1. Institute for Environment and Sustainability1 Meteorology

2. Institute for Environment and Sustainability2 METEOROLOGY (I) Computational Domains: D1 D2

3. Institute for Environment and Sustainability3 METEOROLOGY (II) MM5 runs: (1): 28 periods of 14 days with restart (2): 28 independent periods of 14 days with 4 days spin-up 2-way nested domains: D1 and D2 D1: resolution 6x6 km (95x65 cells) D2: resolution 2x2 km (136x112 cells) 24 vertical layers (up to 12 km) WRF run: Similar to MM5(1) with 5 km (115x79 cells) and 2.5 km (95x87 cells)

4. Institute for Environment and Sustainability4 METEOROLOGY (III) Meteo availability: MM5: cdf format: D1 365 x 161 Mb ~ 60 Gb D2 365 x 390 Mb ~ 142 Gb WRF: cdf format: D1 365 x 161 Mb ~ 75 Gb D2 365 x 390 Mb ~ 68 Gb TRAMPER:? Transfer: USB disk? Grid configurations – interpolation on own grid left to each modelling group.

5. Institute for Environment and Sustainability5 Variable descriptionUnitDim East-West wind component m/s XYZT North-south wind component m/s Vertical wind component m/s Real Temperature K Potential TemperatureK Water vapour mixing ratio kg/kg Cloud water mixing ratio kg/kg Rain water mixing ratio kg/kg Ice cloud mixing ratiokg/kg Snow mixing ratio (snow fraction) kg/kg Graupelkg/kg Momentum diffusion coefficient m2/s Heat diffusion coefficient m2/s Pressure Pa Model half-sigma levels sigma Landuse category corine XY Longitude Deg Latitude Deg Planetary boundary layer height m Variable descriptionUnitDim Surface temperature K XYT Accum. Convective rainfall cm Accum. Non-convective rainfall cm Surface sensible heat flux W/m2 Surface latent heat flux W/m2 Frictional velocity m/s Surface downward shortwave radiation W/m2 Surface downward longwave radiation W/m2 top outgoing shortwave radiation W/m2 top outgoing longwave radiation W/m2 2m real temperature K 2m water mixing ratio Kg/kg 10m U wind component m/s 10m V component of wind m/s Monin –Obukov length m Sea surface temperature K METEOROLOGY (IV) Terrain height, Coriolis, Soil temp, Albedo, Surface moisture,Surface roughness

6. Institute for Environment and Sustainability6 Meteorological monitoring network and data availability JRC Ispra, 7. March 2008 Po Valley: 464 stations: - Lombardy: 292; - Veneto: 29; - Piedmont: 43; - Emilia-Romagna: 13; - Trentino-Alto Adige: 84; - Aosta Valley: 3. METEOROLOGY (V) Variables: T2, UV10, dirUV10 Validation: Visualisation Tool

7. Institute for Environment and Sustainability7 JRC Ispra, 7. March 2008 Validation of meteorology Statistical benchmarks Environmental Report: MM5 Performance Evaluation Project, Matthew T. Johnson, Kirk Baker (2001) ParameterGross ErrorBiasRMSE Temperature 2 K 0.5 K Wind Speed 0.5 m/s 2 m/s Wind Direction 30 deg 10 deg METEOROLOGY (VI)

8. Institute for Environment and Sustainability8 JRC Ispra, 7. March 2008 Po Valley meteorology, example LAMI long-term evaluation: summary, 2006 ParameterRMSE T 2m 3 C (spring/winter) RH 2m for Appenine: overestimation ~20% Wind Speed~ 2.5 m/s (Po Valley, winter) Wind Direction ~ 70 (Po Valley, Appenine) METEOROLOGY (VII)

9. Institute for Environment and Sustainability9 JRC Ispra, 7. March 2008 Taylor diagram and scatter plots for the annual mean 2 m temperature over all Po Valley stations. METEOROLOGY (VIII)

10. Institute for Environment and Sustainability10 RMSE (with the 3 C benchmark) and BIAS (with -0.5 C benchmark) for the annual mean 2 m temperature over all Po Valley stations. JRC Ispra, 7. March 2008 METEOROLOGY (IX)

11. Institute for Environment and Sustainability11 JRC Ispra, 7. March 2008 GE (with the 2 C benchmark) for 2 m temperature for chosen stations (left: Po Valley, right: Lombardy domain). METEOROLOGY (X)

12. Institute for Environment and Sustainability12 JRC Ispra, 7. March 2008 Taylor diagram and scatter plots for the annual mean 10 m wind speed over all Po Valley stations. METEOROLOGY (XI)

13. Institute for Environment and Sustainability13 JRC Ispra, 7. March 2008 RMSE (with the 2 m/s benchmark) and BIAS (with the 0.5 m/s benchmark) for the annual mean 10 m wind speed over all Po Valley stations. METEOROLOGY (XII)

14. Institute for Environment and Sustainability14 JRC Ispra, 7. March 2008 RMSE (with the 2.5 m/s benchmark) for 10 m wind speed (left: winter, right: summer) over all Po Valley stations. METEOROLOGY (XIII)

15. Institute for Environment and Sustainability15 JRC Ispra, 7. March 2008 Taylor diagram and scatter plots for the annual mean 10 m wind direction over all Po Valley stations. METEOROLOGY (XIV)

16. Institute for Environment and Sustainability16 JRC Ispra, 7. March 2008 RMSE (with the 70 benchmark and BIAS (with the 10 benchmark) for the annual mean 10 m wind direction over all Po Valley stations. METEOROLOGY (XV)

17. Institute for Environment and Sustainability17 JRC Ispra, 7. March 2008 GE (with the 30 benchmark) for 10 m wind direction for chosen stations (left: Po Valley, right: Lombardy domain). METEOROLOGY (XVI)

18. Institute for Environment and Sustainability18 JRC Ispra, 7. March 2008 Conclusions: 1.Both MM5 and WRF produce T2 data with quality corresponding to the statistical benchmarks given by Johnson and Baker and in general – better than it is shown in LAMI long term evaluation for Po Valley (but for other year). However temperatures are slightly underestimated. 2.Both models show large overestimation for wind speeds, although MM5 produces lower RMSE and BIAS values. Benchmark for BIAS is exceeded in both cases. However the values correspond to the example of LAMI. Wind direction has been calculated with similar quality as for the wind speed. 3.The quality of the relative humidity calculations corresponds to the example of LAMI. 4.Evaluation work still on-going 5.Comparison with other meteorological drivers is welcome (e.g TRAMPER,...) METEOROLOGY (XVII)