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VERIFICATION OF ITALIAN COSMO-MODELS IMPLEMENTATIONS

This paper presents the verification system at CNMCAUNI.VER.S.E. for the implementation of Italian COSMO models, focusing on surface and upper air variables and precipitation. Cross-verifications between COSMO-ME, COSMO-I7, and COSMO-IT are conducted, highlighting improvements in accuracy and bias. Results for DJF and MAM seasons are shown using various statistical measures and graphics.

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VERIFICATION OF ITALIAN COSMO-MODELS IMPLEMENTATIONS

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  1. VERIFICATION OF ITALIAN COSMO-MODELS IMPLEMENTATIONS by Angela Celozzi, Adriano Raspanti E-mail: name.surname@meteoam.it Presented by Adriano Raspanti

  2. The verification system at CNMCAUNI.VER.S.E.(UNIfied VERification System Enviroment) • Based on the use of Common Verification Suite (CNMCA version + graphs) • Verifications for continuous variables at surface using 92 synop stations (next implementation of around 50 DCP): T2m, TD2m,10m wind speed, Mslp, TotC; • Verifications for precipitations with the previous stations; • Verification of upper air parameter using 7 (8 when available) Temp stations: G, T, Wind, RH

  3. The verification system at CNMCAUNI.VER.S.E.(UNIfied VERification System Enviroment) • For continues variables (surface and upper air) the following statistics are shown: ME, MAE (and their skill score) • For precipitations contingency table, FBI, POD, FARatio, FARate, TS, ETS, HSS OR, are computed. FBI and ETS are here presented

  4. Italian COSMO Models implementations cross-verifications

  5. Comparison between COSMO-ME and COSMO-I7 Verifications for DJF and MAM show for COSMO-ME (7Km grid) a clear improvement in the second quarter (T2m and Mslp) Mainly due to the introduction of 3-hourly 3D-Var analysis with 14km resolution (interpolated on 7km grid) and the new multi-layer soil model. Precipitation in general tend to be less overestimated, but the soil is still dry (see Td2m) and FBI has minima in the afternoon during MAM. Accuracy (compared with COSMO-I7) is usually higher for COSMO-ME for continuous parameters. COSME-ME ETS is slightly better in DJF then COSMO-I7 and almost the same in MAM (less accuracy during afternoon).

  6. Comparison between COSMO-ME and COSMO-I7 precipitation in 6h Cosmo-ME vs Cosmo-I7 DJF run 00 PREC +06 10mm Cosmo-ME vs Cosmo-I7 MAM run 00 PREC +06 10mm

  7. Comparison between COSMO-ME and COSMO-I7 precipitation in 12 h

  8. Comparison between COSMO-ME and COSMO-I7: T2m and MSLP

  9. TDEW COSMO-ME vs COSMO-I7 MAM run00 3,5 3 2,5 2 1,5 Scores 1 0,5 0 000 003 006 009 012 015 018 021 024 027 030 033 036 039 042 045 048 -0,5 -1 -1,5 Step ME - CM MAE -CM ME - CI7 MAE -CI7 Comparison between COSMO-ME and COSMO-I7: Td2m and Wmod Wmod COSMO-ME vs COSMO-I7 DJF run 00 Wmod COSMO-ME vs COSMO-I7 MAM run 00

  10. Comparison between COSMO-ME and COSMO-IT (no upscaling) COSMO-IT (2.8Km grid), here compared with COSMO-ME, tends to have a better accuracy (lower MAE values) for almost all the continuous parameters for both seasons (especially in MAM after the introduction of observation nudging). ME is better for T2m for COSMO-MEin MAM and TD2m is cold for both models (better tuning of the soil model?). Precipitation scores seem to have different behaviour for the two seasons. During winter the plots are almost the same with a better FBI for COSMO-ME for 12 cumulated precipitation, but a worse ETS. During spring COSMO - IT performs better both in terms of FBI and ETS.

  11. Comparison between COSMO-ME and COSMO-IT precipitation in 6h

  12. Comparison between COSMO-ME and COSMO-IT precipitation in 12 h

  13. Comparison between COSMO-ME and COSMO-IT: T2m and MSLP

  14. Comparison between COSMO-ME and COSMO-IT: Td2m and Wmod

  15. Comparison between COSMO-ME and COSMO-IT (with upscaling)

  16. Comparison between COSMO-ME and COSMO-IT (with upscaling)

  17. Comparison between COSMO-ME and COSMO-IT (with upscaling)

  18. Comparison between COSMO-ME and COSMO-I7 Main results for Upper air - TEMPERATURE DJF: COSMO-ME has a clear colder lower troposphere, compared with COSMO-I7 even if the MAE values are almost the same. MAM: After the introduction of 3D-VAR 3-hours analysis cycle at 14km and the interpolation on the 7km grid of COSMO-ME a clear improvement is evident. MAE values appear to be lower than COSMO-I7. It is worthwhile to stress that both the implementations tend to have a cold bias in the boundary layer, for all the time-steps during DJF and only night-time during MAM, even if COSMO-ME clearly improves.

  19. COSMO-ME vs COSMO-I7 Temp T+12 00run DJF COSMO-ME vs COSMO-I7 Temp T+24 00run DJF 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -1 -0,5 0 0,5 1 1,5 -1,5 -1 -0,5 0 0,5 1 1,5 2 COSMO-ME vs COSMO-I7 Temp T+36 00run DJF COSMO-ME vs COSMO-I7 Temp T+48 00run DJF 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -2 -1,5 -1 -0,5 0 0,5 1 1,5 2 -1 -0,5 0 0,5 1 1,5 2 ME-CME ME-CI7 MAE-CME MAE-CI7

  20. COSMO-ME vs COSMO-I7 Temp T+12 00run MAM COSMO-ME vs COSMO-I7 Temp T+24 00run MAM 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -1,5 -1 -0,5 0 0,5 1 1,5 2 -1 -0,5 0 0,5 1 1,5 2 2,5 COSMO-ME vs COSMO-I7 Temp T+36 00run MAM COSMO-ME vs COSMO-I7 Temp T+48 00run MAM 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -1,5 -1 -0,5 0 0,5 1 1,5 2 2,5 -1,5 -1 -0,5 0 0,5 1 1,5 2 ME-CME ME-CI7 MAE-CME MAE-CI7

  21. Main results for Upper air – Wind Speed DJF-MAM Concerning the wind speed it is evident that bias values are almost the same for the two seasons even if COSMO-I7 seems to have a general underestimation from 700 hPa up, especially in winter and a less evident overestimation in the lower levels, in spring, compared with COSMO-ME MAE values are lower (and then a better accuracy) for COSMO-ME especially around 300 hPa, the climatological jet stream height.

  22. COSMO-ME vs COSMO-I7 Wmod T+12 00run DJF COSMO-ME vs COSMO-I7 Wmod T+24 00run DJF 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -1,5 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 -1,5 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 COSMO-ME vs COSMO-I7 Wmod T+36 00run DJF COSMO-ME vs COSMO-I7 Wmod T+48 00run DJF 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -1, -1 -0, 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 5,5 -1,5 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 5,5 6 5 5 ME-CME ME-CI7 MAE-CME MAE-CI7

  23. COSMO-ME vs COSMO-I7 Wmod T+12 00run MAM COSMO-ME vs COSMO-I7 Wmod T+24 00run MAM 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 COSMO-ME vs COSMO-I7 Wmod T+36 00run MAM COSMO-ME vs COSMO-I7 Wmod T+48 00run MAM 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -1,5 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 5,5 6 -1,5 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 ME-CME ME-CI7 MAE-CME MAE-CI7

  24. SOME CONCLUSIONS The different behaviour of italian COSMO-model implemetations give us arguments for discussion COSMO-ME seems to perform better (for the periods shown) after introduction of new soil method and higher resolution 3D-Var, especially upper-air parameters COSMO-IT seems to be promising and improved performances after the implementation of nudging The scores obtained from upscaling of COSMO-IT are better for precipitation, while for other parameters results are more confused (more period needed

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