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Canada Canadian Meteorological Centre 1. Summary of highlights All of the operational scripts and programs, working either on the frontend or the backend machines were converted to ensure year 2000 compliance. A considerable effort has been devoted in 1999 towards that important issue. The CMC ensemble prediction system for medium range was upgraded to 16 members in August 1999. The additional 8 members are produced using the unified model (GEM). The mesoscale short range model (HIMAP) was upgraded from 15 km to 10 km resolution, along with improvements in its physics package. The 30-day forecast production methodology was improved by the use of models climatology to get the temperature anomalies. The blending method of the two numerical models producing the seasonal forecasts has been improved. This method uses a hybrid technique, based on twenty-six years of historical runs of seasonal forecasts for each model. 2. Equipment in use at the Centre
3. Data and products from GTS in use a) Data The following types of observations are presently used at the Centre. For these types, we use all observations that are available from the GTS, on the global scale. The numbers indicate typical amounts received during a 24-hour period :
* Not assimilated yet. ** Locally produced GOES moisture profiles. *** A third of these are used for ice analyses .
b) Products GRIB ECMF
4. Data input system Fully automated.
5. Quality control system Various real-time quality control checks are performed for each observation received from the GTS. In particular :
These checks are done at, or after, the decoding phase of the bulletins. Canadian observations are put on the GTS before such quality control is performed. However, Canadian observations are subject to quality control at the observing site, before transmission to the national centre. The information generated by the quality control system inside the objective analysis is fed back into the observations database in order for non real-time monitoring and quality control activities to be performed. This monitoring is done on the global scale. Nationally, we also monitor the bursting altitude of upper-air soundings and results are distributed to data producers on a daily basis and monthly reports are distributed. Each Canadian synoptic report (manned stations only) is also monitored in real time for completeness and timeliness. Requests to individual stations are made if certain criteria are met. Observing stations send corrections if time permits. These corrections are sent to the GTS for transmission. A monthly summary of errors is produced and distributed to data producers.
6. Monitoring of the observing system Monitoring the availability of observations on the global scale is an inherent portion of operations at the CMC. Information on the current content of the observational databases is available in real time, by observation types and by geographical areas. A chart showing the geographical distribution of observations, by types, used to initialize the numerical models is distributed to forecast centres across the country in real-time. A monthly report describing the availability of upper-air observations is produced and distributed to data producers. The information on the availability and quality of observations available for use in the final global analyses is assembled each month into the "CMC Global Data Monitoring Report". The statistics presented in the reports are prepared in accordance to the WMO/CBS approved procedures. The reports are sent to the WMO Secretariat as well as other major GDPS centres. In 1993, CMC was designated by CBS as the lead centre for the monitoring of the quality of land surface observations in WMO RA-IV (North and Central America). In 1994, the CMC began to fulfil its role and since then has regularly produced its 6-monthly reports entitled " Report on the Quality of Land Surface Observations in Region IV". Two such reports were distributed in 1999. Monitoring results are distributed directly to national focal points for most countries within RA-IV. 7. Forecasting system 7.1 System run schedule The following table summarizes the operational runs at CMC. The core of the operational runs executes in batch on the NEC SX-4/32. Most of the postprocessing jobs, including CMC products, execute on the front end computer (SGI Origin 2000).
Note: There are also runs (not described here) that perform surface objective analyses and update geophysical fields; these are runs G3, G4, G5, G6 and R6.
7.2 Medium range forecasting systems (3-10 days) 7.2.1 Data assimilation and objective analysis Upper air
Surface Analysed Surface Fields for the medium range forecasting system
7.2.3 Numerical Weather Prediction Products 7.2.3.1 Analysis A series of classic analysis products are available in electronic or chart form ( i.e. surface analysis of snow and cover, sea surface temperature, surface MSLP and fronts, upper-air geopotential, winds and temperature at 1000, 850, 700, 500, 250 hPa, etc.). 7.2.3.2 Forecasts A series of classic forecast products are available in electronic or chart form ( i.e. MSLP and 1000-500 hPa thickness, 500 hPa geopotential height and absolute vorticity, accumulated precipitation and vertical velocity, 700 hPa geopotential height and relative humidity). A wide range of bulletins containing spot forecasts are produced for many locations across the world. As well, other specialized products such as precipitation and probability of precipitation forecasts, temperature and temperature anomaly forecasts, etc., are produced.
7.2.4 Operational techniques for application of NWP products
7.2.5 Ensemble Prediction System The 16 member ensemble prediction system (EPS) runs once a day up to 10 days (Houtekamer et al., 1996; Lefaivre et al., 1997; Plante et al. 1999). Eight perturbed analyses are obtained by running independent assimilation cycles that use perturbed sets of observations and are driven by eight different versions of the spectral global model (SEF model T95, Ritchie, 1991). The number of perturbed analyses is doubled as follows: the mean of the analyses is subtracted to the operational analysis and a fraction of this difference is added to the original perturbed analyses. Every day, at 00 UTC, two separate models are used to produce the 10-day forecasts: the SEF model and the GEM model (resolution of 1.875°, Côté et al., 1998a and 1998b). Each model uses different versions of their physical parameterizations. Ensemble outputs of the following products are available on the web (http://www.cmc.ec.gc.ca/cmc/htmls/forecasts.html, then select ensemble forecast system): spaghetti plots of the 500 hPa heights; composite MSLP highs and lows; accumulated quantity of precipitation; forecast charts of precipitation amount probability at various thresholds. Ensemble outputs are also used to feed the Perfect Prog statistical package to forecast daily maximum/minimum temperatures.
7.3 Short-range forecasting systems (0-48 hours) 7.3.1 Data assimilation and objective analysis
7.3.3 Numerical Weather Prediction Products 7.3.3.1 Analysis A series of classic analysis products are available in electronic or chart form ( i.e. surface analysis of snow and cover, sea surface temperature, surface MSLP and fronts, upper-air geopotential, winds and temperature at 1000, 850, 700, 500, 250 hPa, etc.). 7.3.3.2 Forecasts A wide variety of forecast products are available in electronic or chart form. These include the classic charts such as MSLP and 1000-500 hPa thickness, 500 hPa geopotential height and absolute vorticity, accumulated precipitation and vertical velocity, 700 hPa geopotential height and relative humidity. A myriad of special charts are produced in the context of the summer or winter severe weather (tropopause, stability indices, wind shear, helicity, wind chill, liquid water content, streamlines, low-level maximum wind, vertical motion, etc.) or in the specific support for aviation forecasting (icing, freezing level, height of cloud ceiling, momentum flux, turbulence, etc.). A wide range of bulletins containing spot forecasts are produced for many locations across North America.
7.3.4 Operational techniques for application of NWP products
7.3.5 High resolution model for short range forecast (HIMAP) A high resolution model is run once a day for 24 hours over two sub-areas of Canada: western Canada and upstream waters; Great Lakes and eastern Canada. This strategy was given the name of High Resolution Model Applications Project (HIMAP, Pellerin et al., 1998). The model used is the same unified model described in section 7.3.2, except for the following differences:
The model is started from the 6-hour forecast of the regional model following the 00 UTC run. Outputs of surface fields covering the uniform grid area are transmitted in GRIB formats to Canadian Regions. Series of coloured images (including animation) are also made available through the internal Web.
7.4 Specialised forecasts 7.4.1 Emergency response model The CMC is able to provide in real-time air concentrations and surface deposition estimates of airborne pollutants. These fields are obtained from a 3-D long range atmospheric transport/dispersion/deposition model, named the "Canadian Emergency Response Model" or "CANERM". The main applications for this model have been for estimating concentrations of radionuclides and volcanic ash. Based on this operational capability, the CMC has been designed by the WMO as a Regional Specialised Meteorological Centre (RSMC) with specialization in Atmospheric Transport Modelling Products for Environmental Emergency Response. In addition, CMC has been designed by the ICAO as a Volcanic Ash Advisory Centre (VAAC). 7.4.1.1 Data assimilation, objective analysis and initialization Fields of wind, moisture, temperature and geopotential heights must be provided to CANERM. These are obtained either from the Global or the Regional forecast and objective analysis systems. Please refer to the above section 7.2 for more information on these NWP products. Latitude, longitude and time of the release are necessary input parameters for CANERM. Estimates of intensity and duration of the release are also required. In the absence of actual source data, the standard default values adopted at the WMO's First International Workshop on Users' Requirements for the Provision of Atmospheric Transport Model Products for Environmental Emergency Response (September 1993) would be used. These are :
7.4.1.2 Model CANERM was developed by Janusz Pudykiewicz of Environment Canada and is described in Pudykiewicz, 1989. The horizontal and vertical advection in the model are performed using the semi-Lagrangian algorithm of Ritchie, 1987. Diffusion is modelled according to K-theory. The diffusivities are constant in the free atmosphere but have a vertical profile in the boundary layer which is dependent on the state of the surface layer; the vertical diffusivity within the surface layer is approximated using the relations provided by the analytical theory of the surface layer. CANERM simulates wet and dry scavenging, wet and dry deposition and radioactive decay for selected tracers. Wet scavenging is modelled by a simplified statistical parameterization based on the relative humidity. The source term is modelled by a narrow gaussian distribution to simulate both the release and subgrid scale mixing. CANERM can be executed in forecast mode up to day 10, using the operational Global forecast model, and up to 2 days using the operational Regional forecast model. CANERM can also be executed in hindcast mode using Global or Regional objective analyses. Presently, three horizontal resolutions are available : a resolution of 150 km on a quasi-hemispheric domain, a movable continental domain with a resolution of 50 km and a mesoscale domain with a resolution of 25 km. CANERM can be executed in both the Northern and the Southern Hemispheres.
7.4.1.3 Numerical weather prediction (atmospheric transport/dispersion/deposition) products Upon request from the appropriate WMO Member Countries Delegated Authorities, the CMC will provide the following standard set of basic products :
The standard set of products was agreed upon at the First International Workshop on Users' Requirements for the Provision of Atmospheric Transport Model Products for Environmental Emergency Response. The CMC can also provide charts of air concentration estimates for the surface, 850, 700, 500, 300 and 250 hPa levels as well as total surface deposition estimates, at 3 or 6-hour intervals, if required. All the products can be transmitted by facsimile, in real time, during environmental emergencies. In addition, CMC is designed by the ICAO as a Volcanic Ash Advisory Centre (VAAC).
7.4.2 Ozone and UV index forecast The Canadian Global model is used to prepare ozone and UV Index forecast at the 18-hour projection time based on 00 UTC data and at the 30-hour projection time based on 12 UTC data (Burrows et al., 1994). A Perfect Prog statistical method is used for forecasting total ozone, which is then supplemented with an error-feedback procedure. UV Index is calculated from the corrected ozone forecast. Charts of the total ozone forecast and of the UV Index forecast are prepared and transmitted to the Regional Offices. Bulletins giving the forecast UV Index at an ensemble of stations across Canada are also generated.
7.4.3 Wave Forecasting Sea-state forecasts of 48 hours over the Eastern Pacific and Western Atlantic are generated twice a day (00 UTC and 12 UTC) by the WAM (WAve Modeling) model. The Pacific version of the wave model uses the surface level winds from the global model while the Atlantic version uses the regional model wind outputs. Various parameters are plotted on the wave forecast chart (wave height, swell period, swell height and direction, etc.).
7.5 Extended range forecasts (10-30 days) Fifteen-day temperature anomaly forecasts (Verret et al. 1998) are generated once a week using a perfect prog approach from the medium-range model described at section 7.2.2. Monthly temperature forecasts based on numerical weather prediction techniques, are issued at the beginning and mid-month of every month. An ensemble of 5 runs, obtained from 24-hour time lag, is produced. The model used is very similar to the former operational spectral global model (Ritchie, 1991), except it has lower horizontal resolution (T63 L23) and has evolving geophysical forcing: the anomalies (analysis-climatology) of sea surface temperature (SST) and snow, observed during the previous 30 days, are added to the daily climatology during the integration. Direct model surface temperature outputs ensemble means are averaged over the 30-day period and subtracted from model climatology obtained from a 26-year hindcast period (see section 7.6). These temperature anomalies are then normalised by the model standard deviation multiplied by .43 (to get equiprobable classes) and categorised in above, below and normal classes. Charts are produced, showing above normal, and below normal temperatures. Monthly forecast products are on the Web (address http://www.cmc.ec.gc.ca/climate/htmletc/m_fcst-e.html).
7.6 Long-range forecasts (seasonal forecasts) Seasonal forecasts are issued 4 times a year (at the beginning of March, June, September and December). Seasonal products are distributed internationally and nationally through Internet (address http://www.cmc.ec.gc.ca/~cmcdev/saisons/seasons.html on the Web). They are also distributed nationally on the National Telecommunications System and to selected users by facsimile and made available on electronic bulletin boards. The charts are accompanied by a verification chart giving the performance of the forecast over the hindcast period. Also, verification charts, showing the previous season's prediction and a preliminary analysis of the observed anomaly, are provided.
7.6.1 Season 1 forecasts (zero lead time) Season 1 forecasts are produced using a numerical approach (Derome et al., 2000). Two ensembles of 6 runs, obtained from 24-hour time lag, are produced: 6 from the T63 L23 model described in section 7.5, 6 from a general circulation model (GCM) (McFarlane et al., 1992) (T32 L10). Both models use the same initial operational analyses. SST anomalies, that have been observed over the previous 30 days, are added to climatological values over the period; snow is relaxed towards climatology at the end of the first month, except for the GCM, where it is a prognostic variable. A simple statistical linear regression equations relates the 1000-500 hPa thickness anomalies (forecast minus model climatology) to surface temperature anomalies, using regression coefficients for 90-day forecasts. Maps are similar to monthly ones: 3 classes, separated using the .43 standard deviation of observed climatology.
The precipitation forecast is produced using a more direct approach: the two ensemble means of forecast precipitation are subtracted from their respective models climatologies, and normalised by models standard deviations. These normalised forecasts are then added, divided by two and used to produce a map, categorised in 3 classes, using the .43 value for separation.
Skill maps of temperature and precipitation, as obtained over the 26 years of historical runs, are shown for each of the 4 seasonal forecasts periods.
7.6.2 Season 2, 3 and 4 forecasts Seasonal forecasts at lead time of 3, 6 and 9 months are produced, using a Canonical Correlation Analysis technique (Shabbar and Barnston, 1996). The technique uses the SST anomalies observed over the last year to predict temperature and precipitation anomalies at Canadian stations (51 for temperatures; 69 for precipitation) for the following 3 seasons. Maps of above, normal and below temperature and precipitation are produced. These are accompanied by skill maps, as obtained from cross-validation over a 40-year period.
8. Verifications of prognostic products The objective verification of the operational numerical models is done on a continuing basis. S1 skill scores, bias and root mean square error are produced for the Canadian verification area. A monthly verification summary is produced and distributed to our clients. A verification system following the WMO/CBS recommendations has been
implemented in 1987. Results are regularly exchanged with the other participating centres.
The table on the following page is a summary of the verification scores for 1998 according
to the recommended format.
9. Plans for the future Improvements will be made to the 3D-Variational system: revision of error covariance statistics, analysis on models eta levels, assimilation of additional type of observations (ACARS/AMDARS, TOVS/ATOVS, high density SATOBS). The regional model resolution will be increased to about 16 km, with improved surface and condensation schemes. The model code will be converted to MPI and will then run on multiple nodes on the SX-4 machine. Ensemble prediction system will be used to issue probabilistic products. Air quality forecasts will become fully operational with the implementation of an updated version of the statistical system and the implementation of a dynamically based ozone forecast model. The UMOS system will become fully operational. Instead of issuing 4 «seasonal» forecasts per year, 90 day forecasts are to be issued every month, blending dynamical and empirical techniques.
Verification summary - 1999 Verification against analysis
Verification against radiosondes
10. References Bélair, S., A. Méthot, J. Mailhot, B. Bilodeau, A. Patoine, G. Pellerin and J. Côté, 2000: Operational Implementation of the Fritsch-Chappell Convective Scheme in the 24-km Canadian Regional Model. To be published in Wea. Forecasting. Brasnett, B. 1997: A global analysis of sea surface temperature for numerical weather prediction. J. Atmos. Oceanic Technol., 14, 925-937. Brasnett, B. 1999: A global analysis of Snow Depth for Numerical Weather Prediction. J. Appl. Meteor., 38, 726-740.Benoît, R., J. Côté and J. Mailhot, 1989: Inclusion of a TKE boundary layer parameterization in the Canadian regional finite-element model. Mon. Wea. Rev., 117, 1726-1750. Bourgouin, P., 1992 : Criteria for determining precipitation types. 4th AES/CMOS Workshop on Operational Meteorology, September 15-18, 1992, Whistler, B.C. 460-469. Brunet, N. and N. Yacowar, 1982 : Forecasts of maximum and minimum temperatures by statistical methods. CMC Technical Document, No. 18. Brunet, N., 1987 : Development of a perfect prog system for spot time temperature forecasts. CMC Technical Document, No. 30, 55 pp. Burrows, R. B., M. Vallée, D. I. Wardle, J. B. Kerr, L. J. Wilson and D. W. Tarasick, 1994 : The Canadian operational procedure for forecasting total ozone and UV radiation. Met. Apps., 1, 247-265. Burrows, R. B., 1998 : CART Neuro-Fuzzy statistical data modelling, part 1 : method. Preprints 14th Conference on Probability and Statistics in the Atmospheric Sciences, AMS, Phoenix Arizona, January 11-16 1998. Burrows, R. B., J. Montpetit, M. Faucher and J. Walmsley, 1998 : CART Neuro-Fuzzy statistical data modelling, part 2 : results. Preprints 14th Conference on Probability and Statistics in the Atmospheric Sciences, AMS, Phoenix Arizona, January 11-16 1998. Côté, J., 1997: Variable Resolution Techniques for Weather Prediction, Meteorology and Atmospheric Physics, 63, 31-38 Côté, J., S. Gravel, A. Méthot, A. Patoine, M. Roch and A. Staniforth, 1998a: The Operational CMC-MRB Global Environmental Multiscale (GEM) Model: Part I - Design Considerations and Formulation, Mon. Wea. Rev . 126, 1373-1395.Côté, J., J.-G. Desmarais, S. Gravel, A. Méthot, A. Patoine, M. Roch and A. Staniforth, 1998b: The Operational CMC-MRB Global Environmental Multiscale (GEM) Model: Part II - Results, Mon. Wea. Rev . 126, 1397-1418.Deardorff, J. W., 1978: Efficient prediction of ground surface temperature and moisture with inclusion of a layer of vegetation. J. Geophy. Res., 83, 1889-1903. Delage, Y., 1988a: The position of the lowest levels in the boundary layer of atmospheric circulation models. Atmos.-Ocean, 26, 329-340. Delage, Y., 1988b: A parameterization of the stable atmospheric boundary layer. Boundary-Layer Meteor., 43, 365-381. Derome, J., G. Brunet, A. Plante, N. Gagnon, G. J. Boer, F. W. Zwiers, S. J. Lambert and H. Ritchie 2000: Seasonal Prediction Based on Two Dynamical Models, in preparation. Elrod, G. P., 1989 : An index for clear air turbulence based on horizontal deformation and vertical wind shear. Preprints of the Third International Conference on the Aviation Weather System, Anaheim, California. Fillion, L., H. L. Mitchell, H. Ritchie and A. Staniforth, 1995: The impact of a digital filter finalization technique in a global data assimilation system, Tellus, 47A, 304-323. Fritsch, J. M. and C. F. Chappell, 1980: Numerical prediction of convectively driven mesoscale pressure systems. Part I: Convective parameterization. J. Atmos. Sci., 37, 1722-1733. Garand, L., 1983: Some improvements and complements to the infrared emissivity algorithm including a parameterization of the absorption in the continuum region, J. Atmos. Sci., 40, 230-244. Garand, L., and J. Mailhot, 1990: The influence of infrared radiation on numerical weather forecasts. Preprints 7th Conference on Atmospheric Radiation, July 23-27, 1990, San Francisco, California. Gauthier, P., S. Laroche, C. Charette and P. Koclas, 1997: Preprints 11th Conference on Numerical Weather Prediction, Norfolk, Virginia, August 19-23 1997. Gauthier, P., C. Charette, L. Fillion, P. Koclas and S. Laroche 1999: Implementation of a 3D Variational Data Assimilation System at the Canadian Meteorological Centre. Part I: The Global Analysis, Atmos.-Ocean, 37, 103-156. Houtekamer, P. L., L. Lefaivre, J. Derome, H. Ritchie and H. L. Mitchell, 1996: A system simulation approach to ensemble prediction. Mon. Wea. Rev . 124, 1225-1242.Kuo, H. L., 1974: Further studies on the parameterization of the influence of cumulus convection on large-scale flow. J. Atmos. Sci., 31, 1232-1240. Laroche, S., P. Gauthier, J. Morneau, M. Roch and J. St.James, 1998: Preprints 12th Conference on Numerical Weather Prediction, Phoenix Arizona, January 11-16 1998. Laroche, S., P. Gauthier, J. St.James and J. Morneau, 1999: Implementation of a 3D Variational Data Assimilation System at the Canadian Meteorological Centre. Part II: The Regional Analysis, Atmos.-Ocean, 37, 281-307. Lefaivre, L., P. L. Houtekamer, A. Bergeron and R. Verret, 1997: The CMC Ensemble Prediction System. Proc. ECMWF 6th Workshop on Meteorological Operational Systems, Reading, U.K., ECMWF, 31-44. Mailhot, J., R. Sarrazin, B. Bilodeau, N. Brunet and G. Pellerin, 1997: Development of the 35-km Version of the Canadian Regional Forecast System. Atmos.-Ocean, 35, 1-28. McFarlane, N.A., 1987 : The effect of orographically excited gravity wave drag on the general circulation of the lower stratosphere and troposhere. J. Atmos. Sci., 44, 1775-1800. McFarlane, N.A., C. Girard and D.W. Shantz, 1987 : Reduction of systematic errors in NWP and General Circulation models by parameterized gravity wave drag. Short and Medium-Range Numerical Weather Prediction, Collection of Papers Presented at the WMO/IUGG NWP Symposium, Tokyo, 4-8 August 1986, 713-728. McFarlane, N.A., G. J. Boer, J.-P. Blanchet and M. Lazare, 1992: The Canadian Climate Centre second generation circulation model and its equilibrium climate. J. Climate, 5, 1013-1044. Pellerin, G., A. Méthot, R. Moffet and A. Patoine, 1998: Development of a 15 km model at the Canadian Meteorological Centre, Proc. of the 16th Conference on Weather Analysis and Forecasting, Phoenix, Arizona, 253-255. Plante, A., P. L. Houtekamer, N. Gagnon, L. Lefaivre, G. Pellerin and R. Verret, 1999: CMC medium to long-range dynamic forecasts: Methods and results. To appear in Proc. ECMWF 7th Workshop on Meteorological Operational Systems. Pudykiewicz, J. 1989 : Simulation of the Chernobyl dispersion with a 3-D hemispheric tracer model. Tellus, 41B, 391-412. Ritchie, H., 1987 : Semi-Lagrangian advection on a Gaussian grid. Mon. Wea. Rev., 115, 608-619. Ritchie, H., 1991 : Application of the semi-Lagrangian method to a multilevel spectral primitive equations model. Quart. J. Roy, Meteor. Soc., 117, 91-106. Shabbar, A. and A. G. Barnston, 1996, Skill of Seasonal Climate Forecasts in Canada Using Canonical Correlation Analysis. Mon. Wea. Rev., 124, 2370-2385. Soucy D., 1991 : Revised users guide to days 3-4-5 automated forecast composition program. CMC Technical Document, 37, 45 pp. Sundqvist, H., E. Berge and J. E. Kristjansson, 1989: Condensation and cloud parameterization studies with a mesoscale numerical weather prediction model. Mon. Wea. Rev., 117, 1641-1657. Tremblay A., A. Glazer, W. Szyrmer, G. Isaac and I. Zawadzki, 1995: Forecasting of supercooled clouds Mon. Wea. Rev., 123, 2098-2113. Vallée M. and L. J. Wilson, 1998 : The new Canadian Updateable MOS forecast system. Preprints 14th Conference on Probability and Statistics in the Atmospheric Sciences, AMS, Phoenix Arizona, January 11-16 1998. Verret, R., 1987 : Development of a perfect prog system for forecast of probability of precipitation and sky cover. CMC Technical Document, 29, 28 pp. Verret, R., 1988 : Postprocessing of statistical weather element forecasts. CMC Monthly Review, 7, 5, 2-16. Verret R., 1989 : A statistical forecasting system with auto-correction error feedback. Preprints, 11th Conference on Probability and Statistics, AMS, Monterey, California, Oct. 1989, 88-92. Verret, R., 1990 : Automated plain language composition of weather forecasts "RAPELS". CMC Technical Document, 34, 49 pp. Verret, R., G. Babin, D. Vigneux, R. Parent and J. Marcoux, 1993: SCRIBE: An Interactive System for Composition of Meteorological Forecasts. Preprints, 13th AMS Conference on Weather Analysis and Forecasting, Vienna, Virginia, August 2-6 1993, 213-216. Verret, R., G. Babin, D. Vigneux, J. Marcoux, J. Boulais, R. Parent, S. Payer and F. Petrucci, 1995: SCRIBE an interactive system for composition of meteorological forecasts. Preprints 11th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography and Hydrology, AMS, Dallas, Texas, January 15-20 1995, 56-61. Verret, R., D. Vigneux, J. Marcoux, R. Parent, F. Petrucci, C. Landry, L. Pelletier and G. Hardy, 1997: SCRIBE 3.0 a product generator. Preprints 13th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography and Hydrology, AMS, Long Beach, California, February 2-7 1997, 392-395. Verret R., A. Bergeron, L. Lefaivre and A. Plante, 1998: Surface temperature anomaly forecasts over periods ranging from five to ninety days. Preprints 14th Conference on Probability and Statistics in the Atmospheric Sciences, Phoenix Arizona, January 11-16 1998. Wagneur, N., 1991: Une évaluation des schémas de type Kuo pour le paramétrage de la convection, Msc Thesis, UQAM, 76 pp. Yacowar N., 1975 : Probability forecast using finely tuned analogs. Preprints 4th Conference on Probability and Statistics in Atmospheric Sciences, AMS, Talahassee, 49-50. Yacowar N. and D. Soucy, 1990 : Wind forecasts for days 3-4-5. CMC Monthly Review, 9, 8, 2-19. Yu, W., L. Garand and A. Dastoor, 1997: Evaluation of model clouds and radiation at 100 km scale using GOES data, Tellus, 49A, 246-262.
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