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Confrontate le nostre previsioni con i dati osservati per gli ultimi giorni con la nostra verifica a breve termine per Woodbridge.

Comparison of weather models for Woodbridge

The blue lines correspond to the forecasts computed by different high-resolution weather models. Also shown are the members of a traditional ensemble prediction, where the same weather model (GFS) is run several times with slightly different initial conditions, to reflect uncertainties in the observations required to run a forecast model. The GFS members have been downscaled and bias corrected to match local weather conditions, data from the high-resolution models is untouched.

  • In the top graph, the temperature forecast for Woodbridge is shown using light blue for different high-resolution models and red for the GFS ensemble members. The black line represents the mean of all forecasts and the dashed line the meteoblue consensus forecast as shown in our weather forecasts.
  • The 2nd graph shows the accumulated precipitation forecast, that is the total amount that falls from today up to the date shown on the time axis. Purple colour is used to indicate times where precipitation is falling.
  • The 3rd graph is forecast cloud cover in percent using light blue for the high-resolution weather models and green for the GFS ensemble members.
  • The 4th graph indicates the wind forecast as computed by high resolution models (light blue) and by the ensemble prediction (green). Also shown is the daily wind direction summary in form of a wind rose. Larger segments indicate that this wind direction is more likely and more frequent over the day than directions having smaller segments. If you have many segments of all about equal size than the forecast of wind direction is very uncertain. If there are predominantly two opposing directions this often indicates a thermal wind circulation where wind blows from a different direction during the day than at night.

Why do we show a traditional ensemble forecast and a multi model forecast at the same time?

A traditional ensemble (e.g. GFS) computed with the same forecast model often underestimates the uncertainties in the weather for the first 3 to 5 days thus overestimating the confidence in the forecast. Furthermore, the traditional ensemble is run at much lower resolution, thus neglecting some of the local weather phenomenon, which can be seen in high resolution models. It is very important to note, that all members of a traditional ensemble have the same likelihood of being true (there is no way to tell in advance which one will be better). This contrasts with the high-resolution models, where some deliver better forecasts than others depending on the location and weather conditions.


Modelli meteorologici

I modelli meteorologici simulano processi fisici. Un modello meteo divide il mondo o una regione in piccole "celle di griglia". Ogni cella è grande da 4 a 40km re alta da 100m a 2km. I nostri modelli hanno 60 livelli verticali e raggiungono la stratosfera fino a 10-25 hPa (60km d'altezza). Il tempo atmosferico è previsto dalla risoluzione di complesse equazioni matematiche su tutte le celle ogni pochi secondi e parametri come temperature, vento o nuvolosità sono salvate per ogni ora.

meteoblue utilizza un grande numero di diversi modelli meteorologici ed integra open data da diverse fonti. Tutti i modelli meteoblue sono calcolati due volte al giorno su un cluster di calcolo dedicato ad alte performance.

Modello Regione Risoluzione Ultimo aggiornamento Fonte

La famiglia di modelli NEMS è il successore migliorato dei modelli NMM (operativo dal 2013). NEMS è un modello multi-scala (usato sia per modelli globali che locali) che migliora le previsioni di precipitazioni e nuvolosità.

NEMS4 Europa Centrale 4 km 72 h 14:40 EDT meteoblue
NEMS12 Europa 12 km 168 h 15:05 EDT meteoblue
NEMS-8 America Centrale 12 km 144 h 17:24 EDT meteoblue
NEMS12 India 12 km 168 h 16:07 EDT meteoblue
NEMS10 Sud America 10 km 168 h 17:33 EDT meteoblue
NEMS10 South Africa 10 km 144 h 16:13 EDT meteoblue
NEMS8 Nuova Zelanda 8 km 144 h 14:58 EDT meteoblue
NEMS8 Japan East Asia 8 km 144 h 14:25 EDT meteoblue
NEMS30 Global 30 km 168 h 12:48 EDT meteoblue
NEMS2-30 Global 30 km 168 h 18:49 EDT meteoblue

La famiglia di modelli NMM i primi modelli meteoblue (operativi dal 2007). NMM è un modello meteo locale e altamente ottimizzato per ortografie complesse.

NMM4 Europa Centrale 4 km 72 h 13:12 EDT meteoblue
NMM12 Europa 12 km 168 h 14:44 EDT meteoblue
NMM18 Sud America 18 km 144 h 16:37 EDT meteoblue
NMM18 South Africa 18 km 144 h 15:13 EDT meteoblue
NMM18 Sudest Asiatico 18 km 144 h 15:43 EDT meteoblue

Domini da terze parti Come visti su molti altri siti internet.

GFS22 Global 22 km 180 h (@ 3 h) 12:31 EDT NOAA NCEP
GFS40 Global 40 km 168 h (@ 3 h) 12:29 EDT NOAA NCEP
GFSENS05 Global 40 km 336 h (@ 6 h) 15:54 EDT NOAA NCEP
NAM5 Nord America 5 km 48 h 13:16 EDT NOAA NCEP
NAM12 Nord America 12 km 84 h (@ 3 h) 22:46 EDT NOAA NCEP
ICON7 Europa 7 km 120 h (@ 3 h) 12:11 EDT Deutscher Wetterdienst
ICON13 Global 13 km 78 h 13:31 EDT Deutscher Wetterdienst
COSMO2 Germania 2.5 km 27 h 21:30 EDT Deutscher Wetterdienst
GEM25 Global 25 km 168 h (@ 3 h) 14:07 EDT Environment Canada
AROME2 Francia 2 km 36 h 13:02 EDT METEO FRANCE
ARPEGE11 Europa 11 km 96 h 14:27 EDT METEO FRANCE
ARPEGE40 Global 40 km 96 h (@ 3 h) 13:06 EDT METEO FRANCE
HIRLAM11 Europa 11 km 48 h 13:30 EDT KNMI

Copertura globale

meteoblue domain overview I modelli meteorologici di meteoblue coprono le aree più popolate del pianeta in alta definizione (3-10km) e tutto il Mondo a risoluzione intermedia (30km). L'immagine sulla destra mostra i modelli NMM con una linea rossa e i modelli NEMS con una nera. Per una singola previsione vengono considerati molti modelli meteorologici, analisi statistiche, misure, telemetria radar e satellitare al fine di generare la previsione meteo più probabile per ogni singola località.