia, P. and A. Deckmyn, 2007: Model-Inspired Predictors for Model Output Statistics (MOS). Mon. Wea. Rev., 135, 3496-3505.
Termonia, P., 2008: Scale-Selective Digital Filtering Initialization. Mon. Wea. Rev., 136, 5246-5255.
Termonia, P., and F. Voitus, 2008: Externalizing the lateral boundary conditions from the dynamic core in semi-implicit semi-Lagrangian models. Tellus, 60A, 632-648.
Termonia, P., A. Deckmyn, and R. Hamdi, 2009: Study of the Lateral-Boundary-Condition Temporal-Resolution Problem and a Proposed Solution by means of Boundary-Error Restarts. Mon. Wea. Rev., in press, DOI: 10.1175/2009MWR2964.1
Voitus, F., P. Termonia, and P. Bénard, 2009: Well-posed Lateral Boundary Conditions for Spectral Semi-implicit Semi-Lagrangian schemes: Tests in a one-dimensional mode. Mon. Wea. Rev., 137, 315-330.
Vannitsem, S. and F. Chomé, 2005. One-way nested regional climate simulations and domain size. J. Clim., 18, 229-233.
Vannitsem, S., 2008: Dynamical properties of MOS forecasts. Analysis of the ECMWF operational forecasting system. Wea. Forecasting, 23, 1034-1043.
Vannitsem S. and C. Nicolis, 2008: Dynamical properties of Model Output Statistics forecasts. Mon. Wea. Rev., 136, 405-419.
Yang Sh., M. Corazza, A. Carrassi, E. Kalnay and T. Miyoshi, 2009: Comparison of ensemble-based and variational-based data assimilation schemes in a quasi-geostrophic model. Mon. Wea. Rev., 137, 693-709