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 General strengths and weaknesses of NWP models

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

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

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

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

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

? forecast range / max. lead-time ? ? T574L64 ~27km ? Models ? EPS 50 members +1 control ? ? 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

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

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)

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

UK Met Office Limited Area Models North Atlantic European (NAE) 12 km horizontal resolution, 70 vertical levels Stretches from Newfoundland to Eastern Mediterranean and Northern Scandinavia to North Africa Four times daily to t+48h

UK Met Office Africa LAM – retired October 2013

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

Strengths & Weaknesses of NWP models

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

NWP Strengths Convection Extra-tropical latitudes 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

Generic Problems Inaccurate Initial Conditions Resolution 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

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

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

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

NWP convection switched on….

NWP convection switched off….

Questions & Answers