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Numerical Weather Prediction Models

Numerical Weather Prediction Models. Prepared by C. Tubbs, P. Davies, Met Office UK Revised, delivered by P. Chen, WMO Secretariat SWFDP-Eastern Africa Training Workshop Bujumbura, Burundi, 11-22 November 2013. NWP Model Formulation. Different types of model Model Characteristics

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Numerical Weather Prediction Models

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  1. Numerical Weather Prediction Models Prepared by C. Tubbs, P. Davies, Met Office UK Revised, delivered by P. Chen, WMO Secretariat SWFDP-Eastern Africa Training Workshop Bujumbura, Burundi, 11-22 November 2013

  2. NWP Model Formulation • Different types of model • Model Characteristics • General strengths and weaknesses of NWP models

  3. Types of atmospheric model • Climatological • Global Climate Models (GCM’s) • Hindcasts and forecasts • Climate change – global warming • Non-operational weather forecasting models

  4. Types of atmospheric model • Long-term and seasonal • Coupled ocean-atmosphere models • Aims to infer climate from indicators such as Sea Surface Temperature (El Nino) • Forecasts issued by ECMWF every month • Typically based on ensemble methods

  5. Types of atmospheric model • Global NWP models • Operational forecasting models • Run twice to four times daily • Generally short- to medium-range (typically t+144h) • Global output coverage (datasets) • Hi-res “deterministic” vs EPS

  6. Types of atmospheric model • Limited Area Models (mesoscale/LAMs) • Add local detail to broad picture from global model • Take boundary conditions from global • Higher resolution, so better representation of small scale events • Shorter forecast range (typically t+48h) • Careful (especially if approaching cloud-scale!): kinematic effects vs dynamical processes

  7. Types of atmospheric model • Very-short-range (<12h) incl. Nowcasting • Nowcasting aims to give best forecast for time period of <4-6h hours lead-time • Blend of model and observational data • e.g. UK Met Office uses the NIMROD system • Specific applications • Atmospheric Dispersion • Air quality • Lee-wave forecasting models

  8. ? T574L64 ~27km ? ? EPS 50 members +1 control ? Models ? forecast range / max. lead-time ? t+144h ? ? domain ? « Anticipated advances in NWP, and the growing technology gap in weather forecasting » (2013) http://www.wmo.int/pages/prog/www/swfdp/Meetings/documents/Advances_NWP.pdf See Annex II for NWP systems

  9. ECMWF Global High-Res. IFS • Horizontal resolution of T1279 (16km), 91 vertical levels • 240h forecast range (10 days ahead) • 4-D VAR Global EPS – Ensemble Prediction System • 50 members, T319 (65km), 62 levels T= spectral truncation

  10. NCEP National Centers for Environmental Prediction (Washington, USA) • GFS (Global Forecasting System) model – T574 L64 (27km, 2010), T1148 (18km, planned 2013), and • GEPS ensemble model – 42 members, T190 (70km)

  11. Met Office UK Global model “UM” • Horizontal resolution of 25 km and L70 vertical levels • 4 times daily • Run out to t+144h • 4DVar MOGREPS-15 (UM) Global 23 members, 60km, L70

  12. UK Met Office • Africa LAM – retired October 2013

  13. UK Met Office Lake Victoria LAM • 4 km horizontal resolution, 70 vertical levels • Available via password protected website http://www.metoffice.gov.uk/weather/africa/lam/ • Username is afr_nms and password is uk_alam • Intermittent data assimilation • Run to t+48h

  14. Strengths & Weaknesses of NWP models

  15. Strengths & Weaknesses • There are generic problems common to most NWP • If we know about these we can account for them in our initial verification • Most problems are related to resolution

  16. NWP Strengths • Convection • General area of convection is well captured • Extra-tropical latitudes • Model is much better here • Frontal systems are well represented • Orographically enhanced rainfall better than Global Model

  17. Generic Problems • Inaccurate Initial Conditions • Lack of data • Imperfect data assimilation • Resolution • Horizontal resolution may cause small scale features to be missed • Vertical profile may not capture full detail e.g. inversions, localised temperature advection

  18. Generic Problems • Orography • Generally flattened – less steep and less high • Some features completely omitted • Orography in LAMs is better than in global models but still not perfect

  19. Generic Problems • Lateral Boundary Conditions • Only a problem for LAM’s • Spin up problems when transposing low resolution data onto a high resolution grid • Potential problems at edge of domain

  20. NWP Weaknesses • Tropical Convection • Representation of diurnal cycle is poor • Convection initiated too early and is too widespread • 0600-1200 ppn accumulation frames contain much spurious ppn but can indicate areas of activity • Fails to develop large scale, long-lived mesoscale convective systems

  21. NWP convection switched on….

  22. NWP convection switched off….

  23. Questions & Answers

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